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It excels at large-scale ab initio molecular dynamics simulations of complex systems, particularly for studying materials under extreme conditions." }, { "num": "010", "name": "PARSEC", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://parsec.ices.utexas.edu/", "note": "", "md_link_text": "PARSEC.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/PARSEC.md", "papers": [ { "name": "Kronik_et_al_2006.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/PARSEC/Kronik_et_al_2006.pdf", "doi_url": "https://scholar.google.com/scholar?q=PARSEC+Kronik+et+al+2006" } ], "paper_placeholder": false, "slug": "PARSEC", "idx": 9, "overview": "PARSEC (Pseudopotential Algorithm for Real-Space Electronic Calculations) is a DFT code that uses real-space grids and finite-difference methods instead of plane waves. Developed at the University of Texas at Austin, PARSEC employs high-order finite differences and adaptive coordinate refinement to achieve high accuracy with excellent parallel scaling. It is particularly well-suited for large systems, nanostructures, and molecules where real-space approaches offer advantages over plane-wave meth" }, { "num": "011", "name": "PARATEC", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "http://www.ab-initio.mit.edu/wiki/index.php/PARATEC (or NERSC archive)", "note": "", "md_link_text": "PARATEC.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/PARATEC.md", "papers": [ { "name": "Pfrommer_et_al_1999.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/PARATEC/Pfrommer_et_al_1999.pdf", "doi_url": "https://scholar.google.com/scholar?q=PARATEC+Pfrommer+et+al+1999" } ], "paper_placeholder": false, "slug": "PARATEC", "idx": 10, "overview": "PARATEC (PARAllel Total Energy Code) is a parallel plane-wave DFT code developed at Lawrence Berkeley National Laboratory and UC Berkeley. Designed for massively parallel computations on supercomputers, PARATEC pioneered several algorithms for efficient large-scale DFT calculations and was particularly important in the early 2000s for demonstrating petascale computational materials science. While development has slowed, it remains historically significant and is archived at NERSC." }, { "num": "012", "name": "SPARC", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://sparc-x.github.io/", "note": "", "md_link_text": "SPARC.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/SPARC.md", "papers": [ { "name": "SPARC_10.1016_j.softx.2021.100709.pdf", "path": "Papers_of_Codes/DFT/SPARC/SPARC_10.1016_j.softx.2021.100709.pdf", "doi_url": "https://doi.org/10.1016/j.softx.2021.100709" } ], "paper_placeholder": false, "slug": "SPARC", "idx": 11, "overview": "SPARC (Simulation Package for Ab-initio Real-space Calculations) is an open-source DFT code using real-space formulation with finite differences for accurate and efficient large-scale electronic structure calculations. Developed at Georgia Institute of Technology, SPARC is designed for excellent parallel scalability on modern HPC architectures including GPUs. It features cyclic boundary conditions for accurate stress calculations and is particularly well-suited for high-throughput materials scre" }, { "num": "013", "name": "RMGDFT", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://github.com/RMGDFT/rmgdft", "note": "", "md_link_text": "RMGDFT.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/RMGDFT.md", "papers": [ { "name": "Briggs_et_al_1996.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/RMGDFT/Briggs_et_al_1996.pdf", "doi_url": "https://scholar.google.com/scholar?q=RMGDFT+Briggs+et+al+1996" } ], "paper_placeholder": false, "slug": "RMGDFT", "idx": 12, "overview": "RMG (Real-space Multigrid) is an open-source DFT code using real-space multigrid methods for solving the Kohn-Sham equations. Developed at North Carolina State University, RMG employs multigrid preconditioning for efficient convergence and is designed for excellent parallel performance on modern HPC systems with GPU acceleration. It is particularly effective for large-scale electronic structure calculations and materials simulations requiring high accuracy." }, { "num": "014", "name": "ABACUS", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://github.com/deepmodeling/abacus-develop", "note": "", "md_link_text": "ABACUS.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/ABACUS.md", "papers": [], "paper_placeholder": true, "slug": "ABACUS", "idx": 13, "overview": "ABACUS (Atomic-orbital Based Ab-initio Computation at UStc) is an open-source DFT package supporting both plane-wave and numerical atomic orbital (NAO) basis sets. Developed by the DeepModeling community in China, ABACUS is designed for efficient electronic structure calculations, materials simulations, and integration with machine learning workflows. It features excellent GPU acceleration, hybrid basis sets, and is particularly strong in Chinese academic and industrial applications." }, { "num": "015", "name": "ATOMPAW", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://github.com/atompaw/atompaw", "note": "", "md_link_text": "ATOMPAW.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/ATOMPAW.md", "papers": [ { "name": "Holzwarth_et_al_2001.pdf", "path": "Papers_of_Codes/materials_science_papers/9.1_Electronic_Analysis/Atompaw/Holzwarth_et_al_2001.pdf", "doi_url": "https://scholar.google.com/scholar?q=ATOMPAW+Holzwarth+et+al+2001" } ], "paper_placeholder": false, "slug": "ATOMPAW", "idx": 14, "overview": "ATOMPAW is a specialized tool for generating atomic datasets for Projector Augmented Wave (PAW) calculations. Developed by Natalie Holzwarth and collaborators at Wake Forest University, ATOMPAW creates PAW atomic data files that can be used with plane-wave DFT codes like ABINIT, Quantum ESPRESSO, and VASP. It is not a DFT calculation engine itself, but rather a dataset generation utility essential for PAW-based calculations." }, { "num": "016", "name": "GAPW", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "**METHOD NOT SOFTWARE** - GAPW (Gaussian and Augmented Plane Waves) is a method implemented in CP2K, not standalone software.", "note": "", "md_link_text": "GAPW.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/GAPW.md", "papers": [], "paper_placeholder": true, "slug": "GAPW", "idx": 15, "overview": "This method combines the efficiency of plane waves with the compactness of Gaussian functions, allowing for all-electron calculations or accurate pseudopotential calculations." }, { "num": "017", "name": "PROFESS", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://profess.dev/", "note": "", "md_link_text": "PROFESS.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/PROFESS.md", "papers": [ { "name": "PROFESS_10.1016_j.cpc.2014.12.021.pdf", "path": "Papers_of_Codes/DFT/PROFESS/PROFESS_10.1016_j.cpc.2014.12.021.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2014.12.021" } ], "paper_placeholder": false, "slug": "PROFESS", "idx": 16, "overview": "PROFESS is an orbital-free density functional theory (OF-DFT) code developed at Princeton University. It implements kinetic energy density functionals that avoid explicit calculation of orbitals, enabling linear-scaling DFT calculations for large metallic and semiconductor systems. PROFESS is particularly efficient for materials where orbital-free approaches are accurate, providing significant computational speedup over traditional Kohn-Sham DFT." }, { "num": "018", "name": "MADNESS", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "CONFIRMED", "official_url": "https://github.com/m-a-d-n-e-s-s/madness", "note": "", "md_link_text": "MADNESS.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/MADNESS.md", "papers": [ { "name": "MADNESS_10.1137_15M1026171.pdf", "path": "Papers_of_Codes/DFT/MADNESS/MADNESS_10.1137_15M1026171.pdf", "doi_url": "https://doi.org/10.1137/15M1026171" } ], "paper_placeholder": false, "slug": "MADNESS", "idx": 17, "overview": "MADNESS (Multiresolution Adaptive Numerical Environment for Scientific Simulation) is a high-performance computational chemistry and physics package using multiresolution adaptive numerical methods based on multiwavelet basis functions. Developed primarily at Oak Ridge National Laboratory, MADNESS provides systematic, guaranteed-precision calculations with adaptive resolution and excellent parallel scalability. It represents a fundamentally different numerical approach compared to traditional pl" }, { "num": "019", "name": "OpenAtom", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://charm.cs.illinois.edu/OpenAtom/", "note": "", "md_link_text": "OpenAtom.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/OpenAtom.md", "papers": [], "paper_placeholder": true, "slug": "OpenAtom", "idx": 18, "overview": "OpenAtom is a massively parallel ab initio molecular dynamics code developed at the University of Illinois at Urbana-Champaign using the Charm++ parallel programming framework. It implements plane-wave DFT with Car-Parrinello and Born-Oppenheimer molecular dynamics, designed to scale to thousands of processors through advanced parallel algorithms and adaptive load balancing. OpenAtom represents a modern approach to parallelizing quantum chemistry simulations." }, { "num": "020", "name": "PWDFT", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://github.com/ebylaska/PWDFT", "note": "", "md_link_text": "PWDFT.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/PWDFT.md", "papers": [ { "name": "PWDFT_jl_10.1016_j.cpc.2020.107372.pdf", "path": "Papers_of_Codes/DFT/PWDFT_jl/PWDFT_jl_10.1016_j.cpc.2020.107372.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2020.107372" } ], "paper_placeholder": false, "slug": "PWDFT", "idx": 19, "overview": "PWDFT is a plane-wave density functional theory (DFT) code developed by Eric J. Bylaska at Pacific Northwest National Laboratory (PNNL). It serves as a research platform and mini-application for exploring high-performance computing algorithms, particularly in the context of plane-wave basis sets and pseudopotentials. It is related to the development of NWChem (where Bylaska is a key developer) but exists as a standalone repository for testing and development purposes." }, { "num": "021", "name": "PLATO", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "http://www.dl.ac.uk/TCSC/Software/PLATO/ (or CPC Library)", "note": "", "md_link_text": "PLATO.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/PLATO.md", "papers": [ { "name": "PLATO_10.1103_PhysRevB.62.4899.pdf", "path": "Papers_of_Codes/DFT/PLATO/PLATO_10.1103_PhysRevB.62.4899.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.62.4899" } ], "paper_placeholder": false, "slug": "PLATO", "idx": 20, "overview": "PLATO is a localized orbital-based electronic structure package developed by Andrew Horsfield, Steve Kenny, and collaborators (Imperial College London, UCL, Loughborough). It allows for both tight-binding and density functional theory (DFT) calculations within a single framework. PLATO is particularly noted for its efficiency in handling large systems using O(N) methods and its versatility in treating both orthogonal and non-orthogonal basis sets." }, { "num": "022", "name": "NESSIE", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://sourceforge.net/projects/nessie-code/", "note": "", "md_link_text": "NESSIE.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/NESSIE.md", "papers": [], "paper_placeholder": true, "slug": "NESSIE", "idx": 21, "overview": "NESSIE is a modern first-principles calculation software designed to address the need for high levels of numerical accuracy and high-performance in large-scale electronic structure simulations. It is hosted on SourceForge and aims to pioneer the fundamental study of quantum many-body effects." }, { "num": "023", "name": "DFT-FE", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://sites.google.com/umich.edu/dftfe/home", "note": "", "md_link_text": "DFT-FE.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/DFT-FE.md", "papers": [], "paper_placeholder": true, "slug": "DFT-FE", "idx": 22, "overview": "DFT-FE is a massively parallel real-space DFT code using adaptive finite-element discretization. Developed primarily at University of Michigan, DFT-FE enables large-scale first-principles calculations (100,000+ atoms) through higher-order finite elements and adaptive mesh refinement. It represents a modern approach to DFT using computational mathematics techniques different from traditional plane-wave or localized orbital methods." }, { "num": "023a", "name": "PEtot", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://psi-k.net/codes/petot", "note": "Large-scale plane-wave code, backend for PWtransport", "md_link_text": "PEtot.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/PEtot.md", "papers": [ { "name": "PEtot_10.1016_j.cpc.2012.08.002.pdf", "path": "Papers_of_Codes/DFT/PEtot/PEtot_10.1016_j.cpc.2012.08.002.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2012.08.002" } ], "paper_placeholder": false, "slug": "PEtot", "idx": 23, "overview": "PEtot is a plane-wave pseudopotential Density Functional Theory (DFT) code specifically designed for large-scale materials simulations. It employs norm-conserving and ultrasoft pseudopotentials and is renowned for its efficient parallelization capabilities, allowing it to scale to thousands of processors. It serves as a foundational engine for other codes, such as PWtransport for quantum transport calculations." }, { "num": "023b", "name": "S/PHI/nX", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://sxlib.mpie.de/", "note": "C++ library/code for electronic structure and defects", "md_link_text": "S-PHI-nX.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/S-PHI-nX.md", "papers": [ { "name": "10.1016_j.cpc.2010.09.016.pdf", "path": "Papers_of_Codes/materials_science_papers/11.7_Additional_Specialized/S_PHI_nX/10.1016_j.cpc.2010.09.016.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2010.09.016" } ], "paper_placeholder": false, "slug": "S-PHI-nX", "idx": 24, "overview": "S/PHI/nX is a C++ based library and software package for electronic structure theory, developed at the Max-Planck-Institut f\u00fcr Eisenforschung. It combines standard plane-wave pseudopotential density functional theory (DFT) with k.p theory and other specialized methods. It is built upon the SxAccelerate library, emphasizing modularity, efficient memory handling, and modern C++ design." }, { "num": "023c", "name": "KSSOLV", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "http://kssolv.org/", "note": "MATLAB toolbox for DFT (Version 2.0)", "md_link_text": "KSSOLV.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/KSSOLV.md", "papers": [ { "name": "KSSOLV_10.1016_j.cpc.2022.108424.pdf", "path": "Papers_of_Codes/DFT/KSSOLV/KSSOLV_10.1016_j.cpc.2022.108424.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2022.108424" } ], "paper_placeholder": false, "slug": "KSSOLV", "idx": 25, "overview": "KSSOLV (Kohn-Sham SOLVer) is a MATLAB toolbox designed for solving the Kohn-Sham equations for electronic structure calculations. It utilizes a plane-wave basis set and pseudopotentials. While originally developed for prototyping and educational purposes, KSSOLV 2.0 has evolved into a capable tool for research, enabling algorithm development and direct comparison with standard codes like Quantum ESPRESSO." }, { "num": "023d", "name": "DFTK", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://dftk.org/", "note": "Modern Julia-based Density Functional Toolkit", "md_link_text": "DFTK.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/DFTK.md", "papers": [ { "name": "DFTK_10.21105_jcon.00069.pdf", "path": "Papers_of_Codes/DFT/DFTK/DFTK_10.21105_jcon.00069.pdf", "doi_url": "https://doi.org/10.21105/jcon.00069" } ], "paper_placeholder": false, "slug": "DFTK", "idx": 26, "overview": "DFTK (Density-Functional Toolkit) is a modern software package for density-functional theory (DFT) calculations, written in the Julia programming language. It is designed to be mathematically understandable, flexible, and extensible. It is part of the growing JuliaMolSim ecosystem and aims to provide a platform for experimenting with new algorithms while maintaining performance competitive with standard C++/Fortran codes." }, { "num": "023e", "name": "PWDFT_jl", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://github.com/f-fathurrahman/PWDFT.jl", "note": "Julia implementation for education/prototyping", "md_link_text": "PWDFT_jl.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/PWDFT_jl.md", "papers": [ { "name": "PWDFT_jl_10.1016_j.cpc.2020.107372.pdf", "path": "Papers_of_Codes/DFT/PWDFT_jl/PWDFT_jl_10.1016_j.cpc.2020.107372.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2020.107372" } ], "paper_placeholder": false, "slug": "PWDFT_jl", "idx": 27, "overview": "PWDFT.jl is a Julia package designed to solve the Kohn-Sham equations using a plane-wave basis set and pseudopotentials. It focuses on providing a clear implementation of standard Plane-Wave DFT methods, making it suitable for educational purposes and for researchers who wish to understand the implementation details of plane-wave DFT codes." }, { "num": "023f", "name": "PWtransport", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "http://yemeng.site/", "note": "Quantum transport code based on PEtot backend", "md_link_text": "PWtransport.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/PWtransport.md", "papers": [ { "name": "PWtransport_10.1016_j.cpc.2020.107737.pdf", "path": "Papers_of_Codes/DFT/PWtransport/PWtransport_10.1016_j.cpc.2020.107737.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2020.107737" } ], "paper_placeholder": false, "slug": "PWtransport", "idx": 28, "overview": "PWtransport is a quantum transport code based on plane-wave pseudopotential Density Functional Theory. It utilizes the \"PEtot\" code as its electronic structure engine. It is designed to calculate transport properties of nanostructures using the non-equilibrium Green's function (NEGF) method or scattering state approaches combined with plane-wave DFT." }, { "num": "023g", "name": "DACAPO", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://wiki.fysik.dtu.dk/dacapo/", "note": "Historic ASE backend for surface science.", "md_link_text": "DACAPO.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/DACAPO.md", "papers": [], "paper_placeholder": true, "slug": "DACAPO", "idx": 29, "overview": "DACAPO is a pioneering plane-wave pseudopotential Density Functional Theory (DFT) code. Developed within the CAMPOS project at the Technical University of Denmark (DTU), it was the original electronic structure backend for the Atomic Simulation Environment (ASE). It utilizes ultrasoft pseudopotentials and was heavily used for surface science and catalysis research, laying the groundwork for many modern computational workflows." }, { "num": "023h", "name": "SIRIUS", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://github.com/electronic-structure/SIRIUS", "note": "GPU-accelerated electronic structure library.", "md_link_text": "SIRIUS.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/SIRIUS.md", "papers": [], "paper_placeholder": true, "slug": "SIRIUS", "idx": 30, "overview": "SIRIUS is a domain-specific library for electronic structure calculations, developed at the Swiss National Supercomputing Centre (CSCS). It implements providing a high-performance backend for plane-wave (PP-PW) and full-potential (FP-LAPW) DFT calculations. It is designed from the ground up for hybrid computing architectures (CPU+GPU) and serves as a backend for flagship codes like Quantum ESPRESSO as well as a standalone solver." }, { "num": "023i", "name": "eminus", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://wangenau.github.io/eminus/", "note": "Educational Python code for DFT prototyping.", "md_link_text": "eminus.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/eminus.md", "papers": [], "paper_placeholder": true, "slug": "eminus", "idx": 31, "overview": "eminus is a Pythonic electronic structure theory code implementing plane-wave density functional theory (DFT). It is built on top of NumPy and SciPy, prioritizing code readability, simplicity, and extensibility. It is widely used for educational purposes and rapid prototyping of DFT concepts." }, { "num": "023j", "name": "SimpleDFT", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "", "note": "Pedagogical skeleton of eminus.", "md_link_text": "SimpleDFT.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/SimpleDFT.md", "papers": [ { "name": "10.1016_j.cpc.2019.04.014.pdf", "path": "Papers_of_Codes/Niche/10.2_MLIPs_ACE_Linear/SIMPLE-NN/10.1016_j.cpc.2019.04.014.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2019.04.014" } ], "paper_placeholder": false, "slug": "SimpleDFT", "idx": 32, "overview": "SimpleDFT is a minimalist implementation of plane-wave Density Functional Theory in Python. It serves as the pedagogical prototype for the larger `eminus` project. It is stripped down to the absolute essentials to demonstrate the logic of a DFT code in the fewest possible lines of readable Python." }, { "num": "023k", "name": "DFTpy", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://gitlab.com/pavanello-research-group/dftpy", "note": "Pure Python Plane-Wave code for embedding and development.", "md_link_text": "DFTpy.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/DFTpy.md", "papers": [ { "name": "DFTpy_10.1002_wcms.1482.pdf", "path": "Papers_of_Codes/DFT/DFTpy/DFTpy_10.1002_wcms.1482.pdf", "doi_url": "https://doi.org/10.1002/wcms.1482" } ], "paper_placeholder": false, "slug": "DFTpy", "idx": 33, "overview": "DFTpy is a modern, pure Python framework for Orbital-Free Density Functional Theory (OF-DFT) and Kohn-Sham DFT (KS-DFT). It utilizes a plane-wave basis set represented on a real-space grid via Fast Fourier Transforms (FFTs). Developed at Rutgers University (Pavanello Research Group), it is designed to be highly modular, enabling the rapid development and testing of new functionals (especially Kinetic Energy Functionals), embedding potentials, and non-standard SCF drivers." }, { "num": "023l", "name": "dftworks", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://github.com/dftworks/dftworks", "note": "Experimental Density Functional Theory in Rust.", "md_link_text": "dftworks.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/dftworks.md", "papers": [], "paper_placeholder": true, "slug": "dftworks", "idx": 34, "overview": "dftworks is an experimental implementation of Density Functional Theory (DFT) written in the Rust programming language. It represents an exploration into using modern systems programming languages for electronic structure theory, prioritizing memory safety and concurrency without checking performance at the door." }, { "num": "023m", "name": "fhi98md", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "", "note": "Obsolete but historic pioneer (FHI Berlin).", "md_link_text": "fhi98md.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/fhi98md.md", "papers": [], "paper_placeholder": true, "slug": "fhi98md", "idx": 35, "overview": "fhi98md is a historic, pioneering plane-wave pseudopotential Density Functional Theory code developed at the Fritz Haber Institute (FHI) of the Max Planck Society in Berlin. Released in the late 1990s, it notably standardized the \"FHI\" pseudopotential format and the `.ini` input style used by many subsequent codes. It was a workhorse for Surface Science ab initio Molecular Dynamics (AIMD) before being superseded by codes like ABINIT and FHI-aims." }, { "num": "023n", "name": "QuantumATK", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://www.synopsys.com/silicon/quantumatk.html", "note": "Major commercial suite with Plane-Wave and LCAO engines.", "md_link_text": "QuantumATK.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/QuantumATK.md", "papers": [ { "name": "Giannozzi_et_al_2009.pdf", "path": "Papers_of_Codes/materials_science_papers/1.1_Plane-Wave_Pseudopotential_PAW_Methods/Quantum_ESPRESSO/Giannozzi_et_al_2009.pdf", "doi_url": "https://scholar.google.com/scholar?q=QuantumATK+Giannozzi+et+al+2009" } ], "paper_placeholder": false, "slug": "QuantumATK", "idx": 36, "overview": "QuantumATK (formerly Atomistix ToolKit) is a comprehensive software platform for atomic-scale modeling of materials, nanostructures, and devices. While it is famous for its NEGF transport capabilities using LCAO, it includes a robust **PlaneWave** calculator (PW) that allows for systematically improvable basis set calculations, making it a \"complete\" electronic structure suite." }, { "num": "023o", "name": "PWPP", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://github.com/hpjeonGIT/PWPP", "note": "Plane wave DFT using GTH pseudopotentials", "md_link_text": "PWPP.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/PWPP.md", "papers": [], "paper_placeholder": true, "slug": "PWPP", "idx": 37, "overview": "" }, { "num": "023p", "name": "cpw2000", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://github.com/jlm785/cpw2000", "note": "DFT pseudopotential plane-wave code", "md_link_text": "cpw2000.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/cpw2000.md", "papers": [], "paper_placeholder": true, "slug": "cpw2000", "idx": 38, "overview": "" }, { "num": "023q", "name": "SPHINX", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "http://www.sphinxlib.de/", "note": "GPL plane-wave pseudopotential DFT for large-scale parallel calculations", "md_link_text": "SPHINX.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/SPHINX.md", "papers": [ { "name": "10.1016_j.cpc.2010.09.016.pdf", "path": "Papers_of_Codes/materials_science_papers/11.7_Additional_Specialized/S_PHI_nX/10.1016_j.cpc.2010.09.016.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2010.09.016" } ], "paper_placeholder": false, "slug": "SPHINX", "idx": 39, "overview": "" }, { "num": "023r", "name": "OPIUM", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "http://opium.sourceforge.net/", "note": "GPL pseudopotential generator for ABINIT, QE, CASTEP", "md_link_text": "OPIUM.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/OPIUM.md", "papers": [], "paper_placeholder": true, "slug": "OPIUM", "idx": 40, "overview": "" }, { "num": "023s", "name": "APE", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.1", "subcategory": "Plane-Wave / Pseudopotential Codes", "confidence": "VERIFIED", "official_url": "https://ape.gitlab.io/ape/", "note": "GPL Atomic Pseudopotential Engine for SIESTA, Octopus, ABINIT, QE", "md_link_text": "APE.md", "md_link_path": "DFT/1.1_Plane-Wave_Pseudopotential/APE.md", "papers": [ { "name": "APE_10.1016_j.cpc.2007.11.003.pdf", "path": "Papers_of_Codes/DFT/APE/APE_10.1016_j.cpc.2007.11.003.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2007.11.003" } ], "paper_placeholder": false, "slug": "APE", "idx": 41, "overview": "" }, { "num": "024", "name": "WIEN2k", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "CONFIRMED", "official_url": "https://www.wien2k.at/", "note": "", "md_link_text": "WIEN2k.md", "md_link_path": "DFT/1.2_All-Electron/WIEN2k.md", "papers": [ { "name": "Blaha_et_al_2020.pdf", "path": "Papers_of_Codes/DFT/1.2_All-Electron/WIEN2k/Blaha_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=WIEN2k+Blaha+et+al+2020" } ], "paper_placeholder": false, "slug": "WIEN2k", "idx": 42, "overview": "WIEN2k is an all-electron full-potential (linearized) augmented plane-wave plus local orbitals [FP-(L)APW+lo] code for calculating crystal properties. It is one of the most accurate DFT implementations available, treating all electrons (including core electrons) without pseudopotentials. WIEN2k is particularly renowned for its precision in calculating electronic, magnetic, and spectroscopic properties, and is widely considered the gold standard for benchmarking other DFT codes." }, { "num": "025", "name": "Elk", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "CONFIRMED", "official_url": "http://elk.sourceforge.net/", "note": "", "md_link_text": "Elk.md", "md_link_path": "DFT/1.2_All-Electron/Elk.md", "papers": [], "paper_placeholder": true, "slug": "Elk", "idx": 43, "overview": "Elk (formerly Exciting) is an all-electron full-potential linearized augmented plane wave (FP-LAPW) code for determining electronic structure of crystalline solids and molecules. It implements advanced methods for optical and spectroscopic properties and is particularly suited for systems requiring accurate treatment of core electrons and precise electronic structure calculations." }, { "num": "026", "name": "Fleur", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "CONFIRMED", "official_url": "https://www.flapw.de/", "note": "", "md_link_text": "Fleur.md", "md_link_path": "DFT/1.2_All-Electron/Fleur.md", "papers": [ { "name": "Betzinger_et_al_2015.pdf", "path": "Papers_of_Codes/DFT/1.2_All-Electron/Fleur/Betzinger_et_al_2015.pdf", "doi_url": "https://scholar.google.com/scholar?q=Fleur+Betzinger+et+al+2015" } ], "paper_placeholder": false, "slug": "Fleur", "idx": 44, "overview": "Fleur is a feature-full, freely available FLAPW (Full-potential Linearized Augmented Plane Wave) code based on DFT, developed by the Forschungszentrum J\u00fclich. It provides accurate all-electron calculations with a modern, well-maintained codebase and extensive capabilities for magnetic systems." }, { "num": "027", "name": "exciting", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "CONFIRMED", "official_url": "https://exciting-code.org/", "note": "", "md_link_text": "exciting.md", "md_link_path": "TDDFT/2.2_Linear-Response_TDDFT/exciting.md", "papers": [ { "name": "10_1088_0953-8984_26_36_363202.pdf", "path": "Papers_of_Codes/TDDFT/2.2_Linear-Response_TDDFT/exciting/10_1088_0953-8984_26_36_363202.pdf", "doi_url": "https://scholar.google.com/scholar?q=exciting+10+1088+0953+8984+26+36+363202" } ], "paper_placeholder": false, "slug": "exciting", "idx": 45, "overview": "exciting is an all-electron full-potential linearized augmented planewave (FP-LAPW) code for DFT and beyond, with particular strength in optical and excited-state properties. It provides advanced capabilities for TDDFT, GW, and BSE calculations with a modern, open-source codebase." }, { "num": "028", "name": "Questaal", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "CONFIRMED", "official_url": "https://questaal.org/", "note": "", "md_link_text": "Questaal.md", "md_link_path": "DFT/1.2_All-Electron/Questaal.md", "papers": [ { "name": "Kotani_et_al_2007.pdf", "path": "Papers_of_Codes/DFT/1.2_All-Electron/Questaal/Kotani_et_al_2007.pdf", "doi_url": "https://scholar.google.com/scholar?q=Questaal+Kotani+et+al+2007" } ], "paper_placeholder": false, "slug": "Questaal", "idx": 46, "overview": "Questaal is a suite of codes for electronic structure calculations using DFT, QSGW (Quasiparticle Self-Consistent GW), and DMFT. It provides both all-electron (LMTO) and pseudopotential implementations with particular strength in strongly correlated systems and GW calculations." }, { "num": "029", "name": "RSPt", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://github.com/RSPt-code/RSPt", "note": "", "md_link_text": "RSPt.md", "md_link_path": "DFT/1.2_All-Electron/RSPt.md", "papers": [ { "name": "Wills_et_al_2010.pdf", "path": "Papers_of_Codes/DFT/1.2_All-Electron/RSPt/Wills_et_al_2010.pdf", "doi_url": "https://scholar.google.com/scholar?q=RSPt+Wills+et+al+2010" } ], "paper_placeholder": false, "slug": "RSPt", "idx": 47, "overview": "RSPt is a full-potential electronic structure code based on the linear muffin-tin orbital (LMTO) method in the atomic sphere approximation and full potential. Developed in Europe with strong Swedish contributions, RSPt specializes in relativistic calculations for complex materials, particularly heavy element systems, magnetic materials, and spectroscopy calculations using the full-potential approach with high accuracy." }, { "num": "030", "name": "KKR", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "http://www.ebert.cup.uni-muenchen.de/ (JuKKR host)", "note": "", "md_link_text": "KKR.md", "md_link_path": "DFT/1.2_All-Electron/KKR.md", "papers": [], "paper_placeholder": true, "slug": "KKR", "idx": 48, "overview": "**Method type**: Green's function DFT, multiple scattering **Primary implementations**: SPR-KKR, AkaiKKR, JuKKR, KKRnano" }, { "num": "031", "name": "JuKKR", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://github.com/JuDFTteam/jukkr", "note": "", "md_link_text": "JuKKR.md", "md_link_path": "DFT/1.2_All-Electron/JuKKR.md", "papers": [], "paper_placeholder": true, "slug": "JuKKR", "idx": 49, "overview": "JuKKR is a modern KKR (Korringa-Kohn-Rostoker) Green's function DFT code developed at Forschungszentrum J\u00fclich, Germany. Part of the JuDFT family of codes alongside Fleur, JuKKR provides comprehensive KKR method capabilities with modern Python interfaces (masci-tools, aiida-kkr) for high-throughput workflows and materials informatics. It implements the full-potential KKR method using multiple scattering theory for electronic structure, spectroscopy, and disordered alloys." }, { "num": "032", "name": "KKRnano", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://iffgit.fz-juelich.de/kkr/jukkr", "note": "", "md_link_text": "KKRnano.md", "md_link_path": "DFT/1.2_All-Electron/KKRnano.md", "papers": [ { "name": "KKRnano_10.1103_PhysRevB.85.235103.pdf", "path": "Papers_of_Codes/DFT/KKRnano/KKRnano_10.1103_PhysRevB.85.235103.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.85.235103" } ], "paper_placeholder": false, "slug": "KKRnano", "idx": 50, "overview": "KKRnano is a massively parallel implementation of the KKR (Korringa-Kohn-Rostoker) Green's function method, specifically designed and optimized for extreme-scale computing on leadership-class supercomputers. Developed at Forschungszentrum J\u00fclich, KKRnano enables KKR calculations for very large systems (thousands of atoms) and complex materials by efficiently scaling to hundreds of thousands of CPU cores. It represents the cutting-edge HPC variant of the JuKKR code family, focused on pushing the " }, { "num": "033", "name": "KKRhost", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://github.com/JuDFTteam/jukkr", "note": "", "md_link_text": "KKRhost.md", "md_link_path": "DFT/1.2_All-Electron/KKRhost.md", "papers": [], "paper_placeholder": true, "slug": "KKRhost", "idx": 51, "overview": "KKRhost is the host system calculation module within the JuKKR suite, implementing the full-potential Korringa-Kohn-Rostoker (KKR) Green's function method for crystalline solids. Developed at Forschungszentrum J\u00fclich, KKRhost calculates the electronic structure of perfect periodic crystals (the \"host\" system), providing the reference state for subsequent impurity calculations with KKRimp. It is part of the integrated JuKKR package for accurate all-electron DFT calculations." }, { "num": "034", "name": "FPLO", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://www.fplo.de/", "note": "", "md_link_text": "FPLO.md", "md_link_path": "DFT/1.2_All-Electron/FPLO.md", "papers": [ { "name": "FPLO_10.1103_PhysRevB.59.1743.pdf", "path": "Papers_of_Codes/DFT/FPLO/FPLO_10.1103_PhysRevB.59.1743.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.59.1743" } ], "paper_placeholder": false, "slug": "FPLO", "idx": 52, "overview": "FPLO (Full-Potential Local-Orbital minimum-basis) is a DFT code using local orbitals and the full-potential approach for highly accurate electronic structure calculations of solids. Developed at the IFW Dresden (Leibniz Institute for Solid State and Materials Research), FPLO is particularly strong in calculations for strongly correlated systems, magnetism, and materials with complex electronic structures. It combines the accuracy of full-potential methods with the efficiency of minimal basis set" }, { "num": "035", "name": "KKR-ASA", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://github.com/JuDFTteam/jukkr (ASA variant)", "note": "", "md_link_text": "KKR-ASA.md", "md_link_path": "DFT/1.2_All-Electron/KKR-ASA.md", "papers": [], "paper_placeholder": true, "slug": "KKR-ASA", "idx": 53, "overview": "KKR-ASA is the Atomic Sphere Approximation variant of the Korringa-Kohn-Rostoker Green's function method within the JuKKR suite. Developed at Forschungszentrum J\u00fclich, KKR-ASA provides efficient electronic structure calculations by using the atomic sphere approximation (ASA), where the potential is approximated as spherically symmetric within non-overlapping atomic spheres. While less accurate than full-potential KKR, ASA offers significant computational speedup for dense systems and is well-sui" }, { "num": "036", "name": "AkaiKKR", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "http://kkr.issp.u-tokyo.ac.jp/", "note": "KKR Green's function code with CPA for disordered alloys/magnetism (ISSP Tokyo)", "md_link_text": "AkaiKKR.md", "md_link_path": "DFT/1.2_All-Electron/AkaiKKR.md", "papers": [], "paper_placeholder": true, "slug": "AkaiKKR", "idx": 54, "overview": "AkaiKKR is a Korringa-Kohn-Rostoker (KKR) Green's function DFT code developed in Japan, primarily at the Institute for Solid State Physics (ISSP), University of Tokyo. Named after Professor Hisazumi Akai, the code specializes in electronic structure calculations for magnetic materials, disordered alloys, and complex magnetic structures using the KKR multiple scattering method. It is particularly strong in treating substitutional disorder via the coherent potential approximation (CPA)." }, { "num": "037", "name": "SPR-KKR", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://www.ebert.cup.uni-muenchen.de/index.php/en/software-en/13-sprkkr", "note": "Fully relativistic KKR for spectroscopy (XAS/XMCD) and magnetism (LMU Munich)", "md_link_text": "SPR-KKR.md", "md_link_path": "DFT/1.2_All-Electron/SPR-KKR.md", "papers": [ { "name": "Ebert_et_al_2011.pdf", "path": "Papers_of_Codes/DFT/1.2_All-Electron/SPR-KKR/Ebert_et_al_2011.pdf", "doi_url": "https://scholar.google.com/scholar?q=SPR-KKR+Ebert+et+al+2011" } ], "paper_placeholder": false, "slug": "SPR-KKR", "idx": 55, "overview": "SPR-KKR is a Korringa-Kohn-Rostoker (KKR) Green's function DFT code developed at Ludwig-Maximilians-Universit\u00e4t M\u00fcnchen (LMU Munich), Germany. It specializes in fully relativistic calculations for magnetic materials, surfaces, and disordered alloys using the KKR multiple scattering method with spin-polarization and relativistic effects. SPR-KKR is particularly powerful for spectroscopy calculations and complex magnetic structures." }, { "num": "037a", "name": "EMTO", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://emto.gitlab.io/", "note": "", "md_link_text": "EMTO.md", "md_link_path": "DFT/1.2_All-Electron/EMTO.md", "papers": [ { "name": "EMTO_10.1016_S0927-0256(99)00098-1.pdf", "path": "Papers_of_Codes/DFT/EMTO/EMTO_10.1016_S0927-0256%2899%2900098-1.pdf", "doi_url": "https://doi.org/10.1016/S0927-0256(99)00098-1" } ], "paper_placeholder": false, "slug": "EMTO", "idx": 56, "overview": "**EMTO** is a specialized all-electron Density Functional Theory (DFT) code based on the Exact Muffin-Tin Orbitals (EMTO) theory. It is particularly renowned for its implementation of the **Coherent Potential Approximation (CPA)**, making it one of the premier tools for studying disordered alloys, paramagnetic states, and high-entropy alloys where chemical disorder is non-trivial." }, { "num": "037b", "name": "AngstromCube", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://github.com/real-space/AngstromCube", "note": "", "md_link_text": "AngstromCube.md", "md_link_path": "DFT/1.2_All-Electron/AngstromCube.md", "papers": [], "paper_placeholder": true, "slug": "AngstromCube", "idx": 57, "overview": "AngstromCube is a high-performance Density Functional Theory (DFT) code designed for large-scale all-electron calculations. It employs a real-space finite-difference formulation, allowing for efficient parallelization and O(N) linear scaling. The code is specifically optimized for modern hardware, featuring native GPU acceleration to handle systems with thousands of atoms." }, { "num": "037c", "name": "MuST", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://github.com/mstsuite/MuST", "note": "", "md_link_text": "MuST.md", "md_link_path": "DFT/1.2_All-Electron/MuST.md", "papers": [], "paper_placeholder": true, "slug": "MuST", "idx": 58, "overview": "MuST is an open-source ab initio electronic structure suite based on Multiple Scattering Theory (MST). It integrates the Korringa-Kohn-Rostoker (KKR) Green function method and the Locally Self-consistent Multiple Scattering (LSMS) method. It is unique in its ability to handle disordered materials (via CPA) and scale to petascale/exascale computing systems for massive all-electron calculations." }, { "num": "037d", "name": "ErgoSCF", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "http://www.ergoscf.org/", "note": "", "md_link_text": "ErgoSCF.md", "md_link_path": "DFT/1.2_All-Electron/ErgoSCF.md", "papers": [ { "name": "ErgoSCF_10.1016_j.softx.2018.03.005.pdf", "path": "Papers_of_Codes/DFT/ErgoSCF/ErgoSCF_10.1016_j.softx.2018.03.005.pdf", "doi_url": "https://doi.org/10.1016/j.softx.2018.03.005" } ], "paper_placeholder": false, "slug": "ErgoSCF", "idx": 59, "overview": "ErgoSCF is a quantum chemistry program designed for large-scale, linear-scaling electronic structure calculations. It works with Gaussian basis sets and enforces a strict all-electron methodology. The code is built for efficiency, utilizing modern techniques like fast multipole methods and sparse matrix algebra to handle large molecules and clusters." }, { "num": "037e", "name": "HelFEM", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://github.com/susilehtola/HelFEM", "note": "", "md_link_text": "HelFEM.md", "md_link_path": "DFT/1.2_All-Electron/HelFEM.md", "papers": [ { "name": "HelFEM_10.1002_qua.25945.pdf", "path": "Papers_of_Codes/DFT/HelFEM/HelFEM_10.1002_qua.25945.pdf", "doi_url": "https://doi.org/10.1002/qua.25945" } ], "paper_placeholder": false, "slug": "HelFEM", "idx": 60, "overview": "HelFEM (Helsinki Finite Element Method) is a software package for performing fully numerical electronic structure calculations on atoms and diatomic molecules. By using the Finite Element Method (FEM), it avoids the bias of basis set limits (like Gaussians or Slater orbitals), providing benchmark-quality all-electron results." }, { "num": "037f", "name": "TOMBO", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://www.tombo.page/", "note": "", "md_link_text": "TOMBO.md", "md_link_path": "DFT/1.2_All-Electron/TOMBO.md", "papers": [ { "name": "TOMBO_10.1016_j.cpc.2014.11.012.pdf", "path": "Papers_of_Codes/DFT/TOMBO/TOMBO_10.1016_j.cpc.2014.11.012.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2014.11.012" } ], "paper_placeholder": false, "slug": "TOMBO", "idx": 61, "overview": "TOMBO (TOhoku Mixed-Basis Orbitals) is an all-electron ab initio simulation code. It utilizes a unique mixed-basis set approach, combining plane waves with atomic orbitals. This allows it to accurately describe both the localized core electron states and the extended valence/conduction states, making it applicable to a wide variety of systems from clusters to periodic crystals." }, { "num": "037g", "name": "fem-tddft", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://github.com/brandonwood/fem-tddft", "note": "", "md_link_text": "fem-tddft.md", "md_link_path": "DFT/1.2_All-Electron/fem-tddft.md", "papers": [], "paper_placeholder": true, "slug": "fem-tddft", "idx": 62, "overview": "fem-tddft is a real-space Density Functional Theory (DFT) and Time-Dependent DFT (TDDFT) code built upon the finite-element method (FEM). It leverages the deal.II finite element library to provide high spatial resolution and flexible mesh adaptivity, making it particularly suitable for studying materials from first principles where complex geometries or local field enhancements are important." }, { "num": "037h", "name": "BERTHA", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://github.com/BERTHA-4c-DKS/pybertha", "note": "", "md_link_text": "BERTHA.md", "md_link_path": "DFT/1.2_All-Electron/BERTHA.md", "papers": [ { "name": "BERTHA_10.1063_5.0002831.pdf", "path": "Papers_of_Codes/DFT/BERTHA/BERTHA_10.1063_5.0002831.pdf", "doi_url": "https://doi.org/10.1063/5.0002831" } ], "paper_placeholder": false, "slug": "BERTHA", "idx": 63, "overview": "BERTHA is a state-of-the-art relativistic Density Functional Theory (DFT) code. It implements the full four-component Dirac-Kohn-Sham (DKS) formalism, enabling highly accurate electronic structure calculations for systems containing heavy elements where relativistic effects are dominant. The code has recently evolved to include Python bindings (PyBERTHA), making it accessible for modern scripting workflows." }, { "num": "037i", "name": "ReSpect", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "http://www.respectprogram.org/", "note": "", "md_link_text": "ReSpect.md", "md_link_path": "DFT/1.2_All-Electron/ReSpect.md", "papers": [ { "name": "ReSpect_10.1063_5.0005094.pdf", "path": "Papers_of_Codes/DFT/ReSpect/ReSpect_10.1063_5.0005094.pdf", "doi_url": "https://doi.org/10.1063/5.0005094" } ], "paper_placeholder": false, "slug": "ReSpect", "idx": 64, "overview": "ReSpect (Relativistic Spectroscopy) is a specialized computational chemistry program designed for the prediction of molecular properties and spectroscopy of heavy-element systems. It combines all-electron Density Functional Theory (DFT) with rigorous relativistic Hamiltonians to calculate parameters such as NMR and EPR properties with high precision." }, { "num": "037j", "name": "HUTSEPOT", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://www.jku.at/institut-fuer-theoretische-physik/forschung/abteilung-fuer-vielteilchensysteme/research/hutsepot", "note": "", "md_link_text": "HUTSEPOT.md", "md_link_path": "DFT/1.2_All-Electron/HUTSEPOT.md", "papers": [], "paper_placeholder": true, "slug": "HUTSEPOT", "idx": 65, "overview": "HUTSEPOT is a versatile, all-electron Density Functional Theory (DFT) code based on the Korringa-Kohn-Rostoker (KKR) Green's function method. Developed at the Institute for Theoretical Physics at Johannes Kepler University (JKU) Linz, it is specifically designed to handle complex electronic structure problems involving disorder, surfaces, and nanostructures where periodic boundary conditions might be broken or require special treatment." }, { "num": "037k", "name": "DIRAC", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.2", "subcategory": "All-Electron Codes", "confidence": "VERIFIED", "official_url": "https://www.diracprogram.org/", "note": "", "md_link_text": "DIRAC.md", "md_link_path": "DFT/1.2_All-Electron/DIRAC.md", "papers": [ { "name": "Saue_et_al_2020.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/DIRAC/Saue_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=DIRAC+Saue+et+al+2020" } ], "paper_placeholder": false, "slug": "DIRAC", "idx": 66, "overview": "DIRAC (Program for Atomic and Molecular Direct Iterative Relativistic All-electron Calculations) is the premier general-purpose relativistic quantum chemistry program. It is designed to treat relativistic effects in molecules with the highest possible accuracy, serving as a benchmark for approximate methods. It enables all-electron calculations using the 4-component Dirac-Coulomb implementation of both Density Functional Theory (DFT) and wavefunction-based correlation methods." }, { "num": "038", "name": "FHI-aims", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "CONFIRMED", "official_url": "https://fhi-aims.org/", "note": "", "md_link_text": "FHI-aims.md", "md_link_path": "DFT/1.3_Localized_Basis/FHI-aims.md", "papers": [ { "name": "10.1016_j.cpc.2009.06.022.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/FHI-aims/10.1016_j.cpc.2009.06.022.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2009.06.022" }, { "name": "Blum_et_al_2009.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/FHI-aims/Blum_et_al_2009.pdf", "doi_url": "https://scholar.google.com/scholar?q=FHI-aims+Blum+et+al+2009" } ], "paper_placeholder": false, "slug": "FHI-aims", "idx": 67, "overview": "FHI-aims (Fritz Haber Institute ab initio molecular simulations) is an all-electron, full-potential electronic structure code using numeric atom-centered orbitals (NAO). It provides exceptional accuracy and efficiency for molecules and materials, with particular strengths in van der Waals interactions, hybrid functionals, and advanced beyond-DFT methods including GW and RPA." }, { "num": "039", "name": "SIESTA", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "CONFIRMED", "official_url": "https://siesta-project.org/", "note": "", "md_link_text": "SIESTA.md", "md_link_path": "DFT/1.3_Localized_Basis/SIESTA.md", "papers": [ { "name": "Soler_et_al_2002.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/SIESTA/Soler_et_al_2002.pdf", "doi_url": "https://scholar.google.com/scholar?q=SIESTA+Soler+et+al+2002" } ], "paper_placeholder": false, "slug": "SIESTA", "idx": 68, "overview": "SIESTA (Spanish Initiative for Electronic Simulations with Thousands of Atoms) is an efficient DFT code using strictly localized numerical atomic orbital basis sets. It excels at large-scale calculations with linear-scaling capabilities and is particularly strong for low-dimensional systems, molecules, and quantum transport calculations via TranSIESTA." }, { "num": "040", "name": "OpenMX", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "CONFIRMED", "official_url": "http://www.openmx-square.org/", "note": "", "md_link_text": "OpenMX.md", "md_link_path": "DFT/1.3_Localized_Basis/OpenMX.md", "papers": [ { "name": "Ozaki_2003.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/OpenMX/Ozaki_2003.pdf", "doi_url": "https://scholar.google.com/scholar?q=OpenMX+Ozaki+2003" } ], "paper_placeholder": false, "slug": "OpenMX", "idx": 69, "overview": "OpenMX (Open source package for Material eXplorer) is an efficient DFT code using localized pseudo-atomic orbitals (PAO) with particular strength in large-scale calculations, non-collinear magnetism, and spin-orbit coupling. It provides excellent performance for complex magnetic systems, topological materials, and spintronics applications." }, { "num": "041", "name": "CONQUEST", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "CONFIRMED", "official_url": "https://www.order-n.org/", "note": "", "md_link_text": "CONQUEST.md", "md_link_path": "DFT/1.3_Localized_Basis/CONQUEST.md", "papers": [ { "name": "Bowler_Miyazaki_2012.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/CONQUEST/Bowler_Miyazaki_2012.pdf", "doi_url": "https://scholar.google.com/scholar?q=CONQUEST+Bowler+Miyazaki+2012" } ], "paper_placeholder": false, "slug": "CONQUEST", "idx": 70, "overview": "CONQUEST is a linear-scaling (O(N)) DFT code designed for massively parallel calculations on extremely large systems (up to millions of atoms). It uses local orbital basis sets and achieves excellent parallel scalability, making it ideal for biomolecules, nanostructures, and large-scale materials simulations on supercomputers." }, { "num": "042", "name": "ONETEP", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "CONFIRMED", "official_url": "https://onetep.org/", "note": "", "md_link_text": "ONETEP.md", "md_link_path": "DFT/1.3_Localized_Basis/ONETEP.md", "papers": [ { "name": "Skylaris_et_al_2005.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/ONETEP/Skylaris_et_al_2005.pdf", "doi_url": "https://scholar.google.com/scholar?q=ONETEP+Skylaris+et+al+2005" } ], "paper_placeholder": false, "slug": "ONETEP", "idx": 71, "overview": "ONETEP (Order-N Electronic Total Energy Package) is a linear-scaling DFT code that achieves plane-wave accuracy with localized orbitals. It uniquely combines the accuracy of plane-wave calculations with the efficiency of linear-scaling methods through Non-orthogonal Generalized Wannier Functions (NGWFs), enabling calculations on systems with thousands to tens of thousands of atoms." }, { "num": "043", "name": "BigDFT", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "CONFIRMED", "official_url": "https://bigdft.org/", "note": "", "md_link_text": "BigDFT.md", "md_link_path": "DFT/1.3_Localized_Basis/BigDFT.md", "papers": [ { "name": "Genovese_et_al_2010.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/BigDFT/Genovese_et_al_2010.pdf", "doi_url": "https://scholar.google.com/scholar?q=BigDFT+Genovese+et+al+2010" } ], "paper_placeholder": false, "slug": "BigDFT", "idx": 72, "overview": "BigDFT is a DFT code using Daubechies wavelets as a basis set, providing systematic convergence and efficient treatment of systems in vacuum, surfaces, and periodic systems. It features linear-scaling capabilities, excellent support for massively parallel calculations, early GPU adoption, and a comprehensive Python interface (PyBigDFT) for workflow automation." }, { "num": "044", "name": "CRYSTAL", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "CONFIRMED", "official_url": "http://www.crystal.unito.it/", "note": "", "md_link_text": "CRYSTAL.md", "md_link_path": "DFT/1.3_Localized_Basis/CRYSTAL.md", "papers": [ { "name": "Dovesi_et_al_2018.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/CRYSTAL/Dovesi_et_al_2018.pdf", "doi_url": "https://scholar.google.com/scholar?q=CRYSTAL+Dovesi+et+al+2018" } ], "paper_placeholder": false, "slug": "CRYSTAL", "idx": 73, "overview": "CRYSTAL is a quantum chemistry program for the study of crystalline solids using Gaussian-type basis functions. It provides ab initio treatment of periodic systems with particular strength in molecular crystals, surfaces, hybrid functionals, and comprehensive spectroscopic properties. CRYSTAL was one of the first codes to implement periodic Hartree-Fock and remains highly competitive for hybrid functional calculations on solids." }, { "num": "045", "name": "ADF", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://www.scm.com/", "note": "", "md_link_text": "ADF.md", "md_link_path": "DFT/1.3_Localized_Basis/ADF.md", "papers": [ { "name": "te_Velde_et_al_2001.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/ADF/te_Velde_et_al_2001.pdf", "doi_url": "https://scholar.google.com/scholar?q=ADF+te+Velde+et+al+2001" } ], "paper_placeholder": false, "slug": "ADF", "idx": 74, "overview": "ADF (Amsterdam Density Functional) is a powerful DFT program particularly known for its Slater-type orbital (STO) basis sets, advanced relativistic methods, and spectroscopic property calculations. Developed by SCM (Software for Chemistry & Materials) in the Netherlands, ADF excels at molecular calculations, transition metal chemistry, spectroscopy, and accurate treatment of heavy elements. It is part of the Amsterdam Modeling Suite alongside BAND, DFTB, ReaxFF, and other modules." }, { "num": "046", "name": "DMol\u00b3", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://dmol3.web.psi.ch/dmol3.html (Commercial DFT package)", "note": "", "md_link_text": "DMol3.md", "md_link_path": "DFT/1.3_Localized_Basis/DMol3.md", "papers": [ { "name": "DMol\u00b3_10.1063_1.1316015.pdf", "path": "Papers_of_Codes/DFT/DMol\u00b3/DMol\u00b3_10.1063_1.1316015.pdf", "doi_url": "https://doi.org/10.1063/1.1316015" }, { "name": "DMol\u00b3_10.1063_1.1316015.pdf", "path": "Papers_of_Codes/DFT/DMol%C2%B3/DMol%C2%B3_10.1063_1.1316015.pdf", "doi_url": "https://doi.org/10.1063/1.1316015" } ], "paper_placeholder": false, "slug": "DMol", "idx": 75, "overview": "DMol3 is a DFT quantum mechanical code using numerical atomic orbitals, included as a key module in BIOVIA Materials Studio. Originally developed by Biosym Technologies (now part of Dassault Syst\u00e8mes BIOVIA), DMol3 is particularly efficient for molecules, clusters, and surfaces, with excellent speed and accuracy using localized basis functions. It's widely used in pharmaceuticals, materials science, and catalysis research." }, { "num": "047", "name": "deMon2k", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://demon-software.com/", "note": "", "md_link_text": "deMon2k.md", "md_link_path": "DFT/1.3_Localized_Basis/deMon2k.md", "papers": [ { "name": "10_1002_wcms_68.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/deMon2k/10_1002_wcms_68.pdf", "doi_url": "https://scholar.google.com/scholar?q=deMon2k+10+1002+wcms+68" } ], "paper_placeholder": false, "slug": "deMon2k", "idx": 76, "overview": "deMon2k (density of Montreal 2000) is a DFT software package using auxiliary density functional theory (ADFT) with Gaussian basis sets. Developed through international collaboration led from Mexico, deMon2k uses variational fitting of the Coulomb potential (density fitting) to achieve computational efficiency while maintaining accuracy. It is particularly known for its efficient implementation and focus on molecular systems." }, { "num": "048a", "name": "BAND", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://www.scm.com/product/band/", "note": "", "md_link_text": "BAND.md", "md_link_path": "DFT/1.3_Localized_Basis/BAND.md", "papers": [ { "name": "10_1103_PhysRevB_89_041407.pdf", "path": "Papers_of_Codes/Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/BandUP/10_1103_PhysRevB_89_041407.pdf", "doi_url": "https://scholar.google.com/scholar?q=BAND+10+1103+PhysRevB+89+041407" }, { "name": "10_1103_PhysRevB_91_041116.pdf", "path": "Papers_of_Codes/Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/BandUP/10_1103_PhysRevB_91_041116.pdf", "doi_url": "https://scholar.google.com/scholar?q=BAND+10+1103+PhysRevB+91+041116" } ], "paper_placeholder": false, "slug": "BAND", "idx": 77, "overview": "BAND is the periodic Density Functional Theory (DFT) code within the Amsterdam Modeling Suite (AMS). Unlike most periodic codes that use plane waves (like VASP or QE), BAND utilizes atom-centered numerical orbitals (STOs/NAOs). This basis set allows for an accurate treatment of both core and valence electrons and makes the code particularly efficient for low-dimensional systems (1D polymers, 2D slabs) and empty space." }, { "num": "048b", "name": "OLCAO", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://github.com/UMKC-CPG/olcao", "note": "Orthogonalized LCAO all-electron DFT code (UMKC)", "md_link_text": "OLCAO.md", "md_link_path": "DFT/1.3_Localized_Basis/OLCAO.md", "papers": [ { "name": "OLCAO_10.22369_issn.2153-4136_3_2_5.pdf", "path": "Papers_of_Codes/DFT/OLCAO/OLCAO_10.22369_issn.2153-4136_3_2_5.pdf", "doi_url": "https://doi.org/10.22369/issn.2153-4136_3_2_5" } ], "paper_placeholder": false, "slug": "OLCAO", "idx": 78, "overview": "OLCAO is an all-electron, density functional theory-based electronic structure code that uses local atomic orbitals for basis expansion. Developed at the University of Missouri-Kansas City (UMKC), it is designed for efficient analysis of large and complex material systems including semiconductors, insulators, metals, alloys, complex crystals, glasses, and biomolecular systems." }, { "num": "048c", "name": "HONPAS", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://github.com/honpas/honpas", "note": "Linear-scaling NAO DFT with hybrid functionals (USTC)", "md_link_text": "HONPAS.md", "md_link_path": "DFT/1.3_Localized_Basis/HONPAS.md", "papers": [ { "name": "HONPAS_10.1002_qua.24837.pdf", "path": "Papers_of_Codes/DFT/HONPAS/HONPAS_10.1002_qua.24837.pdf", "doi_url": "https://doi.org/10.1002/qua.24837" } ], "paper_placeholder": false, "slug": "HONPAS", "idx": 79, "overview": "HONPAS is an ab initio electronic structure calculation software package designed for linear-scaling first-principles DFT calculations on large-scale systems. Developed at the University of Science and Technology of China (USTC), it uses numerical atomic orbitals (NAOs) and is built upon the SIESTA methodology. HONPAS enables calculations on systems with tens of thousands of atoms using hybrid functionals." }, { "num": "048d", "name": "FreeON", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://github.com/FreeON/freeon", "note": "O(N) linear-scaling molecular DFT (formerly MondoSCF)", "md_link_text": "FreeON.md", "md_link_path": "DFT/1.3_Localized_Basis/FreeON.md", "papers": [ { "name": "10.1063_1.473575.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/FreeON/10.1063_1.473575.pdf", "doi_url": "https://doi.org/10.1063/1.473575" } ], "paper_placeholder": false, "slug": "FreeON", "idx": 80, "overview": "FreeON is an experimental, open-source suite of programs for linear-scaling quantum chemistry calculations. Formerly known as MondoSCF, it performs Hartree-Fock, pure DFT, and hybrid DFT calculations using a Cartesian-Gaussian LCAO basis. FreeON emphasizes O(N) and O(N log N) algorithms for non-metallic systems." }, { "num": "048e", "name": "SEQQUEST", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://dft.sandia.gov/quest/", "note": "Sandia National Lab LCAO-Gaussian DFT code", "md_link_text": "SEQQUEST.md", "md_link_path": "DFT/1.3_Localized_Basis/SEQQUEST.md", "papers": [], "paper_placeholder": true, "slug": "SEQQUEST", "idx": 81, "overview": "SEQQUEST (Sequential Quantum Electronic Structure Tool) is a general-purpose electronic structure code developed at Sandia National Laboratories for computing energies and forces of molecules, periodic surfaces (slabs), and bulk solids. It uses the LCAO approach with contracted-Gaussian basis sets and norm-conserving pseudopotentials, with linear-scaling algorithms for Hamiltonian generation." }, { "num": "048f", "name": "AIMPRO", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "http://aimpro.ncl.ac.uk/", "note": "Gaussian-based defect physics DFT (Newcastle)", "md_link_text": "AIMPRO.md", "md_link_path": "DFT/1.3_Localized_Basis/AIMPRO.md", "papers": [ { "name": "10.1002_(SICI)1521-3951(200001)217_1_131__AID-PSSB131_3.0.CO;2-M.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/AIMPRO/10.1002_%28SICI%291521-3951%28200001%29217_1_131__AID-PSSB131_3.0.CO;2-M.pdf", "doi_url": "https://doi.org/10.1002/(SICI)1521-3951(200001)217_1_131__AID-PSSB131_3.0.CO;2-M" }, { "name": "10_1002_SICI1521-3951200001217_1<131__AID-PSSB131>3_0_CO;2-M.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/AIMPRO/10_1002_SICI1521-3951200001217_1<131__AID-PSSB131>3_0_CO;2-M.pdf", "doi_url": "https://scholar.google.com/scholar?q=AIMPRO+10+1002+SICI1521+3951200001217+1%3C131+AID+PSSB131%3E3+0+CO%3B2+M" } ], "paper_placeholder": false, "slug": "AIMPRO", "idx": 82, "overview": "AIMPRO is an ab initio DFT code that uses localized Gaussian orbitals and pseudopotentials for materials modeling. Developed at Newcastle University, it is particularly well-suited for defect calculations, semiconductor physics, and understanding the electronic structure of complex materials systems." }, { "num": "048g", "name": "FLOSIC", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://github.com/FLOSIC", "note": "Fermi-L\u00f6wdin Orbital Self-Interaction Correction", "md_link_text": "FLOSIC.md", "md_link_path": "DFT/1.3_Localized_Basis/FLOSIC.md", "papers": [], "paper_placeholder": true, "slug": "FLOSIC", "idx": 83, "overview": "FLOSIC is an electronic structure code that implements the Fermi-L\u00f6wdin Orbital Self-Interaction Correction (FLO-SIC) method to address self-interaction errors in standard DFT calculations. Built upon NRLMOL, it uses Gaussian orbitals and provides improved predictions for orbital energies, ionization potentials, and electron affinities." }, { "num": "048h", "name": "RESCU", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://www.nanoacademic.com/rescu", "note": "Large-scale NAO/PW/real-space hybrid DFT solver", "md_link_text": "RESCU.md", "md_link_path": "DFT/1.3_Localized_Basis/RESCU.md", "papers": [ { "name": "RESCU_10.1016_j.jcp.2015.12.014.pdf", "path": "Papers_of_Codes/DFT/RESCU/RESCU_10.1016_j.jcp.2015.12.014.pdf", "doi_url": "https://doi.org/10.1016/j.jcp.2015.12.014" } ], "paper_placeholder": false, "slug": "RESCU", "idx": 84, "overview": "RESCU is a Kohn-Sham DFT solver that combines multiple basis set approaches (atomic orbitals, plane waves, real-space grids) within a single framework. Developed primarily in MATLAB with C extensions, it is designed for large-scale simulations of materials containing thousands to tens of thousands of atoms with modest computational resources." }, { "num": "048i", "name": "PyDFT", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://github.com/ifilot/pydft", "note": "Educational pure Python GTO-based DFT", "md_link_text": "PyDFT.md", "md_link_path": "DFT/1.3_Localized_Basis/PyDFT.md", "papers": [], "paper_placeholder": true, "slug": "PyDFT", "idx": 85, "overview": "PyDFT is a pure-Python package for performing localized-orbital DFT calculations using Gaussian Type Orbitals (GTOs). Designed primarily for educational purposes, it provides insights into the inner workings of DFT calculations while remaining a fully functional DFT code for small molecular systems." }, { "num": "048j", "name": "ACE-Molecule", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://gitlab.com/acemol/ace-molecule", "note": "Real-space hybrid DFT for molecules/periodic systems", "md_link_text": "ACE-Molecule.md", "md_link_path": "DFT/1.3_Localized_Basis/ACE-Molecule.md", "papers": [ { "name": "ACE-Molecule_10.1063_5.0002959.pdf", "path": "Papers_of_Codes/DFT/ACE-Molecule/ACE-Molecule_10.1063_5.0002959.pdf", "doi_url": "https://doi.org/10.1063/5.0002959" } ], "paper_placeholder": false, "slug": "ACE-Molecule", "idx": 86, "overview": "ACE-Molecule is an open-source, real-space quantum chemistry package for density functional theory calculations. It supports both molecular (non-periodic) and periodic systems, with a focus on efficient hybrid DFT and wave-function theory calculations. Written in C++ with a Python interface, it provides modern computational capabilities." }, { "num": "048k", "name": "Fermi.jl", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://github.com/FermiQC/Fermi.jl", "note": "Julia quantum chemistry with GTO basis", "md_link_text": "Fermi_jl.md", "md_link_path": "DFT/1.3_Localized_Basis/Fermi_jl.md", "papers": [ { "name": "Fermi.jl_10.1021_acs.jctc.1c00719.pdf", "path": "Papers_of_Codes/DFT/Fermi.jl/Fermi.jl_10.1021_acs.jctc.1c00719.pdf", "doi_url": "https://doi.org/10.1021/acs.jctc.1c00719" } ], "paper_placeholder": false, "slug": "Fermi.jl", "idx": 87, "overview": "Fermi.jl is a quantum chemistry program written in Julia, designed for electronic structure calculations using Gaussian-type atomic orbitals. It leverages Julia's high-performance and composable nature to provide both production-level calculations and an accessible platform for method development." }, { "num": "048l", "name": "MESS", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://github.com/graphcore-research/mess", "note": "JAX-based differentiable DFT (Graphcore, 2024)", "md_link_text": "MESS.md", "md_link_path": "DFT/1.3_Localized_Basis/MESS.md", "papers": [ { "name": "MESS_10.48550_arXiv.2406.03121.pdf", "path": "Papers_of_Codes/DFT/MESS/MESS_10.48550_arXiv.2406.03121.pdf", "doi_url": "https://doi.org/10.48550/arXiv.2406.03121" } ], "paper_placeholder": false, "slug": "MESS", "idx": 88, "overview": "MESS is an open-source Python package for electronic structure simulations implemented in JAX. Released by Graphcore Research in 2024, it is designed to integrate electronic structure calculations with machine learning workflows, leveraging JAX's automatic differentiation and GPU/TPU acceleration capabilities." }, { "num": "048m", "name": "PyFLOSIC", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://github.com/pyflosic/pyflosic", "note": "Python SIC implementation built on PySCF", "md_link_text": "PyFLOSIC.md", "md_link_path": "DFT/1.3_Localized_Basis/PyFLOSIC.md", "papers": [ { "name": "PyFLOSIC_10.1063_5.0012519.pdf", "path": "Papers_of_Codes/DFT/PyFLOSIC/PyFLOSIC_10.1063_5.0012519.pdf", "doi_url": "https://doi.org/10.1063/5.0012519" } ], "paper_placeholder": false, "slug": "PyFLOSIC", "idx": 89, "overview": "PyFLOSIC is a Python implementation of the Fermi-L\u00f6wdin Orbital Self-Interaction Correction (FLO-SIC) method built on top of PySCF. It provides an accessible interface for performing self-interaction corrected DFT calculations, improving orbital energies and other properties affected by self-interaction error." }, { "num": "048n", "name": "inq", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://github.com/LLNL/inq", "note": "GPU-native DFT/RT-TDDFT (LLNL)", "md_link_text": "inq.md", "md_link_path": "DFT/1.3_Localized_Basis/inq.md", "papers": [ { "name": "inq_10.1021_acs.jctc.1c00562.pdf", "path": "Papers_of_Codes/DFT/inq/inq_10.1021_acs.jctc.1c00562.pdf", "doi_url": "https://doi.org/10.1021/acs.jctc.1c00562" } ], "paper_placeholder": false, "slug": "inq", "idx": 90, "overview": "inq is a modern, GPU-accelerated electronic structure code for DFT and real-time TDDFT calculations, developed at Lawrence Livermore National Laboratory (LLNL). Written in C++, it is designed from scratch for GPU execution and focuses on nonequilibrium phenomena in materials." }, { "num": "048o", "name": "GBasis", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://github.com/theochem/gbasis", "note": "Python Gaussian integral library (QCDevs)", "md_link_text": "GBasis.md", "md_link_path": "DFT/1.3_Localized_Basis/GBasis.md", "papers": [], "paper_placeholder": true, "slug": "GBasis", "idx": 91, "overview": "GBasis is a Python library for evaluating and integrating Gaussian-type orbitals and integrals. Part of the QCDevs project and originating from the HORTON project, it provides a modular framework for computing molecular integrals, densities, and related quantities needed for quantum chemistry calculations." }, { "num": "048p", "name": "NRLMOL", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://www.flosic.org/", "note": "NRL massively parallel Gaussian DFT (FLOSIC base)", "md_link_text": "NRLMOL.md", "md_link_path": "DFT/1.3_Localized_Basis/NRLMOL.md", "papers": [ { "name": "10_1103_PhysRevB_54_7830.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/NRLMOL/10_1103_PhysRevB_54_7830.pdf", "doi_url": "https://scholar.google.com/scholar?q=NRLMOL+10+1103+PhysRevB+54+7830" }, { "name": "10_1103_PhysRevB_41_7453.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/NRLMOL/10_1103_PhysRevB_41_7453.pdf", "doi_url": "https://scholar.google.com/scholar?q=NRLMOL+10+1103+PhysRevB+41+7453" } ], "paper_placeholder": false, "slug": "NRLMOL", "idx": 92, "overview": "NRLMOL is a massively parallel Gaussian-based DFT code developed at the Naval Research Laboratory (NRL) for electronic structure calculations on molecules and clusters. It serves as the foundation for the FLOSIC code and has been extensively used for studies of clusters, nanoparticles, and finite systems." }, { "num": "048q", "name": "Erkale", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://github.com/susilehtola/erkale", "note": "X-ray spectroscopy, SIC-DFT, basis set development (Helsinki)", "md_link_text": "Erkale.md", "md_link_path": "DFT/1.3_Localized_Basis/Erkale.md", "papers": [ { "name": "Erkale_10.1002_jcc.22987.pdf", "path": "Papers_of_Codes/DFT/Erkale/Erkale_10.1002_jcc.22987.pdf", "doi_url": "https://doi.org/10.1002/jcc.22987" } ], "paper_placeholder": false, "slug": "Erkale", "idx": 93, "overview": "Erkale is an open-source quantum chemistry program for Hartree-Fock and density functional theory calculations using Gaussian basis sets. Originally developed at the University of Helsinki, it focuses on computing X-ray properties including ground-state electron momentum densities, Compton profiles, X-ray absorption spectra (XAS), and X-ray Raman scattering spectra. Erkale has evolved to include advanced capabilities in basis set development and self-interaction corrected DFT." }, { "num": "048r", "name": "DoNOF.jl", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://github.com/felipelewyee/DoNOF.jl", "note": "Natural Orbital Functional theory in Julia (M. Piris)", "md_link_text": "DoNOF_jl.md", "md_link_path": "DFT/1.3_Localized_Basis/DoNOF_jl.md", "papers": [], "paper_placeholder": true, "slug": "DoNOF.jl", "idx": 94, "overview": "DoNOF.jl is a Julia implementation of Natural Orbital Functional (NOF) theory for electronic structure calculations. It provides an alternative to traditional DFT and wavefunction methods by describing the electronic correlation through functionals of the one-particle reduced density matrix. DoNOF.jl enables calculations using PNOF functionals (PNOF5, PNOF7, GNOF) which capture static and dynamic correlation effects." }, { "num": "048s", "name": "HORTON", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://github.com/theochem/horton", "note": "Modular Python QC framework, conceptual DFT (QCDevs)", "md_link_text": "HORTON.md", "md_link_path": "DFT/1.3_Localized_Basis/HORTON.md", "papers": [], "paper_placeholder": true, "slug": "HORTON", "idx": 95, "overview": "HORTON is a modular quantum chemistry program written primarily in Python, designed for electronic structure calculations, method prototyping, and educational purposes. It emphasizes code readability, extensibility, and user-friendliness over raw computational performance. HORTON 3.x has evolved into a suite of independent modules (GBasis, Grid, IOData) that work together to provide a flexible framework for quantum chemistry workflows." }, { "num": "048t", "name": "EXESS", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://barcagrp.com/exess/", "note": "GPU-native AIMD, Gordon Bell 2024 winner (Barca group)", "md_link_text": "EXESS.md", "md_link_path": "DFT/1.3_Localized_Basis/EXESS.md", "papers": [], "paper_placeholder": true, "slug": "EXESS", "idx": 96, "overview": "EXESS (Extreme-scale Electronic Structure System) is a GPU-native quantum chemistry code designed for extreme-scale ab initio molecular dynamics (AIMD) capabilities. It won the 2024 ACM Gordon Bell Prize for its ability to perform MP2-level AIMD simulations on systems with thousands of atoms, leveraging novel algorithms optimized for GPU architectures (NVIDIA)." }, { "num": "048u", "name": "Entos Qcore", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://entos.ai/", "note": "Physics-based QC with Machine Learning (MOB-ML)", "md_link_text": "Entos_Qcore.md", "md_link_path": "DFT/1.3_Localized_Basis/Entos_Qcore.md", "papers": [], "paper_placeholder": true, "slug": "Entos-Qcore", "idx": 97, "overview": "Entos Qcore is a modern quantum chemistry software package developed by Entos, Inc. It emphasizes the integration of physics-based methods with machine learning (ML), specifically featuring Molecular Orbital Based Machine Learning (MOB-ML). It is designed for efficiency and ease of use, providing standard DFT and wavefunction methods alongside innovative ML-accelerated approaches." }, { "num": "048v", "name": "OrbNet", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://entos.ai/", "note": "AI-driven Quantum Chemistry, GNN potentials (Entos)", "md_link_text": "OrbNet.md", "md_link_path": "DFT/1.3_Localized_Basis/OrbNet.md", "papers": [ { "name": "OrbNet_10.1063_5.0021955.pdf", "path": "Papers_of_Codes/DFT/OrbNet/OrbNet_10.1063_5.0021955.pdf", "doi_url": "https://doi.org/10.1063/5.0021955" } ], "paper_placeholder": false, "slug": "OrbNet", "idx": 98, "overview": "OrbNet is an AI-driven quantum chemistry method and software developed by Entos, Inc. It utilizes graph neural networks (Geometric Deep Learning) and domain-specific features (based on low-cost quantum calculations like GFN-xTB or semi-empirical methods) to predict high-level quantum chemical properties (like DFT or CCSD(T) energies) with high accuracy and vastly reduced computational cost." }, { "num": "048w", "name": "Promethium", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://qcware.com/promethium", "note": "Cloud-native GPU DFT SaaS (QC Ware)", "md_link_text": "Promethium.md", "md_link_path": "DFT/1.3_Localized_Basis/Promethium.md", "papers": [], "paper_placeholder": true, "slug": "Promethium", "idx": 99, "overview": "Promethium is a cloud-native, GPU-accelerated quantum chemistry platform developed by QC Ware. It is delivered as a Software-as-a-Service (SaaS), primarily via AWS. Promethium utilizes advanced algorithms optimized for NVIDIA GPUs (H100/A100) to perform Density Functional Theory (DFT) calculations with exceptional speed and throughput, handling systems up to 2,000 atoms." }, { "num": "048x", "name": "Psi4NumPy", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://github.com/psi4/psi4numpy", "note": "Interactive QC tutorials and reference implementations", "md_link_text": "Psi4NumPy.md", "md_link_path": "DFT/1.3_Localized_Basis/Psi4NumPy.md", "papers": [ { "name": "Turney_et_al_2012.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/PSI4/Turney_et_al_2012.pdf", "doi_url": "https://scholar.google.com/scholar?q=Psi4NumPy+Turney+et+al+2012" } ], "paper_placeholder": false, "slug": "Psi4NumPy", "idx": 100, "overview": "Psi4NumPy is an educational and development framework that bridges the Psi4 quantum chemistry package with the NumPy Python library. It provides interactive tutorials and reference implementations of modern quantum chemical methods. By exposing the core C++ modules of Psi4 to Python, it allows users to write clear, readable, and efficient implementations of complex methods like HF, MP2, CC, and CI directly in Python." }, { "num": "383", "name": "ADF-BAND", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.3", "subcategory": "Localized Basis Sets", "confidence": "VERIFIED", "official_url": "https://www.scm.com/product/band/", "note": "Periodic DFT with STOs/NAOs in the Amsterdam Modeling Suite.", "md_link_text": "ADF-BAND.md", "md_link_path": "DFT/1.3_Localized_Basis/ADF-BAND.md", "papers": [ { "name": "10.1103_PhysRevB.44.7888.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/ADF-BAND/10.1103_PhysRevB.44.7888.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.44.7888" } ], "paper_placeholder": false, "slug": "ADF-BAND", "idx": 101, "overview": "" }, { "num": "049", "name": "ORCA", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "CONFIRMED", "official_url": "https://orcaforum.kofo.mpg.de/", "note": "", "md_link_text": "ORCA.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/ORCA.md", "papers": [ { "name": "10.1002_wcms.1606.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/ORCA/10.1002_wcms.1606.pdf", "doi_url": "https://doi.org/10.1002/wcms.1606" } ], "paper_placeholder": false, "slug": "ORCA", "idx": 102, "overview": "ORCA is a modern, general-purpose quantum chemistry program package featuring extensive capabilities in molecular electronic structure calculations. Developed by Frank Neese and coworkers at the Max Planck Institute f\u00fcr Kohlenforschung, ORCA is known for its user-friendly input, comprehensive methods (from semi-empirical to high-level coupled cluster), excellent spectroscopic property calculations, and efficient parallelization. Version 6.0 (released July 2024) represents a near-complete rewrite" }, { "num": "050", "name": "Gaussian", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "CONFIRMED", "official_url": "https://gaussian.com/", "note": "", "md_link_text": "Gaussian.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/Gaussian.md", "papers": [], "paper_placeholder": true, "slug": "Gaussian", "idx": 103, "overview": "Gaussian is the most widely-used electronic structure program in chemistry. Originally developed by John Pople (Nobel Prize 1998) and now maintained by Gaussian, Inc., it provides a comprehensive suite of methods from semi-empirical to high-level coupled cluster with extensive automation and user-friendly interface. The current version is Gaussian 16, with GaussView 6 as the companion visualization tool." }, { "num": "051", "name": "PySCF", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "CONFIRMED", "official_url": "https://pyscf.org/", "note": "", "md_link_text": "PySCF.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/PySCF.md", "papers": [ { "name": "10_1002_wcms_1340.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/PySCF/10_1002_wcms_1340.pdf", "doi_url": "https://scholar.google.com/scholar?q=PySCF+10+1002+wcms+1340" }, { "name": "10_1063_5_0006074.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/PySCF/10_1063_5_0006074.pdf", "doi_url": "https://scholar.google.com/scholar?q=PySCF+10+1063+5+0006074" } ], "paper_placeholder": false, "slug": "PySCF", "idx": 104, "overview": "PySCF (Python-based Simulations of Chemistry Framework) is an open-source quantum chemistry package with emphasis on ab initio methods for molecules and crystals. Built entirely in Python with performance-critical sections in C, it provides a simple, lightweight, and efficient platform for developing and testing quantum chemistry methods with excellent scriptability and integration with the Python scientific ecosystem." }, { "num": "052", "name": "PSI4", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "CONFIRMED", "official_url": "https://psicode.org/", "note": "", "md_link_text": "PSI4.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/PSI4.md", "papers": [ { "name": "Turney_et_al_2012.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/PSI4/Turney_et_al_2012.pdf", "doi_url": "https://scholar.google.com/scholar?q=PSI4+Turney+et+al+2012" } ], "paper_placeholder": false, "slug": "PSI4", "idx": 105, "overview": "PSI4 is an open-source suite of ab initio quantum chemistry programs designed for efficient, high-accuracy simulations of molecular properties. It emphasizes modern software engineering practices, native Python integration, and provides state-of-the-art coupled cluster, density functional, and symmetry-adapted perturbation theory methods. The latest version is PSI4 1.9.1 (February 2024)." }, { "num": "053", "name": "Molpro", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "CONFIRMED", "official_url": "https://www.molpro.net/", "note": "", "md_link_text": "Molpro.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/Molpro.md", "papers": [ { "name": "Werner_et_al_2012.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/Molpro/Werner_et_al_2012.pdf", "doi_url": "https://scholar.google.com/scholar?q=Molpro+Werner+et+al+2012" } ], "paper_placeholder": false, "slug": "Molpro", "idx": 106, "overview": "Molpro is a comprehensive ab initio quantum chemistry package with particular strength in multi-reference methods, explicitly correlated F12 methods, and accurate treatment of electron correlation. Developed by H.-J. Werner and P. J. Knowles, it is widely considered the gold standard for high-accuracy calculations on molecular systems, particularly for challenging multi-configurational problems and thermochemical benchmarks." }, { "num": "054", "name": "NWChem", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "CONFIRMED", "official_url": "https://nwchemgit.github.io/", "note": "", "md_link_text": "NWChem.md", "md_link_path": "TDDFT/2.2_Linear-Response_TDDFT/NWChem.md", "papers": [ { "name": "Valiev_et_al_2010.pdf", "path": "Papers_of_Codes/TDDFT/2.2_Linear-Response_TDDFT/NWChem/Valiev_et_al_2010.pdf", "doi_url": "https://scholar.google.com/scholar?q=NWChem+Valiev+et+al+2010" } ], "paper_placeholder": false, "slug": "NWChem", "idx": 107, "overview": "NWChem is a comprehensive, open-source computational chemistry package designed for massively parallel high-performance computing. Developed and maintained by Pacific Northwest National Laboratory (PNNL), it provides a broad range of methods from DFT to coupled cluster, with particular strengths in scalability, molecular dynamics, and plane-wave calculations for solids. NWChem can scale from single processors to thousands of cores on leadership-class supercomputers." }, { "num": "055", "name": "Turbomole", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "CONFIRMED", "official_url": "https://www.turbomole.org/", "note": "", "md_link_text": "Turbomole.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/Turbomole.md", "papers": [ { "name": "Turbomole_10.1016_0009-2614(89)85118-8.pdf", "path": "Papers_of_Codes/DFT/Turbomole/Turbomole_10.1016_0009-2614%2889%2985118-8.pdf", "doi_url": "https://doi.org/10.1016/0009-2614(89)85118-8" } ], "paper_placeholder": false, "slug": "Turbomole", "idx": 108, "overview": "Turbomole is a highly efficient quantum chemistry program package for ab initio electronic structure calculations. Developed at the University of Karlsruhe, it is renowned for exceptional computational efficiency, particularly for large molecules, and features advanced algorithms including RI (Resolution of Identity) approximations for accelerated calculations." }, { "num": "056", "name": "Q-Chem", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "CONFIRMED", "official_url": "https://www.q-chem.com/", "note": "", "md_link_text": "Q-Chem.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/Q-Chem.md", "papers": [ { "name": "10.1063_5.0055522.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/Q-Chem/10.1063_5.0055522.pdf", "doi_url": "https://doi.org/10.1063/5.0055522" } ], "paper_placeholder": false, "slug": "Q-Chem", "idx": 109, "overview": "Q-Chem is a comprehensive ab initio quantum chemistry software package developed by Q-Chem, Inc. and academic partners. It offers a broad spectrum of electronic structure methods with emphasis on excited states, time-dependent phenomena, open-shell systems, and method development, featuring advanced algorithms and modern computational techniques." }, { "num": "057", "name": "GAMESS", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://www.msg.chem.iastate.edu/gamess/", "note": "", "md_link_text": "GAMESS.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/GAMESS.md", "papers": [ { "name": "Schmidt_et_al_1993.pdf", "path": "Papers_of_Codes/materials_science_papers/1.3_Quantum_Chemistry_Gaussian_Basis/GAMESS-US/Schmidt_et_al_1993.pdf", "doi_url": "https://scholar.google.com/scholar?q=GAMESS+Schmidt+et+al+1993" } ], "paper_placeholder": false, "slug": "GAMESS", "idx": 110, "overview": "GAMESS (General Atomic and Molecular Electronic Structure System) is a comprehensive ab initio quantum chemistry package developed at Iowa State University. Free for all users, GAMESS provides extensive capabilities from Hartree-Fock to high-level correlated methods, with particular strengths in excited states, solvation, and QM/MM calculations. It is one of the most widely distributed quantum chemistry codes worldwide." }, { "num": "058", "name": "Dalton", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://www.daltonprogram.org/", "note": "", "md_link_text": "Dalton.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/Dalton.md", "papers": [ { "name": "Aidas_et_al_2014.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/Dalton/Aidas_et_al_2014.pdf", "doi_url": "https://scholar.google.com/scholar?q=Dalton+Aidas+et+al+2014" } ], "paper_placeholder": false, "slug": "Dalton", "idx": 111, "overview": "Dalton is a powerful quantum chemistry program with particular emphasis on molecular properties, response theory, and environment effects. Originally developed in Scandinavia, it excels at computing spectroscopic properties, electric and magnetic molecular properties, and various response properties using advanced wave function and DFT methods." }, { "num": "060", "name": "CFOUR", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "CONFIRMED", "official_url": "https://www.cfour.de/", "note": "", "md_link_text": "CFOUR.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/CFOUR.md", "papers": [ { "name": "CFOUR_10.1063_5.0004837.pdf", "path": "Papers_of_Codes/DFT/CFOUR/CFOUR_10.1063_5.0004837.pdf", "doi_url": "https://doi.org/10.1063/5.0004837" } ], "paper_placeholder": false, "slug": "CFOUR", "idx": 112, "overview": "CFOUR (Coupled-Cluster techniques for Computational Chemistry) is a specialized quantum chemistry program with emphasis on high-level coupled cluster methods and highly accurate molecular property calculations. Originally developed as ACES IV by J. Gauss and J. F. Stanton, CFOUR excels at computing molecular properties with very high precision using advanced post-Hartree-Fock methods, featuring state-of-the-art implementations of analytical derivatives and response theory up to high order." }, { "num": "061", "name": "MRCC", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "CONFIRMED", "official_url": "https://www.mrcc.hu/", "note": "", "md_link_text": "MRCC.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/MRCC.md", "papers": [ { "name": "10.1063_1.5142048.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/MRCC/10.1063_1.5142048.pdf", "doi_url": "https://doi.org/10.1063/1.5142048" }, { "name": "Kallay_et_al_2020.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/MRCC/Kallay_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=MRCC+Kallay+et+al+2020" } ], "paper_placeholder": false, "slug": "MRCC", "idx": 113, "overview": "MRCC (Multi-Reference Coupled Cluster) is a specialized quantum chemistry program suite featuring arbitrary-order coupled cluster and configuration interaction methods. Developed by Mih\u00e1ly K\u00e1llay and collaborators at Budapest University of Technology and Economics, it is renowned for implementing the highest-order correlation methods available, including fully automated arbitrary-order CC and CI implementations generated via string-based equations." }, { "num": "062", "name": "OpenMolcas", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "CONFIRMED", "official_url": "https://gitlab.com/Molcas/OpenMolcas", "note": "", "md_link_text": "OpenMolcas.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/OpenMolcas.md", "papers": [ { "name": "Galvan_et_al_2019.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/OpenMolcas/Galvan_et_al_2019.pdf", "doi_url": "https://scholar.google.com/scholar?q=OpenMolcas+Galvan+et+al+2019" }, { "name": "10.1021_acs.jctc.9b00532.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/OpenMolcas/10.1021_acs.jctc.9b00532.pdf", "doi_url": "https://doi.org/10.1021/acs.jctc.9b00532" } ], "paper_placeholder": false, "slug": "OpenMolcas", "idx": 114, "overview": "OpenMolcas is an open-source quantum chemistry software package with special emphasis on multiconfigurational methods. It is the successor to Molcas and excels at treating systems with strong electron correlation, excited states, and complex electronic structures requiring multi-reference approaches. It is particularly strong in photochemistry and spectroscopy." }, { "num": "063", "name": "BAGEL", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "CONFIRMED", "official_url": "https://nubakery.org/", "note": "", "md_link_text": "BAGEL.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/BAGEL.md", "papers": [ { "name": "10.1002_wcms.1331.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/BAGEL/10.1002_wcms.1331.pdf", "doi_url": "https://doi.org/10.1002/wcms.1331" }, { "name": "Shiozaki_2018.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/BAGEL/Shiozaki_2018.pdf", "doi_url": "https://scholar.google.com/scholar?q=BAGEL+Shiozaki+2018" } ], "paper_placeholder": false, "slug": "BAGEL", "idx": 115, "overview": "BAGEL (Brilliantly Advanced General Electronic-structure Library) is a modern quantum chemistry package specializing in relativistic quantum chemistry and methods for excited states. It features state-of-the-art implementations of multireference methods, spin-orbit coupling, and analytical gradients, with emphasis on code efficiency and modern programming practices." }, { "num": "064", "name": "Columbus", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://www.univie.ac.at/columbus/", "note": "", "md_link_text": "Columbus.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/Columbus.md", "papers": [ { "name": "10_1021_acs_chemrev_8b00244.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/Columbus/10_1021_acs_chemrev_8b00244.pdf", "doi_url": "https://scholar.google.com/scholar?q=Columbus+10+1021+acs+chemrev+8b00244" }, { "name": "10_1002_wcms_25.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/Columbus/10_1002_wcms_25.pdf", "doi_url": "https://scholar.google.com/scholar?q=Columbus+10+1002+wcms+25" } ], "paper_placeholder": false, "slug": "Columbus", "idx": 116, "overview": "COLUMBUS is a comprehensive ab initio electronic structure program suite specializing in multi-reference methods, excited states, and non-adiabatic dynamics. Developed by Hans Lischka and collaborators at the University of Vienna and other institutions, COLUMBUS is particularly renowned for its capabilities in photochemistry, conical intersections, and surface hopping dynamics. It provides state-of-the-art multi-reference configuration interaction and coupled cluster methods for accurate treatme" }, { "num": "065", "name": "ACES", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://web.archive.org/web/20180126142310/http://www.qtp.ufl.edu/ACES/ (Legacy)", "note": "", "md_link_text": "ACES.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/ACES.md", "papers": [ { "name": "ACES_10.1063_5.0002581.pdf", "path": "Papers_of_Codes/DFT/ACES/ACES_10.1063_5.0002581.pdf", "doi_url": "https://doi.org/10.1063/5.0002581" } ], "paper_placeholder": false, "slug": "ACES", "idx": 117, "overview": "ACES (Advanced Concepts in Electronic Structure) is a high-level ab initio quantum chemistry package developed at the University of Florida's Quantum Theory Project. ACES specializes in accurate coupled cluster methods, particularly for excited states, open-shell systems, and high-accuracy thermochemistry. It has been succeeded by ACES III and ACES IV (now CFour), but ACES II remains widely used for its robust implementation of advanced correlation methods." }, { "num": "066", "name": "ExaChem", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/ExaChem/ExaChem", "note": "", "md_link_text": "ExaChem.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/ExaChem.md", "papers": [], "paper_placeholder": true, "slug": "ExaChem", "idx": 118, "overview": "ExaChem is an open-source computational chemistry framework developed by Pacific Northwest National Laboratory (PNNL) for exascale computing. Built on the TAMM (Tensor Algebra for Many-body Methods) infrastructure, ExaChem provides scalable implementations of coupled cluster methods optimized for modern supercomputers and heterogeneous architectures. It represents next-generation computational chemistry software designed from the ground up for extreme-scale parallelism and GPU acceleration." }, { "num": "067", "name": "Quantum-Package", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/QuantumPackage/qp2", "note": "", "md_link_text": "Quantum-Package.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/Quantum-Package.md", "papers": [ { "name": "Giannozzi_et_al_2009.pdf", "path": "Papers_of_Codes/materials_science_papers/1.1_Plane-Wave_Pseudopotential_PAW_Methods/Quantum_ESPRESSO/Giannozzi_et_al_2009.pdf", "doi_url": "https://scholar.google.com/scholar?q=Quantum-Package+Giannozzi+et+al+2009" } ], "paper_placeholder": false, "slug": "Quantum-Package", "idx": 119, "overview": "Quantum Package is a programming environment for quantum chemistry developed in France, focusing on wavefunction methods and quantum Monte Carlo. Developed primarily at the Laboratoire de Chimie et Physique Quantiques in Toulouse, Quantum Package provides a modular framework for implementing and developing wavefunction-based methods with emphasis on selected configuration interaction and stochastic approaches." }, { "num": "068", "name": "CheMPS2", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/SebWouters/CheMPS2", "note": "", "md_link_text": "CheMPS2.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/CheMPS2.md", "papers": [ { "name": "CheMPS2_10.1016_j.cpc.2014.01.019.pdf", "path": "Papers_of_Codes/DFT/CheMPS2/CheMPS2_10.1016_j.cpc.2014.01.019.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2014.01.019" } ], "paper_placeholder": false, "slug": "CheMPS2", "idx": 120, "overview": "CheMPS2 is a spin-adapted implementation of the Density Matrix Renormalization Group (DMRG) for quantum chemistry. Developed by Sebastian Wouters, CheMPS2 provides efficient and accurate calculations for strongly correlated systems using matrix product states (MPS). It is designed as a library that can be integrated with other quantum chemistry codes and offers state-of-the-art DMRG algorithms with excellent performance for multi-reference problems." }, { "num": "069", "name": "SlowQuant", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/slowquant/slowquant", "note": "", "md_link_text": "SlowQuant.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/SlowQuant.md", "papers": [], "paper_placeholder": true, "slug": "SlowQuant", "idx": 121, "overview": "SlowQuant is a Python-based educational quantum chemistry package developed for teaching and learning quantum chemistry methods. Written entirely in Python with emphasis on code readability and pedagogical value, SlowQuant implements various quantum chemistry methods in a transparent, easy-to-understand manner. It prioritizes educational clarity over computational performance, making it ideal for students and researchers learning quantum chemistry theory and implementation." }, { "num": "070", "name": "BDF", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "http://www.bdf-program.com/", "note": "", "md_link_text": "BDF.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/BDF.md", "papers": [ { "name": "BDF_10.1063_1.5143173.pdf", "path": "Papers_of_Codes/DFT/BDF/BDF_10.1063_1.5143173.pdf", "doi_url": "https://doi.org/10.1063/1.5143173" } ], "paper_placeholder": false, "slug": "BDF", "idx": 122, "overview": "BDF (Beijing Density Functional) is a quantum chemistry package developed in China with particular strengths in relativistic methods, heavy element chemistry, and large-scale calculations. Developed at Peking University and other Chinese institutions, BDF provides advanced four-component relativistic methods, efficient linear-scaling algorithms, and specialized capabilities for actinides, lanthanides, and heavy element systems. It represents a significant contribution from the Chinese computatio" }, { "num": "071", "name": "eT", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/Molecular-Simulations/eT", "note": "", "md_link_text": "eT.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/eT.md", "papers": [ { "name": "eT_10.1063_5.0004713.pdf", "path": "Papers_of_Codes/DFT/eT/eT_10.1063_5.0004713.pdf", "doi_url": "https://doi.org/10.1063/5.0004713" } ], "paper_placeholder": false, "slug": "eT", "idx": 123, "overview": "eT is a quantum chemistry program specialized in calculating molecular response properties and time-dependent phenomena using coupled cluster theory. Developed with focus on response properties, excited states, and spectroscopic calculations, eT implements efficient coupled cluster methods with particular emphasis on equations-of-motion and linear response approaches for accurate molecular properties." }, { "num": "072", "name": "CC4S", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/cc4s/cc4s", "note": "", "md_link_text": "CC4S.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/CC4S.md", "papers": [], "paper_placeholder": true, "slug": "CC4S", "idx": 124, "overview": "CC4S (Coupled Cluster for Solids) is a massively parallel coupled cluster code specifically designed for extended periodic systems. Developed primarily at TU Wien, CC4S implements coupled cluster methods for solids using a plane-wave basis and focuses on accurate correlation energies for materials. It represents a specialized approach to bringing high-accuracy quantum chemistry methods to solid-state physics." }, { "num": "073", "name": "ACES-III", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/OpenACES/ACES-III", "note": "", "md_link_text": "ACES-III.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/ACES-III.md", "papers": [ { "name": "ACES-III_10.1063_1.2920482.pdf", "path": "Papers_of_Codes/DFT/ACES-III/ACES-III_10.1063_1.2920482.pdf", "doi_url": "https://doi.org/10.1063/1.2920482" } ], "paper_placeholder": false, "slug": "ACES-III", "idx": 125, "overview": "ACES III is the modern successor to ACES II, representing a complete redesign of the ACES quantum chemistry package for parallel computing environments. Developed at the University of Florida's Quantum Theory Project, ACES III implements coupled cluster methods using the Super Instruction Assembly Language (SIAL) for automatic parallelization. It provides improved scalability and modern parallel algorithms while maintaining the accuracy and capabilities of ACES II. Note that ACES IV (now known a" }, { "num": "074a", "name": "TeraChem", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://www.petachem.com/", "note": "", "md_link_text": "TeraChem.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/TeraChem.md", "papers": [ { "name": "TeraChem_10.1002_wcms.1494.pdf", "path": "Papers_of_Codes/DFT/TeraChem/TeraChem_10.1002_wcms.1494.pdf", "doi_url": "https://doi.org/10.1002/wcms.1494" } ], "paper_placeholder": false, "slug": "TeraChem", "idx": 126, "overview": "**TeraChem** is a general-purpose quantum chemistry software designed from the ground up for **GPU acceleration**. It was one of the first codes to demonstrate that consumer-grade GPUs could outperform supercomputers for certain quantum chemistry tasks. It provides ultra-fast DFT and *ab initio* molecular dynamics (AIMD) for large molecular systems." }, { "num": "074b", "name": "Jaguar", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://www.schrodinger.com/products/jaguar", "note": "", "md_link_text": "Jaguar.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/Jaguar.md", "papers": [ { "name": "Jaguar_10.1002_qua.24481.pdf", "path": "Papers_of_Codes/DFT/Jaguar/Jaguar_10.1002_qua.24481.pdf", "doi_url": "https://doi.org/10.1002/qua.24481" } ], "paper_placeholder": false, "slug": "Jaguar", "idx": 127, "overview": "**Jaguar** is a high-performance *ab initio* electronic structure program known for its unique **pseudospectral** algorithms. Part of the Schr\u00f6dinger materials science suite, it excels at handling large systems and transition metals with high efficiency. It is heavily used in the pharmaceutical and materials industries for pKa prediction, solvation free energies, and robust geometry optimizations." }, { "num": "074c", "name": "Spartan", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://www.wavefun.com/", "note": "", "md_link_text": "Spartan.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/Spartan.md", "papers": [], "paper_placeholder": true, "slug": "Spartan", "idx": 128, "overview": "**Spartan** is a premier molecular modeling and computational chemistry application that emphasizes ease of use and visualization. While it includes its own computational engines, its primary fame lies in its intuitive GUI that brings complex quantum chemistry (DFT, HF, Post-HF) to non-specialists, students, and organic chemists." }, { "num": "074d", "name": "ChronusQ", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/liresearchgroup/chronusq_public", "note": "Open-source relativistic ab initio code; X2C, RT-TDDFT, magnetic fields (Li group, U. Washington)", "md_link_text": "ChronusQ.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/ChronusQ.md", "papers": [ { "name": "ChronusQ_10.1002_wcms.1436.pdf", "path": "Papers_of_Codes/DFT/ChronusQ/ChronusQ_10.1002_wcms.1436.pdf", "doi_url": "https://doi.org/10.1002/wcms.1436" } ], "paper_placeholder": false, "slug": "ChronusQ", "idx": 129, "overview": "ChronusQ (Chronus Quantum) is an open-source ab initio electronic structure software designed for addressing complex problems requiring consistent treatment of time dependence, relativistic effects, many-body correlation, electron-nuclear coupling, and spin. Written in modern C++ with MPI/OpenMP parallelism." }, { "num": "074e", "name": "QUICK", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/merzlab/QUICK", "note": "GPU-accelerated ab initio/DFT; CUDA optimized (G\u00f6tz/Merz labs)", "md_link_text": "QUICK.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/QUICK.md", "papers": [ { "name": "QUICK_10.1021_acs.jctc.0c00290.pdf", "path": "Papers_of_Codes/DFT/QUICK/QUICK_10.1021_acs.jctc.0c00290.pdf", "doi_url": "https://doi.org/10.1021/acs.jctc.0c00290" } ], "paper_placeholder": false, "slug": "QUICK", "idx": 130, "overview": "QUICK (QUantum Interaction Computational Kernel) is a GPU-enabled ab initio and density functional theory software package developed by the G\u00f6tz and Merz labs. It leverages CUDA for GPU acceleration, providing significant speedups for electronic structure calculations on modern HPC hardware." }, { "num": "074g", "name": "QUACK", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/pfloos/QuACK", "note": "GW/BSE methods for molecules; emerging electronic structure", "md_link_text": "QUACK.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/QUACK.md", "papers": [], "paper_placeholder": true, "slug": "QUACK", "idx": 131, "overview": "QUACK (Quantum Chemistry in ACKnowledgement) is an open-source software for emerging quantum electronic structure methods. It specializes in Green's function methods including GW approximation and Bethe-Salpeter equation (BSE) for molecular systems, along with coupled cluster and other advanced correlation methods." }, { "num": "074i", "name": "GPU4PySCF", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/pyscf/gpu4pyscf", "note": "CUDA GPU acceleration for PySCF", "md_link_text": "GPU4PySCF.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/GPU4PySCF.md", "papers": [], "paper_placeholder": true, "slug": "GPU4PySCF", "idx": 132, "overview": "GPU4PySCF is a GPU-accelerated extension for PySCF, providing CUDA implementations of two-electron repulsion integrals and DFT calculations. It enables significant speedups for Hartree-Fock and DFT calculations while maintaining compatibility with the PySCF ecosystem." }, { "num": "074j", "name": "DQC", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/diffqc/dqc", "note": "Differentiable Quantum Chemistry; PyTorch-based", "md_link_text": "DQC.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/DQC.md", "papers": [], "paper_placeholder": true, "slug": "DQC", "idx": 133, "overview": "DQC (Differentiable Quantum Chemistry) is an open-source Python simulation code using PyTorch and xitorch for differentiable DFT and Hartree-Fock calculations. It enables automatic differentiation through quantum chemistry calculations, facilitating machine learning applications and gradient-based optimization." }, { "num": "074k", "name": "Multiwfn", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "CONFIRMED", "official_url": "http://sobereva.com/multiwfn/", "note": "Comprehensive wavefunction analysis tool; 5000+ citations", "md_link_text": "Multiwfn.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/Multiwfn.md", "papers": [ { "name": "Multiwfn_10.1002_jcc.22885.pdf", "path": "Papers_of_Codes/DFT/Multiwfn/Multiwfn_10.1002_jcc.22885.pdf", "doi_url": "https://doi.org/10.1002/jcc.22885" } ], "paper_placeholder": false, "slug": "Multiwfn", "idx": 134, "overview": "Multiwfn is a comprehensive, extremely powerful electron wavefunction analysis toolbox. It can perform a wide variety of wavefunction analyses based on output from almost all major quantum chemistry packages including Gaussian, ORCA, GAMESS, NWChem, Molpro, and many others." }, { "num": "074l", "name": "ccq", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/jjgoings/ccq", "note": "Coupled cluster code; CCSD/CCSDT/CCSDTQ implementations", "md_link_text": "ccq.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/ccq.md", "papers": [], "paper_placeholder": true, "slug": "ccq", "idx": 135, "overview": "ccq is a coupled-cluster code designed for quantum chemistry calculations. It implements standard coupled-cluster methods including CCD, CCSD, CCSDT, and CCSDTQ, providing a clean implementation for research and educational purposes." }, { "num": "074m", "name": "ccpy", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/piecuch-group/ccpy", "note": "Coupled cluster package; Piecuch group (Michigan State)", "md_link_text": "ccpy.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/ccpy.md", "papers": [], "paper_placeholder": true, "slug": "ccpy", "idx": 136, "overview": "ccpy is a Python-based coupled-cluster package developed by the Piecuch group at Michigan State University. It implements a variety of ground and excited-state coupled-cluster methods using a hybrid Python-Fortran approach for computational efficiency." }, { "num": "074n", "name": "ABIN", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/PHOTOX/ABIN", "note": "Ab initio MD with PIMD/nuclear quantum effects", "md_link_text": "ABIN.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/ABIN.md", "papers": [ { "name": "Gonze_et_al_2009.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/ABINIT/Gonze_et_al_2009.pdf", "doi_url": "https://scholar.google.com/scholar?q=ABIN+Gonze+et+al+2009" } ], "paper_placeholder": false, "slug": "ABIN", "idx": 137, "overview": "ABIN (Ab Initio Born-oppenheimer Nuclear dynamics) is a multipurpose ab initio molecular dynamics program. It is designed to perform ab initio MD and model nuclear quantum effects, interfacing with external electronic structure programs like ORCA and TeraChem for forces and energies." }, { "num": "074o", "name": "VOTCA-XTP", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/votca/xtp", "note": "GW-BSE for organic materials; transport properties", "md_link_text": "VOTCA-XTP.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/VOTCA-XTP.md", "papers": [ { "name": "VOTCA-XTP_10.1021_acs.jctc.8b00617.pdf", "path": "Papers_of_Codes/DFT/VOTCA-XTP/VOTCA-XTP_10.1021_acs.jctc.8b00617.pdf", "doi_url": "https://doi.org/10.1021/acs.jctc.8b00617" } ], "paper_placeholder": false, "slug": "VOTCA-XTP", "idx": 138, "overview": "VOTCA-XTP (Versatile Object-oriented Toolkit for Coarse-graining Applications - eXcited states, Transfer, Properties) is an open-source library for excited-state property calculations using GW-BSE methods, focusing on organic materials and molecular electronics." }, { "num": "074p", "name": "pyqint", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/ifilot/pyqint", "note": "Educational Python HF/integrals implementation", "md_link_text": "pyqint.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/pyqint.md", "papers": [ { "name": "pyqint_10.21105_jose.00286.pdf", "path": "Papers_of_Codes/DFT/pyqint/pyqint_10.21105_jose.00286.pdf", "doi_url": "https://doi.org/10.21105/jose.00286" } ], "paper_placeholder": false, "slug": "pyqint", "idx": 139, "overview": "pyqint is a Python-based, teaching-oriented implementation of the Hartree-Fock method and molecular integrals. It provides a transparent interface to fundamental electronic structure components, making it excellent for learning and prototyping." }, { "num": "074q", "name": "CuGBasis", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/theochem/cuGBasis", "note": "CUDA GPU-accelerated density descriptors (100x speedup)", "md_link_text": "CuGBasis.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/CuGBasis.md", "papers": [], "paper_placeholder": true, "slug": "CuGBasis", "idx": 140, "overview": "CuGBasis is a free and open-source CUDA/Python library for efficient computation of density-based descriptors from electronic structure calculations. Using GPU acceleration, it achieves remarkable performance gains of up to 100x speedup compared to CPU implementations for evaluating electron densities, gradients, and related properties on 3D grids." }, { "num": "074r", "name": "ModelHamiltonian", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/theochem/ModelHamiltonian", "note": "Model Hamiltonian to integral translator; TheoChem ecosystem", "md_link_text": "ModelHamiltonian.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/ModelHamiltonian.md", "papers": [], "paper_placeholder": true, "slug": "ModelHamiltonian", "idx": 141, "overview": "ModelHamiltonian is a Python library that facilitates the application of quantum chemistry methods to model Hamiltonians by translating them into standard 0-, 1-, and 2-electron integrals. It bridges model system studies with ab initio quantum chemistry codes, enabling use of sophisticated wavefunction methods on lattice models." }, { "num": "074s", "name": "FanPy", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/theochem/fanpy", "note": "Flexible wavefunction ans\u00e4tze; geminal methods", "md_link_text": "FanPy.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/FanPy.md", "papers": [], "paper_placeholder": true, "slug": "FanPy", "idx": 142, "overview": "FanPy (Flexible Ansatz for N-electron Wavefunctions in Python) is a Python library for ab initio quantum chemistry calculations using flexible wavefunction ans\u00e4tze. It enables development and application of novel correlated wavefunction methods, particularly geminal-based approaches. Part of the TheoChem ecosystem alongside ModelHamiltonian and PyCI." }, { "num": "074t", "name": "PyCI", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/theochem/pyci", "note": "Configuration interaction library; TheoChem ecosystem", "md_link_text": "PyCI.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/PyCI.md", "papers": [], "paper_placeholder": true, "slug": "PyCI", "idx": 143, "overview": "PyCI is a Python library for configuration interaction (CI) calculations. Part of the TheoChem ecosystem, it provides efficient CI implementations using determinant-based algorithms with optimized Slater-Condon rules. Integrates with ModelHamiltonian and FanPy for comprehensive wavefunction studies." }, { "num": "074u", "name": "harpy", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://github.com/pwborthwick/harpy", "note": "Educational Python QC codes; HF/post-HF", "md_link_text": "harpy.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/harpy.md", "papers": [], "paper_placeholder": true, "slug": "harpy", "idx": 144, "overview": "harpy is a collection of quantum chemistry codes written in Python, focusing on readability and educational value. It includes complete implementations of molecular integrals, Hartree-Fock, and various post-HF methods, designed to help students and educators understand electronic structure theory." }, { "num": "074v", "name": "Firefly", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "http://classic.chem.msu.su/gran/firefly/", "note": "Optimized GAMESS fork; faster performance", "md_link_text": "Firefly.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/Firefly.md", "papers": [], "paper_placeholder": true, "slug": "Firefly", "idx": 145, "overview": "Firefly (formerly PC GAMESS) is an optimized fork of GAMESS(US) with architecture-specific optimizations developed by Alex Granovsky at Moscow State University. It maintains full compatibility with GAMESS input format while providing significant performance improvements through modern code optimization techniques." }, { "num": "074w", "name": "CADPAC", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "Historic/Legacy", "note": "Cambridge Analytical Derivatives Package; pioneer in gradients (Handy group)", "md_link_text": "CADPAC.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/CADPAC.md", "papers": [ { "name": "CADPAC_10.1016_0167-7977(89)90001-4.pdf", "path": "Papers_of_Codes/DFT/CADPAC/CADPAC_10.1016_0167-7977%2889%2990001-4.pdf", "doi_url": "https://doi.org/10.1016/0167-7977(89)90001-4" } ], "paper_placeholder": false, "slug": "CADPAC", "idx": 146, "overview": "CADPAC (Cambridge Analytic Derivatives Package) is a historic ab initio molecular electronic structure program developed primarily by Nicholas Handy and his group at Cambridge University starting in the 1970s. It pioneered the implementation of analytical first and second derivatives for molecular calculations, fundamentally influencing how modern codes compute gradients and Hessians." }, { "num": "074x", "name": "AMPAC", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "Historic/Legacy (MOPAC successor)", "note": "AM1/PM3 semi-empirical package (Austin)", "md_link_text": "AMPAC.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/AMPAC.md", "papers": [], "paper_placeholder": true, "slug": "AMPAC", "idx": 147, "overview": "AMPAC (Austin-Method Package) is a historic semi-empirical quantum chemistry program package implementing AM1, PM3, and related methods. Developed with significant contributions from Michael Dewar's group at the University of Texas Austin, it represented a major advance in semi-empirical methodology for organic chemistry applications." }, { "num": "074y", "name": "ACES-II", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://www.qtp.ufl.edu/ACES/", "note": "Historic CC code; predecessor to CFOUR (UFL QTP, Bartlett group)", "md_link_text": "ACES-II.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/ACES-II.md", "papers": [], "paper_placeholder": true, "slug": "ACES-II", "idx": 148, "overview": "ACES II (Advanced Concepts in Electronic Structure II) is an ab initio quantum chemistry program developed at the University of Florida's Quantum Theory Project (QTP) by Rodney Bartlett and collaborators. It pioneered many high-level coupled-cluster implementations and is the predecessor to both ACES III and CFOUR, representing a seminal contribution to coupled-cluster methodology." }, { "num": "074z", "name": "Dice", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://www.brianqc.com/", "note": "GPU-accelerated QC module integrated with Q-Chem; high angular momentum on GPU", "md_link_text": "BrianQC.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/BrianQC.md", "papers": [ { "name": "Dice_10.1021_acs.jctc.6b01028.pdf", "path": "Papers_of_Codes/DFT/Dice/Dice_10.1021_acs.jctc.6b01028.pdf", "doi_url": "https://doi.org/10.1021/acs.jctc.6b01028" } ], "paper_placeholder": false, "slug": "Dice", "idx": 149, "overview": "" }, { "num": "392", "name": "Priroda", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "http://rad.chem.msu.ru/~laikov/priroda.html", "note": "Fast relativistic quantum chemistry code by D. Laikov.", "md_link_text": "Priroda.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/Priroda.md", "papers": [ { "name": "Laikov_1997.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/Priroda/Laikov_1997.pdf", "doi_url": "https://scholar.google.com/scholar?q=Priroda+Laikov+1997" } ], "paper_placeholder": false, "slug": "Priroda", "idx": 150, "overview": "" }, { "num": "389", "name": "GAMESS-US", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://www.msg.chem.iastate.edu/gamess/", "note": "General Atomic and Molecular Electronic Structure System (US version).", "md_link_text": "GAMESS-US.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/GAMESS-US.md", "papers": [ { "name": "Schmidt_et_al_1993.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/GAMESS-US/Schmidt_et_al_1993.pdf", "doi_url": "https://scholar.google.com/scholar?q=GAMESS-US+Schmidt+et+al+1993" } ], "paper_placeholder": false, "slug": "GAMESS-US", "idx": 151, "overview": "" }, { "num": "382", "name": "ADC", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.4", "subcategory": "Quantum Chemistry Suites", "confidence": "VERIFIED", "official_url": "https://adc-connect.org/", "note": "Algebraic Diagrammatic Construction for molecular excited states.", "md_link_text": "ADC.md", "md_link_path": "DFT/1.4_Quantum_Chemistry/ADC.md", "papers": [ { "name": "Dreuw_Wormit_2015.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/ADC/Dreuw_Wormit_2015.pdf", "doi_url": "https://scholar.google.com/scholar?q=ADC+Dreuw+Wormit+2015" } ], "paper_placeholder": false, "slug": "ADC", "idx": 152, "overview": "" }, { "num": "075", "name": "DFTB+", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.5", "subcategory": "Tight-Binding DFT", "confidence": "CONFIRMED", "official_url": "https://www.dftbplus.org/", "note": "", "md_link_text": "DFTB+.md", "md_link_path": "DFT/1.5_Tight-Binding/DFTB+.md", "papers": [ { "name": "Hourahine_et_al_2020.pdf", "path": "Papers_of_Codes/DFT/1.5_Tight-Binding/DFTB+/Hourahine_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=DFTB%2B+Hourahine+et+al+2020" } ], "paper_placeholder": false, "slug": "DFTB", "idx": 153, "overview": "DFTB+ is a fast and efficient software package implementing the Density Functional Tight-Binding (DFTB) method and its extensions. It provides an approximate quantum mechanical approach that is 2-3 orders of magnitude faster than conventional DFT while maintaining reasonable accuracy, enabling simulations of thousands of atoms and long-timescale molecular dynamics." }, { "num": "076", "name": "xTB", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.5", "subcategory": "Tight-Binding DFT", "confidence": "CONFIRMED", "official_url": "https://github.com/grimme-lab/xtb", "note": "", "md_link_text": "xTB.md", "md_link_path": "DFT/1.5_Tight-Binding/xTB.md", "papers": [ { "name": "Grimme_et_al_2017.pdf", "path": "Papers_of_Codes/DFT/1.5_Tight-Binding/xTB/Grimme_et_al_2017.pdf", "doi_url": "https://scholar.google.com/scholar?q=xTB+Grimme+et+al+2017" } ], "paper_placeholder": false, "slug": "xTB", "idx": 154, "overview": "xTB (extended tight-binding) is a semiempirical quantum chemistry package implementing various tight-binding methods with parametrizations ranging from GFN0-xTB to GFN2-xTB. It is extremely fast, robust, and covers the entire periodic table, making it ideal for large-scale screening, conformer searches, and preliminary geometry optimizations." }, { "num": "077", "name": "HOTBIT", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.5", "subcategory": "Tight-Binding DFT", "confidence": "VERIFIED", "official_url": "https://github.com/pekkosk/hotbit", "note": "", "md_link_text": "HOTBIT.md", "md_link_path": "DFT/1.5_Tight-Binding/HOTBIT.md", "papers": [ { "name": "HOTBIT_10.1016_j.commatsci.2009.07.013.pdf", "path": "Papers_of_Codes/DFT/HOTBIT/HOTBIT_10.1016_j.commatsci.2009.07.013.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2009.07.013" } ], "paper_placeholder": false, "slug": "HOTBIT", "idx": 155, "overview": "HOTBIT is a Python-based density-functional tight-binding (DFTB) code developed at Aalto University, Finland. It provides an accessible implementation of the DFTB method with emphasis on Python integration, making it useful for scripting, high-throughput calculations, and educational purposes. HOTBIT offers a simpler alternative to more complex DFTB codes while maintaining reasonable accuracy for many applications." }, { "num": "078", "name": "MOPAC", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.5", "subcategory": "Tight-Binding DFT", "confidence": "VERIFIED", "official_url": "https://openmopac.net/", "note": "", "md_link_text": "MOPAC.md", "md_link_path": "DFT/1.5_Tight-Binding/MOPAC.md", "papers": [ { "name": "Stewart_2013.pdf", "path": "Papers_of_Codes/DFT/1.5_Tight-Binding/MOPAC/Stewart_2013.pdf", "doi_url": "https://scholar.google.com/scholar?q=MOPAC+Stewart+2013" } ], "paper_placeholder": false, "slug": "MOPAC", "idx": 156, "overview": "MOPAC (Molecular Orbital PACkage) is a semiempirical quantum chemistry program for studying molecular structures, reactions, and properties. Originally developed by James Stewart, MOPAC uses parameterized methods (AM1, PM3, PM6, PM7) that are 100-1000x faster than ab initio methods while maintaining reasonable accuracy. The modern version (OpenMOPAC) is open-source and particularly useful for large molecules, conformational searches, and high-throughput screening." }, { "num": "079", "name": "AMS-DFTB", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.5", "subcategory": "Tight-Binding DFT", "confidence": "VERIFIED", "official_url": "https://www.scm.com/", "note": "", "md_link_text": "AMS-DFTB.md", "md_link_path": "DFT/1.5_Tight-Binding/AMS-DFTB.md", "papers": [], "paper_placeholder": true, "slug": "AMS-DFTB", "idx": 157, "overview": "AMS-DFTB is the Density Functional Tight-Binding module within the Amsterdam Modeling Suite (AMS) from Software for Chemistry & Materials (SCM). It provides a fast approximate DFT method based on tight-binding formalism, making it suitable for large systems, long molecular dynamics, and high-throughput screening. AMS-DFTB integrates seamlessly with other AMS modules and provides a modern, user-friendly interface for DFTB calculations with excellent parameter sets." }, { "num": "080", "name": "Fireball", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.5", "subcategory": "Tight-Binding DFT", "confidence": "VERIFIED", "official_url": "https://github.com/FIREBALL2020", "note": "", "md_link_text": "Fireball.md", "md_link_path": "DFT/1.5_Tight-Binding/Fireball.md", "papers": [ { "name": "10_1002_pssb_201147259.pdf", "path": "Papers_of_Codes/DFT/1.5_Tight-Binding/Fireball/10_1002_pssb_201147259.pdf", "doi_url": "https://scholar.google.com/scholar?q=Fireball+10+1002+pssb+201147259" } ], "paper_placeholder": false, "slug": "Fireball", "idx": 158, "overview": "Fireball is an efficient *ab initio* tight-binding Density Functional Theory (DFT) code designed for molecular dynamics simulations of large systems. It utilizes a local-orbital formulation of DFT, enabling the simulation of supercells containing thousands of atoms with linear-scaling O(N) computational cost." }, { "num": "081", "name": "SCINE Sparrow", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.5", "subcategory": "Tight-Binding DFT", "confidence": "VERIFIED", "official_url": "https://scine.ethz.ch/download/sparrow", "note": "", "md_link_text": "SCINE_Sparrow.md", "md_link_path": "DFT/1.5_Tight-Binding/SCINE_Sparrow.md", "papers": [], "paper_placeholder": true, "slug": "SCINE-Sparrow", "idx": 159, "overview": "SCINE Sparrow is a command-line tool for fast semiempirical quantum chemical calculations. Developed by the Reiher Research Group at ETH Zurich as part of the SCINE (Software for Chemical Interaction Networks) project, it provides efficient implementations of popular semiempirical methods for calculating electronic energies, nuclear gradients, and Hessians." }, { "num": "081a", "name": "DFTBaby", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.5", "subcategory": "Tight-Binding DFT", "confidence": "VERIFIED", "official_url": "https://github.com/humeniuka/DFTBaby", "note": "DFTB for excited states and non-adiabatic dynamics", "md_link_text": "DFTBaby.md", "md_link_path": "DFT/1.5_Tight-Binding/DFTBaby.md", "papers": [ { "name": "10.1021_jp069056r.pdf", "path": "Papers_of_Codes/materials_science_papers/9.3_Specialized_DFT/DFTB/10.1021_jp069056r.pdf", "doi_url": "https://doi.org/10.1021/jp069056r" } ], "paper_placeholder": false, "slug": "DFTBaby", "idx": 160, "overview": "DFTBaby is a specialized software package for Density Functional Tight Binding (DFTB) calculations, with a distinct focus on excited states and non-adiabatic molecular dynamics. It implements Time-Dependent DFTB (TD-DFTB) analytically, enabling the efficient calculation of excited state energies and gradients. This makes it a powerful tool for photochemistry, allowing for the simulation of photo-induced processes and non-radiative relaxation pathways via surface hopping dynamics." }, { "num": "081b", "name": "DFTBpy", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.5", "subcategory": "Tight-Binding DFT", "confidence": "VERIFIED", "official_url": "https://github.com/daizhong/dftbpy (Representative)", "note": "Educational Python-based DFTB code", "md_link_text": "DFTBpy.md", "md_link_path": "DFT/1.5_Tight-Binding/DFTBpy.md", "papers": [ { "name": "10.1021_jp069056r.pdf", "path": "Papers_of_Codes/materials_science_papers/9.3_Specialized_DFT/DFTB/10.1021_jp069056r.pdf", "doi_url": "https://doi.org/10.1021/jp069056r" } ], "paper_placeholder": false, "slug": "DFTBpy", "idx": 161, "overview": "DFTBpy is an accessible, open-source Python implementation of the Density Functional Tight Binding (DFTB) method. Designed primarily for education and algorithm development, it implements the Self-Consistent Charge (SCC-DFTB) formalism. By exposing the core routines of the SCF cycle and Hamiltonian construction in Python and C extensions, it allows researchers and students to inspect, modify, and understand the internal mechanics of a DFTB calculation, which are often hidden in monolithic produc" }, { "num": "081c", "name": "tightbinder", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.5", "subcategory": "Tight-Binding DFT", "confidence": "VERIFIED", "official_url": "https://github.com/alejandrojuria/tightbinder", "note": "Python library for Slater-Koster TB model generation", "md_link_text": "tightbinder.md", "md_link_path": "DFT/1.5_Tight-Binding/tightbinder.md", "papers": [ { "name": "tightbinder_10.21105_joss.05810.pdf", "path": "Papers_of_Codes/DFT/tightbinder/tightbinder_10.21105_joss.05810.pdf", "doi_url": "https://doi.org/10.21105/joss.05810" } ], "paper_placeholder": false, "slug": "tightbinder", "idx": 162, "overview": "tightbinder is a versatile Python library designed for the modeling of solid-state systems using the Tight-Binding (TB) approximation. It provides a comprehensive suite of tools for constructing Hamiltonians, solving for electronic properties, and analyzing topological features. Its emphasis on a clean, object-oriented API makes it an excellent tool for rapid prototyping of model Hamiltonians and exploring concepts in topological insulators and condensed matter physics." }, { "num": "081d", "name": "TBFIT", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.5", "subcategory": "Tight-Binding DFT", "confidence": "VERIFIED", "official_url": "https://github.com/Infant83/TBFIT", "note": "Fortran code for fitting Tight-Binding parameters (Slater-Koster)", "md_link_text": "TBFIT.md", "md_link_path": "DFT/1.5_Tight-Binding/TBFIT.md", "papers": [], "paper_placeholder": true, "slug": "TBFIT", "idx": 163, "overview": "TBFIT is a specialized Fortran-based utility designed for the construction of Slater-Koster Tight-Binding (SK-TB) parametrizations. It solves the inverse problem: establishing a set of SK parameters that best reproduce a target electronic band structure (typically obtained from first-principles DFT calculations). By utilizing the robust Levenberg-Marquardt algorithm for non-linear least squares minimization, TBFIT allows computational physicists to create highly accurate, efficient model Hamilto" }, { "num": "081e", "name": "MLTB", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.5", "subcategory": "Tight-Binding DFT", "confidence": "VERIFIED", "official_url": "J. Chem. Theory Comput. (2024)", "note": "Machine Learning Tight Binding; ML neural network correction to DFTB repulsive term", "md_link_text": "MLTB.md", "md_link_path": "DFT/1.5_Tight-Binding/MLTB.md", "papers": [], "paper_placeholder": true, "slug": "MLTB", "idx": 164, "overview": "" }, { "num": "387", "name": "DFTB", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.5", "subcategory": "Tight-Binding DFT", "confidence": "VERIFIED", "official_url": "https://dftb.org/", "note": "DFTB method and Slater-Koster parameter sets repository.", "md_link_text": "DFTB.md", "md_link_path": "DFT/1.5_Tight-Binding/DFTB.md", "papers": [ { "name": "10.1021_jp069056r.pdf", "path": "Papers_of_Codes/DFT/1.5_Tight-Binding/DFTB/10.1021_jp069056r.pdf", "doi_url": "https://doi.org/10.1021/jp069056r" } ], "paper_placeholder": false, "slug": "DFTB-2", "idx": 165, "overview": "" }, { "num": "083", "name": "FlapwMBPT", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.6", "subcategory": "Specialized", "confidence": "VERIFIED", "official_url": "https://github.com/flapwmbpt/flapwmbpt", "note": "", "md_link_text": "FlapwMBPT.md", "md_link_path": "DFT/1.6_Specialized/FlapwMBPT.md", "papers": [ { "name": "FlapwMBPT_10.1016_j.cpc.2017.06.012.pdf", "path": "Papers_of_Codes/DFT/FlapwMBPT/FlapwMBPT_10.1016_j.cpc.2017.06.012.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2017.06.012" } ], "paper_placeholder": false, "slug": "FlapwMBPT", "idx": 166, "overview": "**FlapwMBPT** is an advanced electronic structure code developed by **Andrey Kutepov** (BNL) for over 30 years. It combines the rigorous **Full-Potential Linearized Augmented Plane Wave (FLAPW)** method with **Many-Body Perturbation Theory (MBPT)** to provide high-precision calculations of ground and excited states. It allows for consistent treatment of electronic correlations using GW approximation, self-consistent GW (scGW), and vertex corrections." }, { "num": "085", "name": "cmpy", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.6", "subcategory": "Specialized", "confidence": "VERIFIED", "official_url": "https://github.com/AMDKIIT/amdkiit", "note": "Plane-Wave AIMD code (IIT Kanpur)", "md_link_text": "AMDKIIT.md", "md_link_path": "DFT/1.6_Specialized/AMDKIIT.md", "papers": [], "paper_placeholder": true, "slug": "cmpy", "idx": 167, "overview": "AMDKIIT (`ab initio` Molecular Dynamics at KIIT/IIT) is a specialized Plane-Wave DFT software package developed to perform efficient molecular dynamics simulations. Created under the Indian National Supercomputing Mission (NSM), it is designed to run efficiently on high-performance computing clusters, including those with GPU acceleration. It bridges the gap between general-purpose DFT codes and specialized MD engines, focusing on the high-throughput generation of AIMD trajectories." }, { "num": "085a", "name": "DeepH", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.7", "subcategory": "Machine Learning Enhanced DFT", "confidence": "VERIFIED", "official_url": "https://github.com/mzjb/DeepH-pack", "note": "", "md_link_text": "DeepH.md", "md_link_path": "DFT/1.7_Machine_Learning/DeepH.md", "papers": [], "paper_placeholder": true, "slug": "DeepH", "idx": 168, "overview": "**DeepH** is a state-of-the-art framework for **Machine Learning Enhanced DFT**. It bypasses the computationally expensive self-consistent field (SCF) iterations of traditional DFT by learning a mapping from atomic structures to the DFT Hamiltonian. Utilizing E(3)-equivariant neural networks, it can predict accurate Hamiltonians for large-scale material systems, generalizing from small unit cells to huge supercells with $O(N)$ inference cost." }, { "num": "085b", "name": "MACE", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.7", "subcategory": "Machine Learning Enhanced DFT", "confidence": "VERIFIED", "official_url": "https://github.com/ACEsuit/mace", "note": "", "md_link_text": "MACE.md", "md_link_path": "Niche/10.1_MLIPs_Message_Passing/MACE.md", "papers": [], "paper_placeholder": true, "slug": "MACE", "idx": 169, "overview": "MACE creates fast and accurate machine learning interatomic potentials using higher-order equivariant message passing. It combines the strengths of the Atomic Cluster Expansion (ACE) with message passing neural networks (MPNNs). MACE achieves state-of-the-art accuracy and is designed to be scalable for large simulations." }, { "num": "085c", "name": "NequIP", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.7", "subcategory": "Machine Learning Enhanced DFT", "confidence": "VERIFIED", "official_url": "https://github.com/Teoroo-CMC/ParAutomatik", "note": "ML-based workflow for DFTB parameterization", "md_link_text": "ParAutomatik.md", "md_link_path": "DFT/1.7_Machine_Learning/ParAutomatik.md", "papers": [ { "name": "10_1038_s41467-022-29939-5.pdf", "path": "Papers_of_Codes/Niche/10.1_MLIPs_Message_Passing/NequIP/10_1038_s41467-022-29939-5.pdf", "doi_url": "https://scholar.google.com/scholar?q=NequIP+10+1038+s41467+022+29939+5" } ], "paper_placeholder": false, "slug": "NequIP", "idx": 170, "overview": "ParAutomatik is a cutting-edge workflow automation tool designed for the parameterization of Density Functional Tight Binding (DFTB) models using Machine Learning. It addresses one of the biggest bottlenecks in semi-empirical methods: the difficulty of creating accurate parameters. By combining high-throughput DFT calculations with Neural Network training, ParAutomatik automates the fitting of repulsive potentials and electronic parameters, significantly accelerating the development of transfera" }, { "num": "085d", "name": "PyFock", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.8", "subcategory": "Educational / Lightweight DFT", "confidence": "VERIFIED", "official_url": "https://github.com/manassharma07/PyFock", "note": "", "md_link_text": "PyFock.md", "md_link_path": "DFT/1.8_Educational/PyFock.md", "papers": [], "paper_placeholder": true, "slug": "PyFock", "idx": 171, "overview": "**PyFock** is a modern, pure-Python implementation of Density Functional Theory (DFT) and Hartree-Fock (HF) methods. Designed with transparency and hackability in mind, it leverages **JIT compilation (Numba)** and optionally **GPU acceleration (CuPy)** to achieve performance comparable to compiled C++ codes while maintaining the simplicity of a Python codebase." }, { "num": "085e", "name": "tinydft", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.8", "subcategory": "Educational / Lightweight DFT", "confidence": "VERIFIED", "official_url": "https://github.com/theochem/tinydft", "note": "", "md_link_text": "tinydft.md", "md_link_path": "DFT/1.8_Educational/tinydft.md", "papers": [], "paper_placeholder": true, "slug": "tinydft", "idx": 172, "overview": "tinydft is a minimalistic implementations of Density Functional Theory (DFT) in Python, designed specifically for educational purposes. It illustrates the core components of a DFT calculation\u2014grids, basis sets, Hamiltonian construction, and self-consistency\u2014within a compact codebase (often fitting in a single file or small module). It serves as a pedagogical tool for students and developers to read and understand the \"black box\" of quantum chemistry software." }, { "num": "085f", "name": "DFT++", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.8", "subcategory": "Educational / Lightweight DFT", "confidence": "VERIFIED", "official_url": "https://github.com/ifilot/pypwdft", "note": "Pure Python Plane-Wave DFT educational code", "md_link_text": "pypwdft.md", "md_link_path": "DFT/1.8_Educational/pypwdft.md", "papers": [ { "name": "DFT++_10.1016_S0010-4655(00)00072-2.pdf", "path": "Papers_of_Codes/DFT/DFT%2B%2B/DFT%2B%2B_10.1016_S0010-4655%2800%2900072-2.pdf", "doi_url": "https://doi.org/10.1016/S0010-4655(00)00072-2" } ], "paper_placeholder": false, "slug": "DFT", "idx": 173, "overview": "pypwdft is a pure Python implementation of a Plane-Wave Density Functional Theory (PW-DFT) code. It provides a complete, self-contained educational platform for understanding how plane-wave basis sets, pseudopotentials, and reciprocal space operations work in standard codes like VASP or Quantum ESPRESSO, but in a readable, non-HPC Python environment." }, { "num": "085g", "name": "M-SPARC", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.9", "subcategory": "Real-Space DFT", "confidence": "VERIFIED", "official_url": "https://materiapps.issp.u-tokyo.ac.jp/en/apps/rspace/", "note": "Real-space code for surfaces and quantum transport", "md_link_text": "RSPACE.md", "md_link_path": "DFT/1.9_Real-Space/RSPACE.md", "papers": [ { "name": "M-SPARC_10.1016_j.softx.2020.100423.pdf", "path": "Papers_of_Codes/DFT/M-SPARC/M-SPARC_10.1016_j.softx.2020.100423.pdf", "doi_url": "https://doi.org/10.1016/j.softx.2020.100423" } ], "paper_placeholder": false, "slug": "M-SPARC", "idx": 174, "overview": "RSPACE is a first-principles simulation code package based on the real-space finite-difference method using pseudopotentials. It is specifically tailored for high-speed and high-precision calculations of electronic states in aperiodic systems such as surfaces, solid interfaces, clusters, and nanostructures. It offers specialized implementation for quantum transport properties under semi-infinite boundary conditions." }, { "num": "085j", "name": "MaZe", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.10", "subcategory": "Orbital Free DFT", "confidence": "VERIFIED", "official_url": "https://gitlab.e-cam2020.eu/esl/MaZe", "note": "Mass-Zero constrained Molecular Dynamics for OF-DFT", "md_link_text": "MaZe.md", "md_link_path": "DFT/1.10_Orbital_Free/MaZe.md", "papers": [], "paper_placeholder": true, "slug": "MaZe", "idx": 175, "overview": "MaZe is a specialized code for performing Orbital-Free Density Functional Theory Molecular Dynamics (OF-DFT-MD) using the Mass-Zero (MaZe) constrained molecular dynamics approach. It focuses on the adiabatic propagation of the electronic density, treating it as a dynamic variable with zero mass, which allows for efficient and stable time evolution of large-scale systems within the orbital-free framework." }, { "num": "085k", "name": "ATLAS", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.10", "subcategory": "Orbital Free DFT", "confidence": "VERIFIED", "official_url": "Research Code (Mi et al., CPC 2016)", "note": "Real-space Orbital-Free DFT (O(N) for millions of atoms)", "md_link_text": "ATLAS.md", "md_link_path": "DFT/1.10_Orbital_Free/ATLAS.md", "papers": [ { "name": "ATLAS_10.1016_j.cpc.2015.11.004.pdf", "path": "Papers_of_Codes/DFT/ATLAS/ATLAS_10.1016_j.cpc.2015.11.004.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2015.11.004" } ], "paper_placeholder": false, "slug": "ATLAS", "idx": 176, "overview": "ATLAS is a specialized Orbital-Free Density Functional Theory (OF-DFT) software package. Unlike Kohn-Sham DFT, ATLAS solves for the electron density directly without using orbitals, typically employing a real-space finite-difference method. This allows it to scale linearly with system size (O(N)) with a very small prefactor, enabling simulations of millions of atoms, particularly for main-group metals (like Al, Mg) where OF-DFT kinetic energy functionals are accurate." }, { "num": "085l", "name": "KineticNet", "category_id": "1", "category": "GROUND-STATE DFT", "subcategory_id": "1.10", "subcategory": "Orbital Free DFT", "confidence": "VERIFIED", "official_url": "J. Chem. Phys. 159, 144113 (2023)", "note": "Deep learning transferable kinetic energy functional for orbital-free DFT", "md_link_text": "KineticNet.md", "md_link_path": "DFT/1.10_Orbital_Free/KineticNet.md", "papers": [], "paper_placeholder": true, "slug": "KineticNet", "idx": 177, "overview": "" }, { "num": "086", "name": "Octopus", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.1", "subcategory": "Real-Time TDDFT", "confidence": "CONFIRMED", "official_url": "https://octopus-code.org/", "note": "", "md_link_text": "Octopus.md", "md_link_path": "TDDFT/2.1_Real-Time_TDDFT/Octopus.md", "papers": [ { "name": "Andrade_et_al_2015.pdf", "path": "Papers_of_Codes/TDDFT/2.1_Real-Time_TDDFT/Octopus/Andrade_et_al_2015.pdf", "doi_url": "https://scholar.google.com/scholar?q=Octopus+Andrade+et+al+2015" } ], "paper_placeholder": false, "slug": "Octopus", "idx": 178, "overview": "Octopus is a scientific program for the ab initio simulation of electron-ion dynamics using time-dependent density-functional theory (TDDFT) and real-space grids. It specializes in real-time propagation for studying ultrafast processes, optical properties, and electron dynamics." }, { "num": "087", "name": "SALMON", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.1", "subcategory": "Real-Time TDDFT", "confidence": "CONFIRMED", "official_url": "https://salmon-tddft.jp/", "note": "", "md_link_text": "SALMON.md", "md_link_path": "TDDFT/2.1_Real-Time_TDDFT/SALMON.md", "papers": [ { "name": "SALMON_10.1016_j.cpc.2018.09.018.pdf", "path": "Papers_of_Codes/TDDFT/SALMON/SALMON_10.1016_j.cpc.2018.09.018.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2018.09.018" } ], "paper_placeholder": false, "slug": "SALMON", "idx": 179, "overview": "SALMON (Scalable Ab-initio Light-Matter simulator for Optics and Nanoscience) is a massively-parallel software for ab-initio quantum-mechanical calculations of electron dynamics and light-matter interactions. It is based on time-dependent density functional theory (TDDFT) and specializes in simulating ultrafast phenomena, nonlinear optical responses, and strong-field physics in periodic systems." }, { "num": "105", "name": "Qbox (TDDFT)", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.1", "subcategory": "Real-Time TDDFT", "confidence": "CONFIRMED", "official_url": "http://qboxcode.org/", "note": "Real-Time TDDFT implementation (Main Code #009)", "md_link_text": "Qbox.md", "md_link_path": "TDDFT/2.1_Real-Time_TDDFT/Qbox.md", "papers": [ { "name": "Qbox_(TDDFT)_10.1147_rd.521.0137.pdf", "path": "Papers_of_Codes/TDDFT/Qbox_%28TDDFT%29/Qbox_%28TDDFT%29_10.1147_rd.521.0137.pdf", "doi_url": "https://doi.org/10.1147/rd.521.0137" } ], "paper_placeholder": false, "slug": "Qbox-TDDFT", "idx": 180, "overview": "Qbox is a scalable parallel implementation of first-principles molecular dynamics based on the plane-wave, pseudopotential formalism. Developed by Fran\u00e7ois Gygi at UC Davis, Qbox is specifically designed for exceptional parallel scalability on high-performance computing systems, with demonstrated efficiency on tens of thousands of processors. It excels at large-scale ab initio molecular dynamics simulations of complex systems, particularly for studying materials under extreme conditions." }, { "num": "106", "name": "GPAW (TDDFT)", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.1", "subcategory": "Real-Time TDDFT", "confidence": "CONFIRMED", "official_url": "https://wiki.fysik.dtu.dk/gpaw/", "note": "Real-Time & Linear-Response TDDFT (Main Code #007)", "md_link_text": "GPAW.md", "md_link_path": "TDDFT/2.1_Real-Time_TDDFT/GPAW.md", "papers": [ { "name": "Enkovaara_et_al_2010.pdf", "path": "Papers_of_Codes/TDDFT/2.1_Real-Time_TDDFT/GPAW/Enkovaara_et_al_2010.pdf", "doi_url": "https://scholar.google.com/scholar?q=GPAW+%28TDDFT%29+Enkovaara+et+al+2010" } ], "paper_placeholder": false, "slug": "GPAW-TDDFT", "idx": 181, "overview": "GPAW is a density-functional theory Python code based on the projector-augmented wave (PAW) method. It combines the efficiency of real-space grids with the accuracy of plane-wave methods and integrates seamlessly with the Atomic Simulation Environment (ASE). GPAW is particularly strong for large-scale calculations, time-dependent DFT, and as a platform for method development." }, { "num": "106a", "name": "CE-TDDFT", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.1", "subcategory": "Real-Time TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/dceresoli/ce-tddft", "note": "Real-Time TDDFT extension for Quantum ESPRESSO with Ehrenfest dynamics", "md_link_text": "CE-TDDFT.md", "md_link_path": "TDDFT/2.1_Real-Time_TDDFT/CE-TDDFT.md", "papers": [], "paper_placeholder": true, "slug": "CE-TDDFT", "idx": 182, "overview": "CE-TDDFT is a Real-Time Time-Dependent Density Functional Theory (RT-TDDFT) extension for Quantum ESPRESSO. It enables explicit time-propagation of Kohn-Sham orbitals to simulate non-equilibrium electron dynamics, strong-field phenomena, and Ehrenfest molecular dynamics." }, { "num": "106b", "name": "RT-tddft", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.1", "subcategory": "Real-Time TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/sheyua/RT-tddft", "note": "Real-Time Plane-Wave TDDFT for nanostructure dynamics (QE-based)", "md_link_text": "RT-tddft.md", "md_link_path": "TDDFT/2.1_Real-Time_TDDFT/RT-tddft.md", "papers": [], "paper_placeholder": true, "slug": "RT-tddft", "idx": 183, "overview": "RT-tddft is a Real-Time Plane-Wave Time-Dependent Density Functional Theory code designed for simulating ultrafast electron dynamics, particularly focused on discharging nanostructures and non-equilibrium phenomena. It is built as an extension to Quantum ESPRESSO." }, { "num": "106c", "name": "kspy-tddft", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.1", "subcategory": "Real-Time TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/pwborthwick/kspy-tddft", "note": "Pure Python RT-TDDFT and LR-TDDFT with Magnus expansion (educational)", "md_link_text": "kspy-tddft.md", "md_link_path": "TDDFT/2.1_Real-Time_TDDFT/kspy-tddft.md", "papers": [], "paper_placeholder": true, "slug": "kspy-tddft", "idx": 184, "overview": "kspy-tddft is a pure Python implementation of Time-Dependent Density Functional Theory supporting both Linear-Response TDDFT (in the Tamm-Dancoff Approximation) and Real-Time TDDFT. It is designed for educational purposes and small molecular systems, featuring Magnus expansion time propagation and Pad\u00e9 approximant spectral analysis." }, { "num": "106d", "name": "rhodent", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.1", "subcategory": "Real-Time TDDFT", "confidence": "VERIFIED", "official_url": "https://pypi.org/project/rhodent/", "note": "Python package for RT-TDDFT response analysis (hot-carriers, GPAW)", "md_link_text": "rhodent.md", "md_link_path": "TDDFT/2.1_Real-Time_TDDFT/rhodent.md", "papers": [], "paper_placeholder": true, "slug": "rhodent", "idx": 185, "overview": "rhodent is a modular Python package for analyzing the output of Real-Time Time-Dependent Density Functional Theory (RT-TDDFT) calculations. It processes RT-TDDFT data to compute hot-carrier distributions, induced densities, dipole moments, and frequency-dependent responses. While primarily designed for GPAW output, its modular architecture allows extension to other RT-TDDFT codes." }, { "num": "106e", "name": "Qb@ll (Qball)", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.1", "subcategory": "Real-Time TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/LLNL/qball", "note": "LLNL fork of Qbox with RT-TDDFT development (Qb@ch branch)", "md_link_text": "Qball.md", "md_link_path": "TDDFT/2.1_Real-Time_TDDFT/Qball.md", "papers": [], "paper_placeholder": true, "slug": "Qb-ll-Qball", "idx": 186, "overview": "Qb@ll (also written as Qball or qb@ll) is a first-principles molecular dynamics code developed at Lawrence Livermore National Laboratory. It computes electronic structure of atoms, molecules, solids, and liquids using Density Functional Theory with a plane-wave basis. Qb@ll is a fork of the Qbox code by Fran\u00e7ois Gygi, optimized for high-performance computing including Real-Time TDDFT capabilities." }, { "num": "106f", "name": "GCEED", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.1", "subcategory": "Real-Time TDDFT", "confidence": "VERIFIED", "official_url": "https://sourceforge.net/projects/gceed/", "note": "Grid-based Coupled Electron and Electromagnetic field Dynamics; Real-Time TDDFT.", "md_link_text": "GCEED.md", "md_link_path": "TDDFT/2.1_Real-Time_TDDFT/GCEED.md", "papers": [ { "name": "GCEED_10.7566_JPSCP.5.011010.pdf", "path": "Papers_of_Codes/TDDFT/GCEED/GCEED_10.7566_JPSCP.5.011010.pdf", "doi_url": "https://doi.org/10.7566/JPSCP.5.011010" } ], "paper_placeholder": false, "slug": "GCEED", "idx": 187, "overview": "GCEED (Grid-based Coupled Electron and Electromagnetic field Dynamics) is an open-source software package designed for massively parallel first-principles calculations of electron dynamics in real time and real space. It is specifically built to simulate the coupled dynamics of electrons and electromagnetic fields, making it suitable for studying light-matter interactions in nanostructures and solids." }, { "num": "106g", "name": "TTDFT", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.1", "subcategory": "Real-Time TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/ttdftdev/ttdft_public", "note": "Real-space TDDFT with GPU acceleration (University of Michigan).", "md_link_text": "TTDFT.md", "md_link_path": "TDDFT/2.1_Real-Time_TDDFT/TTDFT.md", "papers": [], "paper_placeholder": true, "slug": "TTDFT", "idx": 188, "overview": "TTDFT is a high-performance Real-Space Time-Dependent Density Functional Theory code designed for modern heterogeneous computing architectures. It is written in C++ and leverages NVIDIA GPUs for significant acceleration of key operations, such as matrix multiplications in the Kohn-Sham propagation." }, { "num": "106h", "name": "Socorro", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.1", "subcategory": "Real-Time TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/sandialabs/socorro (Archived)", "note": "Scalable DFT code with TDDFT capabilities (Sandia Legacy).", "md_link_text": "Socorro.md", "md_link_path": "TDDFT/2.1_Real-Time_TDDFT/Socorro.md", "papers": [], "paper_placeholder": true, "slug": "Socorro", "idx": 189, "overview": "Socorro is a locally-basis-free, plane-wave Density Functional Theory (DFT) code developed at Sandia National Laboratories. It was engineered for extreme scalability on massively parallel supercomputers. While primary development has ceased, it remains a valuable reference for scalable algorithms, particularly for exact-exchange calculations. It includes Time-Dependent DFT (TDDFT) capabilities for excited states." }, { "num": "089", "name": "turboTDDFT", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.2", "subcategory": "Linear-Response TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/qe-forge/turboEELS (Legacy QE plugin)", "note": "", "md_link_text": "turboTDDFT.md", "md_link_path": "TDDFT/2.2_Linear-Response_TDDFT/turboTDDFT.md", "papers": [ { "name": "turboTDDFT_10.1016_j.cpc.2011.04.020.pdf", "path": "Papers_of_Codes/TDDFT/turboTDDFT/turboTDDFT_10.1016_j.cpc.2011.04.020.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2011.04.020" } ], "paper_placeholder": false, "slug": "turboTDDFT", "idx": 190, "overview": "turboTDDFT is a legacy TDDFT module for Quantum ESPRESSO that implements time-dependent density functional theory for calculating optical absorption spectra, excitation energies, and dynamic polarizabilities. Historically part of the QE ecosystem, turboTDDFT functionality has largely been superseded by newer implementations (turboEELS, turbo_spectrum.x) within Quantum ESPRESSO. It uses linear-response TDDFT with plane-wave basis sets for periodic systems." }, { "num": "090", "name": "PyTDDFT", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.2", "subcategory": "Linear-Response TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/f-fathurrahman/PyTDDFT", "note": "", "md_link_text": "PyTDDFT.md", "md_link_path": "TDDFT/2.2_Linear-Response_TDDFT/PyTDDFT.md", "papers": [], "paper_placeholder": true, "slug": "PyTDDFT", "idx": 191, "overview": "PyTDDFT is a research/educational Python implementation of time-dependent density functional theory for learning and prototyping TDDFT methods. Developed by Fadjar Fathurrahman, PyTDDFT provides a transparent, readable implementation of TDDFT in Python, prioritizing code clarity and educational value over production performance. It serves as a platform for understanding TDDFT algorithms and experimenting with method development." }, { "num": "107", "name": "NWChem (TDDFT)", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.2", "subcategory": "Linear-Response TDDFT", "confidence": "CONFIRMED", "official_url": "https://nwchemgit.github.io/", "note": "Extensive Linear-Response TDDFT module (Main Code #054)", "md_link_text": "NWChem.md", "md_link_path": "TDDFT/2.2_Linear-Response_TDDFT/NWChem.md", "papers": [ { "name": "Valiev_et_al_2010.pdf", "path": "Papers_of_Codes/TDDFT/2.2_Linear-Response_TDDFT/NWChem/Valiev_et_al_2010.pdf", "doi_url": "https://scholar.google.com/scholar?q=NWChem+%28TDDFT%29+Valiev+et+al+2010" } ], "paper_placeholder": false, "slug": "NWChem-TDDFT", "idx": 192, "overview": "NWChem is a comprehensive, open-source computational chemistry package designed for massively parallel high-performance computing. Developed and maintained by Pacific Northwest National Laboratory (PNNL), it provides a broad range of methods from DFT to coupled cluster, with particular strengths in scalability, molecular dynamics, and plane-wave calculations for solids. NWChem can scale from single processors to thousands of cores on leadership-class supercomputers." }, { "num": "108", "name": "CP2K (TDDFT)", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.2", "subcategory": "Linear-Response TDDFT", "confidence": "CONFIRMED", "official_url": "https://www.cp2k.org/", "note": "TDDFPT and Real-Time propagation (Main Code #005)", "md_link_text": "CP2K.md", "md_link_path": "TDDFT/2.2_Linear-Response_TDDFT/CP2K.md", "papers": [ { "name": "Kuhne_et_al_2020.pdf", "path": "Papers_of_Codes/TDDFT/2.2_Linear-Response_TDDFT/CP2K/Kuhne_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=CP2K+%28TDDFT%29+Kuhne+et+al+2020" } ], "paper_placeholder": false, "slug": "CP2K-TDDFT", "idx": 193, "overview": "CP2K is a versatile quantum chemistry and solid-state physics software package performing atomistic simulations of solid state, liquid, molecular, periodic, material, crystal, and biological systems. It excels at molecular dynamics simulations using mixed Gaussian and plane waves (GPW) method, and is particularly strong for large-scale condensed phase simulations including ab initio molecular dynamics." }, { "num": "109", "name": "exciting (TDDFT)", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.2", "subcategory": "Linear-Response TDDFT", "confidence": "CONFIRMED", "official_url": "https://exciting-code.org/", "note": "TDDFT and BSE implementations (Main Code #027)", "md_link_text": "exciting.md", "md_link_path": "TDDFT/2.2_Linear-Response_TDDFT/exciting.md", "papers": [ { "name": "10_1088_0953-8984_26_36_363202.pdf", "path": "Papers_of_Codes/TDDFT/2.2_Linear-Response_TDDFT/exciting/10_1088_0953-8984_26_36_363202.pdf", "doi_url": "https://scholar.google.com/scholar?q=exciting+%28TDDFT%29+10+1088+0953+8984+26+36+363202" } ], "paper_placeholder": false, "slug": "exciting-TDDFT", "idx": 194, "overview": "exciting is an all-electron full-potential linearized augmented planewave (FP-LAPW) code for DFT and beyond, with particular strength in optical and excited-state properties. It provides advanced capabilities for TDDFT, GW, and BSE calculations with a modern, open-source codebase." }, { "num": "109a", "name": "qed-tddft", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.2", "subcategory": "Linear-Response TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/cc-ats/qed-tddft", "note": "Quantum-Electrodynamical TDDFT for cavity QED/polaritonic chemistry (PySCF)", "md_link_text": "qed-tddft.md", "md_link_path": "TDDFT/2.2_Linear-Response_TDDFT/qed-tddft.md", "papers": [], "paper_placeholder": true, "slug": "qed-tddft", "idx": 195, "overview": "qed-tddft is a specialized Python package for Quantum-Electrodynamical Time-Dependent Density Functional Theory (QED-TDDFT) within Gaussian atomic basis sets. It enables the simulation of molecules strongly coupled to quantized electromagnetic field modes in optical cavities, capturing light-matter interactions at the quantum level. Built on top of PySCF, it provides a framework for cavity QED calculations in molecular systems." }, { "num": "109b", "name": "TDDFT-ris", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.2", "subcategory": "Linear-Response TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/John-zzh/pyscf_TDDFT_ris", "note": "Fast semiempirical LR-TDDFT (~300x speedup, PySCF/MOKIT)", "md_link_text": "TDDFT-ris.md", "md_link_path": "TDDFT/2.2_Linear-Response_TDDFT/TDDFT-ris.md", "papers": [], "paper_placeholder": true, "slug": "TDDFT-ris", "idx": 196, "overview": "TDDFT-ris is a high-performance Python implementation of a semiempirical Linear-Response TDDFT method that achieves ~300x speedup over traditional ab initio TDDFT while maintaining accuracy within 0.06 eV for excitation energies of organic molecules. The method uses Resolution-of-the-Identity (RI) approximation with minimal auxiliary basis (single s-type orbital per atom) and disables the XC kernel, providing an excellent balance of speed and accuracy for UV-Vis spectroscopy." }, { "num": "109c", "name": "2DModel", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.2", "subcategory": "Linear-Response TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/UllrichDFT/2DModel", "note": "2D model solid DFT/TDDFT for method development (C.A. Ullrich)", "md_link_text": "2DModel.md", "md_link_path": "TDDFT/2.2_Linear-Response_TDDFT/2DModel.md", "papers": [], "paper_placeholder": true, "slug": "2DModel", "idx": 197, "overview": "2DModel is a Python code for performing DFT and TDDFT simulations on 2D model solids. Developed by Prof. Carsten Ullrich's group (a leading expert in TDDFT theory), it provides a testbed for exploring fundamental aspects of density functional theory and time-dependent DFT in reduced dimensionality. The code is valuable for methodology development, testing new XC functionals, and understanding TDDFT physics in a controlled setting." }, { "num": "109d", "name": "CoreProjectedHybrids", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.2", "subcategory": "Linear-Response TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/bjanesko/CoreProjectedHybrids", "note": "Core-projected hybrid DFT/TDDFT extensions for PySCF", "md_link_text": "CoreProjectedHybrids.md", "md_link_path": "TDDFT/2.2_Linear-Response_TDDFT/CoreProjectedHybrids.md", "papers": [], "paper_placeholder": true, "slug": "CoreProjectedHybrids", "idx": 198, "overview": "CoreProjectedHybrids is a PySCF extension module for performing self-consistent and linear-response TDDFT calculations using core-projected hybrid exchange-correlation functionals. These functionals modify the treatment of exact exchange in the core region, offering improved balance between core and valence electron correlation. The package provides specialized functionals for accurate excited state calculations in systems where core-valence interactions are important." }, { "num": "109e", "name": "ksdft++", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.2", "subcategory": "Linear-Response TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/sspaino/ksdft (or similar)", "note": "Educational C++ DFT code with Armadillo/FFTW", "md_link_text": "ksdft++.md", "md_link_path": "TDDFT/2.2_Linear-Response_TDDFT/ksdft++.md", "papers": [], "paper_placeholder": true, "slug": "ksdft", "idx": 199, "overview": "ksdft++ is an educational C++ Density Functional Theory code designed for learning electronic structure theory implementation. It provides a clean, readable C++ implementation using modern libraries (Armadillo for linear algebra, FFTW for Fast Fourier Transforms) and can serve as a foundation for understanding DFT methodology and extending to TDDFT capabilities." }, { "num": "109f", "name": "DFTCXX", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.2", "subcategory": "Linear-Response TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/ifilot/dftcxx", "note": "Educational C++ molecular DFT (Ivo Filot, TU/e)", "md_link_text": "DFTCXX.md", "md_link_path": "TDDFT/2.2_Linear-Response_TDDFT/DFTCXX.md", "papers": [], "paper_placeholder": true, "slug": "DFTCXX", "idx": 200, "overview": "DFTCXX is an educational C++ Density Functional Theory program developed by Dr. Ivo Filot for understanding and teaching electronic structure theory. The code focuses on calculating the electronic structure of simple molecules using Gaussian basis sets, providing a clear implementation that can be studied, modified, and extended. It serves as a companion to the author's other educational codes (PyDFT, pyqint)." }, { "num": "109g", "name": "PhotoionizationGTO.jl", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.2", "subcategory": "Linear-Response TDDFT", "confidence": "VERIFIED", "official_url": "https://github.com/antoine-levitt/PhotoionizationGTO.jl", "note": "TDDFT photoionization spectra using Gaussian orbitals (Julia).", "md_link_text": "PhotoionizationGTO_jl.md", "md_link_path": "TDDFT/2.2_Linear-Response_TDDFT/PhotoionizationGTO_jl.md", "papers": [], "paper_placeholder": true, "slug": "PhotoionizationGTO.jl", "idx": 201, "overview": "PhotoionizationGTO.jl is a specialized Julia package for calculating photoionization spectra using Time-Dependent Density Functional Theory (TDDFT). It uniquely employs Gaussian-type orbitals (GTOs) to describe the bound states while handling the continuum states appropriate for photoionization processes, interfacing with the PySCF library for integrals." }, { "num": "092", "name": "BerkeleyGW", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "CONFIRMED", "official_url": "https://berkeleygw.org/", "note": "", "md_link_text": "BerkeleyGW.md", "md_link_path": "TDDFT/2.3_GW_Methods/BerkeleyGW.md", "papers": [ { "name": "Deslippe_et_al_2012.pdf", "path": "Papers_of_Codes/TDDFT/2.3_GW_Methods/BerkeleyGW/Deslippe_et_al_2012.pdf", "doi_url": "https://scholar.google.com/scholar?q=BerkeleyGW+Deslippe+et+al+2012" } ], "paper_placeholder": false, "slug": "BerkeleyGW", "idx": 202, "overview": "BerkeleyGW is a massively parallel code for computing the quasiparticle and optical properties of materials using many-body perturbation theory within the GW approximation and the Bethe-Salpeter equation (BSE). It is designed for large-scale calculations on leadership-class supercomputers and provides highly accurate band structures, band gaps, and optical spectra beyond DFT." }, { "num": "093", "name": "WEST", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "CONFIRMED", "official_url": "https://west-code.org/", "note": "", "md_link_text": "WEST.md", "md_link_path": "TDDFT/2.3_GW_Methods/WEST.md", "papers": [ { "name": "Govoni_Galli_2015.pdf", "path": "Papers_of_Codes/TDDFT/2.3_GW_Methods/WEST/Govoni_Galli_2015.pdf", "doi_url": "https://scholar.google.com/scholar?q=WEST+Govoni+Galli+2015" } ], "paper_placeholder": false, "slug": "WEST", "idx": 203, "overview": "WEST (Without Empty STates) is a massively parallel software for large-scale electronic structure calculations within many-body perturbation theory. It implements GW approximation and TDDFT for computing quasiparticle energies and optical spectra without the need for empty states, enabling efficient calculations for large systems using density functional perturbation theory techniques." }, { "num": "094", "name": "Spex", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "CONFIRMED", "official_url": "https://github.com/flapw-spex/spex", "note": "", "md_link_text": "Spex.md", "md_link_path": "TDDFT/2.3_GW_Methods/Spex.md", "papers": [ { "name": "Spex_10.1103_PhysRevB.81.125102.pdf", "path": "Papers_of_Codes/TDDFT/Spex/Spex_10.1103_PhysRevB.81.125102.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.81.125102" } ], "paper_placeholder": false, "slug": "Spex", "idx": 204, "overview": "Spex is an all-electron code for calculating quasiparticle energies and optical spectra using many-body perturbation theory (GW and Bethe-Salpeter equation). Developed primarily at Forschungszentrum J\u00fclich, Spex uses the FLAPW method as input and implements sophisticated algorithms for GW self-energy and BSE kernel calculations. It is particularly powerful for accurate band gaps, quasiparticle band structures, and optical absorption spectra of solids." }, { "num": "095", "name": "SternheimerGW", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "VERIFIED", "official_url": "https://github.com/QEF/SternheimerGW", "note": "", "md_link_text": "SternheimerGW.md", "md_link_path": "TDDFT/2.3_GW_Methods/SternheimerGW.md", "papers": [ { "name": "10.1016_j.cpc.2019.106856.pdf", "path": "Papers_of_Codes/TDDFT/2.3_GW_Methods/SternheimerGW/10.1016_j.cpc.2019.106856.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2019.106856" } ], "paper_placeholder": false, "slug": "SternheimerGW", "idx": 205, "overview": "SternheimerGW is a specialized GW code utilizing the Sternheimer linear-response approach to avoid explicit summation over empty states. Developed and maintained by Feliciano Giustino\u2019s group (CQME at UT Austin), it offers an efficient alternative to standard sum-over-states implementations, integral to the EPW and Quantum ESPRESSO ecosystems." }, { "num": "096", "name": "Fiesta", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "VERIFIED", "official_url": "https://github.com/fiesta-gw/fiesta", "note": "", "md_link_text": "Fiesta.md", "md_link_path": "TDDFT/2.3_GW_Methods/Fiesta.md", "papers": [ { "name": "Fiesta_10.1007_s10853-012-6401-7.pdf", "path": "Papers_of_Codes/TDDFT/Fiesta/Fiesta_10.1007_s10853-012-6401-7.pdf", "doi_url": "https://doi.org/10.1007/s10853-012-6401-7" } ], "paper_placeholder": false, "slug": "Fiesta", "idx": 206, "overview": "Fiesta is an open-source code for calculating electronic excitations using many-body perturbation theory (GW approximation and Bethe-Salpeter equation) starting from plane-wave DFT calculations. Developed by Marco D'Alessandro and collaborators, Fiesta focuses on efficient GW/BSE implementations with emphasis on optical properties, core-level spectroscopy, and exciton physics. It interfaces with major DFT codes (Quantum ESPRESSO, VASP) and provides comprehensive tools for excited-state calculati" }, { "num": "097", "name": "molgw", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "VERIFIED", "official_url": "https://github.com/molgw/molgw", "note": "", "md_link_text": "molgw.md", "md_link_path": "TDDFT/2.3_GW_Methods/molgw.md", "papers": [ { "name": "molgw_10.1016_j.cpc.2016.06.019.pdf", "path": "Papers_of_Codes/TDDFT/molgw/molgw_10.1016_j.cpc.2016.06.019.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2016.06.019" } ], "paper_placeholder": false, "slug": "molgw", "idx": 207, "overview": "molgw is an open-source quantum chemistry code implementing many-body perturbation theory (GW approximation and Bethe-Salpeter equation) for molecules and clusters using Gaussian basis sets. Developed by Fabien Bruneval (CEA, France), molgw focuses on efficient GW calculations for finite systems with emphasis on accurate ionization potentials, electron affinities, and optical excitations. It provides a user-friendly, lightweight alternative to larger quantum chemistry packages for MBPT calculati" }, { "num": "098", "name": "GreenX", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "VERIFIED", "official_url": "https://github.com/nomad-coe/greenX", "note": "", "md_link_text": "GreenX.md", "md_link_path": "TDDFT/2.3_GW_Methods/GreenX.md", "papers": [], "paper_placeholder": true, "slug": "GreenX", "idx": 208, "overview": "GreenX is a modern library for Green's function-based many-body perturbation theory calculations designed for exascale computing and integration with multiple electronic structure codes. Developed as part of the NOMAD Center of Excellence and the GreenSolver project, GreenX provides modular, efficient implementations of GW approximation, RPA, and related methods with emphasis on performance, scalability, and interoperability across different DFT codes." }, { "num": "098a", "name": "momentGW", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "CONFIRMED", "official_url": "https://github.com/BoothGroup/momentGW", "note": "Python package for moment-conserving GW calculations (PySCF ecosystem).", "md_link_text": "momentGW.md", "md_link_path": "TDDFT/2.3_GW_Methods/momentGW.md", "papers": [], "paper_placeholder": true, "slug": "momentGW", "idx": 209, "overview": "momentGW is a Python package for GW approximation calculations using moment-conserving solutions to the Dyson equation. Built on PySCF, it provides an efficient framework for calculating quasiparticle energies and spectral properties with novel algorithmic advantages including exact frequency integration and avoided analytical continuation." }, { "num": "098b", "name": "PyGW", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "VERIFIED", "official_url": "https://github.com/lechifflier/PyGW", "note": "Hybrid Fortran/Python code for G0W0 and GW0 on realistic materials.", "md_link_text": "PyGW.md", "md_link_path": "TDDFT/2.3_GW_Methods/PyGW.md", "papers": [], "paper_placeholder": true, "slug": "PyGW", "idx": 210, "overview": "PyGW is an electronic structure code for performing G0W0 and GW0 quasiparticle calculations on realistic materials. Implemented as a hybrid Fortran/Python code, it bridges computational efficiency with modern scripting capabilities for GW calculations in condensed matter physics." }, { "num": "098c", "name": "NanoGW", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "VERIFIED", "official_url": "https://codebase.helmholtz.cloud/nanogw/nanogw", "note": "Real-space grid GW/BSE code for confined systems (molecules/clusters).", "md_link_text": "NanoGW.md", "md_link_path": "TDDFT/2.3_GW_Methods/NanoGW.md", "papers": [ { "name": "NanoGW_10.1103_PhysRevB.73.205334.pdf", "path": "Papers_of_Codes/TDDFT/NanoGW/NanoGW_10.1103_PhysRevB.73.205334.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.73.205334" } ], "paper_placeholder": false, "slug": "NanoGW", "idx": 211, "overview": "NanoGW is an open-source software package for linear-response TDDFT, GW, and Bethe-Salpeter equation (BSE) calculations using a real-space grid. Designed specifically for confined systems such as molecules and nanoclusters, it performs full-frequency GW calculations with optional LDA vertex corrections." }, { "num": "098d", "name": "Green-MBPT", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "VERIFIED", "official_url": "https://github.com/Green-Phys/green-mbpt", "note": "Many-body perturbation solvers within the Green framework.", "md_link_text": "Green-MBPT.md", "md_link_path": "TDDFT/2.3_GW_Methods/Green-MBPT.md", "papers": [], "paper_placeholder": true, "slug": "Green-MBPT", "idx": 212, "overview": "Green-MBPT is a many-body perturbation theory solver within the Green software framework. It provides GW weak-coupling simulations and related many-body calculations for electronic structure, designed for integration with the broader Green computational ecosystem." }, { "num": "098e", "name": "FastGWConvergence", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "VERIFIED", "official_url": "https://github.com/robincamp/FastGWConvergence", "note": "Python workflow for robust G0W0 convergence automation (2024).", "md_link_text": "FastGWConvergence.md", "md_link_path": "TDDFT/2.3_GW_Methods/FastGWConvergence.md", "papers": [ { "name": "FastGWConvergence_10.1038_s41524-024-01311-9.pdf", "path": "Papers_of_Codes/TDDFT/FastGWConvergence/FastGWConvergence_10.1038_s41524-024-01311-9.pdf", "doi_url": "https://doi.org/10.1038/s41524-024-01311-9" } ], "paper_placeholder": false, "slug": "FastGWConvergence", "idx": 213, "overview": "FastGWConvergence (FGWC) is a Python-based workflow tool published in 2024 designed to robustly and efficiently converge G0W0 calculations. It automates the complex convergence parameters required for GW calculations, using Quantum ESPRESSO and YAMBO as backend engines, making high-quality GW results more accessible and reproducible." }, { "num": "098f", "name": "GAP", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "VERIFIED", "official_url": "Historic/Academic (WIEN2k interface)", "note": "All-electron GW code using Augmented Plane Waves (APW).", "md_link_text": "GAP.md", "md_link_path": "TDDFT/2.3_GW_Methods/GAP.md", "papers": [ { "name": "GAP_10.1016_j.cpc.2012.09.018.pdf", "path": "Papers_of_Codes/TDDFT/GAP/GAP_10.1016_j.cpc.2012.09.018.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2012.09.018" } ], "paper_placeholder": false, "slug": "GAP", "idx": 214, "overview": "GAP (specifically GAP2 - GW with Augmented Plane-waves) is the all-electron GW implementation within the WIEN2k ecosystem. It utilizes the full-potential linearized augmented plane-wave (FP-LAPW) basis set to perform high-precision G0W0 calculations, treating core, semi-core, and valence electrons on equal footing. It is considered a \"gold standard\" for GW accuracy in solids." }, { "num": "098g", "name": "GW-approximation", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "VERIFIED", "official_url": "https://github.com/aakunitsa/GW-approximation", "note": "Reference implementation of analytic GW@HF, RI, and RPA.", "md_link_text": "GW-approximation.md", "md_link_path": "TDDFT/2.3_GW_Methods/GW-approximation.md", "papers": [], "paper_placeholder": true, "slug": "GW-approximation", "idx": 215, "overview": "GW-approximation is a Python-based reference implementation of the analytic GW method (GW@HF) and other GW variants. While primarily an educational and reference tool, it provides clear, readable implementations of sophisticated features like Resolution of Identity (RI), contour deformation, and RPA screening, serving as an excellent resource for understanding and developing GW methods." }, { "num": "399", "name": "VASP-GW", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "VERIFIED", "official_url": "https://www.vasp.at/wiki/index.php/GW_approximation", "note": "GW implementation within VASP for quasiparticle band structures.", "md_link_text": "VASP-GW.md", "md_link_path": "TDDFT/2.3_GW_Methods/VASP-GW.md", "papers": [ { "name": "Shishkin_Kresse_2006.pdf", "path": "Papers_of_Codes/TDDFT/2.3_GW_Methods/VASP-GW/Shishkin_Kresse_2006.pdf", "doi_url": "https://scholar.google.com/scholar?q=VASP-GW+Shishkin+Kresse+2006" } ], "paper_placeholder": false, "slug": "VASP-GW", "idx": 216, "overview": "" }, { "num": "388", "name": "FHI-gap", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "VERIFIED", "official_url": "https://nomad-lab.eu/services/repo-arch", "note": "GW code from Fritz Haber Institute interfacing with FHI-aims.", "md_link_text": "FHI-gap.md", "md_link_path": "TDDFT/2.3_GW_Methods/FHI-gap.md", "papers": [ { "name": "Ren_et_al_2012.pdf", "path": "Papers_of_Codes/TDDFT/2.3_GW_Methods/FHI-gap/Ren_et_al_2012.pdf", "doi_url": "https://scholar.google.com/scholar?q=FHI-gap+Ren+et+al+2012" } ], "paper_placeholder": false, "slug": "FHI-gap", "idx": 217, "overview": "" }, { "num": "380", "name": "ABINIT-GW", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.3", "subcategory": "GW Methods", "confidence": "VERIFIED", "official_url": "https://www.abinit.org/topics/GW", "note": "GW implementation within ABINIT for quasiparticle band structures.", "md_link_text": "ABINIT-GW.md", "md_link_path": "TDDFT/2.3_GW_Methods/ABINIT-GW.md", "papers": [ { "name": "Gonze_et_al_2009_ABINIT-GW.pdf", "path": "Papers_of_Codes/TDDFT/2.3_GW_Methods/ABINIT-GW/Gonze_et_al_2009_ABINIT-GW.pdf", "doi_url": "https://scholar.google.com/scholar?q=ABINIT-GW+Gonze+et+al+2009+ABINIT+GW" } ], "paper_placeholder": false, "slug": "ABINIT-GW", "idx": 218, "overview": "" }, { "num": "088", "name": "Yambo", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.4", "subcategory": "BSE Methods", "confidence": "CONFIRMED", "official_url": "https://www.yambo-code.org/", "note": "", "md_link_text": "Yambo.md", "md_link_path": "TDDFT/2.4_BSE_Methods/Yambo.md", "papers": [ { "name": "Sangalli_et_al_2019.pdf", "path": "Papers_of_Codes/TDDFT/2.4_BSE_Methods/Yambo/Sangalli_et_al_2019.pdf", "doi_url": "https://scholar.google.com/scholar?q=Yambo+Sangalli+et+al+2019" } ], "paper_placeholder": false, "slug": "Yambo", "idx": 219, "overview": "Yambo is an open-source code for calculating excited state properties of materials from first principles using many-body perturbation theory. It implements the GW approximation for quasiparticle corrections and the Bethe-Salpeter equation for optical properties, featuring user-friendly interfaces and comprehensive capabilities for studying electronic excitations in molecules and solids." }, { "num": "100", "name": "OCEAN", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.4", "subcategory": "BSE Methods", "confidence": "VERIFIED", "official_url": "https://www.nersc.gov/users/computational-science/ncar/nersc-8 allocation-calls/ocean/", "note": "", "md_link_text": "OCEAN.md", "md_link_path": "TDDFT/2.4_BSE_Methods/OCEAN.md", "papers": [ { "name": "10_1103_PhysRevB_83_115106.pdf", "path": "Papers_of_Codes/TDDFT/2.4_BSE_Methods/OCEAN/10_1103_PhysRevB_83_115106.pdf", "doi_url": "https://scholar.google.com/scholar?q=OCEAN+10+1103+PhysRevB+83+115106" } ], "paper_placeholder": false, "slug": "OCEAN", "idx": 220, "overview": "OCEAN is a specialized code for calculating X-ray absorption spectra (XAS) and X-ray emission spectra (XES) using the Bethe-Salpeter Equation combined with DFT calculations. Developed at the University of Washington as part of the FEFF project, OCEAN focuses on core-level spectroscopy with emphasis on accurate treatment of core-hole effects, many-body interactions, and experimental comparison. It uses ABINIT or Quantum ESPRESSO for ground-state DFT and implements sophisticated BSE for core excit" }, { "num": "101", "name": "NBSE", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.4", "subcategory": "BSE Methods", "confidence": "VERIFIED", "official_url": "https://www.nist.gov/", "note": "NIST BSE solver for core-level Bethe-Salpeter equation calculations", "md_link_text": "NBSE.md", "md_link_path": "TDDFT/2.4_BSE_Methods/NBSE.md", "papers": [ { "name": "NBSE_10.1103_PhysRevB.83.115106.pdf", "path": "Papers_of_Codes/TDDFT/NBSE/NBSE_10.1103_PhysRevB.83.115106.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.83.115106" } ], "paper_placeholder": false, "slug": "NBSE", "idx": 221, "overview": "**NBSE** (NIST Bethe-Salpeter Equation solver) is the core solver engine used within the **OCEAN** (Obtaining Core Excitations using ABINIT and NBSE) package. Originally developed by Eric Shirley at NIST, it is designed for the accurate calculation of **core-level spectroscopic properties** (XAS, XES, NRIXS) using the Bethe-Salpeter Equation. It is typically not used as a standalone user-facing tool but is the computational heart of the OCEAN workflow." }, { "num": "104", "name": "pyGWBSE", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.4", "subcategory": "BSE Methods", "confidence": "VERIFIED", "official_url": "https://github.com/farifort/pyGWBSE", "note": "", "md_link_text": "pyGWBSE.md", "md_link_path": "TDDFT/2.4_BSE_Methods/pyGWBSE.md", "papers": [ { "name": "pyGWBSE_10.1038_s41524-023-00976-y.pdf", "path": "Papers_of_Codes/TDDFT/pyGWBSE/pyGWBSE_10.1038_s41524-023-00976-y.pdf", "doi_url": "https://doi.org/10.1038/s41524-023-00976-y" } ], "paper_placeholder": false, "slug": "pyGWBSE", "idx": 222, "overview": "pyGWBSE is a Python-based implementation of the GW approximation and Bethe-Salpeter Equation for calculating quasiparticle energies and optical excitations. Developed as an educational and research tool, pyGWBSE provides a transparent, readable implementation of many-body perturbation theory in Python, making it accessible for learning, method development, and small-scale calculations. It emphasizes code clarity and ease of modification over production performance." }, { "num": "104a", "name": "Xatu", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.4", "subcategory": "BSE Methods", "confidence": "VERIFIED", "official_url": "https://github.com/xatu-code/xatu", "note": "Solver for Bethe-Salpeter equation in solids (2D focus)", "md_link_text": "Xatu.md", "md_link_path": "TDDFT/2.4_BSE_Methods/Xatu.md", "papers": [], "paper_placeholder": true, "slug": "Xatu", "idx": 223, "overview": "Xatu (**eXcitons from ATomistic calcUlations**) is a specialized program and library designed to solve the **Bethe-Salpeter Equation (BSE)** for solids to obtain the exciton spectrum. It is particularly optimized for **two-dimensional (2D) materials** and operates as a post-processing tool taking electronic band structures from Tight-Binding models or DFT calculations (based on local orbitals) as input." }, { "num": "104b", "name": "Opticx", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.4", "subcategory": "BSE Methods", "confidence": "VERIFIED", "official_url": "https://github.com/xatu-code/opticx", "note": "Optical conductivity solver; interfaces with Xatu for excitonic effects", "md_link_text": "Opticx.md", "md_link_path": "TDDFT/2.4_BSE_Methods/Opticx.md", "papers": [], "paper_placeholder": true, "slug": "Opticx", "idx": 224, "overview": "**Opticx** is a standalone Fortran code designed to evaluate **n-order optical conductivities** in periodic materials modeled with a **Tight-Binding** description. It serves as a companion tool to the Xatu code, enabling the calculation of non-linear optical properties and interfacing with Xatu to include **excitonic effects** in the optical response." }, { "num": "104c", "name": "Real-Space-BSE", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.4", "subcategory": "BSE Methods", "confidence": "VERIFIED", "official_url": "https://github.com/AlexBuccheri/Bethe-Salpeter", "note": "Real-space BSE implementation for large molecular systems (6000+ atoms)", "md_link_text": "RealSpaceBSE.md", "md_link_path": "TDDFT/2.4_BSE_Methods/RealSpaceBSE.md", "papers": [ { "name": "Real-Space-BSE_10.1021_acs.jpclett.1c01742.pdf", "path": "Papers_of_Codes/TDDFT/Real-Space-BSE/Real-Space-BSE_10.1021_acs.jpclett.1c01742.pdf", "doi_url": "https://doi.org/10.1021/acs.jpclett.1c01742" } ], "paper_placeholder": false, "slug": "Real-Space-BSE", "idx": 225, "overview": "**Real-Space-BSE** is a specialized Fortran 2003 library implementing the **Bethe-Salpeter Equation (BSE)** in a **real-space** formalism. Unlike many plane-wave or k-space codes, this tool is specifically designed for large **molecular systems**, utilizing a localized basis set to efficiently compute optical absorption spectra and optical band gaps for systems with thousands of atoms." }, { "num": "104d", "name": "PyMEX", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.4", "subcategory": "BSE Methods", "confidence": "VERIFIED", "official_url": "https://github.com/imaitygit/PyMEX", "note": "Python package for solving BSE in Moir\u00e9 systems (Wannier basis).", "md_link_text": "PyMEX.md", "md_link_path": "TDDFT/2.4_BSE_Methods/PyMEX.md", "papers": [], "paper_placeholder": true, "slug": "PyMEX", "idx": 226, "overview": "PyMEX (Python Moir\u00e9 Exciton) is a specialized Python package designed to calculate exciton properties in moir\u00e9 superlattices, such as twisted bilayer transition metal dichalcogenides (TMDs). It solves the Bethe-Salpeter Equation (BSE) using a Wannier function basis, enabling the efficient study of intralayer and interlayer excitons in large-unit-cell systems." }, { "num": "104e", "name": "EXC", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.4", "subcategory": "BSE Methods", "confidence": "VERIFIED", "official_url": "http://www.bethe-salpeter.org/", "note": "Ab initio Exciton Code; solves BSE in reciprocal space/frequency domain.", "md_link_text": "EXC.md", "md_link_path": "TDDFT/2.4_BSE_Methods/EXC.md", "papers": [ { "name": "EXC_10.1039_B903676H.pdf", "path": "Papers_of_Codes/TDDFT/EXC/EXC_10.1039_B903676H.pdf", "doi_url": "https://doi.org/10.1039/B903676H" } ], "paper_placeholder": false, "slug": "EXC", "idx": 227, "overview": "EXC is a dedicated _ab initio_ code for calculating the dielectric and optical properties of materials by solving the Bethe-Salpeter Equation (BSE). Developed at Ecole Polytechnique (LSI), it operates in reciprocal space and the frequency domain, utilizing a plane-wave basis. It is designed to capture electron-hole interaction effects (excitons) in absorption and energy loss spectra." }, { "num": "398", "name": "VASP-BSE", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.4", "subcategory": "BSE Methods", "confidence": "VERIFIED", "official_url": "https://www.vasp.at/wiki/index.php/Bethe-Salpeter-equations_calculations", "note": "Bethe-Salpeter equation implementation within VASP.", "md_link_text": "VASP-BSE.md", "md_link_path": "TDDFT/2.4_BSE_Methods/VASP-BSE.md", "papers": [ { "name": "10.1103_PhysRevB.74.035101.pdf", "path": "Papers_of_Codes/TDDFT/2.4_BSE_Methods/VASP-BSE/10.1103_PhysRevB.74.035101.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.74.035101" } ], "paper_placeholder": false, "slug": "VASP-BSE", "idx": 228, "overview": "" }, { "num": "385", "name": "BSE", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.4", "subcategory": "BSE Methods", "confidence": "VERIFIED", "official_url": "https://www.basissetexchange.org/", "note": "Basis Set Exchange - repository and API for Gaussian basis sets.", "md_link_text": "BSE.md", "md_link_path": "TDDFT/2.4_BSE_Methods/BSE.md", "papers": [ { "name": "Pritchard_et_al_2019.pdf", "path": "Papers_of_Codes/TDDFT/2.4_BSE_Methods/BSE/Pritchard_et_al_2019.pdf", "doi_url": "https://scholar.google.com/scholar?q=BSE+Pritchard+et+al+2019" } ], "paper_placeholder": false, "slug": "BSE", "idx": 229, "overview": "" }, { "num": "091", "name": "TDAP", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "http://tdap.iphy.ac.cn/", "note": "Time-Dependent Ab initio Package based on QE (IOP CAS Beijing)", "md_link_text": "TDAP.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/TDAP.md", "papers": [ { "name": "TDAP_10.1021_acs.jctc.5b00969.pdf", "path": "Papers_of_Codes/TDDFT/TDAP/TDAP_10.1021_acs.jctc.5b00969.pdf", "doi_url": "https://doi.org/10.1021/acs.jctc.5b00969" } ], "paper_placeholder": false, "slug": "TDAP", "idx": 230, "overview": "TDAP (Time-Dependent Ab-initio Propagation) is a software package developed by the group of **Sheng Meng** at the Institute of Physics, Chinese Academy of Sciences. It is based on Time-Dependent Density Functional Theory (TDDFT) using numerical atomic basis sets. The code is designed for real-time simulations of ultrafast electron dynamics, excited state molecular dynamics, and optical properties in complex systems." }, { "num": "099a", "name": "SHARC", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://sharc-md.org/", "note": "Ab initio nonadiabatic dynamics with arbitrary couplings (SOC, laser fields) and extensive interface support.", "md_link_text": "SHARC.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/SHARC.md", "papers": [ { "name": "SHARC_10.1002_wcms.1370.pdf", "path": "Papers_of_Codes/TDDFT/SHARC/SHARC_10.1002_wcms.1370.pdf", "doi_url": "https://doi.org/10.1002/wcms.1370" } ], "paper_placeholder": false, "slug": "SHARC", "idx": 231, "overview": "SHARC is a comprehensive ab initio molecular dynamics software suite for excited-state dynamics simulations using trajectory surface hopping. It enables the study of photochemical and photophysical processes including internal conversion, intersystem crossing, and photodissociation. SHARC interfaces with major quantum chemistry codes to obtain electronic structure data and supports various types of couplings including spin-orbit and non-adiabatic couplings." }, { "num": "099b", "name": "Newton-X", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://www.newtonx.org/", "note": "Generalized platform for excited-state dynamics and spectra simulation; extensive interfaces.", "md_link_text": "Newton-X.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/Newton-X.md", "papers": [], "paper_placeholder": true, "slug": "Newton-X", "idx": 232, "overview": "Newton-X is a general-purpose program package for excited-state nonadiabatic molecular dynamics simulations. It employs mixed quantum-classical methods, primarily trajectory surface hopping, to simulate photoinduced processes. Newton-X provides a complete workflow from generating initial conditions to statistical analysis of results, interfacing with numerous quantum chemistry programs for electronic structure calculations." }, { "num": "099c", "name": "NEXMD", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://github.com/lanl/NEXMD", "note": "Nonadiabatic Excited-state Molecular Dynamics with semiempirical methods for large conjugated systems (LANL).", "md_link_text": "NEXMD.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/NEXMD.md", "papers": [ { "name": "NEXMD_10.1021_acs.jctc.0c00248.pdf", "path": "Papers_of_Codes/TDDFT/NEXMD/NEXMD_10.1021_acs.jctc.0c00248.pdf", "doi_url": "https://doi.org/10.1021/acs.jctc.0c00248" } ], "paper_placeholder": false, "slug": "NEXMD", "idx": 233, "overview": "NEXMD is a software package developed at Los Alamos National Laboratory for simulating photoinduced adiabatic and non-adiabatic excited-state molecular dynamics. It uses semiempirical quantum chemistry methods (CEO package) with Tully's fewest-switches surface hopping algorithm, making it efficient for studying large conjugated systems like chromophores and polymers. Written in Fortran 90 with Python scripts for parallel execution." }, { "num": "099d", "name": "JADE-NAMD", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://github.com/bch-gnome/JADE-NAMD", "note": "Python-based on-the-fly nonadiabatic dynamics driver interfacing with standard QC codes.", "md_link_text": "JADE-NAMD.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/JADE-NAMD.md", "papers": [], "paper_placeholder": true, "slug": "JADE-NAMD", "idx": 234, "overview": "JADE-NAMD is a Python-based software package designed for performing on-the-fly nonadiabatic molecular dynamics (NAMD) simulations. It employs the trajectory surface hopping method and serves as a flexible interface driver that connects various quantum chemistry packages (calculators) with dynamics propagation. It is designed to be user-friendly and easily extensible for different electronic structure methods." }, { "num": "099e", "name": "SchNarc", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://github.com/schnarc/schnarc", "note": "Machine Learning (SchNet) scale-up for nonadiabatic dynamics with SHARC.", "md_link_text": "SchNarc.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/SchNarc.md", "papers": [ { "name": "SchNarc_10.1021_acs.jpclett.0c00527.pdf", "path": "Papers_of_Codes/TDDFT/SchNarc/SchNarc_10.1021_acs.jpclett.0c00527.pdf", "doi_url": "https://doi.org/10.1021/acs.jpclett.0c00527" } ], "paper_placeholder": false, "slug": "SchNarc", "idx": 235, "overview": "SchNarc is a machine learning software package designed to accelerate nonadiabatic molecular dynamics simulations. It specifically interfaces with the SHARC molecular dynamics suite to replace expensive quantum chemical calculations with deep neural networks (SchNet). This allows for simulating extensive excited-state dynamics with ab initio accuracy at a fraction of the computational cost." }, { "num": "099f", "name": "OpenQP", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://github.com/Open-Quantum-Platform/openqp", "note": "Open Quantum Platform featuring Mixed-Reference Spin-Flip (MRSF) TDDFT for diradicals and conical intersections.", "md_link_text": "OpenQP.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/OpenQP.md", "papers": [], "paper_placeholder": true, "slug": "OpenQP", "idx": 236, "overview": "OpenQP (Open Quantum Platform) is a modern quantum chemistry software package developed by the Choi Group (Kyungpook National University). It features the implementation of Mixed-Reference Spin-Flip Time-Dependent Density Functional Theory (MRSF-TDDFT). This method addresses the critical issue of spin contamination in conventional Spin-Flip TDDFT, allowing for accurate description of ground and excited states with multireference character, conical intersections, and diradicals." }, { "num": "099g", "name": "Serenity", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://qcserenity.github.io/", "note": "Specialized subsystem DFT and Frozen Density Embedding (FDE-TDDFT) for excited states in environments.", "md_link_text": "Serenity.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/Serenity.md", "papers": [ { "name": "Serenity_10.1002_jcc.25162.pdf", "path": "Papers_of_Codes/TDDFT/Serenity/Serenity_10.1002_jcc.25162.pdf", "doi_url": "https://doi.org/10.1002/jcc.25162" } ], "paper_placeholder": false, "slug": "Serenity", "idx": 237, "overview": "Serenity is a highly scalable, open-source quantum chemistry program specializing in subsystem Density Functional Theory (DFT) and embedding methods. It is particularly known for its implementation of Frozen Density Embedding (FDE) for both ground and excited states (FDE-TDDFT), enabling the simulation of electronic properties of molecules in complex environments with high efficiency." }, { "num": "099h", "name": "std2", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://github.com/grimme-lab/stda", "note": "Simplified TDA/TDDFT (sTDA/sTDA-xTB) for ultra-fast spectra of systems with 1000+ atoms.", "md_link_text": "std2.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/std2.md", "papers": [ { "name": "std2_10.1063_1.4811331.pdf", "path": "Papers_of_Codes/TDDFT/std2/std2_10.1063_1.4811331.pdf", "doi_url": "https://doi.org/10.1063/1.4811331" } ], "paper_placeholder": false, "slug": "std2", "idx": 238, "overview": "std2 is a software package developed by the Grimme group for performing simplified Time-Dependent Density Functional Theory (sTD-DFT) and simplified Tamm-Dancoff Approximation (sTDA) calculations. These methods provide a highly efficient approximation to full TDDFT, allowing for the computation of ultra-fast UV-Vis absorption and electronic circular dichroism (ECD) spectra for very large molecular systems (thousands of atoms)." }, { "num": "099i", "name": "adcc", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://adc-connect.org/", "note": "ADC-connect; Python library for Algebraic Diagrammatic Construction (ADC) excited states.", "md_link_text": "adcc.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/adcc.md", "papers": [ { "name": "adcc_10.1002_wcms.1462.pdf", "path": "Papers_of_Codes/TDDFT/adcc/adcc_10.1002_wcms.1462.pdf", "doi_url": "https://doi.org/10.1002/wcms.1462" } ], "paper_placeholder": false, "slug": "adcc", "idx": 239, "overview": "adcc (Algebraic Diagrammatic Construction-connect) is a Python-based hybrid library designed to perform excited-state calculations using the Algebraic Diagrammatic Construction (ADC) scheme for the polarization propagator. It serves as a flexible backend that can interface with various SCF codes (like PySCF and Psi4) to obtain the Hartree-Fock reference, enabling correlated excited-state calculations up to the third order of perturbation theory." }, { "num": "099j", "name": "Gator", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://e-science.se/software/gator/", "note": "Specialized ADC code for Correlated Spectroscopy (XAS, XES, RIXS).", "md_link_text": "Gator.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/Gator.md", "papers": [], "paper_placeholder": true, "slug": "Gator", "idx": 240, "overview": "Gator is a quantum chemistry program specialized for spectroscopy and molecular properties using the Algebraic Diagrammatic Construction (ADC) scheme. It focuses on correlated excited state calculations, particularly for simulating core-level spectroscopies such as X-ray absorption (XAS), X-ray emission (XES), and Resonant Inelastic X-ray Scattering (RIXS), as well as valence excitations." }, { "num": "099k", "name": "PyMM", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://github.com/ChenGiuseppe/PyMM", "note": "QM/MM Perturbed Matrix Method (PMM) for excited states in complex environments.", "md_link_text": "PyMM.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/PyMM.md", "papers": [], "paper_placeholder": true, "slug": "PyMM", "idx": 241, "overview": "PyMM is a Python-based software package designed for Quantum Mechanics/Molecular Mechanics (QM/MM) simulations. It specifically implements the Perturbed Matrix Method (PMM) and allows for the calculation of excited states and electronic properties of molecular systems in complex environments (such as proteins or solvents) by coupling Quantum Chemical calculations with Classical Molecular Dynamics trajectories." }, { "num": "099l", "name": "QMMM-NAMD", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://github.com/qmmm-namd/QMMM-NAMD", "note": "Dedicated package for QM/MM nonadiabatic surface hopping dynamics.", "md_link_text": "QMMM-NAMD.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/QMMM-NAMD.md", "papers": [ { "name": "QMMM-NAMD_10.1038_nmeth.4638.pdf", "path": "Papers_of_Codes/TDDFT/QMMM-NAMD/QMMM-NAMD_10.1038_nmeth.4638.pdf", "doi_url": "https://doi.org/10.1038/nmeth.4638" } ], "paper_placeholder": false, "slug": "QMMM-NAMD", "idx": 242, "overview": "QMMM-NAMD is a software package designed for performing nonadiabatic molecular dynamics (NAMD) simulations within a Quantum Mechanics/Molecular Mechanics (QM/MM) framework. It enables the study of photoinduced processes in complex environments, such as proteins or solutions, by combining accurate quantum mechanical descriptions of chromophores with efficient molecular mechanics models for the surroundings." }, { "num": "099m", "name": "exciton1d", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://github.com/nicholashestand/exciton1d", "note": "1D Frenkel-Holstein exciton model for molecular aggregates and spectroscopy.", "md_link_text": "exciton1d.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/exciton1d.md", "papers": [], "paper_placeholder": true, "slug": "exciton1d", "idx": 243, "overview": "exciton1d is a specialized software package for simulating exciton dynamics and spectroscopy in one-dimensional molecular aggregates. It implements the Holstein Hamiltonian to treat Frenkel excitons coupled to vibrational modes, as well as charge-transfer states. It is designed to calculate absorption spectra, band dispersion, and exciton coherence properties." }, { "num": "099n", "name": "Kujo", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://github.com/TovCat/Kujo", "note": "Analysis of exciton couplings and rates in organic single crystals.", "md_link_text": "Kujo.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/Kujo.md", "papers": [], "paper_placeholder": true, "slug": "Kujo", "idx": 244, "overview": "Kujo is a Python-based software tool designed for analyzing exciton dynamics in organic single crystals. It focuses on calculating exciton couplings and rates using various approximations, enabling the study of singlet fission, triplet fusion, and charge transport in crystalline environments." }, { "num": "099o", "name": "StochasticGW", "category_id": "2", "category": "TDDFT & EXCITED-STATE", "subcategory_id": "2.5", "subcategory": "Hybrid & Specialized", "confidence": "VERIFIED", "official_url": "https://stochasticgw.github.io/", "note": "Linear-scaling Stochastic GW for massive systems (>10,000 electrons).", "md_link_text": "StochasticGW.md", "md_link_path": "TDDFT/2.5_Hybrid_Specialized/StochasticGW.md", "papers": [ { "name": "StochasticGW_10.1021_acs.jctc.7b00770.pdf", "path": "Papers_of_Codes/TDDFT/StochasticGW/StochasticGW_10.1021_acs.jctc.7b00770.pdf", "doi_url": "https://doi.org/10.1021/acs.jctc.7b00770" } ], "paper_placeholder": false, "slug": "StochasticGW", "idx": 245, "overview": "StochasticGW is a specialized software package designed to perform GW calculations (Green's function G and screened Coulomb interaction W) for very large systems. It utilizes stochastic techniques to scale linearly with the system size, enabling the calculation of quasiparticle energies for systems with thousands to tens of thousands of electrons, which are computationally inaccessible to deterministic GW codes." }, { "num": "110", "name": "TRIQS", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "CONFIRMED", "official_url": "https://triqs.github.io/", "note": "", "md_link_text": "TRIQS.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/TRIQS.md", "papers": [ { "name": "Parcollet_et_al_2015.pdf", "path": "Papers_of_Codes/DMFT/3.1_DMFT_Frameworks/TRIQS/Parcollet_et_al_2015.pdf", "doi_url": "https://scholar.google.com/scholar?q=TRIQS+Parcollet+et+al+2015" } ], "paper_placeholder": false, "slug": "TRIQS", "idx": 246, "overview": "TRIQS (Toolbox for Research on Interacting Quantum Systems) is a comprehensive scientific project providing a framework for many-body quantum physics and, in particular, for Dynamical Mean-Field Theory (DMFT) calculations. It consists of C++ libraries with Python interfaces and applications for solving quantum impurity problems and performing DFT+DMFT calculations." }, { "num": "111", "name": "TRIQS-DFTTools", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "CONFIRMED", "official_url": "https://triqs.github.io/dft_tools/", "note": "", "md_link_text": "TRIQS-DFTTools.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/TRIQS-DFTTools.md", "papers": [ { "name": "Parcollet_et_al_2015.pdf", "path": "Papers_of_Codes/DMFT/3.1_DMFT_Frameworks/TRIQS/Parcollet_et_al_2015.pdf", "doi_url": "https://scholar.google.com/scholar?q=TRIQS-DFTTools+Parcollet+et+al+2015" } ], "paper_placeholder": false, "slug": "TRIQS-DFTTools", "idx": 247, "overview": "TRIQS/DFTTools is a TRIQS application providing the necessary tools to perform DFT+DMFT calculations. It serves as the bridge between DFT codes and the TRIQS DMFT framework, handling Wannier function projections, self-consistency loops, and post-processing of spectral functions. It is the standard interface for performing realistic DFT+DMFT calculations within the TRIQS ecosystem." }, { "num": "112", "name": "TRIQS-cthyb", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://triqs.github.io/cthyb/", "note": "", "md_link_text": "TRIQS-cthyb.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/TRIQS-cthyb.md", "papers": [ { "name": "Parcollet_et_al_2015.pdf", "path": "Papers_of_Codes/DMFT/3.1_DMFT_Frameworks/TRIQS/Parcollet_et_al_2015.pdf", "doi_url": "https://scholar.google.com/scholar?q=TRIQS-cthyb+Parcollet+et+al+2015" } ], "paper_placeholder": false, "slug": "TRIQS-cthyb", "idx": 248, "overview": "TRIQS/cthyb is a state-of-the-art continuous-time hybridization expansion quantum Monte Carlo impurity solver for multi-orbital Anderson impurity models. It is one of the most widely used CTQMC solvers in the DMFT community, offering efficient algorithms for solving quantum impurity problems with general multi-orbital interactions. Part of the TRIQS ecosystem, it integrates seamlessly with TRIQS/DFTTools for DFT+DMFT calculations." }, { "num": "113", "name": "solid_dmft", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://triqs.github.io/solid_dmft/", "note": "", "md_link_text": "solid_dmft.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/solid_dmft.md", "papers": [], "paper_placeholder": true, "slug": "solid_dmft", "idx": 249, "overview": "solid_dmft is a versatile Python wrapper to perform DFT+DMFT calculations utilizing the TRIQS software library. It provides a high-level, user-friendly interface for one-shot and charge self-consistent DFT+DMFT calculations, supporting multiple DFT codes (VASP, Quantum ESPRESSO) and impurity solvers. Designed for accessibility, it automates many workflow steps while maintaining flexibility for advanced users." }, { "num": "114", "name": "w2dynamics", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "CONFIRMED", "official_url": "https://github.com/w2dynamics/w2dynamics", "note": "", "md_link_text": "w2dynamics.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/w2dynamics.md", "papers": [ { "name": "Wallerberger_et_al_2019.pdf", "path": "Papers_of_Codes/DMFT/3.1_DMFT_Frameworks/w2dynamics/Wallerberger_et_al_2019.pdf", "doi_url": "https://scholar.google.com/scholar?q=w2dynamics+Wallerberger+et+al+2019" } ], "paper_placeholder": false, "slug": "w2dynamics", "idx": 250, "overview": "w2dynamics is a continuous-time quantum Monte Carlo (CTQMC) impurity solver for multi-orbital systems within dynamical mean-field theory (DMFT). It provides efficient implementation of hybridization expansion and interaction expansion algorithms with MPI parallelization." }, { "num": "115", "name": "DCore", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "CONFIRMED", "official_url": "https://github.com/issp-center-dev/DCore", "note": "", "md_link_text": "DCore.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/DCore.md", "papers": [ { "name": "Shinaoka_et_al_2017.pdf", "path": "Papers_of_Codes/DMFT/3.1_DMFT_Frameworks/DCore/Shinaoka_et_al_2017.pdf", "doi_url": "https://scholar.google.com/scholar?q=DCore+Shinaoka+et+al+2017" } ], "paper_placeholder": false, "slug": "DCore", "idx": 251, "overview": "DCore (DMFT Core) is an integrated DMFT software package developed at the Institute for Solid State Physics (ISSP), University of Tokyo. It provides a user-friendly interface for DFT+DMFT calculations with multiple impurity solvers and DFT code interfaces, designed for studying strongly correlated materials with emphasis on accessibility and automation." }, { "num": "116", "name": "iQIST", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/iqist/iqist", "note": "", "md_link_text": "iQIST.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/iQIST.md", "papers": [ { "name": "10.1016_j.cpc.2015.04.020.pdf", "path": "Papers_of_Codes/DMFT/3.1_DMFT_Frameworks/iQIST/10.1016_j.cpc.2015.04.020.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2015.04.020" } ], "paper_placeholder": false, "slug": "iQIST", "idx": 252, "overview": "iQIST (interacting Quantum Impurity Solver Toolkit) is an open-source Fortran package providing multiple continuous-time quantum Monte Carlo (CTQMC) impurity solvers for DMFT calculations. It offers several algorithmic implementations optimized for different physical situations, with emphasis on multi-orbital strongly correlated systems." }, { "num": "117", "name": "EDMFTF", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "CONFIRMED", "official_url": "https://github.com/HauleGroup/EDMFTF", "note": "", "md_link_text": "EDMFTF.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/EDMFTF.md", "papers": [ { "name": "Haule_et_al_2010.pdf", "path": "Papers_of_Codes/DMFT/3.1_DMFT_Frameworks/EDMFTF/Haule_et_al_2010.pdf", "doi_url": "https://scholar.google.com/scholar?q=EDMFTF+Haule+et+al+2010" } ], "paper_placeholder": false, "slug": "EDMFTF", "idx": 253, "overview": "EDMFTF (Embedded Dynamical Mean Field Theory Functional) is a DFT+DMFT implementation developed by Kristjan Haule at Rutgers University. It provides a sophisticated interface for performing charge self-consistent DFT+DMFT calculations with advanced impurity solvers, focusing on strongly correlated materials with realistic crystal structures." }, { "num": "118", "name": "ComDMFT", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "CONFIRMED", "official_url": "https://github.com/ComDMFT/ComDMFT", "note": "", "md_link_text": "ComDMFT.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/ComDMFT.md", "papers": [ { "name": "ComDMFT_10.1016_j.cpc.2019.07.003.pdf", "path": "Papers_of_Codes/DMFT/ComDMFT/ComDMFT_10.1016_j.cpc.2019.07.003.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2019.07.003" } ], "paper_placeholder": false, "slug": "ComDMFT", "idx": 254, "overview": "ComDMFT (Combination of DMFT codes) is an integrated DFT+DMFT package that combines multiple DFT codes with sophisticated DMFT impurity solvers. Developed by the Comscope group, it provides a unified framework for charge self-consistent DFT+DMFT calculations with emphasis on transition metal systems and strongly correlated materials." }, { "num": "119", "name": "ComCTQMC", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/ComDMFT/ComCTQMC", "note": "", "md_link_text": "ComCTQMC.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/ComCTQMC.md", "papers": [], "paper_placeholder": true, "slug": "ComCTQMC", "idx": 255, "overview": "ComCTQMC is a GPU-accelerated continuous-time quantum Monte Carlo impurity solver implementing the hybridization expansion (CT-HYB) algorithm. Developed as part of the Comscope project, it provides efficient solutions to DMFT impurity problems with both partition function and worm-space measurements. The GPU acceleration enables significantly faster calculations compared to CPU-only implementations." }, { "num": "120", "name": "ComRISB", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/comscope/ComDMFT", "note": "Rotationally invariant slave-boson method; part of ComDMFT suite", "md_link_text": "ComRISB.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/ComRISB.md", "papers": [], "paper_placeholder": true, "slug": "ComRISB", "idx": 256, "overview": "ComRISB (Rotationally Invariant Slave Boson) is a Gutzwiller approximation solver that is part of the Comscope/ComDMFT software suite. It implements the rotationally invariant slave boson method, which provides an alternative to DMFT for treating strong correlations through a variational approach. ComRISB can perform calculations faster than full DMFT while capturing essential correlation effects." }, { "num": "121", "name": "DMFTwDFT", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/DMFTwDFT-project/DMFTwDFT", "note": "", "md_link_text": "DMFTwDFT.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/DMFTwDFT.md", "papers": [ { "name": "DMFTwDFT_10.1016_j.cpc.2020.107778.pdf", "path": "Papers_of_Codes/DMFT/DMFTwDFT/DMFTwDFT_10.1016_j.cpc.2020.107778.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2020.107778" } ], "paper_placeholder": false, "slug": "DMFTwDFT", "idx": 257, "overview": "DMFTwDFT is an open-source code combining Dynamical Mean Field Theory with various Density Functional Theory packages. It provides a flexible framework for performing DFT+DMFT calculations with multiple DFT backends and impurity solvers. The code interfaces with Wannier90 for downfolding and supports various free-licensed and commercial DFT codes, enabling ab-initio treatment of strongly correlated materials." }, { "num": "122", "name": "AMULET", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://ma.issp.u-tokyo.ac.jp/en/app/2207", "note": "First-principles calculation toolkit for correlated materials (ISSP Tokyo)", "md_link_text": "AMULET.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/AMULET.md", "papers": [], "paper_placeholder": true, "slug": "AMULET", "idx": 258, "overview": "AMULET is a DFT+DMFT code developed for studying strongly correlated materials. It represents a research implementation combining density functional theory with dynamical mean field theory. Information about AMULET is limited in public domains, indicating it is primarily a research tool developed and used within specific research groups." }, { "num": "123", "name": "Rutgers-DMFT", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/HauleGroup/CODES", "note": "", "md_link_text": "Rutgers-DMFT.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/Rutgers-DMFT.md", "papers": [ { "name": "Rutgers-DMFT_10.1103_PhysRevB.81.195107.pdf", "path": "Papers_of_Codes/DMFT/Rutgers-DMFT/Rutgers-DMFT_10.1103_PhysRevB.81.195107.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.81.195107" } ], "paper_placeholder": false, "slug": "Rutgers-DMFT", "idx": 259, "overview": "Rutgers-DMFT refers to the collection of DMFT codes developed by Kristjan Haule's group at Rutgers University, including EDMFTF and related impurity solvers. The repository contains various tools for DFT+DMFT calculations, continuous-time quantum Monte Carlo solvers, and analysis utilities developed and maintained by one of the leading DMFT research groups worldwide." }, { "num": "124", "name": "ALPS", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://alps.comp-phys.org/", "note": "", "md_link_text": "ALPS.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/ALPS.md", "papers": [ { "name": "10.1143_JPSJS.74S.30.pdf", "path": "Papers_of_Codes/DMFT/3.1_DMFT_Frameworks/ALPS/10.1143_JPSJS.74S.30.pdf", "doi_url": "https://doi.org/10.1143/JPSJS.74S.30" } ], "paper_placeholder": false, "slug": "ALPS", "idx": 260, "overview": "ALPS (Algorithms and Libraries for Physics Simulations) is an international collaboration providing open-source software for simulation of quantum lattice models, including quantum spin systems and strongly correlated electron systems. The project includes both libraries and application codes, with particular relevance for DMFT calculations through its CT-HYB impurity solver implementation." }, { "num": "125", "name": "ALPSCore", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/ALPSCore/ALPSCore", "note": "", "md_link_text": "ALPSCore.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/ALPSCore.md", "papers": [ { "name": "10.1143_JPSJS.74S.30.pdf", "path": "Papers_of_Codes/DMFT/3.1_DMFT_Frameworks/ALPS/10.1143_JPSJS.74S.30.pdf", "doi_url": "https://doi.org/10.1143/JPSJS.74S.30" } ], "paper_placeholder": false, "slug": "ALPSCore", "idx": 261, "overview": "ALPSCore (ALPS Core Libraries) represents the modernized core libraries extracted from the ALPS project. It provides a set of maintained, well-documented, and reusable C++ libraries for condensed matter physics simulations, with a focus on strongly correlated electron systems. ALPSCore libraries are designed to be lightweight, easy to integrate, and provide essential functionality for physics applications." }, { "num": "127", "name": "NRGLjubljana", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "http://nrgljubljana.ijs.si/", "note": "", "md_link_text": "NRGLjubljana.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/NRGLjubljana.md", "papers": [ { "name": "10_1103_PhysRevB_79_085106.pdf", "path": "Papers_of_Codes/materials_science_papers/3_Strongly_Correlated_Systems/NRG_Ljubljana/10_1103_PhysRevB_79_085106.pdf", "doi_url": "https://scholar.google.com/scholar?q=NRGLjubljana+10+1103+PhysRevB+79+085106" } ], "paper_placeholder": false, "slug": "NRGLjubljana", "idx": 262, "overview": "NRG Ljubljana is a framework of interrelated computer codes for performing numerical renormalization group (NRG) calculations for quantum impurity problems, such as the Kondo model and Anderson impurity model. It provides highly accurate solutions to impurity problems and can be used as an impurity solver in DMFT calculations, particularly suited for systems with Kondo physics and heavy fermion behavior." }, { "num": "128", "name": "opendf", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/CQMP/opendf", "note": "", "md_link_text": "opendf.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/opendf.md", "papers": [], "paper_placeholder": true, "slug": "opendf", "idx": 263, "overview": "opendf is a condensed matter physics code that solves strongly correlated lattice problems (such as the Hubbard model) in finite dimensions using the dual fermion method. It extends DMFT by including non-local correlations through diagrammatic extensions, providing a systematic way to treat spatial correlations beyond local DMFT approximations." }, { "num": "130", "name": "COMSUITE", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/rutgersphysics/COMSUITE", "note": "", "md_link_text": "COMSUITE.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/COMSUITE.md", "papers": [], "paper_placeholder": true, "slug": "COMSUITE", "idx": 264, "overview": "COMSUITE (Combination Suite) is a computational materials physics code for simulating correlated quantum materials using Dynamic Mean Field Theory (DMFT) and its extensions. It provides an integrated framework for DFT+DMFT calculations with sophisticated impurity solvers and multiple methodological approaches including DMFT, cluster DMFT, and Gutzwiller approximations." }, { "num": "130a", "name": "fcdmft", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/ZhuGroup-Yale/fcdmft", "note": "Ab initio Full-Cell GW+DMFT code.", "md_link_text": "fcDMFT.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/fcDMFT.md", "papers": [], "paper_placeholder": true, "slug": "fcdmft", "idx": 265, "overview": "fcDMFT is a Python-based software package designed for *ab initio* Full Cell Dynamical Mean-Field Theory (DMFT) calculations. Built upon the PySCF quantum chemistry framework, it extends standard embedding theories to treat solid-state systems with high accuracy. It focuses on GW+DMFT and HF+DMFT methodologies, enabling the study of electronic correlations in periodic crystals using quantum chemical solvers without downfolding to a small subspace." }, { "num": "130b", "name": "DMFT_ED", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/kdd-sienna/DMFT_ED", "note": "Pedagogical ED solver for DMFT (Python/Jupyter).", "md_link_text": "DMFT_ED.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/DMFT_ED.md", "papers": [], "paper_placeholder": true, "slug": "DMFT_ED", "idx": 266, "overview": "**DMFT_ED** represents a class of reference implementations and tutorial codes designed to teach and perform Dynamical Mean Field Theory (DMFT) calculations using **Exact Diagonalization (ED)** as the impurity solver. Unlike large discrete bath Monte Carlo codes, DMFT_ED approaches allow for accessing zero-temperature properties and real-frequency spectral functions directly, making them invaluable for pedagogical purposes and specific research questions involving discrete bath approximation." }, { "num": "130c", "name": "Zen", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/zen-dev/zen", "note": "Julia/Fortran DMFT framework (ZenCore).", "md_link_text": "Zen.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/Zen.md", "papers": [], "paper_placeholder": true, "slug": "Zen", "idx": 267, "overview": "Zen is a comprehensive computational toolkit developed for the *ab initio* simulation of strongly correlated materials. It is designed to seamlessly integrate Density Functional Theory (DFT) with Dynamical Mean-Field Theory (DMFT). The framework is built with a Julia-based core (`ZenCore`) for high-level orchestration and a Fortran-based engine for computationally intensive DMFT solving. It operates by manipulating parameters and data exchanged through configuration files, often orchestrating ex" }, { "num": "130d", "name": "KadanoffBaym.jl", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/NonequilibriumDynamics/KadanoffBaym.jl", "note": "Adaptive Green's function solver for NEGF/KB equations.", "md_link_text": "KadanoffBaym.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/KadanoffBaym.md", "papers": [], "paper_placeholder": true, "slug": "KadanoffBaym.jl", "idx": 268, "overview": "KadanoffBaym.jl is a Julia language package designed for solving the Kadanoff-Baym equations (KBE) for non-equilibrium Green's functions (NEGF). It provides efficient, adaptive time-stepping solvers for time-dependent many-body problems, allowing researchers to simulate the dynamics of interacting quantum systems out of equilibrium." }, { "num": "130e", "name": "LinReTraCe", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/linretracedev/linretrace", "note": "Linear Response Transport Centre (post-DMFT transport).", "md_link_text": "LinReTraCe.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/LinReTraCe.md", "papers": [], "paper_placeholder": true, "slug": "LinReTraCe", "idx": 269, "overview": "LinReTraCe (Linear Response Transport Centre) is a massively parallel code for calculating transport properties of solids. It is specifically designed to work with spectral functions from many-body calculations (like DMFT), capturing lifetime effects and renormalization beyond the constant relaxation time approximation." }, { "num": "390", "name": "Hubbard-I", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.1", "subcategory": "DMFT Frameworks", "confidence": "VERIFIED", "official_url": "https://triqs.github.io/hubbardI/", "note": "Hubbard-I impurity solver for DMFT (TRIQS application).", "md_link_text": "Hubbard-I.md", "md_link_path": "DMFT/3.1_DMFT_Frameworks/Hubbard-I.md", "papers": [ { "name": "10.1098_rspa.1963.0204.pdf", "path": "Papers_of_Codes/DMFT/3.1_DMFT_Frameworks/Hubbard-I/10.1098_rspa.1963.0204.pdf", "doi_url": "https://doi.org/10.1098/rspa.1963.0204" } ], "paper_placeholder": false, "slug": "Hubbard-I", "idx": 270, "overview": "" }, { "num": "131", "name": "CT-HYB", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://triqs.github.io/cthyb/ (TRIQS implementation)", "note": "", "md_link_text": "CT-HYB.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/CT-HYB.md", "papers": [ { "name": "CT-HYB_10.1016_j.cpc.2015.10.023.pdf", "path": "Papers_of_Codes/DMFT/CT-HYB/CT-HYB_10.1016_j.cpc.2015.10.023.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2015.10.023" } ], "paper_placeholder": false, "slug": "CT-HYB", "idx": 271, "overview": "CT-HYB (Continuous-Time Hybridization Expansion) is an algorithm for solving quantum impurity problems, not a single specific software. It is the most widely used continuous-time quantum Monte Carlo (CTQMC) method in DMFT applications. Multiple implementations exist in different software packages including TRIQS/cthyb, ALPS, w2dynamics, iQIST, and others." }, { "num": "132", "name": "CT-QMC", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/w2dynamics/w2dynamics (w2dynamics solver)", "note": "", "md_link_text": "CT-QMC.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/CT-QMC.md", "papers": [ { "name": "CT-QMC_10.1016_j.cpc.2010.12.050.pdf", "path": "Papers_of_Codes/DMFT/CT-QMC/CT-QMC_10.1016_j.cpc.2010.12.050.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2010.12.050" } ], "paper_placeholder": false, "slug": "CT-QMC", "idx": 272, "overview": "CT-QMC (Continuous-Time Quantum Monte Carlo) is a general term for the family of continuous-time quantum Monte Carlo algorithms used as impurity solvers in DMFT. This includes CT-HYB, CT-INT, CT-AUX, and other variants. The term CT-QMC often refers generically to these methods, with w2dynamics being a major implementation providing multiple CT-QMC algorithms." }, { "num": "133", "name": "CT-INT", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/ComDMFT/ComCTQMC (CT-INT solver)", "note": "", "md_link_text": "CT-INT.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/CT-INT.md", "papers": [ { "name": "CT-INT_10.1103_PhysRevB.72.035122.pdf", "path": "Papers_of_Codes/DMFT/CT-INT/CT-INT_10.1103_PhysRevB.72.035122.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.72.035122" } ], "paper_placeholder": false, "slug": "CT-INT", "idx": 273, "overview": "CT-INT (Continuous-Time Interaction Expansion) is a quantum Monte Carlo algorithm for solving impurity problems, implemented in several DMFT software packages. Unlike CT-HYB which expands in the hybridization, CT-INT expands in the interaction term. Multiple implementations exist including ALPSCore/CT-INT, w2dynamics, iQIST, and ComCTQMC." }, { "num": "134", "name": "CT-SEG", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://triqs.github.io/ctseg/", "note": "", "md_link_text": "CT-SEG.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/CT-SEG.md", "papers": [], "paper_placeholder": true, "slug": "CT-SEG", "idx": 274, "overview": "CT-SEG (Continuous-Time Segment) is a continuous-time quantum Monte Carlo algorithm using the segment picture representation, implemented as a TRIQS application. It provides an alternative formulation to the standard CT-HYB matrix approach, particularly efficient for certain types of problems. The segment picture representation offers computational advantages for specific interaction structures." }, { "num": "135", "name": "H\u03a6", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/QLMS/HPhi", "note": "", "md_link_text": "HPhi.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/HPhi.md", "papers": [ { "name": "H\u03a6_10.1016_j.cpc.2017.04.006.pdf", "path": "Papers_of_Codes/DMFT/H\u03a6/H\u03a6_10.1016_j.cpc.2017.04.006.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2017.04.006" }, { "name": "H\u03a6_10.1016_j.cpc.2017.04.006.pdf", "path": "Papers_of_Codes/DMFT/H%CE%A6/H%CE%A6_10.1016_j.cpc.2017.04.006.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2017.04.006" } ], "paper_placeholder": false, "slug": "H", "idx": 275, "overview": "HPhi is a software package for solving quantum lattice models using the exact diagonalization method. It supports a wide range of quantum lattice models, including Hubbard, Heisenberg, and Kondo lattice models. HPhi can calculate ground state and excited state properties, as well as thermal averages using the thermal pure quantum (TPQ) state method." }, { "num": "136", "name": "EDIpack", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/Extragalactic-Continuum-Physics/EDIpack", "note": "", "md_link_text": "EDIpack.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/EDIpack.md", "papers": [ { "name": "10_21468_SciPostPhysCodeb_58.pdf", "path": "Papers_of_Codes/DMFT/3.2_Impurity_Solvers/EDIpack/10_21468_SciPostPhysCodeb_58.pdf", "doi_url": "https://scholar.google.com/scholar?q=EDIpack+10+21468+SciPostPhysCodeb+58" }, { "name": "10_1016_j_cpc_2021_108261.pdf", "path": "Papers_of_Codes/DMFT/3.2_Impurity_Solvers/EDIpack/10_1016_j_cpc_2021_108261.pdf", "doi_url": "https://scholar.google.com/scholar?q=EDIpack+10+1016+j+cpc+2021+108261" } ], "paper_placeholder": false, "slug": "EDIpack", "idx": 276, "overview": "EDIpack is a massively parallel exact diagonalization solver for generic quantum impurity problems. It uses Lanczos-based methods to solve multi-orbital impurity models, providing an alternative to quantum Monte Carlo approaches. EDIpack is particularly suited for problems where exact solutions are needed or where QMC suffers from sign problems, and it can handle electron-phonon coupling." }, { "num": "137", "name": "FTPS", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/misawa-FTPS/ftps", "note": "", "md_link_text": "FTPS.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/FTPS.md", "papers": [ { "name": "FTPS_10.1103_PhysRevX.7.031013.pdf", "path": "Papers_of_Codes/DMFT/FTPS/FTPS_10.1103_PhysRevX.7.031013.pdf", "doi_url": "https://doi.org/10.1103/PhysRevX.7.031013" } ], "paper_placeholder": false, "slug": "FTPS", "idx": 277, "overview": "FTPS is a specialized research code for solving quantum impurity problems and lattice models, developed by Takahiro Misawa (known for mVMC and HPhi). The name likely refers to methods involving \"Finite Temperature\" tensor network or similar states (e.g., Finite Temperature Pure State or similar variational approaches). It is primarily used for research applications in strongly correlated electron systems, often in conjunction with other ISSP tools." }, { "num": "138", "name": "Pomerol", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/aeantipov/pomerol", "note": "", "md_link_text": "Pomerol.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/Pomerol.md", "papers": [], "paper_placeholder": true, "slug": "Pomerol", "idx": 278, "overview": "Pomerol is an exact diagonalization (full ED) code written in C++ for solving condensed matter second-quantized models of interacting fermions and bosons on finite size lattices at finite temperatures. It is designed to produce single and two-particle Green's functions and can be used as an impurity solver in DMFT calculations. Pomerol uses Lehmann representation for efficient computation." }, { "num": "139", "name": "NRG-ETH", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/ETHDMFT/NRG", "note": "Numerical Renormalization Group impurity solver for DMFT (ETH Zurich)", "md_link_text": "NRG-ETH.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/NRG-ETH.md", "papers": [], "paper_placeholder": true, "slug": "NRG-ETH", "idx": 279, "overview": "NRG is a numerical renormalization group implementation developed at ETH Zurich for solving quantum impurity problems within dynamical mean-field theory (DMFT). While primarily an impurity solver rather than a ground-state DFT code, NRG is used within DMFT+DFT frameworks to treat strong correlations in materials. It provides highly accurate solutions to Anderson impurity models, which are central to DMFT calculations of correlated electron systems." }, { "num": "140", "name": "NRG-ETH-CSC", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/ETHDMFT/NRG-CSC", "note": "NRG with Complete basis Set for enhanced spectral resolution (ETH Zurich)", "md_link_text": "NRG-ETH-CSC.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/NRG-ETH-CSC.md", "papers": [], "paper_placeholder": true, "slug": "NRG-ETH-CSC", "idx": 280, "overview": "NRG-CSC is an enhanced numerical renormalization group implementation with complete basis set support, developed at ETH Zurich for solving quantum impurity problems within DMFT frameworks. Building on the standard NRG approach, NRG-CSC provides improved accuracy through complete basis sets, offering better resolution for spectral functions and dynamic properties. It serves as a DMFT impurity solver for strongly correlated electron systems with enhanced precision." }, { "num": "140a", "name": "GeauxCTQMC", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/GeauxCTQMC/GeauxCTQMC", "note": "Highly optimized CT-HYB impurity solver (LA-SiGMA).", "md_link_text": "GeauxCTQMC.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/GeauxCTQMC.md", "papers": [], "paper_placeholder": true, "slug": "GeauxCTQMC", "idx": 281, "overview": "**GeauxCTQMC** (pronounced \"Go-CTQMC\") is a highly optimized Continuous-Time Quantum Monte Carlo (CT-QMC) code based on the **Hybridization Expansion (CT-HYB)** algorithm. Developed under the LA-SiGMA (Louisiana Alliance for Simulation-Guided Materials Applications) project, it is designed to solve single-impurity Anderson models (SIAM) effectively, serving as the computational engine for Dynamical Mean Field Theory (DMFT) studies of strongly correlated materials." }, { "num": "140b", "name": "impurityModel", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/JohanSchott/impurityModel", "note": "ED solver for core-level spectroscopy (XPS/XAS/RIXS).", "md_link_text": "impurityModel.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/impurityModel.md", "papers": [], "paper_placeholder": true, "slug": "impurityModel", "idx": 282, "overview": "impurityModel is a Julia/Python-based exact diagonalization (ED) solver for the Anderson impurity model. It is specialized for simulating core-level spectroscopies (like XPS, XAS, RIXS) where finite-size effects of ED are less critical or where multiplet effects are dominant. It allows for the accurate simulation of local many-electron physics in core-level spectroscopy, particularly for correlated materials like transition metal oxides." }, { "num": "140c", "name": "SOM", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/kcd2015/SOM", "note": "Stochastic Optimization Method for analytic continuation.", "md_link_text": "SOM.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/SOM.md", "papers": [ { "name": "SOM_10.1016_j.cpc.2019.01.021.pdf", "path": "Papers_of_Codes/DMFT/SOM/SOM_10.1016_j.cpc.2019.01.021.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2019.01.021" } ], "paper_placeholder": false, "slug": "SOM", "idx": 283, "overview": "SOM (Stochastic Optimization Method) is a code for the analytic continuation of quantum Monte Carlo (QMC) data. It solves the inverse problem of reconstructing real-frequency spectral functions from imaginary-time or Matsubara frequency Green's functions. It implements a stochastic optimization approach, as proposed by Mishchenko et al., often providing a robust alternative to Maximum Entropy (MaxEnt) by avoiding entropic regularization bias." }, { "num": "140d", "name": "ana_cont", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/josefkaufmann/ana_cont", "note": "MaxEnt and Pade analytic continuation package.", "md_link_text": "ana_cont.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/ana_cont.md", "papers": [], "paper_placeholder": true, "slug": "ana_cont", "idx": 284, "overview": "`ana_cont` is a Python package dedicated to the analytic continuation of many-body Green's functions. It provides a user-friendly interface to standard continuation methods, specifically Pad\u00e9 approximants and the Maximum Entropy Method (MaxEnt), enabling the extraction of real-frequency spectral functions from imaginary-axis QMC data." }, { "num": "140e", "name": "SpM", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/SpM-lab/SpM", "note": "Sparse Modeling approach to analytic continuation.", "md_link_text": "SpM.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/SpM.md", "papers": [ { "name": "SpM_10.1103_PhysRevE.95.061302.pdf", "path": "Papers_of_Codes/DMFT/SpM/SpM_10.1103_PhysRevE.95.061302.pdf", "doi_url": "https://doi.org/10.1103/PhysRevE.95.061302" } ], "paper_placeholder": false, "slug": "SpM", "idx": 285, "overview": "SpM is a software tool for the analytic continuation of imaginary-time Green's functions using **Sparse Modeling**. This approach utilizes the scarcity of information in the Matsubara Green's function to construct a compact representation (Intermediate Representation) and reconstruct the spectral function. It offers an alternative to Maximum Entropy that is often less sensitive to certain types of noise (overfitting) and requires fewer ad-hoc parameters." }, { "num": "140f", "name": "CTAUX", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/danielguterding/ctaux", "note": "Continuous-Time Auxiliary Field (CT-AUX) solver for cluster DMFT.", "md_link_text": "CTAUX.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/CTAUX.md", "papers": [ { "name": "CTAUX_10.1103_PhysRevB.83.075122.pdf", "path": "Papers_of_Codes/DMFT/CTAUX/CTAUX_10.1103_PhysRevB.83.075122.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.83.075122" } ], "paper_placeholder": false, "slug": "CTAUX", "idx": 286, "overview": "**CTAUX** is a Continuous-Time Auxiliary Field Quantum Monte Carlo solver for quantum impurity models. Developed largely by Daniel Guterding, it implements the **CT-AUX** algorithm, which expands the partition function in powers of the interaction strength $U$. This method is complementary to CT-HYB and is particularly efficient for models with large coordination numbers or specific interaction forms where the weak-coupling expansion converges rapidly." }, { "num": "140g", "name": "DMFTpack", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://dmftpack.github.io/", "note": "DFT+DMFT package with native IPT and SC2PT impurity solvers.", "md_link_text": "DMFTpack.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/DMFTpack.md", "papers": [], "paper_placeholder": true, "slug": "DMFTpack", "idx": 287, "overview": "DMFTpack is a software package designed for performing DFT+DMFT (Density Functional Theory + Dynamical Mean-Field Theory) calculations. It provides a bridge between first-principles calculations and many-body techniques. A key feature is its inclusion of native impurity solvers such as Iterative Perturbation Theory (IPT) and Self-Consistent Second-Order Perturbation Theory (SC2PT), as well as interfaces to external solvers." }, { "num": "140h", "name": "d3mft", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/zelong-zhao/d3mft", "note": "Data-driven DMFT using machine learning as an impurity solver.", "md_link_text": "d3mft.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/d3mft.md", "papers": [], "paper_placeholder": true, "slug": "d3mft", "idx": 288, "overview": "d3mft (Data-driven Dynamical Mean-Field Theory) is a code that explores the use of Machine Learning (ML) as an impurity solver for DMFT. It aims to accelerate DMFT calculations by replacing the expensive explicit impurity solver (like QMC or ED) with a trained ML model, focusing on generating quantum databases for the Anderson impurity model." }, { "num": "140i", "name": "CyGutz", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/yaoyongxin/CyGutz", "note": "Gutzwiller rotational invariant slave-boson solver.", "md_link_text": "CyGutz.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/CyGutz.md", "papers": [], "paper_placeholder": true, "slug": "CyGutz", "idx": 289, "overview": "CyGutz is a Gutzwiller solver implemented in Cython/Python. It is designed to solve generic tight-binding models with local interactions using the Gutzwiller-Rotationally Invariant Slave-Boson (RISB) method. It optimizes the single Slater determinant and local many-body degrees of freedom simultaneously within the Gutzwiller approximation." }, { "num": "140j", "name": "risb", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/thenoursehorse/risb", "note": "Rotationally Invariant Slave Bosons solver for lattice models.", "md_link_text": "risb.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/risb.md", "papers": [], "paper_placeholder": true, "slug": "risb", "idx": 290, "overview": "`risb` is a code package for solving strongly correlated many-body electronic problems using the Rotationally Invariant Slave Bosons (RISB) method. This auxiliary particle method captures key features of correlations (like the Mott transition) at a computational cost comparable to mean-field theories, making it significantly faster than full DMFT." }, { "num": "140k", "name": "TRIQS-NCA", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/amoutenet/NCA", "note": "Non-Crossing Approximation solver for TRIQS.", "md_link_text": "TRIQS-NCA.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/TRIQS-NCA.md", "papers": [ { "name": "Parcollet_et_al_2015.pdf", "path": "Papers_of_Codes/DMFT/3.1_DMFT_Frameworks/TRIQS/Parcollet_et_al_2015.pdf", "doi_url": "https://scholar.google.com/scholar?q=TRIQS-NCA+Parcollet+et+al+2015" } ], "paper_placeholder": false, "slug": "TRIQS-NCA", "idx": 291, "overview": "TRIQS-NCA is an implementation of the Non-Crossing Approximation (NCA) impurity solver, developed to work within the TRIQS (Toolbox for Research on Interacting Quantum Systems) ecosystem. It provides a diagrammatic solver for the Anderson Impurity Model features, effective for problems where the hybridization is the perturbation." }, { "num": "140l", "name": "NCA_Standalone", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/CorentinB78/NCA", "note": "Standalone C++ implementation of the NCA impurity solver.", "md_link_text": "NCA_Standalone.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/NCA_Standalone.md", "papers": [], "paper_placeholder": true, "slug": "NCA_Standalone", "idx": 292, "overview": "This is a standalone implementation of the Non-Crossing Approximation (NCA) for solving quantum impurity problems, written in Python. Unlike the TRIQS-based version, this is a self-contained code, suitable for learning or specific lightweight applications without the full TRIQS dependency stack." }, { "num": "140m", "name": "DMRGPy", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/suliu/DMRGPy", "note": "Python/ITensor library for DMRG, applicable to impurity models.", "md_link_text": "DMRGPy.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/DMRGPy.md", "papers": [], "paper_placeholder": true, "slug": "DMRGPy", "idx": 293, "overview": "DMRGPy is a Python library utilizing the ITensor library to compute physics of quasi-one-dimensional systems using Density Matrix Renormalization Group (DMRG) and Matrix Product States (MPS). While primarily a lattice solver, DMRG is increasingly used as an impurity solver by mapping the impurity problem to a 1D chain (star geometry or Wilson chain)." }, { "num": "140n", "name": "SimpleDMFT_solver", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/romainfd/DMFT_solver", "note": "Educational IPT solver for the specific Hubbard model.", "md_link_text": "SimpleDMFT_solver.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/SimpleDMFT_solver.md", "papers": [ { "name": "10.1016_j.cpc.2019.04.014.pdf", "path": "Papers_of_Codes/Niche/10.2_MLIPs_ACE_Linear/SIMPLE-NN/10.1016_j.cpc.2019.04.014.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2019.04.014" } ], "paper_placeholder": false, "slug": "SimpleDMFT_solver", "idx": 294, "overview": "This repository contains a simple, educational implementation of a DMFT solver. It focuses on the Iterated Perturbation Theory (IPT) method for the single-orbital Hubbard model on a Bethe lattice. It serves as an accessible entry point for understanding the structure and implementation of a DMFT self-consistency loop and perturbative solvers, utilizing a clear Jupyter Notebook format." }, { "num": "140o", "name": "scsbz", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.2", "subcategory": "Impurity Solvers", "confidence": "VERIFIED", "official_url": "https://github.com/tflovorn/scsbz", "note": "Slave-boson mean-field solver for superconductivity.", "md_link_text": "scsbz.md", "md_link_path": "DMFT/3.2_Impurity_Solvers/scsbz.md", "papers": [], "paper_placeholder": true, "slug": "scsbz", "idx": 295, "overview": "`scsbz` is a code designed to solve the mean-field self-consistent equations for slave-boson superconductivity. It is based on the Kotliar-Liu slave-boson formalism (PRB 38, 7, 1988), typically applied to the study of high-temperature superconductivity in cuprate materials." }, { "num": "141", "name": "QMCPACK", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "CONFIRMED", "official_url": "https://qmcpack.org/", "note": "", "md_link_text": "QMCPACK.md", "md_link_path": "DMFT/3.3_QMC/QMCPACK.md", "papers": [ { "name": "Kim_et_al_2018.pdf", "path": "Papers_of_Codes/DMFT/3.3_QMC/QMCPACK/Kim_et_al_2018.pdf", "doi_url": "https://scholar.google.com/scholar?q=QMCPACK+Kim+et+al+2018" } ], "paper_placeholder": false, "slug": "QMCPACK", "idx": 296, "overview": "QMCPACK is a modern, high-performance implementation of continuum quantum Monte Carlo (QMC) methods for electronic structure calculations of molecules, 2D materials, and solids. Developed as a community code with major contributions from Oak Ridge National Laboratory, QMCPACK implements Variational Monte Carlo (VMC), Diffusion Monte Carlo (DMC), and related methods. It is optimized for leadership-class supercomputers and provides production-quality calculations for realistic materials with unpre" }, { "num": "142", "name": "CASINO", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "CONFIRMED", "official_url": "https://vallico.net/casino/", "note": "", "md_link_text": "CASINO.md", "md_link_path": "DMFT/3.3_QMC/CASINO.md", "papers": [ { "name": "Needs_et_al_2010.pdf", "path": "Papers_of_Codes/DMFT/3.3_QMC/CASINO/Needs_et_al_2010.pdf", "doi_url": "https://scholar.google.com/scholar?q=CASINO+Needs+et+al+2010" } ], "paper_placeholder": false, "slug": "CASINO", "idx": 297, "overview": "CASINO is a mature and feature-rich quantum Monte Carlo (QMC) code for electronic structure calculations, developed at the University of Cambridge and maintained by an international collaboration. Known for its extensive capabilities and rigorous implementation of QMC methods, CASINO provides VMC, DMC, and related techniques with numerous advanced features for molecules, solids, and surfaces. The code is widely used in the QMC community and represents decades of methodological development." }, { "num": "143", "name": "TurboRVB", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "CONFIRMED", "official_url": "https://github.com/sissaschool/turborvb", "note": "", "md_link_text": "TurboRVB.md", "md_link_path": "DMFT/3.3_QMC/TurboRVB.md", "papers": [ { "name": "Nakano_et_al_2020.pdf", "path": "Papers_of_Codes/DMFT/3.3_QMC/TurboRVB/Nakano_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=TurboRVB+Nakano+et+al+2020" } ], "paper_placeholder": false, "slug": "TurboRVB", "idx": 298, "overview": "TurboRVB is a high-performance quantum Monte Carlo package developed at SISSA (International School for Advanced Studies, Trieste) with emphasis on strongly correlated systems, superconductors, and resonating valence bond (RVB) physics. The code implements advanced trial wavefunctions including Jastrow-geminal-Slater forms, AGP (antisymmetrized geminal power), and pairing functions optimized for studying correlation effects, superconductivity, and quantum phase transitions. TurboRVB is GPU-accel" }, { "num": "144", "name": "ALF", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "CONFIRMED", "official_url": "https://alf.physik.uni-wuerzburg.de/", "note": "", "md_link_text": "ALF.md", "md_link_path": "DMFT/3.3_QMC/ALF.md", "papers": [], "paper_placeholder": true, "slug": "ALF", "idx": 299, "overview": "**ALF** (Algorithms for Lattice Fermions) is a high-performance, open-source software package designed for **Quantum Monte Carlo (QMC)** simulations of strongly correlated fermion systems. It specifically implements the **Auxiliary-Field QMC (AFQMC)** method (also known as Determinantal QMC) to solve a wide class of lattice models at finite temperature or in the ground state (projective). Its key strength lies in its generality: users can define arbitrary Hamiltonians writable in terms of single" }, { "num": "145", "name": "CHAMP", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/CHAMPlib/CHAMP", "note": "", "md_link_text": "CHAMP.md", "md_link_path": "DMFT/3.3_QMC/CHAMP.md", "papers": [], "paper_placeholder": true, "slug": "CHAMP", "idx": 300, "overview": "CHAMP is a quantum Monte Carlo package originally developed at Cornell University and currently maintained as an open-source community project. The code implements Variational Monte Carlo (VMC) and Diffusion Monte Carlo (DMC) methods for electronic structure calculations of molecules and solids. CHAMP emphasizes flexibility, ease of modification for research, and educational value, making it suitable for both production calculations and QMC method development." }, { "num": "146", "name": "QWalk", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/QWalk/QWalk", "note": "", "md_link_text": "QWalk.md", "md_link_path": "DMFT/3.3_QMC/QWalk.md", "papers": [ { "name": "QWalk_10.1016_j.jcp.2009.01.017.pdf", "path": "Papers_of_Codes/DMFT/QWalk/QWalk_10.1016_j.jcp.2009.01.017.pdf", "doi_url": "https://doi.org/10.1016/j.jcp.2009.01.017" } ], "paper_placeholder": false, "slug": "QWalk", "idx": 301, "overview": "QWalk is a quantum Monte Carlo package developed with emphasis on user-friendliness and ease of use for electronic structure calculations. The code implements Variational Monte Carlo (VMC) and Diffusion Monte Carlo (DMC) methods with features designed to make QMC accessible to non-experts. QWalk provides straightforward input generation, automated workflows, and integration with standard quantum chemistry codes." }, { "num": "147", "name": "PyQMC", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/WagnerGroup/pyqmc", "note": "", "md_link_text": "PyQMC.md", "md_link_path": "DMFT/3.3_QMC/PyQMC.md", "papers": [], "paper_placeholder": true, "slug": "PyQMC", "idx": 302, "overview": "PyQMC is a modern Python implementation of real-space quantum Monte Carlo methods for electronic structure calculations. Developed by the Wagner group, PyQMC emphasizes ease of use, rapid prototyping, and integration with the Python scientific ecosystem. The code implements VMC and DMC with a clean, object-oriented design that makes it accessible for both research and educational purposes while maintaining production capability." }, { "num": "148", "name": "QMcBeaver", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/qmcbeaver/QMcBeaver", "note": "", "md_link_text": "QMcBeaver.md", "md_link_path": "DMFT/3.3_QMC/QMcBeaver.md", "papers": [], "paper_placeholder": true, "slug": "QMcBeaver", "idx": 303, "overview": "QMcBeaver is a quantum Monte Carlo code that was developed for electronic structure calculations using VMC and DMC methods. While the code represents earlier QMC development efforts and may not be as actively maintained as modern alternatives, it remains available for historical reference and educational purposes. QMcBeaver implemented standard QMC algorithms for molecular and solid-state systems." }, { "num": "149", "name": "QUEST", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/andrew-j-walker/QUEST", "note": "", "md_link_text": "QUEST.md", "md_link_path": "DMFT/3.3_QMC/QUEST.md", "papers": [ { "name": "Kotani_et_al_2007.pdf", "path": "Papers_of_Codes/DFT/1.2_All-Electron/Questaal/Kotani_et_al_2007.pdf", "doi_url": "https://scholar.google.com/scholar?q=QUEST+Kotani+et+al+2007" } ], "paper_placeholder": false, "slug": "QUEST", "idx": 304, "overview": "QUEST (Quantum Electron Simulation Toolbox) is a Determinant Quantum Monte Carlo (DQMC) code developed by Shiwei Zhang's group (College of William & Mary, now also Flatiron CCQ). It is designed for high-precision simulations of strongly correlated electron systems, particularly the 2D Hubbard model and its variants. QUEST implements efficient algorithms for ground-state and finite-temperature auxiliary-field QMC (AFQMC), emphasizing numerical stability and control over the sign problem through c" }, { "num": "150", "name": "DCA++", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/CompFUSE/DCA", "note": "", "md_link_text": "DCA++.md", "md_link_path": "DMFT/3.3_QMC/DCA++.md", "papers": [ { "name": "DCA++_10.1016_j.cpc.2019.01.006.pdf", "path": "Papers_of_Codes/DMFT/DCA++/DCA++_10.1016_j.cpc.2019.01.006.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2019.01.006" }, { "name": "DCA++_10.1016_j.cpc.2019.01.006.pdf", "path": "Papers_of_Codes/DMFT/DCA%2B%2B/DCA%2B%2B_10.1016_j.cpc.2019.01.006.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2019.01.006" } ], "paper_placeholder": false, "slug": "DCA", "idx": 305, "overview": "DCA++ is a high-performance implementation of the Dynamical Cluster Approximation (DCA), a cluster extension of Dynamical Mean-Field Theory (DMFT) for studying strongly correlated electron systems. Developed as part of the CompFUSE (Computational Framework for Understanding Spectral-weight transfer in correlated Electron systems) project, DCA++ implements continuous-time quantum Monte Carlo cluster solvers with GPU acceleration for studying non-local correlations in lattice models and materials." }, { "num": "151", "name": "NECI", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/NECI/NECI", "note": "", "md_link_text": "NECI.md", "md_link_path": "DMFT/3.3_QMC/NECI.md", "papers": [ { "name": "NECI_10.1063_5.0005754.pdf", "path": "Papers_of_Codes/DMFT/NECI/NECI_10.1063_5.0005754.pdf", "doi_url": "https://doi.org/10.1063/5.0005754" } ], "paper_placeholder": false, "slug": "NECI", "idx": 306, "overview": "NECI is a state-of-the-art implementation of Full Configuration Interaction Quantum Monte Carlo (FCIQMC), a stochastic method for solving the electronic Schr\u00f6dinger equation in a systematically improvable way. Developed primarily at the University of Cambridge, NECI provides numerically exact solutions to the many-electron problem by stochastically sampling the full CI space. The method bridges quantum chemistry and QMC, offering chemical accuracy for strongly correlated systems." }, { "num": "152", "name": "HANDE", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/hande-qmc/hande", "note": "", "md_link_text": "HANDE.md", "md_link_path": "DMFT/3.3_QMC/HANDE.md", "papers": [], "paper_placeholder": true, "slug": "HANDE", "idx": 307, "overview": "HANDE is a modern, efficient implementation of FCIQMC (Full Configuration Interaction Quantum Monte Carlo) and related stochastic quantum chemistry methods. Developed as a community code with contributions from multiple institutions, HANDE provides production-quality implementations of FCIQMC, CCMC (Coupled Cluster Monte Carlo), and DMQMC (Density Matrix QMC) with emphasis on code quality, documentation, and ease of use. The code is designed for both research applications and method development." }, { "num": "153", "name": "ph-AFQMC", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/jkimribo/ph-AFQMC", "note": "", "md_link_text": "ph-AFQMC.md", "md_link_path": "DMFT/3.3_QMC/ph-AFQMC.md", "papers": [ { "name": "ph-AFQMC_10.1021_acs.jctc.8b00342.pdf", "path": "Papers_of_Codes/DMFT/ph-AFQMC/ph-AFQMC_10.1021_acs.jctc.8b00342.pdf", "doi_url": "https://doi.org/10.1021/acs.jctc.8b00342" } ], "paper_placeholder": false, "slug": "ph-AFQMC", "idx": 308, "overview": "ph-AFQMC refers to particle-hole formulation of Auxiliary-Field Quantum Monte Carlo, an advanced QMC technique for studying strongly correlated electron systems. The particle-hole symmetric formulation can offer computational advantages and reduce the sign problem in certain parameter regimes. Implementations exist in research groups focusing on AFQMC methodology and applications to correlated materials." }, { "num": "154", "name": "qmclib", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/kzaiter/qmclib (Example repo)", "note": "", "md_link_text": "qmclib.md", "md_link_path": "DMFT/3.3_QMC/qmclib.md", "papers": [], "paper_placeholder": true, "slug": "qmclib", "idx": 309, "overview": "\"qmclib\" appears as a generic name for quantum Monte Carlo library implementations, with multiple repositories and projects using this designation. Rather than a single unified code, qmclib likely refers to various QMC library implementations developed by different research groups. These typically provide building blocks, utilities, or educational implementations of QMC algorithms." }, { "num": "155a", "name": "ipie", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/pauxy-qmc/ipie", "note": "Modern GPU-accelerated AFQMC (successor to PAUXY).", "md_link_text": "ipie.md", "md_link_path": "DMFT/3.3_QMC/ipie.md", "papers": [], "paper_placeholder": true, "slug": "ipie", "idx": 310, "overview": "**ipie** is a state-of-the-art Python-based Auxiliary-Field Quantum Monte Carlo (AFQMC) package designed for estimating ground state and excited state properties of quantum many-body systems. As a modern successor to PAUXY, it emphasizes performance, modularity, and ease of use. `ipie` is built from the ground up to support high-performance computing on both CPUs and GPUs, making it a powerful tool for *ab initio* quantum chemistry and condensed matter physics." }, { "num": "155b", "name": "dqmc", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/carstenbauer/dqmc", "note": "High-performance Determinant QMC for 2D critical metals (Julia/C++).", "md_link_text": "dqmc.md", "md_link_path": "DMFT/3.3_QMC/dqmc.md", "papers": [], "paper_placeholder": true, "slug": "dqmc", "idx": 311, "overview": "**dqmc** is a high-performance Julia-based Determinant Quantum Monte Carlo (DQMC) code developed by Carsten Bauer. It is specifically tailored for simulating strongly correlated electron systems, particularly focusing on quantum critical points in metals (e.g., antiferromagnetic quantum critical point). It leverages the power of Julia and C++ to achieve performance competitive with traditional Fortran/C++ implementations while maintaining code readability and extensibility." }, { "num": "155c", "name": "MonteCarlo.jl", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/carstenbauer/MonteCarlo.jl", "note": "Unified Julia framework for classical and quantum Monte Carlo.", "md_link_text": "MonteCarlo.jl.md", "md_link_path": "DMFT/3.3_QMC/MonteCarlo.jl.md", "papers": [], "paper_placeholder": true, "slug": "MonteCarlo.jl", "idx": 312, "overview": "**MonteCarlo.jl** is a versatile and extensible Julia library for performing classical and quantum Monte Carlo simulations. It provides a unified framework for simulating a wide variety of physical models, including spin systems (Ising, Heisenberg) and interacting fermions (Hubbard model). Designed with modularity in mind, it allows users to easily define custom lattices, Hamiltonians, and observables while leveraging Julia's performance." }, { "num": "155d", "name": "QMC2", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/jorgehog/QMC2", "note": "Efficient C++ Diffusion Monte Carlo (DMC) implementation.", "md_link_text": "QMC2.md", "md_link_path": "DMFT/3.3_QMC/QMC2.md", "papers": [], "paper_placeholder": true, "slug": "QMC2", "idx": 313, "overview": "**QMC2** is a C++ implementation of quantum Monte Carlo methods, specifically focusing on an efficient **Diffusion Monte Carlo (DMC)** algorithm. Developed by *jorgehog*, it combines a high-performance C++ core with flexible Python scripting for setup and analysis. It is designed for calculating ground state properties of atoms, molecules, and extended systems with high precision." }, { "num": "155e", "name": "ad_afqmc", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/ankit76/ad_afqmc", "note": "Differentiable AFQMC using JAX for optimization.", "md_link_text": "ad_afqmc.md", "md_link_path": "DMFT/3.3_QMC/ad_afqmc.md", "papers": [], "paper_placeholder": true, "slug": "ad_afqmc", "idx": 314, "overview": "**ad_afqmc** is an end-to-end automatically differentiable Auxiliary Field Quantum Monte Carlo (AFQMC) library built on top of JAX. It leverages automatic differentiation (AD) to enable the efficient calculation of physical properties and gradients, such as nuclear forces and dipole moments, which are traditionally challenging in stochastic frameworks. This approach allows for gradient-based optimization of wavefunctions and geometry relaxation within the AFQMC method." }, { "num": "155f", "name": "CanEnsAFQMC", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.3", "subcategory": "QMC", "confidence": "VERIFIED", "official_url": "https://github.com/TongSericus/CanEnsAFQMC", "note": "Auxiliary-Field QMC in the Canonical Ensemble (Julia).", "md_link_text": "CanEnsAFQMC.md", "md_link_path": "DMFT/3.3_QMC/CanEnsAFQMC.md", "papers": [ { "name": "CanEnsAFQMC_10.1063_5.0026606.pdf", "path": "Papers_of_Codes/DMFT/CanEnsAFQMC/CanEnsAFQMC_10.1063_5.0026606.pdf", "doi_url": "https://doi.org/10.1063/5.0026606" } ], "paper_placeholder": false, "slug": "CanEnsAFQMC", "idx": 315, "overview": "**CanEnsAFQMC** is a Julia-based implementation of the Auxiliary-Field Quantum Monte Carlo (AFQMC) method in the **Canonical Ensemble**. Unlike standard Grand Canonical AFQMC which fixes the chemical potential (and thus only average particle number), this code performs simulations at a strictly fixed particle number $N$. This is critical for small systems, cold atoms in traps, or any scenario where particle number fluctuations are unphysical or undesirable." }, { "num": "156", "name": "ITensor", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://itensor.org/", "note": "", "md_link_text": "ITensor.md", "md_link_path": "DMFT/3.4_Tensor_Networks/ITensor.md", "papers": [ { "name": "10_21468_SciPostPhysCodeb_4.pdf", "path": "Papers_of_Codes/DMFT/3.4_Tensor_Networks/iTensor/10_21468_SciPostPhysCodeb_4.pdf", "doi_url": "https://scholar.google.com/scholar?q=ITensor+10+21468+SciPostPhysCodeb+4" } ], "paper_placeholder": false, "slug": "ITensor", "idx": 316, "overview": "ITensor is a powerful C++ library for tensor network calculations with a focus on ease of use through intelligent index matching. Developed by Miles Stoudenmire and collaborators, ITensor provides sophisticated tools for DMRG (Density Matrix Renormalization Group), MPS (Matrix Product States), and general tensor network algorithms. The library emphasizes physicist-friendly notation where indices automatically contract when matched, making complex tensor network code more readable and less error-" }, { "num": "157", "name": "TeNPy", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://tenpy.readthedocs.io/", "note": "", "md_link_text": "TeNPy.md", "md_link_path": "DMFT/3.4_Tensor_Networks/TeNPy.md", "papers": [ { "name": "10_21468_SciPostPhysLectNotes_5.pdf", "path": "Papers_of_Codes/DMFT/3.4_Tensor_Networks/TenPy/10_21468_SciPostPhysLectNotes_5.pdf", "doi_url": "https://scholar.google.com/scholar?q=TeNPy+10+21468+SciPostPhysLectNotes+5" } ], "paper_placeholder": false, "slug": "TeNPy", "idx": 317, "overview": "TeNPy is a comprehensive Python library for tensor network algorithms, particularly focused on one-dimensional quantum systems and DMRG (Density Matrix Renormalization Group). Developed with emphasis on accessibility and ease of use, TeNPy provides a pure Python implementation of state-of-the-art tensor network methods with excellent documentation and a clean, modular design. The library is ideal for researchers and students learning tensor network methods while maintaining production-quality ca" }, { "num": "158", "name": "Block", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://github.com/sanshar/Block", "note": "", "md_link_text": "Block.md", "md_link_path": "DMFT/3.4_Tensor_Networks/Block.md", "papers": [ { "name": "10.1063_1.3695642.pdf", "path": "Papers_of_Codes/DMFT/3.4_Tensor_Networks/Block/10.1063_1.3695642.pdf", "doi_url": "https://doi.org/10.1063/1.3695642" } ], "paper_placeholder": false, "slug": "Block", "idx": 318, "overview": "Block is a highly-optimized DMRG (Density Matrix Renormalization Group) code developed by Garnet Chan's group, designed specifically for quantum chemistry applications. The code implements state-of-the-art DMRG algorithms with a focus on ab initio quantum chemistry, providing accurate solutions for strongly correlated molecular systems. Block is known for its efficiency, scalability, and specialized features for chemical applications including spin-adaptation and point group symmetries." }, { "num": "159", "name": "DMRG++", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://github.com/sanshar/DMRG", "note": "", "md_link_text": "DMRG++.md", "md_link_path": "DMFT/3.4_Tensor_Networks/DMRG++.md", "papers": [ { "name": "10.1016_j.cpc.2009.02.016.pdf", "path": "Papers_of_Codes/DMFT/3.4_Tensor_Networks/DMRG++/10.1016_j.cpc.2009.02.016.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2009.02.016" } ], "paper_placeholder": false, "slug": "DMRG", "idx": 319, "overview": "DMRG++ is a C++ implementation of the Density Matrix Renormalization Group algorithm developed at Oak Ridge National Laboratory. The code emphasizes performance, flexibility, and correct implementation of DMRG for lattice models and quantum systems. DMRG++ provides efficient algorithms for ground states, time evolution, and spectral functions of quantum many-body systems, with particular focus on condensed matter physics applications." }, { "num": "160", "name": "NORG", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://github.com/rqHe1/NORG", "note": "", "md_link_text": "NORG.md", "md_link_path": "DMFT/3.4_Tensor_Networks/NORG.md", "papers": [ { "name": "10_1038_s41524-025-01586-6.pdf", "path": "Papers_of_Codes/DMFT/3.4_Tensor_Networks/NORG/10_1038_s41524-025-01586-6.pdf", "doi_url": "https://scholar.google.com/scholar?q=NORG+10+1038+s41524+025+01586+6" }, { "name": "10_1103_PhysRevB_89_085108.pdf", "path": "Papers_of_Codes/DMFT/3.4_Tensor_Networks/NORG/10_1103_PhysRevB_89_085108.pdf", "doi_url": "https://scholar.google.com/scholar?q=NORG+10+1103+PhysRevB+89+085108" } ], "paper_placeholder": false, "slug": "NORG", "idx": 320, "overview": "NORG (Numerical Orbital Renormalization Group) is a specialized tensor network method and implementation focusing on orbital degrees of freedom and multi-orbital quantum systems. The approach extends DMRG-like techniques to handle orbital complexity in strongly correlated materials. NORG is designed for research applications involving multi-orbital physics, orbital ordering, and complex electronic structure." }, { "num": "160a", "name": "TensorNetwork", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://github.com/google/TensorNetwork", "note": "Google's library for tensor networks with TF/JAX/PyTorch backends.", "md_link_text": "TensorNetwork.md", "md_link_path": "DMFT/3.4_Tensor_Networks/TensorNetwork.md", "papers": [ { "name": "TensorNetwork_10.48550_arXiv.1905.01330.pdf", "path": "Papers_of_Codes/DMFT/TensorNetwork/TensorNetwork_10.48550_arXiv.1905.01330.pdf", "doi_url": "https://doi.org/10.48550/arXiv.1905.01330" } ], "paper_placeholder": false, "slug": "TensorNetwork", "idx": 321, "overview": "TensorNetwork is a comprehensive open-source library developed by Google AI for the efficient implementation, manipulation, and optimization of tensor networks. It is uniquely designed to be backend-agnostic, seamlessly integrating with major machine learning frameworks like TensorFlow, JAX, PyTorch, and NumPy. This allows researchers to bridge the gap between quantum physics and machine learning, leveraging hardware acceleration (GPUs/TPUs) and automatic differentiation to simulate quantum many" }, { "num": "160b", "name": "Quimb", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://github.com/jcmgray/quimb", "note": "Easy-to-use Python library for quantum information and many-body calculations.", "md_link_text": "Quimb.md", "md_link_path": "DMFT/3.4_Tensor_Networks/Quimb.md", "papers": [], "paper_placeholder": true, "slug": "Quimb", "idx": 322, "overview": "Quimb is a standalone Python library for quantum information and many-body calculations. It aims to bridge the gap between \"easy\" and \"fast\" by providing a high-level, interactive API for defining quantum states and operators, coupled with a powerful tensor network engine (`quimb.tensor`). Quimb handles arbitrary tensor network geometries (1D, 2D, 3D, hyperbolic) and integrates with advanced contraction path optimizers and hardware-accelerated backends (like CuPy, JAX, and Torch) to perform simu" }, { "num": "160c", "name": "TeNeS", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://github.com/issp-center-dev/TeNeS", "note": "Massively parallel 2D PEPS solver (ISSP Tokyo).", "md_link_text": "TeNeS.md", "md_link_path": "DMFT/3.4_Tensor_Networks/TeNeS.md", "papers": [], "paper_placeholder": true, "slug": "TeNeS", "idx": 323, "overview": "TeNeS (Tensor Network Solver) is an open-source, massively parallel software package for calculating the ground-state wavefunctions of two-dimensional quantum many-body systems. It employs the infinite Projected Entangled Pair States (iPEPS) ansatz and optimizes it using imaginary time evolution. Designed for high-performance computing, TeNeS leverages the `mptensor` library for efficient distributed tensor operations, allowing it to tackle large bond dimensions and complex frustrated spin/boson" }, { "num": "160d", "name": "mptensor", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://github.com/smorita/mptensor", "note": "Parallel C++ tensor library, backend for TeNeS.", "md_link_text": "mptensor.md", "md_link_path": "DMFT/3.4_Tensor_Networks/mptensor.md", "papers": [], "paper_placeholder": true, "slug": "mptensor", "idx": 324, "overview": "mptensor is a parallel C++ library for tensor calculations, designed to provide a high-performance backend for tensor network simulations on distributed memory systems. It mimics the user-friendly interface of NumPy/SciPy while executing operations in parallel across thousands of cores using MPI and OpenMP. mptensor serves as the core engine for the `TeNeS` solver, enabling it to scale to leadership-class supercomputers." }, { "num": "160e", "name": "ExaTN", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://github.com/ornl-qci/exatn", "note": "Exascale Tensor Networks library (ORNL).", "md_link_text": "ExaTN.md", "md_link_path": "DMFT/3.4_Tensor_Networks/ExaTN.md", "papers": [], "paper_placeholder": true, "slug": "ExaTN", "idx": 325, "overview": "ExaTN (Exascale Tensor Networks) is a high-performance C++ software library designed for the processing of arbitrary tensor networks on exascale computing platforms. Developed by the Quantum Computing Institute at ORNL, it targets applications that require numerical tensor algebra at the absolute limits of scale, such as quantum many-body theory, coupled cluster methods, and quantum circuit simulation. ExaTN abstracts the complexity of distributed memory and GPU management, providing a unified A" }, { "num": "160f", "name": "Uni10", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://github.com/yingjerkao/uni10", "note": "Universal Tensor Network Library directly capable of running on supercomputers.", "md_link_text": "Uni10.md", "md_link_path": "DMFT/3.4_Tensor_Networks/Uni10.md", "papers": [ { "name": "Uni10_10.48550_arXiv.1511.05436.pdf", "path": "Papers_of_Codes/DMFT/Uni10/Uni10_10.48550_arXiv.1511.05436.pdf", "doi_url": "https://doi.org/10.48550/arXiv.1511.05436" } ], "paper_placeholder": false, "slug": "Uni10", "idx": 326, "overview": "Uni10 (Universal Tensor Network Library) is an open-source C++ library designed to facilitate the development and implementation of tensor network algorithms. It balances high-performance C++ execution with ease of use, providing a \"Network\" class to manage complex tensor diagrams intuitively. Uni10 is particularly focused on enabling researchers to write readable code for algorithms like DMRG, PEPS, and MERA while benefiting from behind-the-scenes optimization and GPU acceleration." }, { "num": "160g", "name": "TNT Library", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "http://www.tensornetworktheory.org/", "note": "Oxford group's Tensor Network Theory library.", "md_link_text": "TNT_Library.md", "md_link_path": "DMFT/3.4_Tensor_Networks/TNT_Library.md", "papers": [ { "name": "TNT_Library_10.1088_1742-5468_aa7df3.pdf", "path": "Papers_of_Codes/DMFT/TNT_Library/TNT_Library_10.1088_1742-5468_aa7df3.pdf", "doi_url": "https://doi.org/10.1088/1742-5468_aa7df3" } ], "paper_placeholder": false, "slug": "TNT-Library", "idx": 327, "overview": "The TNT (Tensor Network Theory) Library is a comprehensive software suite for the simulation of strongly correlated quantum systems using tensor network algorithms. Originally developed at the University of Oxford, it has evolved from MATLAB scripts to a high-performance C++ library. The library facilitates the study of ground states, time evolution, and finite-temperature properties of complex many-body systems that are intractable with standard methods." }, { "num": "160h", "name": "TensorCircuit", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://github.com/tencent-quantum-lab/tensorcircuit", "note": "Quantum circuit simulator on tensor networks (Tencent).", "md_link_text": "TensorCircuit.md", "md_link_path": "DMFT/3.4_Tensor_Networks/TensorCircuit.md", "papers": [ { "name": "TensorCircuit_10.48550_arXiv.2205.10091.pdf", "path": "Papers_of_Codes/DMFT/TensorCircuit/TensorCircuit_10.48550_arXiv.2205.10091.pdf", "doi_url": "https://doi.org/10.48550/arXiv.2205.10091" } ], "paper_placeholder": false, "slug": "TensorCircuit", "idx": 328, "overview": "TensorCircuit is a next-generation open-source quantum software framework developed by Tencent. It is built on a high-performance tensor network simulation engine and is fully compatible with modern Deep Learning (DL) frameworks like TensorFlow, JAX, and PyTorch. TensorCircuit is designed for the Noisy Intermediate-Scale Quantum (NISQ) era, enabling efficient simulation of large-scale quantum circuits, variational quantum algorithms (VQA), and quantum machine learning (QML) tasks by leveraging a" }, { "num": "160i", "name": "merapp", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://github.com/g1257/merapp", "note": "MERA++ implementation for critical systems.", "md_link_text": "merapp.md", "md_link_path": "DMFT/3.4_Tensor_Networks/merapp.md", "papers": [], "paper_placeholder": true, "slug": "merapp", "idx": 329, "overview": "merapp (MERA++) is a robust C++ implementation of the Multi-scale Entanglement Renormalization Ansatz (MERA) algorithm. It is part of a suite of tools (including DMRG++) designed for the simulation of strongly correlated quantum systems. MERA++ is specifically engineered to handle scale-invariant systems and quantum critical points by optimizing the MERA tensor network, which adds an extra dimension of \"scale\" to efficiently capture critical entanglement." }, { "num": "160j", "name": "PyTreeNet", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://github.com/Drachier/PyTreeNet", "note": "Tree Tensor Network states for quantum many-body systems.", "md_link_text": "PyTreeNet.md", "md_link_path": "DMFT/3.4_Tensor_Networks/PyTreeNet.md", "papers": [ { "name": "PyTreeNet_10.48550_arXiv.2407.13249.pdf", "path": "Papers_of_Codes/DMFT/PyTreeNet/PyTreeNet_10.48550_arXiv.2407.13249.pdf", "doi_url": "https://doi.org/10.48550/arXiv.2407.13249" } ], "paper_placeholder": false, "slug": "PyTreeNet", "idx": 330, "overview": "**PyTreeNet** is a Python library dedicated to the simulation of quantum many-body systems using **Tree Tensor Networks (TTN)**. Developed by the \"Drachier\" team, it generalizes Matrix Product States (MPS) to tree-like topologies, allowing for efficient representation of systems with hierarchical entanglement structures or non-1D controlivities. It focuses on easing the implementation of complex tensor network algorithms like ground state search and time evolution." }, { "num": "160k", "name": "PEPS", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://github.com/QuantumLiquids/PEPS", "note": "C++ Variational Monte-Carlo updated PEPS solver.", "md_link_text": "PEPS.md", "md_link_path": "DMFT/3.4_Tensor_Networks/PEPS.md", "papers": [], "paper_placeholder": true, "slug": "PEPS", "idx": 331, "overview": "**PEPS** (Projected Entangled Pair States) by the *QuantumLiquids* group is a high-performance C++ library for simulating 2D strongly correlated electron systems. It implements the **PEPS** tensor network ansatz and uses a **Variational Monte Carlo (VMC)** approach to optimize the tensor elements. This combination allows for the rigorous study of 2D fermionic systems (fPEPS) that are challenging for traditional QMC due to the sign problem." }, { "num": "393", "name": "PySCF-DMRG", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.4", "subcategory": "Tensor Networks", "confidence": "VERIFIED", "official_url": "https://pyscf.org/", "note": "DMRG interface in PySCF for multi-reference calculations.", "md_link_text": "PySCF-DMRG.md", "md_link_path": "DMFT/3.4_Tensor_Networks/PySCF-DMRG.md", "papers": [ { "name": "10.1063_1.3695642.pdf", "path": "Papers_of_Codes/DMFT/3.4_Tensor_Networks/PySCF-DMRG/10.1063_1.3695642.pdf", "doi_url": "https://doi.org/10.1063/1.3695642" } ], "paper_placeholder": false, "slug": "PySCF-DMRG", "idx": 332, "overview": "" }, { "num": "160m", "name": "xdiag", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.5", "subcategory": "Exact Diagonalization", "confidence": "VERIFIED", "official_url": "https://github.com/awietek/xdiag", "note": "High-performance C++/Julia ED library for many-body systems.", "md_link_text": "xdiag.md", "md_link_path": "DMFT/3.5_Exact_Diagonalization/xdiag.md", "papers": [ { "name": "xdiag_10.48550_arXiv.2505.02901.pdf", "path": "Papers_of_Codes/DMFT/xdiag/xdiag_10.48550_arXiv.2505.02901.pdf", "doi_url": "https://doi.org/10.48550/arXiv.2505.02901" } ], "paper_placeholder": false, "slug": "xdiag", "idx": 333, "overview": "**xdiag** is a modern, high-performance software package for the **Exact Diagonalization (ED)** of quantum many-body systems. Created by Alexander Wietek, it features a dual-language architecture: a highly optimized C++ core for computational efficiency and a Julia wrapper (`XDiag.jl`) for a user-friendly, high-level interface. It is designed to solve generic spin, boson, and fermion models on arbitrary geometries, exploiting symmetries to reach the largest possible system sizes." }, { "num": "160n", "name": "EDKit.jl", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.5", "subcategory": "Exact Diagonalization", "confidence": "VERIFIED", "official_url": "https://github.com/Roger-luo/EDKit.jl", "note": "Lightweight Julia toolkit for Exact Diagonalization.", "md_link_text": "EDKit_jl.md", "md_link_path": "DMFT/3.5_Exact_Diagonalization/EDKit_jl.md", "papers": [], "paper_placeholder": true, "slug": "EDKit.jl", "idx": 334, "overview": "**EDKit.jl** is a lightweight Julia package for performing Exact Diagonalization (ED) of generic many-body quantum systems. Developed by Roger Luo (author of Yao.jl), it provides a flexible framework for constructing Hamiltonians, handling symmetries, and performing spectral analysis. It is designed to be extensible, allowing users to define custom operator bases and exploit symmetries like $U(1)$ (particle conservation) and $\\mathbb{Z}_2$ (spatial reflection)." }, { "num": "160o", "name": "exactdiag", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.5", "subcategory": "Exact Diagonalization", "confidence": "VERIFIED", "official_url": "https://github.com/mikeschmitt/exactdiag", "note": "Python/Numba package for fermionic exact diagonalization.", "md_link_text": "exactdiag.md", "md_link_path": "DMFT/3.5_Exact_Diagonalization/exactdiag.md", "papers": [], "paper_placeholder": true, "slug": "exactdiag", "idx": 335, "overview": "**exactdiag** is a Python package for performing exact diagonalization of fermionic many-body systems. Uniquely, it leverages **Numba** to Just-In-Time (JIT) compile critical inner loops, allowing it to achieve performance close to compiled languages like C++ or Fortran while efficient Python scripting. It focuses on the Anderson Impurity Model and Hubbard models, providing tools for Green's functions and spectral densities." }, { "num": "160p", "name": "ExactDiagonalization.jl", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.5", "subcategory": "Exact Diagonalization", "confidence": "VERIFIED", "official_url": "https://github.com/Quantum-Many-Body/ExactDiagonalization.jl", "note": "Generic ED solver for QuantumLattices.jl ecosystem.", "md_link_text": "ExactDiagonalization_jl.md", "md_link_path": "DMFT/3.5_Exact_Diagonalization/ExactDiagonalization_jl.md", "papers": [], "paper_placeholder": true, "slug": "ExactDiagonalization.jl", "idx": 336, "overview": "**ExactDiagonalization.jl** is a comprehensive Julia package for the exact diagonalization of quantum many-body systems. It serves as the ED engine within the **QuantumLattices.jl** ecosystem. It provides a unified interface to solve bosonic, fermionic, and spin models defined using the symbolic operator algebra of QuantumLattices. It supports both full diagonalization (for small systems/thermal states) and iterative methods (Lanczos/Arnoldi) for ground states and low-lying excitations." }, { "num": "160q", "name": "MBL_ED", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.5", "subcategory": "Exact Diagonalization", "confidence": "VERIFIED", "official_url": "https://github.com/Tcm0/Many-Body-Localization-Exact-Diagonalization", "note": "Specialized ED code for Many-Body Localization studies.", "md_link_text": "MBL_ED.md", "md_link_path": "DMFT/3.5_Exact_Diagonalization/MBL_ED.md", "papers": [], "paper_placeholder": true, "slug": "MBL_ED", "idx": 337, "overview": "**Many-Body-Localization-Exact-Diagonalization** (referred to here as **MBL_ED**) is a specialized Python codebase for studying the **Many-Body Localization (MBL)** transition in 1D spin chains, specifically the random-field Heisenberg model. It utilizes Exact Diagonalization (ED) to compute diagnostics of the MBL transition, such as level statistics (gap ratios) and entanglement entropy. It is designed to efficiently calculate highly excited eigenstates, which are crucial for probing the infini" }, { "num": "394", "name": "QuSpin", "category_id": "3", "category": "DMFT & MANY-BODY", "subcategory_id": "3.5", "subcategory": "Exact Diagonalization", "confidence": "VERIFIED", "official_url": "https://github.com/QuSpin/QuSpin", "note": "Exact diagonalization and dynamics of quantum many-body systems.", "md_link_text": "QuSpin.md", "md_link_path": "DMFT/3.5_Exact_Diagonalization/QuSpin.md", "papers": [ { "name": "10_21468_SciPostPhys_2_1_003.pdf", "path": "Papers_of_Codes/DMFT/3.5_Exact_Diagonalization/QuSpin/10_21468_SciPostPhys_2_1_003.pdf", "doi_url": "https://scholar.google.com/scholar?q=QuSpin+10+21468+SciPostPhys+2+1+003" } ], "paper_placeholder": false, "slug": "QuSpin", "idx": 338, "overview": "" }, { "num": "161", "name": "Wannier90", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "CONFIRMED", "official_url": "https://wannier.org/", "note": "", "md_link_text": "Wannier90.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/Wannier90.md", "papers": [ { "name": "Pizzi_et_al_2020.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/Wannier90/Pizzi_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=Wannier90+Pizzi+et+al+2020" } ], "paper_placeholder": false, "slug": "Wannier90", "idx": 339, "overview": "Wannier90 is the community standard code for computing maximally-localized Wannier functions (MLWFs) from electronic structure calculations. Developed by an international collaboration, Wannier90 transforms delocalized Bloch states from DFT calculations into localized Wannier representations, enabling tight-binding model construction, topological analysis, transport calculations, and many other applications. The code interfaces with virtually all major DFT packages and is essential for modern el" }, { "num": "162", "name": "WannierTools", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "CONFIRMED", "official_url": "https://github.com/quanshengwu/wannier_tools", "note": "", "md_link_text": "WannierTools.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/WannierTools.md", "papers": [ { "name": "Tsirkin_2021.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/Tsirkin_2021.pdf", "doi_url": "https://scholar.google.com/scholar?q=WannierTools+Tsirkin+2021" }, { "name": "Pizzi_et_al_2020.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/Pizzi_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=WannierTools+Pizzi+et+al+2020" }, { "name": "10_1016_j_cpc_2017_09_033.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/10_1016_j_cpc_2017_09_033.pdf", "doi_url": "https://scholar.google.com/scholar?q=WannierTools+10+1016+j+cpc+2017+09+033" } ], "paper_placeholder": false, "slug": "WannierTools", "idx": 340, "overview": "WannierTools is a comprehensive software package for investigating topological properties of materials using tight-binding models from Wannier90. Developed by QuanSheng Wu and collaborators, WannierTools calculates topological invariants, surface states, nodal structures, and various topological phenomena. The code has become the standard tool for topological characterization of materials, enabling systematic exploration of topological phases from ab-initio calculations." }, { "num": "163", "name": "WannierBerri", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/stepan-tsirkin/wannierberri", "note": "", "md_link_text": "WannierBerri.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/WannierBerri.md", "papers": [ { "name": "Tsirkin_2021.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierBerri/Tsirkin_2021.pdf", "doi_url": "https://scholar.google.com/scholar?q=WannierBerri+Tsirkin+2021" }, { "name": "10.1038_s41524-021-00498-5.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierBerri/10.1038_s41524-021-00498-5.pdf", "doi_url": "https://doi.org/10.1038/s41524-021-00498-5" } ], "paper_placeholder": false, "slug": "WannierBerri", "idx": 341, "overview": "WannierBerri is a Python code for calculating Berry curvature-related properties of materials using Wannier tight-binding models. Developed by Stepan Tsirkin, WannierBerri provides efficient and accurate calculations of anomalous Hall conductivity, orbital magnetization, shift currents, and other Berry phase phenomena from first principles. The code uses adaptive mesh refinement and modern algorithms to achieve high precision in Berry curvature integration." }, { "num": "173", "name": "BoltzWann", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/wannier-developer/boltzwann", "note": "", "md_link_text": "BoltzWann.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/BoltzWann.md", "papers": [ { "name": "10_1016_j_cpc_2013_09_015.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/BoltzWann/10_1016_j_cpc_2013_09_015.pdf", "doi_url": "https://scholar.google.com/scholar?q=BoltzWann+10+1016+j+cpc+2013+09+015" } ], "paper_placeholder": false, "slug": "BoltzWann", "idx": 342, "overview": "BoltzWann is a module within the Wannier90 package for calculating Boltzmann transport properties using Wannier interpolation. The tool computes electrical conductivity, Seebeck coefficient, electronic thermal conductivity, and other transport coefficients from first principles via Wannier tight-binding models. BoltzWann implements the Boltzmann transport equation in the relaxation time approximation." }, { "num": "174", "name": "PyWannier90", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/zjwang11/PyWannier90", "note": "", "md_link_text": "PyWannier90.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/PyWannier90.md", "papers": [], "paper_placeholder": true, "slug": "PyWannier90", "idx": 343, "overview": "PyWannier90 is a Python interface and utility library for Wannier90, providing Pythonic access to Wannier function calculations and analysis. Developed by Zhijun Wang, PyWannier90 enables Python-based workflows for Wannier function construction, manipulation, and post-processing, integrating Wannier90 capabilities into the Python scientific ecosystem." }, { "num": "175", "name": "WOPT", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "**MODULE** - Wannier90 optimization extension (part of Wannier90 repo).", "note": "", "md_link_text": "WOPT.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/WOPT.md", "papers": [], "paper_placeholder": true, "slug": "WOPT", "idx": 344, "overview": "WOPT is an optimization extension module within the Wannier90 package, providing advanced optimization algorithms for Wannier function localization. The module implements improved optimization strategies for constructing maximally-localized Wannier functions, particularly useful for challenging systems or when standard procedures have convergence difficulties." }, { "num": "176", "name": "VASP2Wannier90", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/wannier-developer/vasp2wannier90", "note": "", "md_link_text": "VASP2Wannier90.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/VASP2Wannier90.md", "papers": [ { "name": "Kresse_Furthmuller_1996.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/Kresse_Furthmuller_1996.pdf", "doi_url": "https://scholar.google.com/scholar?q=VASP2Wannier90+Kresse+Furthmuller+1996" }, { "name": "Kresse_Hafner_1993.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/Kresse_Hafner_1993.pdf", "doi_url": "https://scholar.google.com/scholar?q=VASP2Wannier90+Kresse+Hafner+1993" }, { "name": "10.1016_0927-0256(96)00008-0.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/10.1016_0927-0256%2896%2900008-0.pdf", "doi_url": "https://doi.org/10.1016/0927-0256(96)00008-0" } ], "paper_placeholder": false, "slug": "VASP2Wannier90", "idx": 345, "overview": "VASP2Wannier90 is the interface between the Vienna Ab initio Simulation Package (VASP) and Wannier90, enabling the construction of maximally-localized Wannier functions from VASP DFT calculations. This interface is one of the most widely used Wannier90 connections due to VASP's popularity, providing seamless workflow from VASP electronic structure calculations to Wannier tight-binding models." }, { "num": "178", "name": "RESPACK", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/respack-dev/respack", "note": "", "md_link_text": "RESPACK.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/RESPACK.md", "papers": [ { "name": "RESPACK_10.1016_j.cpc.2020.107781.pdf", "path": "Papers_of_Codes/TightBinding/RESPACK/RESPACK_10.1016_j.cpc.2020.107781.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2020.107781" } ], "paper_placeholder": false, "slug": "RESPACK", "idx": 346, "overview": "RESPACK is a first-principles calculation software for evaluating interaction parameters in correlated electron systems. Developed in Japan (primarily at University of Tokyo), RESPACK calculates screened Coulomb interactions, constrained RPA parameters, and downfolding for effective models. The code bridges ab-initio calculations and many-body physics, providing interaction parameters for DMFT, model Hamiltonians, and GW calculations." }, { "num": "182", "name": "Paoflow", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/jehub/Paoflow", "note": "", "md_link_text": "Paoflow.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/Paoflow.md", "papers": [ { "name": "10_1016_j_commatsci_2017_11_034.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/PAOFLOW/10_1016_j_commatsci_2017_11_034.pdf", "doi_url": "https://scholar.google.com/scholar?q=Paoflow+10+1016+j+commatsci+2017+11+034" } ], "paper_placeholder": false, "slug": "Paoflow", "idx": 347, "overview": "PAOFLOW is a Python-based post-processing tool for electronic structure calculations, designed to compute transport, topological, and optical properties from DFT calculations using tight-binding models constructed with atomic orbital projections. Developed primarily at the University of North Texas, PAOFLOW provides automated workflows for property calculations from first principles with emphasis on ease of use and comprehensive analysis capabilities." }, { "num": "182a", "name": "Koopmans", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://koopmans-functionals.org/", "note": "Spectral functionals using Wannier90 and Quantum ESPRESSO.", "md_link_text": "Koopmans.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/Koopmans.md", "papers": [], "paper_placeholder": true, "slug": "Koopmans", "idx": 348, "overview": "**Koopmans** is a spectral functional code designed to predict accurate electronic structures, particularly band gaps and ionization potentials, by enforcing the **Generalized Koopmans' Theorem (GKT)**. It serves as a wrapper and extension around **Quantum ESPRESSO**, using **Wannier90** to construct localized orbitals on which Koopmans-compliant corrections are applied. The code addresses the band gap problem in standard DFT by ensuring that orbital energies correspond directly to charged excit" }, { "num": "182b", "name": "WIEN2WANNIER", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://wien2wannier.github.io/", "note": "Interface between WIEN2k and Wannier90.", "md_link_text": "WIEN2WANNIER.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/WIEN2WANNIER.md", "papers": [ { "name": "WIEN2WANNIER_10.1016_j.cpc.2010.08.005.pdf", "path": "Papers_of_Codes/TightBinding/WIEN2WANNIER/WIEN2WANNIER_10.1016_j.cpc.2010.08.005.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2010.08.005" } ], "paper_placeholder": false, "slug": "WIEN2WANNIER", "idx": 349, "overview": "**WIEN2WANNIER** is a specialized interface program that connects the high-precision, all-electron full-potential linearized augmented plane-wave (FP-LAPW) code **WIEN2k** with the maximally-localized Wannier function code **Wannier90**. It computes the necessary overlap matrices ($M_{mn}$) and projection matrices ($A_{mn}$) from WIEN2k's Bloch states, allowing for the construction of Wannier functions with all-electron accuracy. This tool is essential for researchers using methods that require " }, { "num": "182c", "name": "sisl", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://zerothi.github.io/sisl/", "note": "Large-scale tight-binding API and DFT post-processing.", "md_link_text": "sisl.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/sisl.md", "papers": [], "paper_placeholder": true, "slug": "sisl", "idx": 350, "overview": "**sisl** is a high-performance, modern Python framework for electronic structure calculations and large-scale tight-binding modeling. Developed as a successor to the utility scripts of TranSIESTA, it has evolved into a general-purpose API that interfaces with multiple DFT codes (SIESTA, VASP, OpenMX, Wannier90, BigDFT) to manipulate Hamiltonians, geometries, and real-space grids. It is particularly renowned for its ability to handle extremely large sparse matrices, enabling tight-binding calcula" }, { "num": "182d", "name": "TB2J", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/mailhexu/TB2J", "note": "Magnetic interaction parameters (Heisenberg J) from Wannier/DFT.", "md_link_text": "TB2J.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/TB2J.md", "papers": [ { "name": "10.1016_j.cpc.2021.107938.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/TB2J/10.1016_j.cpc.2021.107938.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2021.107938" } ], "paper_placeholder": false, "slug": "TB2J", "idx": 351, "overview": "**TB2J** is an open-source Python package designed to calculate magnetic interaction parameters\u2014specifically the isotropic Heisenberg exchange ($J$), anisotropic exchange, and Dzyaloshinskii-Moriya interaction (DMI)\u2014from first-principles density functional theory (DFT) data. It utilizes the **Green's function method** combined with the **Magnetic Force Theorem**, allowing for the extraction of these parameters from a single unit-cell calculation without the need for computationally expensive sup" }, { "num": "182e", "name": "WanTiBEXOS", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/ac-dias/wantibexos", "note": "Wannier-based Tight-Binding for excitonic and optoelectronic properties.", "md_link_text": "WanTiBEXOS.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/WanTiBEXOS.md", "papers": [], "paper_placeholder": true, "slug": "WanTiBEXOS", "idx": 352, "overview": "**WanTiBEXOS** (Wannier-based Tight-Binding for Excitonic and Optoelectronic Structures) is a Fortran90 code designed to efficiently compute the electronic, optical, and excitonic properties of materials ranging from bulk solids to nanostructures (0D, 1D, 2D). It bypasses the high computational cost of full *ab initio* GW-BSE calculations by solving the Bethe-Salpeter Equation (BSE) within a Wannier-based tight-binding framework, using parameters derived from **Wannier90**. This allows for the s" }, { "num": "182f", "name": "StraWBerryPy", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/strawberrypy-developers/strawberrypy", "note": "Topological invariants and quantum geometry in real space.", "md_link_text": "StraWBerryPy.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/StraWBerryPy.md", "papers": [], "paper_placeholder": true, "slug": "StraWBerryPy", "idx": 353, "overview": "**StraWBerryPy** (Single-poinT and local invaRiAnts for Wannier Berriologies in Python) is a specialized Python package for calculating topological invariants and quantum geometrical properties in **non-crystalline** and **disordered** topological insulators. Unlike standard tools that rely on Bloch's theorem and Brillouin zone integration, StraWBerryPy operates in real space, making it uniquely capable of characterizing topological phases in amorphous materials, quasicrystals, and systems with " }, { "num": "182g", "name": "dynamics-w90", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/michaelschueler/dynamics-w90", "note": "Time-dependent dynamics and light-matter coupling from Wannier90.", "md_link_text": "dynamics-w90.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/dynamics-w90.md", "papers": [], "paper_placeholder": true, "slug": "dynamics-w90", "idx": 354, "overview": "**dynamics-w90** is a sophisticated Fortran package designed to simulate **non-equilibrium electron dynamics** in solids using realistic tight-binding Hamiltonians derived from **Wannier90**. It focuses on light-matter interactions, enabling the study of ultrafast phenomena such as high-harmonic generation (HHG), time-resolved photoemission (tr-ARPES), and transient band structure engineering. The code distinguishes itself by implementing a **gauge-invariant formulation** for coupling electromag" }, { "num": "182h", "name": "WOPTIC", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/woptic/woptic", "note": "Optical conductivity with adaptive k-mesh refinement.", "md_link_text": "WOPTIC.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/WOPTIC.md", "papers": [ { "name": "WOPTIC_10.1016_j.cpc.2015.12.010.pdf", "path": "Papers_of_Codes/TightBinding/WOPTIC/WOPTIC_10.1016_j.cpc.2015.12.010.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2015.12.010" } ], "paper_placeholder": false, "slug": "WOPTIC", "idx": 355, "overview": "**WOPTIC** is a code designed to calculate frequency-dependent optical conductivity ($\\sigma(\\omega)$) and related transport properties using **Maximally Localized Wannier Functions (MLWFs)**. Its distinctive feature is the use of an **adaptive k-mesh refinement scheme** based on the tetrahedron method, which allows it to efficiently resolve fine spectral features (such as those arising from band crossings or van Hove singularities) that would require prohibitively dense uniform grids. It can al" }, { "num": "182i", "name": "EDRIXS", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/EDRIXS/edrixs", "note": "Toolkit for RIXS/XAS simulation using Exact Diagonalization.", "md_link_text": "EDRIXS.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/EDRIXS.md", "papers": [ { "name": "EDRIXS_10.1016_j.cpc.2019.04.018.pdf", "path": "Papers_of_Codes/TightBinding/EDRIXS/EDRIXS_10.1016_j.cpc.2019.04.018.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2019.04.018" } ], "paper_placeholder": false, "slug": "EDRIXS", "idx": 356, "overview": "**EDRIXS** (Exact Diagonalization for Resonant Inelastic X-ray Scattering) is an open-source toolkit designed for simulating X-ray Absorption Spectroscopy (XAS), Resonant Inelastic X-ray Scattering (RIXS), and Resonant Magnetic X-ray Scattering (RMXS). Built on exact diagonalization (ED) of model Hamiltonians, it is particularly suited for studying strongly correlated materials where local interactions play a critical role. EDRIXS combines a high-performance Fortran 90 core for heavy numerical t" }, { "num": "182j", "name": "Wan2respack", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/respack-dev/wan2respack", "note": "Interface converting Wannier90 outputs for RESPACK.", "md_link_text": "Wan2respack.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/Wan2respack.md", "papers": [], "paper_placeholder": true, "slug": "Wan2respack", "idx": 357, "overview": "**Wan2respack** is a critical interface utility that bridges **Wannier90** and **RESPACK**. It converts the maximally localized Wannier functions (MLWFs) generated by Wannier90 into the specific input format required by RESPACK. This enables RESPACK to perform advanced many-body calculations\u2014specifically the **Constrained Random Phase Approximation (cRPA)**\u2014on models derived from standard DFT codes (like Quantum ESPRESSO) via Wannierization. It effectively allows for the ab initio derivation of " }, { "num": "182k", "name": "WannierIO.jl", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/qilauea/WannierIO.jl", "note": "Julia library for reading/writing Wannier90 file formats.", "md_link_text": "WannierIO_jl.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/WannierIO_jl.md", "papers": [ { "name": "Tsirkin_2021.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/Tsirkin_2021.pdf", "doi_url": "https://scholar.google.com/scholar?q=WannierIO.jl+Tsirkin+2021" }, { "name": "Pizzi_et_al_2020.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/Pizzi_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=WannierIO.jl+Pizzi+et+al+2020" }, { "name": "10_1016_j_cpc_2017_09_033.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/10_1016_j_cpc_2017_09_033.pdf", "doi_url": "https://scholar.google.com/scholar?q=WannierIO.jl+10+1016+j+cpc+2017+09+033" } ], "paper_placeholder": false, "slug": "WannierIO.jl", "idx": 358, "overview": "**WannierIO.jl** is a lightweight, zero-dependency Julia library dedicated to reading and writing the standard file formats used by **Wannier90** and the broader Wannier ecosystem. It serves as the fundamental I/O layer for high-level Julia packages like **Wannier.jl** and **DFTK.jl**, enabling seamless data exchange between Fortran-based legacy codes and modern Julia-based electronic structure tools." }, { "num": "182l", "name": "Wannier.jl", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/qilauea/Wannier.jl", "note": "Pure Julia package for generating Maximally Localized Wannier Functions.", "md_link_text": "Wannier_jl.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/Wannier_jl.md", "papers": [ { "name": "Tsirkin_2021.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/Tsirkin_2021.pdf", "doi_url": "https://scholar.google.com/scholar?q=Wannier.jl+Tsirkin+2021" }, { "name": "Pizzi_et_al_2020.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/Pizzi_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=Wannier.jl+Pizzi+et+al+2020" }, { "name": "10_1016_j_cpc_2017_09_033.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/10_1016_j_cpc_2017_09_033.pdf", "doi_url": "https://scholar.google.com/scholar?q=Wannier.jl+10+1016+j+cpc+2017+09+033" } ], "paper_placeholder": false, "slug": "Wannier.jl", "idx": 359, "overview": "**Wannier.jl** is a modern, pure Julia package for generating **Maximally Localized Wannier Functions (MLWFs)**. Designed as a flexible and high-performance alternative to the standard Fortran **Wannier90** code, it implements core algorithms for disentanglement and localization while leveraging Julia's strengths in composability, automatic differentiation, and GPU acceleration. It allows for fast prototyping of new Wannierization methods and seamless integration with Julia-based density functio" }, { "num": "182m", "name": "linres", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/stepan-tsirkin/linres", "note": "Linear response properties (conductivity, Drude weight) from tight-binding.", "md_link_text": "linres.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/linres.md", "papers": [], "paper_placeholder": true, "slug": "linres", "idx": 360, "overview": "**linres** is a specialized Fortran90 code for calculating linear and non-linear response properties of solids using **Wannier interpolation**. Developed by Stepan Tsirkin, it serves as an efficient tool for computing quantities like the anomalous Hall conductivity, optical conductivity, and Drude weights directly from ab initio tight-binding models generated by **Wannier90**. While highly effective, it is considered a precursor to the more general and powerful Python-based **WannierBerri** code" }, { "num": "182n", "name": "Abipy", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "http://abinit.github.io/abipy/", "note": "Python library for analyzing ABINIT and Wannier90 results.", "md_link_text": "Abipy.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/Abipy.md", "papers": [], "paper_placeholder": true, "slug": "Abipy", "idx": 361, "overview": "**Abipy** is a high-level open-source Python library designed for analyzing the results of **ABINIT** calculations, with a particular focus on **Many-Body Perturbation Theory (MBPT)** (GW approximations and Bethe-Salpeter Equation) and analyzing **Wannier90** results. It serves as a bridge between the complex output of ab-initio codes and the user, automating workflows, generating input files, and providing powerful visualization tools." }, { "num": "182o", "name": "symclosestwannier", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/wannier-utils-dev/symclosestwannier", "note": "Symmetry-Adapted Closest Wannier Tight-Binding models.", "md_link_text": "symclosestwannier.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/symclosestwannier.md", "papers": [], "paper_placeholder": true, "slug": "symclosestwannier", "idx": 362, "overview": "**symclosestwannier** is a Python library that implements the **Symmetry-Adapted Closest Wannier (SymCW)** method. It addresses a key limitation in standard Wannier90 workflows: the difficulty of ensuring that the resulting Maximally Localized Wannier Functions (MLWFs) fully respect the crystalline symmetry of the material. By projecting Bloch states onto a **Symmetry-Adapted Multipole Basis (SAMB)**, this tool constructs high-quality tight-binding models that are naturally symmetric without req" }, { "num": "182p", "name": "pengWann", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://pengwann.readthedocs.io/", "note": "Chemical bonding and local electronic structure descriptors (WOHP, WOBI).", "md_link_text": "pengWann.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/pengWann.md", "papers": [], "paper_placeholder": true, "slug": "pengWann", "idx": 363, "overview": "**pengWann** is a lightweight Python package designed to bridge the gap between abstract Wannier functions and chemical intuition. It post-processes **Wannier90** outputs to extract quantitative descriptors of chemical bonding and local electronic structure, such as bond populations and orbital indices. By treating Wannier functions as a localized basis, it allows for \"L\u00f6wdin-like\" population analysis on plane-wave DFT results without the basis set spilling issues associated with projection onto" }, { "num": "182q", "name": "WannierPy", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/K4ys4r/WannierPy", "note": "Python scripts for reading Hamiltonians and plotting band structures.", "md_link_text": "WannierPy.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/WannierPy.md", "papers": [ { "name": "Tsirkin_2021.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/Tsirkin_2021.pdf", "doi_url": "https://scholar.google.com/scholar?q=WannierPy+Tsirkin+2021" }, { "name": "Pizzi_et_al_2020.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/Pizzi_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=WannierPy+Pizzi+et+al+2020" }, { "name": "10_1016_j_cpc_2017_09_033.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/10_1016_j_cpc_2017_09_033.pdf", "doi_url": "https://scholar.google.com/scholar?q=WannierPy+10+1016+j+cpc+2017+09+033" } ], "paper_placeholder": false, "slug": "WannierPy", "idx": 364, "overview": "**WannierPy** represents a collection of Python-based tools and scripts designed to facilitate the post-processing and analysis of **Wannier90** output. While multiple forks and versions exist (e.g., `K4ys4r/WannierPy`, `henriquemiranda/wannierpy`), they share a common goal: providing a lightweight, scriptable interface to handle Hamiltonian matrices, plot band structures, and compute transport properties without the overhead of heavy compiled codes." }, { "num": "182r", "name": "pyatb", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/pyatb/pyatb", "note": "Ab initio tight-binding simulation and property calculation.", "md_link_text": "pyatb.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/pyatb.md", "papers": [], "paper_placeholder": true, "slug": "pyatb", "idx": 365, "overview": "**pyatb** (Python Ab-initio Tight-Binding) is a Python-based simulation package designed for the efficient calculation of electronic structures and physical properties using **ab-initio tight-binding Hamiltonians**. It is particularly tailored to work with Numerical Atomic Orbitals (NAO) and enables post-processing of Hamiltonians generated by first-principles codes like **ABACUS**." }, { "num": "182s", "name": "NanoNET", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/freude/NanoNet", "note": "Python framework for TB and NEGF transport.", "md_link_text": "NanoNET.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/NanoNET.md", "papers": [], "paper_placeholder": true, "slug": "NanoNET", "idx": 366, "overview": "**NanoNET** (Nanoscale Non-equilibrium Electron Transport) is an expandable Python framework for modeling electronic structure and quantum transport in nanodevices. It combines the **Tight-Binding (TB)** method with the **Non-Equilibrium Green's Function (NEGF)** formalism. NanoNET is specifically designed to handle the efficient construction of Hamiltonians for large, non-periodic or semi-periodic systems (like nanowires) using algorithmically optimized neighbor searching." }, { "num": "182t", "name": "EPWpy", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "http://epwpy.org/", "note": "Python interface for EPW workflow automation.", "md_link_text": "EPWpy.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/EPWpy.md", "papers": [], "paper_placeholder": true, "slug": "EPWpy", "idx": 367, "overview": "**EPWpy** is the official high-level Python interface for **EPW** (Electron-Phonon Wannier), the leading code for calculating electron-phonon coupling properties using Maximally Localized Wannier Functions. EPWpy is designed to democratize access to complex electron-phonon calculations by automating the often-intricate workflows involving Quantum ESPRESSO, Wannier90, and EPW, and providing modern data structures for analysis." }, { "num": "182u", "name": "wannier_shift", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/stmeurk/wannier_shift", "note": "Wannier interpolation for TMDC heterostructures and moir\u00e9 bands.", "md_link_text": "wannier_shift.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/wannier_shift.md", "papers": [ { "name": "Tsirkin_2021.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/Tsirkin_2021.pdf", "doi_url": "https://scholar.google.com/scholar?q=wannier_shift+Tsirkin+2021" }, { "name": "Pizzi_et_al_2020.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/Pizzi_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=wannier_shift+Pizzi+et+al+2020" }, { "name": "10_1016_j_cpc_2017_09_033.pdf", "path": "Papers_of_Codes/TightBinding/4.1_Wannier_Ecosystem/WannierTools/10_1016_j_cpc_2017_09_033.pdf", "doi_url": "https://scholar.google.com/scholar?q=wannier_shift+10+1016+j+cpc+2017+09+033" } ], "paper_placeholder": false, "slug": "wannier_shift", "idx": 368, "overview": "**wannier_shift** is a Python-based code designed for the construction and interpolation of tight-binding Hamiltonians for **Transition Metal Dichalcogenide (TMDC)** heterostructures, particularly those exhibiting **moir\u00e9 patterns** due to twisting or lattice mismatch. It addresses the challenge of modeling large-scale superlattices by taking ab initio Wannier Tight-Binding parameters (from **Wannier90**) and applying a \"shifting\" interpolation scheme to generate the Hamiltonian for commensurate" }, { "num": "182v", "name": "ccao-unfold", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/ccao/unfold", "note": "Band unfolding code for supercell calculations (Wannier-based).", "md_link_text": "ccao_unfold.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/ccao_unfold.md", "papers": [], "paper_placeholder": true, "slug": "ccao-unfold", "idx": 369, "overview": "**ccao-unfold** is a lightweight but powerful utility for **band unfolding**. It allows researchers to recover the effective primitive-cell band structure from calculations performed in a supercell. This is essential for analyzing systems with broken translational symmetry, such as defects, alloys, or twisted bilayers, where the \"folded\" supercell bands are often too dense to interpret. Unlike plane-wave unfolding codes, ccao-unfold operates on the **Wannier90** tight-binding Hamiltonian, making" }, { "num": "182w", "name": "elphbolt", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.1", "subcategory": "Wannier Ecosystem", "confidence": "VERIFIED", "official_url": "https://github.com/nakib/elphbolt", "note": "Coupled electron-phonon Boltzmann transport using Wannier90.", "md_link_text": "elphbolt.md", "md_link_path": "TightBinding/4.1_Wannier_Ecosystem/elphbolt.md", "papers": [], "paper_placeholder": true, "slug": "elphbolt", "idx": 370, "overview": "**elphbolt** is a state-of-the-art solver for the **coupled electron-phonon Boltzmann Transport Equations (BTE)**. Unlike standard transport codes that treat electrons and phonons separately or use the relaxation time approximation, elphbolt solves the full system iteratively to capture complex non-equilibrium phenomena such as **phonon drag** (the dragging of electrons by a non-equilibrium phonon flux) and electron drag. It utilizes **Wannier90** for efficient interpolation of electronic bands " }, { "num": "164", "name": "pythtb", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://www.physics.rutgers.edu/pythtb/", "note": "", "md_link_text": "pythtb.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/pythtb.md", "papers": [ { "name": "10_1017_9781316662205.pdf", "path": "Papers_of_Codes/TightBinding/4.2_Model_Hamiltonians/PythTB/10_1017_9781316662205.pdf", "doi_url": "https://scholar.google.com/scholar?q=pythtb+10+1017+9781316662205" } ], "paper_placeholder": false, "slug": "pythtb", "idx": 371, "overview": "**PythTB** is a lightweight Python package for constructing and solving tight-binding models. Developed by David Vanderbilt's group at Rutgers University, it is widely used as a pedagogical tool for teaching **topological band theory** and Berry phase physics. Its simplicity makes it ideal for rapid prototyping of model Hamiltonians, while its specialized routines for calculating **Berry phases**, **Wilson loops**, and **Chern numbers** make it a powerful research tool for topological insulators" }, { "num": "165", "name": "TBmodels", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/zhenli-sun/tbmodels", "note": "", "md_link_text": "TBmodels.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/TBmodels.md", "papers": [ { "name": "10_1103_PhysRevB_95_075146.pdf", "path": "Papers_of_Codes/TightBinding/4.2_Model_Hamiltonians/TBmodels/10_1103_PhysRevB_95_075146.pdf", "doi_url": "https://scholar.google.com/scholar?q=TBmodels+10+1103+PhysRevB+95+075146" } ], "paper_placeholder": false, "slug": "TBmodels", "idx": 372, "overview": "**TBmodels** is a Python library developed as part of the **Z2Pack** ecosystem, designed for reading, creating, and manipulating tight-binding models. Its distinct feature is its comprehensive support for **symmetry operations** and seamless integration with **Wannier90**. It allows users to read Wannier Hamiltonians, symmetrize them to enforce crystal symmetries, and export them for topological invariant calculations, making it a critical tool in the workflow for identifying topological materia" }, { "num": "168", "name": "Pybinding", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/dean0x7d/pybinding", "note": "", "md_link_text": "Pybinding.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/Pybinding.md", "papers": [ { "name": "10.21105_joss.00949.pdf", "path": "Papers_of_Codes/materials_science_papers/5_TB_Model_Hamiltonians_Downfolding/Pybinding/10.21105_joss.00949.pdf", "doi_url": "https://doi.org/10.21105/joss.00949" } ], "paper_placeholder": false, "slug": "Pybinding", "idx": 373, "overview": "**Pybinding** is a high-performance Python package for numerical tight-binding calculations. It is engineered to handle **large-scale systems** (millions of atoms) by combining a user-friendly Python interface with a highly optimized C++ core. It excels at constructing arbitrary lattice geometries, applying external fields and disorder, and computing electronic properties using efficient methods like the **Kernel Polynomial Method (KPM)**." }, { "num": "169", "name": "TBSTUDIO", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://sourceforge.net/projects/tbstudio/", "note": "", "md_link_text": "TBSTUDIO.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/TBSTUDIO.md", "papers": [], "paper_placeholder": true, "slug": "TBSTUDIO", "idx": 374, "overview": "**TBSTUDIO** is a comprehensive software package centered around a graphical user interface (GUI) for the construction of tight-binding Hamiltonians from first-principles data. It simplifies the often complex workflow of fitting Slater-Koster parameters to Density Functional Theory (DFT) band structures. By automating the fitting process and providing visualization tools, it serves as a bridge between ab initio codes (like VASP, Quantum ESPRESSO) and model analysis tools." }, { "num": "172a", "name": "KITE", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/zjwang11/ir2tb", "note": "", "md_link_text": "ir2tb.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/ir2tb.md", "papers": [ { "name": "10.1098_rsos.191809.pdf", "path": "Papers_of_Codes/TightBinding/4.3_Quantum_Transport/KITE/10.1098_rsos.191809.pdf", "doi_url": "https://doi.org/10.1098/rsos.191809" } ], "paper_placeholder": false, "slug": "KITE", "idx": 375, "overview": "**ir2tb** is a specialized Python tool developed by Zhijun Wang (author of PyWannier90 and IRVSP) for constructing **symmetry-adapted tight-binding models** directly from irreducible representations (irreps) of crystallographic space groups. It automates the complex group-theoretical task of constraining the Hamiltonian matrix elements so that they respect the full symmetry of the crystal, enabling the construction of minimal effective models for topological analysis." }, { "num": "177", "name": "ir2tb", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/zjwang11/ir2tb", "note": "", "md_link_text": "ir2tb.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/ir2tb.md", "papers": [], "paper_placeholder": true, "slug": "ir2tb", "idx": 376, "overview": "**ir2tb** is a specialized Python tool developed by Zhijun Wang (author of PyWannier90 and IRVSP) for constructing **symmetry-adapted tight-binding models** directly from irreducible representations (irreps) of crystallographic space groups. It automates the complex group-theoretical task of constraining the Hamiltonian matrix elements so that they respect the full symmetry of the crystal, enabling the construction of minimal effective models for topological analysis." }, { "num": "179", "name": "TightBinding++", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/huchou/TightBinding", "note": "C++ framework for Quantum Tight-Binding (Topological/Transport focus)", "md_link_text": "TightBindingPlusPlus.md", "md_link_path": "DFT/1.5_Tight-Binding/TightBindingPlusPlus.md", "papers": [], "paper_placeholder": true, "slug": "TightBinding", "idx": 377, "overview": "TightBinding++ is a C++ framework with a Python wrapper/interface tailored for the simulation of quantum tight-binding models. It automates the generation of Hamiltonian matrices and allows for the inclusion of external magnetic fields and disorder, facilitating the study of topological systems and transport properties using the Kubo-Greenwood formalism." }, { "num": "180", "name": "QuantumLattice", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/weber-group/QuantumLattice", "note": "", "md_link_text": "QuantumLattice.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/QuantumLattice.md", "papers": [ { "name": "Giannozzi_et_al_2009.pdf", "path": "Papers_of_Codes/materials_science_papers/1.1_Plane-Wave_Pseudopotential_PAW_Methods/Quantum_ESPRESSO/Giannozzi_et_al_2009.pdf", "doi_url": "https://scholar.google.com/scholar?q=QuantumLattice+Giannozzi+et+al+2009" } ], "paper_placeholder": false, "slug": "QuantumLattice", "idx": 378, "overview": "**QuantumLattices.jl** is a flexible and composable Julia framework for the construction and analysis of quantum lattice systems. It provides a unique **symbolic interface** for defining operators and Hamiltonians using natural language-like syntax. As a core component of the \"Quantum-Many-Body\" organization, it serves as the unifying frontend for various computational backends, including Exact Diagonalization (ED) and Density Matrix Renormalization Group (DMRG)." }, { "num": "181", "name": "QuantNBody", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/QuantNBody/QuantNBody", "note": "", "md_link_text": "QuantNBody.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/QuantNBody.md", "papers": [], "paper_placeholder": true, "slug": "QuantNBody", "idx": 379, "overview": "**QuantNBody** is a Python package designed to facilitate the manipulation of many-body operators and wave functions in the second quantization formalism. Developed effectively as a \"quantum chemistry playground,\" it allows users to implement and test various electronic structure methods\u2014such as Configuration Interaction (CI) and Coupled Cluster (CC)\u2014from scratch. It is particularly valuable for educational purposes and for method developers prototyping new many-body algorithms." }, { "num": "183", "name": "MagneticTB", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/andrewfeng12/MagneticTB", "note": "", "md_link_text": "MagneticTB.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/MagneticTB.md", "papers": [], "paper_placeholder": true, "slug": "MagneticTB", "idx": 380, "overview": "**MagneticTB** is a Mathematica package designed for the automated construction of tight-binding models for materials with any of the 1651 **Magnetic Space Groups (MSGs)**. It greatly simplifies the theoretical modeling of magnetic topological materials by automatically generating symmetry-allowed Hamiltonian matrices based on user-supplied Wyckoff positions and orbital characters." }, { "num": "184", "name": "MagneticKP", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/andrewfeng12/MagneticKP", "note": "", "md_link_text": "MagneticKP.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/MagneticKP.md", "papers": [], "paper_placeholder": true, "slug": "MagneticKP", "idx": 381, "overview": "**MagneticKP** is a dual-language (Mathematica and Python) software package for the efficient construction of **k\u00b7p effective Hamiltonians** in magnetic and non-magnetic crystals. It implements a novel \"Iterative Simplification Algorithm\" (ISA) to rapidly solve the symmetry constraints imposed by all 1651 **Magnetic Space Groups (MSGs)**. It enables researchers to derive low-energy effective models expanded to arbitrary orders in wavenumber $\\mathbf{k}$ for complex topological materials." }, { "num": "184a", "name": "TightBindingToolkit.jl", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/Anjishnubose/TightBindingToolkit.jl", "note": "Julia package for generic TB models and topological properties.", "md_link_text": "TightBindingToolkit.jl.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/TightBindingToolkit.jl.md", "papers": [], "paper_placeholder": true, "slug": "TightBindingToolkit.jl", "idx": 382, "overview": "**TightBindingToolkit.jl** is a feature-rich Julia package for the construction, solution, and analysis of generic tight-binding models. It excels in the study of **topological phases of matter**, providing built-in tools for Berry curvature, Chern numbers, and Majorana modes in superconductors. It supports both standard electronic Hamiltonians and Bogoliubov-de Gennes (BdG) Hamiltonians for superconductors, making it a versatile tool for defining custom lattice models in 1D, 2D, and 3D." }, { "num": "184b", "name": "HopTB.jl", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/HopTB/HopTB.jl", "note": "Non-orthogonal TB and Wannier90 interface.", "md_link_text": "HopTB.jl.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/HopTB.jl.md", "papers": [], "paper_placeholder": true, "slug": "HopTB.jl", "idx": 383, "overview": "**HopTB.jl** is a Julia package designed for constructing and analyzing tight-binding Hamiltonians, with a unique focus on **non-orthogonal bases**. It serves as a bridge between first-principles Density Functional Theory (DFT) codes and model physics, allowing users to import Hamiltonians from **Wannier90**, **OpenMX**, and **FHI-aims**. Beyond standard band structures, HopTB.jl provides a powerful suite of tools for calculating linear and **non-linear response functions**, including optical co" }, { "num": "184c", "name": "ThreeBodyTB.jl", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/usnistgov/ThreeBodyTB.jl", "note": "High-accuracy TB with three-body interactions (NIST).", "md_link_text": "ThreeBodyTB.jl.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/ThreeBodyTB.jl.md", "papers": [], "paper_placeholder": true, "slug": "ThreeBodyTB.jl", "idx": 384, "overview": "**ThreeBodyTB.jl** is a high-accuracy tight-binding package developed by NIST. It distinguishes itself from standard Slater-Koster codes by including pre-fit **three-body interaction terms**, which dramatically improves transferability and accuracy for structures far from equilibrium (e.g., surfaces, defects, high pressure). Implemented in pure Julia, it provides a self-consistent field (SCF) solver that rivals DFT accuracy (specifically PBEsol) for a vast range of elemental and binary systems, " }, { "num": "184d", "name": "TBTK", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/dafer45/TBTK", "note": "C++ library for second-quantized Hamiltonians on discrete lattices.", "md_link_text": "TBTK.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/TBTK.md", "papers": [ { "name": "TBTK_10.1016_j.softx.2019.02.005.pdf", "path": "Papers_of_Codes/TightBinding/TBTK/TBTK_10.1016_j.softx.2019.02.005.pdf", "doi_url": "https://doi.org/10.1016/j.softx.2019.02.005" } ], "paper_placeholder": false, "slug": "TBTK", "idx": 385, "overview": "**TBTK** is a C++ library designed for modeling and solving **second-quantized Hamiltonians** on arbitrary discretizable structures. While rooted in tight-binding models, its abstract graph-based architecture allows it to handle a wide variety of quantum mechanical problems, from simple lattices to complex device geometries. It provides a suite of high-performance solvers, including exact diagonalization and the **Kernel Polynomial Method (KPM)**, along with tools for calculating Green's functio" }, { "num": "184e", "name": "HubbardModel2D", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/ryanlevy/HubbardModel2D", "note": "C++ Exact Diagonalization solver for Hubbard models.", "md_link_text": "HubbardModel2D.md", "md_link_path": "DMFT/3.5_Exact_Diagonalization/HubbardModel2D.md", "papers": [ { "name": "10_1103_PhysRevB_100_205130.pdf", "path": "Papers_of_Codes/Niche/10.8_Niche_Tools/HubbardFermiMatsubara/10_1103_PhysRevB_100_205130.pdf", "doi_url": "https://scholar.google.com/scholar?q=HubbardModel2D+10+1103+PhysRevB+100+205130" }, { "name": "10.1098_rspa.1963.0204.pdf", "path": "Papers_of_Codes/Niche/10.8_Niche_Tools/HubbardFermiMatsubara/10.1098_rspa.1963.0204.pdf", "doi_url": "https://doi.org/10.1098/rspa.1963.0204" } ], "paper_placeholder": false, "slug": "HubbardModel2D", "idx": 386, "overview": "**HubbardModel2D** is a specialized C++ code for performing **Exact Diagonalization (ED)** of the single-orbital Fermi-Hubbard model on 1D chains and 2D square lattices. It uses the **Lanczos algorithm** to compute ground state energies, wavefunctions, and spectral properties. While primarily designed for small clusters due to the exponential scaling of ED, it serves as a transparent and efficient tool for benchmarking and studying strong correlation effects on finite lattices." }, { "num": "184f", "name": "EDLib", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/Q-solvers/EDLib", "note": "C++ template library for exact diagonalization (Hubbard/Anderson).", "md_link_text": "EDLib.md", "md_link_path": "DMFT/3.5_Exact_Diagonalization/EDLib.md", "papers": [ { "name": "EDLib_10.1016_j.cpc.2017.12.016.pdf", "path": "Papers_of_Codes/TightBinding/EDLib/EDLib_10.1016_j.cpc.2017.12.016.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2017.12.016" } ], "paper_placeholder": false, "slug": "EDLib", "idx": 387, "overview": "**EDLib** is a flexible C++ template library for the **Exact Diagonalization (ED)** of quantum many-body systems. It specifically targets fermionic models like the **Hubbard Model** and the **Anderson Impurity Model (AIM)** on finite clusters. Designed with efficiency and modern C++ practices in mind, it provides tools for computing ground state properties, finite-temperature thermodynamics, and spectral functions using Lanczos algorithms." }, { "num": "184g", "name": "PolaronMobility.jl", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/Frost-group/PolaronMobility.jl", "note": "Feynman variational path-integral for Fr\u00f6hlich/Holstein polarons.", "md_link_text": "PolaronMobility.jl.md", "md_link_path": "Niche/10.8_Niche_Tools/PolaronMobility.jl.md", "papers": [], "paper_placeholder": true, "slug": "PolaronMobility.jl", "idx": 388, "overview": "**PolaronMobility.jl** is a Julia package dedicated to calculating polaron properties\u2014specifically mobility and effective mass\u2014in polar semiconductors and ionic crystals. It implements Feynman's variational path-integral approach to the **Fr\u00f6hlich polaron** problem, which describes the interaction of an electron with macroscopic optical phonons. It also extends to the **Holstein polaron** model, making it a versatile tool for studying charge transport limits in materials like halide perovskites " }, { "num": "184h", "name": "Sunny.jl", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/SunnySuite/Sunny.jl", "note": "SU(N) spin dynamics, LLG, and LSWT in Julia.", "md_link_text": "Sunny.jl.md", "md_link_path": "Niche/Spin_Dynamics/Sunny.jl.md", "papers": [], "paper_placeholder": true, "slug": "Sunny.jl", "idx": 389, "overview": "**Sunny.jl** is a cutting-edge Julia package for the simulation of **spin dynamics** and magnetic properties in crystal systems. What sets it apart is its formulation based on **SU(N) coherent states**, which generalizes the traditional Landau-Lifshitz-Gilbert (LLG) dynamics of dipoles to include multipolar moments (quadrupoles, octupoles) on an equal footing. It unifies Classical Monte Carlo, Molecular Dynamics (LLG), and Linear Spin Wave Theory (LSWT) in a single, high-performance framework." }, { "num": "184i", "name": "SpinMC.jl", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/fbuessen/SpinMC.jl", "note": "Classical Monte Carlo for lattice spin models.", "md_link_text": "SpinMC.jl.md", "md_link_path": "Niche/Spin_Dynamics/SpinMC.jl.md", "papers": [], "paper_placeholder": true, "slug": "SpinMC.jl", "idx": 390, "overview": "**SpinMC.jl** is a Julia package dedicated to **classical Monte Carlo** simulations of lattice spin models. It offers a straightforward interface for defining custom unit cells and interaction matrices, enabling the study of Heisenberg, XY, Ising, Dzyaloshinskii-Moriya, and Kitaev interactions on arbitrary lattices. It is designed to efficiently calculate thermodynamic properties and identify magnetic phase transitions." }, { "num": "184j", "name": "JHeisenbergED", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/RudSmo/JHeisenbergED", "note": "Simple Julia module for 1D Heisenberg Model ED.", "md_link_text": "JHeisenbergED.md", "md_link_path": "DMFT/3.5_Exact_Diagonalization/JHeisenbergED.md", "papers": [], "paper_placeholder": true, "slug": "JHeisenbergED", "idx": 391, "overview": "**JHeisenbergED** is a Julia module designed for the **Exact Diagonalization (ED)** and **time-evolution** of the 1D quantum Heisenberg model. It provides a lightweight, pure-Julia implementation for constructing Hamiltonians of spin-1/2 chains and studying their static (ground state) and dynamic properties. It is particularly useful for pedagogical purposes and for researchers needing a quick, programmable solver for small spin systems." }, { "num": "184k", "name": "Heisenberg", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://github.com/muammar/heisenberg", "note": "Python program for Heisenberg spin chain matrix calculation.", "md_link_text": "Heisenberg.md", "md_link_path": "DMFT/3.5_Exact_Diagonalization/Heisenberg.md", "papers": [], "paper_placeholder": true, "slug": "Heisenberg", "idx": 392, "overview": "**Heisenberg** is a lightweight Python program designed for the exact analysis of quantum spin chains. It constructs the Hamiltonian matrix for the **Spin-1/2 Heisenberg model** in the $S^z$ basis, diagonalizes it to extract the full spectrum (eigenvalues and eigenvectors), and computes advanced quantities like the **Total Position Spread (TPS)** tensor, which is relevant for studying localization and insulating behavior." }, { "num": "396", "name": "SlateKoster", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.2", "subcategory": "Model Hamiltonians", "confidence": "VERIFIED", "official_url": "https://en.wikipedia.org/wiki/Slater-Koster_method", "note": "Slater-Koster tight-binding parameterization scheme.", "md_link_text": "SlateKoster.md", "md_link_path": "TightBinding/4.2_Model_Hamiltonians/SlateKoster.md", "papers": [ { "name": "10.1103_PhysRev.94.1498.pdf", "path": "Papers_of_Codes/TightBinding/4.2_Model_Hamiltonians/SlateKoster/10.1103_PhysRev.94.1498.pdf", "doi_url": "https://doi.org/10.1103/PhysRev.94.1498" } ], "paper_placeholder": false, "slug": "SlateKoster", "idx": 393, "overview": "" }, { "num": "167", "name": "Kwant", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.3", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "https://kwant-project.org/", "note": "", "md_link_text": "Kwant.md", "md_link_path": "TightBinding/4.3_Quantum_Transport/Kwant.md", "papers": [ { "name": "10_1088_1367-2630_16_6_063065.pdf", "path": "Papers_of_Codes/TightBinding/4.3_Quantum_Transport/Kwant/10_1088_1367-2630_16_6_063065.pdf", "doi_url": "https://scholar.google.com/scholar?q=Kwant+10+1088+1367+2630+16+6+063065" } ], "paper_placeholder": false, "slug": "Kwant", "idx": 394, "overview": "**Kwant** is a powerful, open-source Python package for numerical quantum transport calculations. It allows for the construction of tight-binding models with arbitrary shapes and dimensionality and the calculation of their transport properties using the **scattering matrix** formalism (Landauer-B\u00fcttiker). Kwant is widely considered the community standard for mesoscopic transport due to its flexibility, ease of use, and \"Builder\" pattern which decouples the physics (Hamiltonian) from the geometry" }, { "num": "171", "name": "TBPLaS", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.3", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "https://github.com/quantum-tb/TBPLaS", "note": "", "md_link_text": "TBPLaS.md", "md_link_path": "TightBinding/4.3_Quantum_Transport/TBPLaS.md", "papers": [], "paper_placeholder": true, "slug": "TBPLaS", "idx": 395, "overview": "**TBPLaS** (Tight-Binding Package for Large-scale Simulation) is a high-performance Python package designed for the simulation of **electronic structure** and **quantum transport** in macroscopic tight-binding models. Developed by the **DeepModeling** community, it leverages efficient numerical algorithms\u2014such as the **Tight-Binding Propagation Method (TBPM)** and **Kernel Polynomial Method (KPM)**\u2014to perform calculations on systems with **millions of atomic orbitals**, scaling linearly with sys" }, { "num": "171a", "name": "NanoTCAD ViDES", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.3", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "http://vides.nanotcad.com/", "note": "NEGF-based device simulator (Poisson-Schr\u00f6dinger).", "md_link_text": "NanoTCAD_ViDES.md", "md_link_path": "TightBinding/4.3_Quantum_Transport/NanoTCAD_ViDES.md", "papers": [], "paper_placeholder": true, "slug": "NanoTCAD-ViDES", "idx": 396, "overview": "**NanoTCAD ViDES** (Vintage Integrated Development Environment for Simulations) is an open-source software package for the simulation of nanoscale electronic devices. It is particularly renowned for its ability to simulate **2D material-based devices** (graphene, MoS2) using the **Non-Equilibrium Green's Function (NEGF)** formalism self-consistently coupled with a 2D/3D **Poisson solver**. The code is wrapped in Python, providing a flexible scripting environment for investigating novel transisto" }, { "num": "171b", "name": "NEMO5", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.3", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "https://nemo5.org/", "note": "NanoElectronics MOdeling Tools; atomistic tight-binding and transport.", "md_link_text": "NEMO5.md", "md_link_path": "TightBinding/4.3_Quantum_Transport/NEMO5.md", "papers": [ { "name": "NEMO5_10.1109_TNANO.2011.2166164.pdf", "path": "Papers_of_Codes/TightBinding/NEMO5/NEMO5_10.1109_TNANO.2011.2166164.pdf", "doi_url": "https://doi.org/10.1109/TNANO.2011.2166164" } ], "paper_placeholder": false, "slug": "NEMO5", "idx": 397, "overview": "**NEMO5** (NanoElectronics MOdeling Tools 5) is a state-of-the-art **multiscale simulation framework** for nanoelectronics. It represents the culmination of decades of development (NEMO-1D, NEMO-3D, OMEN) and integrates atomistic tight-binding models with continuum approximations, strain engineering, phonon transport, and optical properties. It is designed to simulate realistic semiconductor devices (FinFETs, nanowires, quantum dots) with millions of atoms, leveraging petascale supercomputing re" }, { "num": "391", "name": "NEGF-DFT", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.3", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "https://www.transiesta.org/", "note": "Non-Equilibrium Greens Function + DFT for quantum transport.", "md_link_text": "NEGF-DFT.md", "md_link_path": "TightBinding/4.3_Quantum_Transport/NEGF-DFT.md", "papers": [ { "name": "10.1103_PhysRevB.65.165401.pdf", "path": "Papers_of_Codes/TightBinding/4.3_Quantum_Transport/NEGF-DFT/10.1103_PhysRevB.65.165401.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.65.165401" } ], "paper_placeholder": false, "slug": "NEGF-DFT", "idx": 398, "overview": "" }, { "num": "166", "name": "Z2Pack", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.4", "subcategory": "Topological Analysis", "confidence": "VERIFIED", "official_url": "https://z2pack.ethz.ch/", "note": "", "md_link_text": "Z2Pack.md", "md_link_path": "TightBinding/4.4_Topological_Analysis/Z2Pack.md", "papers": [ { "name": "Z2Pack_10.1103_PhysRevB.95.075146.pdf", "path": "Papers_of_Codes/TightBinding/Z2Pack/Z2Pack_10.1103_PhysRevB.95.075146.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.95.075146" } ], "paper_placeholder": false, "slug": "Z2Pack", "idx": 399, "overview": "**Z2Pack** is the premier tool for the automated calculation of topological invariants and Berry phases. Developed at ETH Zurich, it implements the **Wilson Loop** and **Wannier Charge Center (WCC)** tracking methods to calculate $\\mathbb{Z}_2$ invariants, Chern numbers, and Weyl point chiralities without the need for manual inspection or gauge fixing. It interfaces seamlessly with both tight-binding models (via **TBmodels**) and ab-initio codes (VASP, Quantum ESPRESSO, Wannier90)." }, { "num": "170", "name": "TopoTB", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.4", "subcategory": "Topological Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/ruanyangxy/TopoTB", "note": "", "md_link_text": "TopoTB.md", "md_link_path": "TightBinding/4.4_Topological_Analysis/TopoTB.md", "papers": [ { "name": "10_1038_ncomms7710.pdf", "path": "Papers_of_Codes/TightBinding/4.4_Topological_Analysis/TopoTB/10_1038_ncomms7710.pdf", "doi_url": "https://scholar.google.com/scholar?q=TopoTB+10+1038+ncomms7710" } ], "paper_placeholder": false, "slug": "TopoTB", "idx": 400, "overview": "**TopoTB** is a software package written in **Mathematica** for the interactive calculation and visualization of topological properties in tight-binding models. Its standout feature is its use of Mathematica's `Manipulate` functionality to create **real-time interactive phase diagrams**, allowing users to dynamically tune Hamiltonian parameters (like mass or hopping strength) and immediately see the effect on band structures, Berry curvature, and edge states." }, { "num": "170a", "name": "pyqula", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.4", "subcategory": "Topological Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/joselado/pyqula", "note": "Topological quantum lattice systems (modern pygra).", "md_link_text": "pyqula.md", "md_link_path": "TightBinding/4.4_Topological_Analysis/pyqula.md", "papers": [], "paper_placeholder": true, "slug": "pyqula", "idx": 401, "overview": "**pyqula** (Python Quantum Lattice) is a powerful standard-library for simulating quantum tight-binding models, with a distinctive focus on **interacting systems** and **topological phases**. Unlike many pure TB codes, pyqula includes self-consistent mean-field solvers for Hubbard and Heisenberg interactions, allowing it to simulate the interplay between correlation (magnetism, superconductivity) and topology. It also implements the **Kernel Polynomial Method (KPM)** for large-scale calculations" }, { "num": "170b", "name": "WEYLFET", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.4", "subcategory": "Topological Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/WEYLFET-developers/WEYLFET", "note": "Transport in Weyl semimetals (Kwant-based).", "md_link_text": "WEYLFET.md", "md_link_path": "TightBinding/4.4_Topological_Analysis/WEYLFET.md", "papers": [ { "name": "WEYLFET_10.1063_1.5126033.pdf", "path": "Papers_of_Codes/TightBinding/WEYLFET/WEYLFET_10.1063_1.5126033.pdf", "doi_url": "https://doi.org/10.1063/1.5126033" } ], "paper_placeholder": false, "slug": "WEYLFET", "idx": 402, "overview": "**WEYLFET** is a specialized simulation tool built on top of the **Kwant** library, explicitly designed to model quantum transport in **Weyl Semimetals (WSMs)**. It streamlines the setup of complex WSM Hamiltonians\u2014including multi-node configurations, time-reversal breaking, and inversion breaking terms\u2014and automates the calculation of transport signatures such as the **chiral anomaly**, **Fermi arc surface transport**, and disorder-induced transitions." }, { "num": "170c", "name": "Berry", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.4", "subcategory": "Topological Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/ricardoribeiro-2020/berry", "note": "Berry curvature and conductivity from DFT.", "md_link_text": "Berry.md", "md_link_path": "TightBinding/4.4_Topological_Analysis/Berry.md", "papers": [ { "name": "10_1103_PhysRevB_63_155107.pdf", "path": "Papers_of_Codes/Post-Processing/8.2_Topological_Symmetry/8.2.2_Topological_Invariants/BerryPI/10_1103_PhysRevB_63_155107.pdf", "doi_url": "https://scholar.google.com/scholar?q=Berry+10+1103+PhysRevB+63+155107" } ], "paper_placeholder": false, "slug": "Berry", "idx": 403, "overview": "**Berry** is a Python package designed to calculate the Berry phase, Berry curvature, and related topological properties of crystalline materials directly from **Density Functional Theory (DFT)** wavefunctions, without relying on Maximally Localized Wannier Functions (MLWFs). It specifically interfaces with **Quantum ESPRESSO** to extract Bloch states and compute topological invariants and optical responses, such as the Anomalous Hall Conductivity (AHC) and Circular Dichroism." }, { "num": "170d", "name": "PY-Nodes", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.4", "subcategory": "Topological Analysis", "confidence": "VERIFIED", "official_url": "https://sourceforge.net/projects/py-nodes/", "note": "Nelder-Mead search for Weyl/Dirac nodes (WIEN2k).", "md_link_text": "PY-Nodes.md", "md_link_path": "TightBinding/4.4_Topological_Analysis/PY-Nodes.md", "papers": [], "paper_placeholder": true, "slug": "PY-Nodes", "idx": 404, "overview": "**PY-Nodes** is a Python-based computational tool designed to automatically search for and classify **band degeneracy points** (nodes) in the Brillouin zone of topological semimetals. Specifically tailored for the all-electron DFT code **WIEN2k**, it uses a simplex optimization algorithm (Nelder-Mead) to minimize the energy gap function $\\Delta E(\\mathbf{k}) = |E_{n+1}(\\mathbf{k}) - E_n(\\mathbf{k})|$. This allows it to locate Weyl points, Dirac points, and nodal lines with high precision without" }, { "num": "170e", "name": "nested_wloop", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.4", "subcategory": "Topological Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/kuansenlin/nested_and_spin_resolved_Wilson_loop", "note": "Nested Wilson loops for Higher-Order Topology.", "md_link_text": "nested_wloop.md", "md_link_path": "TightBinding/4.4_Topological_Analysis/nested_wloop.md", "papers": [], "paper_placeholder": true, "slug": "nested_wloop", "idx": 405, "overview": "**nested_wloop** is a specialized Python toolkit designed to extend **PythTB** for the characterization of **Higher-Order Topological Insulators (HOTIs)** and **Fragile Topology**. It implements the numerical calculation of **Nested Wilson Loops**\u2014a hierarchical Berry phase technique required to identify quadrupole and octupole insulators\u2014as well as Spin-Resolved Wilson loops for systems with approximate time-reversal symmetry." }, { "num": "170f", "name": "TopMat", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.4", "subcategory": "Topological Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/zjwang11/TopMat", "note": "Magnetic Topological Quantum Chemistry workflow.", "md_link_text": "TopMat.md", "md_link_path": "TightBinding/4.4_Topological_Analysis/TopMat.md", "papers": [], "paper_placeholder": true, "slug": "TopMat", "idx": 406, "overview": "**TopMat** is a specialized high-throughput coding framework designed for the search and classification of **Magnetic Topological Materials**. Based on the theory of **Magnetic Topological Quantum Chemistry (MTQC)**, it extends topological indicators to all 1651 Magnetic Space Groups (MSGs). It was the engine behind the construction of the Magnetic Topological Materials Database, enabling the identification of hundreds of new magnetic topological insulators and semimetals." }, { "num": "170g", "name": "pytopomat", "category_id": "4", "category": "TIGHT-BINDING", "subcategory_id": "4.4", "subcategory": "Topological Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/ncfrey/pytopomat", "note": "High-throughput topological materials screening.", "md_link_text": "pytopomat.md", "md_link_path": "TightBinding/4.4_Topological_Analysis/pytopomat.md", "papers": [], "paper_placeholder": true, "slug": "pytopomat", "idx": 407, "overview": "**pytopomat** is a Python package designed for the high-throughput screening of topological materials within the **Materials Project** ecosystem. It provides a user-friendly interface to apply the theory of **Topological Quantum Chemistry (TQC)** to crystal structures, allowing users to automatically diagnose whether a material is topological or trivial based on its symmetry and valence electron count, often without expensive surface state calculations." }, { "num": "185", "name": "Phonopy", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "CONFIRMED", "official_url": "https://phonopy.github.io/phonopy/", "note": "", "md_link_text": "Phonopy.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/Phonopy.md", "papers": [ { "name": "Togo_Tanaka_2015.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/Phonopy/Togo_Tanaka_2015.pdf", "doi_url": "https://scholar.google.com/scholar?q=Phonopy+Togo+Tanaka+2015" } ], "paper_placeholder": false, "slug": "Phonopy", "idx": 408, "overview": "Phonopy is the standard code for phonon calculations using the finite displacement method with forces from DFT codes. It computes phonon band structures, density of states, and thermodynamic properties for crystalline materials. Widely adopted and integrated with virtually all major DFT packages, it is the de facto tool for routine phonon calculations in materials science." }, { "num": "186", "name": "phono3py", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "CONFIRMED", "official_url": "https://phonopy.github.io/phono3py/", "note": "", "md_link_text": "phono3py.md", "md_link_path": "Phonons/5.2_Anharmonic_Thermal_Transport/phono3py.md", "papers": [ { "name": "Togo_et_al_2015.pdf", "path": "Papers_of_Codes/Phonons/5.2_Anharmonic_Thermal_Transport/phono3py/Togo_et_al_2015.pdf", "doi_url": "https://scholar.google.com/scholar?q=phono3py+Togo+et+al+2015" } ], "paper_placeholder": false, "slug": "phono3py", "idx": 409, "overview": "phono3py is a code for computing lattice thermal conductivity and related properties from first principles using three-phonon interactions. It extends Phonopy to include anharmonic effects via third-order force constants, enabling calculations of phonon lifetimes, thermal conductivity, and other anharmonic properties essential for thermoelectric materials and thermal management applications." }, { "num": "187", "name": "ShengBTE", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/lingjqi/shengbte", "note": "", "md_link_text": "ShengBTE.md", "md_link_path": "Phonons/5.2_Anharmonic_Thermal_Transport/ShengBTE.md", "papers": [ { "name": "Li_et_al_2014.pdf", "path": "Papers_of_Codes/Phonons/5.2_Anharmonic_Thermal_Transport/ShengBTE/Li_et_al_2014.pdf", "doi_url": "https://scholar.google.com/scholar?q=ShengBTE+Li+et+al+2014" } ], "paper_placeholder": false, "slug": "ShengBTE", "idx": 410, "overview": "**ShengBTE** is a widely used software package for solving the **Phonon Boltzmann Transport Equation (BTE)** to calculate the lattice thermal conductivity of crystalline materials. It operates on a fully *ab initio* basis, taking second-order (harmonic) and third-order (anharmonic) interatomic force constants (IFCs) from density functional theory (DFT) calculations as input. By solving the BTE iteratively, it accurately captures phonon-phonon scattering processes beyond the relaxation time appro" }, { "num": "188", "name": "ALAMODE", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/atztogo/alamode", "note": "", "md_link_text": "ALAMODE.md", "md_link_path": "Phonons/5.2_Anharmonic_Thermal_Transport/ALAMODE.md", "papers": [ { "name": "Tadano_et_al_2015.pdf", "path": "Papers_of_Codes/Phonons/5.2_Anharmonic_Thermal_Transport/ALAMODE/Tadano_et_al_2015.pdf", "doi_url": "https://scholar.google.com/scholar?q=ALAMODE+Tadano+et+al+2015" } ], "paper_placeholder": false, "slug": "ALAMODE", "idx": 411, "overview": "ALAMODE (Anharmonic Lattice Model) is a comprehensive open-source software for analyzing lattice anharmonicity and lattice thermal conductivity of solids. It extracts harmonic and anharmonic force constants from first-principles calculations and computes phonon-related properties including thermal conductivity via lattice dynamics or molecular dynamics simulations." }, { "num": "189", "name": "almaBTE", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/AlmaBTE/AlmaBTE", "note": "", "md_link_text": "almaBTE.md", "md_link_path": "Phonons/5.2_Anharmonic_Thermal_Transport/almaBTE.md", "papers": [ { "name": "10_1016_j_cpc_2017_06_023.pdf", "path": "Papers_of_Codes/Phonons/5.2_Anharmonic_Thermal_Transport/almaBTE/10_1016_j_cpc_2017_06_023.pdf", "doi_url": "https://scholar.google.com/scholar?q=almaBTE+10+1016+j+cpc+2017+06+023" } ], "paper_placeholder": false, "slug": "almaBTE", "idx": 412, "overview": "**almaBTE** is a high-performance C++ software package designed for calculating the **lattice thermal conductivity** and other phonon transport properties of materials from first principles. It solves the **Peierls-Boltzmann Transport Equation (BTE)** for phonons, moving beyond the relaxation time approximation (RTA) to capture full scattering processes, including three-phonon interactions. It is particularly adept at handling multiscale systems, from bulk crystals to thin films, superlattices, " }, { "num": "190", "name": "TDEP", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/phonon/tdep", "note": "", "md_link_text": "TDEP.md", "md_link_path": "Phonons/5.4_Temperature_Dependent/TDEP.md", "papers": [ { "name": "10_1103_PhysRevB_87_104111.pdf", "path": "Papers_of_Codes/Phonons/5.4_Temperature_Dependent/TDEP/10_1103_PhysRevB_87_104111.pdf", "doi_url": "https://scholar.google.com/scholar?q=TDEP+10+1103+PhysRevB+87+104111" }, { "name": "10_1103_PhysRevB_84_180301.pdf", "path": "Papers_of_Codes/Phonons/5.4_Temperature_Dependent/TDEP/10_1103_PhysRevB_84_180301.pdf", "doi_url": "https://scholar.google.com/scholar?q=TDEP+10+1103+PhysRevB+84+180301" }, { "name": "10_1103_PhysRevB_88_144301.pdf", "path": "Papers_of_Codes/Phonons/5.4_Temperature_Dependent/TDEP/10_1103_PhysRevB_88_144301.pdf", "doi_url": "https://scholar.google.com/scholar?q=TDEP+10+1103+PhysRevB+88+144301" } ], "paper_placeholder": false, "slug": "TDEP", "idx": 413, "overview": "TDEP (Temperature Dependent Effective Potential) is software for extracting temperature-dependent force constants and studying anharmonic lattice dynamics using ab-initio molecular dynamics. Developed by Olle Hellman (Link\u00f6ping University), TDEP uses temperature-dependent effective harmonic theory to capture anharmonic effects, making it powerful for materials with strong temperature dependence, soft phonon modes, and systems where perturbation theory fails." }, { "num": "191", "name": "EPW", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://epw.org.uk/", "note": "", "md_link_text": "EPW.md", "md_link_path": "Phonons/5.3_Electron_Phonon_Coupling/EPW.md", "papers": [ { "name": "EPW_10.1016_j.cpc.2016.07.028.pdf", "path": "Papers_of_Codes/Phonons/EPW/EPW_10.1016_j.cpc.2016.07.028.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2016.07.028" } ], "paper_placeholder": false, "slug": "EPW", "idx": 414, "overview": "EPW is a highly specialized code for calculating electron-phonon coupling and related properties from first principles using maximally localized Wannier functions. Part of the Quantum ESPRESSO distribution, EPW uses Wannier interpolation to achieve extremely efficient calculations of electron-phonon matrix elements on ultra-dense k and q-point grids, enabling accurate predictions of superconductivity, electrical transport, optical properties, and carrier mobilities." }, { "num": "192", "name": "PERTURBO", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://perturbo.org/", "note": "", "md_link_text": "PERTURBO.md", "md_link_path": "Phonons/5.3_Electron_Phonon_Coupling/PERTURBO.md", "papers": [ { "name": "Zhou_et_al_2021.pdf", "path": "Papers_of_Codes/Phonons/5.3_Electron_Phonon_Coupling/PERTURBO/Zhou_et_al_2021.pdf", "doi_url": "https://scholar.google.com/scholar?q=PERTURBO+Zhou+et+al+2021" } ], "paper_placeholder": false, "slug": "PERTURBO", "idx": 415, "overview": "PERTURBO is an open-source software for first-principles calculations of charge transport and ultrafast carrier dynamics in materials with electron-phonon interactions. Developed at Caltech, PERTURBO computes electronic transport properties, carrier relaxation, and nonequilibrium dynamics using ab-initio electron-phonon matrix elements, handling spin-orbit coupling, polar materials, and providing comprehensive tools for studying electronic transport from first principles." }, { "num": "193", "name": "Phoebe", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/AFND-PH/phoebe", "note": "", "md_link_text": "Phoebe.md", "md_link_path": "Phonons/5.3_Electron_Phonon_Coupling/Phoebe.md", "papers": [ { "name": "Bernardi_et_al_2014.pdf", "path": "Papers_of_Codes/Phonons/5.3_Electron_Phonon_Coupling/Phoebe/Bernardi_et_al_2014.pdf", "doi_url": "https://scholar.google.com/scholar?q=Phoebe+Bernardi+et+al+2014" } ], "paper_placeholder": false, "slug": "Phoebe", "idx": 416, "overview": "Phoebe is a modern, high-performance code for calculating phonon and electron thermal transport properties from first principles. Developed at MIT, Phoebe solves the Boltzmann transport equation for both phonons and electrons with electron-phonon coupling, focusing on computational efficiency and advanced transport phenomena. The code features GPU acceleration, advanced algorithms, and handles coupled electron-phonon transport in a unified framework." }, { "num": "194", "name": "PHON", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "http://www.computingformaterials.com/ (Parlinski's code)", "note": "", "md_link_text": "PHON.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/PHON.md", "papers": [ { "name": "10_1103_PhysRevLett_78_4063.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_1103_PhysRevLett_78_4063.pdf", "doi_url": "https://scholar.google.com/scholar?q=PHON+10+1103+PhysRevLett+78+4063" }, { "name": "10_7566_JPSJ_92_012001.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_7566_JPSJ_92_012001.pdf", "doi_url": "https://scholar.google.com/scholar?q=PHON+10+7566+JPSJ+92+012001" }, { "name": "10_1016_j_cpc_2009_03_010.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_1016_j_cpc_2009_03_010.pdf", "doi_url": "https://scholar.google.com/scholar?q=PHON+10+1016+j+cpc+2009+03+010" } ], "paper_placeholder": false, "slug": "PHON", "idx": 417, "overview": "PHON is a computational tool for phonon calculations developed by Krzysztof Parlinski. The code calculates phonon dispersion relations and thermodynamic properties using the direct method with harmonic approximation. PHON is particularly known for its PHONON software which has been widely used in the lattice dynamics community, especially for materials with complex crystal structures." }, { "num": "195", "name": "PHONON", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "http://wolf.ifj.edu.pl/phonon/", "note": "", "md_link_text": "PHONON.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/PHONON.md", "papers": [ { "name": "10_1103_PhysRevLett_78_4063.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHONON/10_1103_PhysRevLett_78_4063.pdf", "doi_url": "https://scholar.google.com/scholar?q=PHONON+10+1103+PhysRevLett+78+4063" } ], "paper_placeholder": false, "slug": "PHONON", "idx": 418, "overview": "PHONON is a software package for lattice dynamics calculations developed at the Institute of Nuclear Physics, Polish Academy of Sciences. The code calculates phonon dispersion relations and related properties using ab-initio force constants. PHONON is closely related to the PHON code and shares similar methodology and applications." }, { "num": "196", "name": "YPHON", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/phonon/pyphon", "note": "", "md_link_text": "YPHON.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/YPHON.md", "papers": [ { "name": "YPHON_10.1016_j.cpc.2014.06.023.pdf", "path": "Papers_of_Codes/Phonons/YPHON/YPHON_10.1016_j.cpc.2014.06.023.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2014.06.023" } ], "paper_placeholder": false, "slug": "YPHON", "idx": 419, "overview": "YPHON (also known as PyPhon) is a Python-based tool for phonon calculations, part of the phonopy ecosystem. The code provides Python interfaces and utilities for phonon-related calculations, offering a Pythonic way to work with phonon data and properties." }, { "num": "197", "name": "ATAT", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://www.brown.edu/Departments/Engineering/Labs/avdw/atat/", "note": "", "md_link_text": "ATAT.md", "md_link_path": "Phonons/5.5_Utilities_Interfaces/ATAT.md", "papers": [ { "name": "ATAT_10.1016_S0364-5916(02)80006-2.pdf", "path": "Papers_of_Codes/Phonons/ATAT/ATAT_10.1016_S0364-5916%2802%2980006-2.pdf", "doi_url": "https://doi.org/10.1016/S0364-5916(02)80006-2" } ], "paper_placeholder": false, "slug": "ATAT", "idx": 420, "overview": "ATAT (Alloy Theoretic Automated Toolkit) is a comprehensive software package for thermodynamic modeling of alloys, including phonon calculations for ordered and disordered systems. Developed by Axel van de Walle (Brown University), ATAT provides tools for cluster expansion, phase diagram prediction, and lattice dynamics in alloy systems." }, { "num": "198", "name": "FROPHO", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/atztogo/fropho", "note": "", "md_link_text": "FROPHO.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/FROPHO.md", "papers": [], "paper_placeholder": true, "slug": "FROPHO", "idx": 421, "overview": "FROPHO is a tool for frozen phonon calculations developed by Atsushi Togo (same author as phonopy). The code facilitates systematic generation and analysis of frozen phonon calculations, providing an alternative or complementary approach to finite displacement methods for extracting force constants." }, { "num": "199", "name": "hiPhive", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://hiphive.materialsmodeling.org/", "note": "", "md_link_text": "hiPhive.md", "md_link_path": "Phonons/5.2_Anharmonic_Thermal_Transport/hiPhive.md", "papers": [ { "name": "10_1002_adts_201800184.pdf", "path": "Papers_of_Codes/Phonons/5.2_Anharmonic_Thermal_Transport/hiPhive/10_1002_adts_201800184.pdf", "doi_url": "https://scholar.google.com/scholar?q=hiPhive+10+1002+adts+201800184" } ], "paper_placeholder": false, "slug": "hiPhive", "idx": 422, "overview": "hiPhive is a Python library for efficiently extracting high-order force constants from ab-initio molecular dynamics or systematic displacement calculations. Using advanced statistical methods including compressive sensing and sparse regression, hiPhive constructs force constant models for accurate prediction of phonon and thermal properties including anharmonic effects. The code integrates seamlessly with ASE and is designed for high-throughput phonon calculations." }, { "num": "200", "name": "ASE-phonons", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://wiki.fysik.dtu.dk/ase/ase/phonons.html", "note": "", "md_link_text": "ASE-phonons.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/ASE-phonons.md", "papers": [ { "name": "ASE-phonons_10.1016_j.cpc.2009.03.010.pdf", "path": "Papers_of_Codes/Phonons/ASE-phonons/ASE-phonons_10.1016_j.cpc.2009.03.010.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2009.03.010" } ], "paper_placeholder": false, "slug": "ASE-phonons", "idx": 423, "overview": "The ASE (Atomic Simulation Environment) phonons module provides basic phonon calculations using the finite displacement method. As part of the comprehensive ASE Python library, it offers simple phonon dispersion and DOS calculations suitable for quick analyses, prototyping, and educational purposes, with direct integration into ASE's broader materials modeling ecosystem." }, { "num": "201", "name": "kALDo", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/nanotheorygroup/kaldo", "note": "", "md_link_text": "kALDo.md", "md_link_path": "Phonons/5.2_Anharmonic_Thermal_Transport/kALDo.md", "papers": [], "paper_placeholder": true, "slug": "kALDo", "idx": 424, "overview": "kALDo (k-Anharmonic Lattice Dynamics) is a modern Python package for computing anharmonic phonon transport using the Boltzmann transport equation. Developed at Boston College, kALDo focuses on user-friendly interfaces, integration with the ASE/phonopy ecosystem, and efficient calculations of lattice thermal conductivity including phonon-phonon scattering." }, { "num": "202", "name": "GPU_PBTE", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/brucefan1983/GPU_PBTE", "note": "", "md_link_text": "GPU_PBTE.md", "md_link_path": "Phonons/5.2_Anharmonic_Thermal_Transport/GPU_PBTE.md", "papers": [ { "name": "10_1039_C2CP43771F.pdf", "path": "Papers_of_Codes/materials_science_papers/6_Phonons_Lattice_Dynamics_e-ph/GPU_PBTE/10_1039_C2CP43771F.pdf", "doi_url": "https://scholar.google.com/scholar?q=GPU_PBTE+10+1039+C2CP43771F" } ], "paper_placeholder": false, "slug": "GPU_PBTE", "idx": 425, "overview": "GPU_PBTE is a GPU-accelerated solver for the phonon Boltzmann transport equation developed by Zheyong Fan (Bohai University). The code uses CUDA to achieve significant speedup in solving the BTE for lattice thermal conductivity calculations. GPU_PBTE is part of the GPUQT (GPU Quantum Transport) package and is designed for high-performance phonon transport calculations on NVIDIA GPUs." }, { "num": "203", "name": "PhonTS", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "http://phon.sourceforge.net/", "note": "", "md_link_text": "PhonTS.md", "md_link_path": "Phonons/5.2_Anharmonic_Thermal_Transport/PhonTS.md", "papers": [ { "name": "10_1039_C7CP01680H.pdf", "path": "Papers_of_Codes/Phonons/5.2_Anharmonic_Thermal_Transport/PhonTS/10_1039_C7CP01680H.pdf", "doi_url": "https://scholar.google.com/scholar?q=PhonTS+10+1039+C7CP01680H" } ], "paper_placeholder": false, "slug": "PhonTS", "idx": 426, "overview": "PhonTS (Phonon Transport Simulator) is a software package for calculating lattice thermal conductivity from first principles. Developed by Aleksandr V. Chernatynskiy and colleagues, it solves the phonon Boltzmann transport equation (BTE) using input from molecular dynamics or lattice dynamics calculations. It is distributed through the Computer Physics Communications (CPC) Program Library." }, { "num": "204", "name": "SCAILD", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/ajf396/scaild", "note": "", "md_link_text": "SCAILD.md", "md_link_path": "Phonons/5.4_Temperature_Dependent/SCAILD.md", "papers": [ { "name": "10_1088_1361-648X_aaa737.pdf", "path": "Papers_of_Codes/Phonons/5.4_Temperature_Dependent/SCAILD/10_1088_1361-648X_aaa737.pdf", "doi_url": "https://scholar.google.com/scholar?q=SCAILD+10+1088+1361+648X+aaa737" }, { "name": "10_1103_PhysRevB_92_054301.pdf", "path": "Papers_of_Codes/Phonons/5.4_Temperature_Dependent/SCAILD/10_1103_PhysRevB_92_054301.pdf", "doi_url": "https://scholar.google.com/scholar?q=SCAILD+10+1103+PhysRevB+92+054301" } ], "paper_placeholder": false, "slug": "SCAILD", "idx": 427, "overview": "SCAILD (Self-Consistent Ab Initio Lattice Dynamics) is a code for self-consistent phonon calculations including anharmonic effects. The tool uses iterative approaches to capture temperature-dependent phonon renormalization and anharmonic lattice dynamics self-consistently." }, { "num": "205", "name": "QSCAILD", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/ajf396/qscaild", "note": "", "md_link_text": "QSCAILD.md", "md_link_path": "Phonons/5.4_Temperature_Dependent/QSCAILD.md", "papers": [ { "name": "QSCAILD_10.1016_j.cpc.2021.107945.pdf", "path": "Papers_of_Codes/Phonons/QSCAILD/QSCAILD_10.1016_j.cpc.2021.107945.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2021.107945" } ], "paper_placeholder": false, "slug": "QSCAILD", "idx": 428, "overview": "QSCAILD (Quantum Self-Consistent Ab Initio Lattice Dynamics) extends SCAILD to include quantum nuclear effects in self-consistent phonon calculations. The code incorporates quantum statistics and zero-point motion into the self-consistent treatment of anharmonic lattice dynamics, making it particularly important for light-element systems and low-temperature physics." }, { "num": "206", "name": "SSCHA", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/epfl-theos/sscha", "note": "", "md_link_text": "SSCHA.md", "md_link_path": "Phonons/5.4_Temperature_Dependent/SSCHA.md", "papers": [ { "name": "10_1088_1361-648X_ac066b.pdf", "path": "Papers_of_Codes/Phonons/5.4_Temperature_Dependent/SSCHA/10_1088_1361-648X_ac066b.pdf", "doi_url": "https://scholar.google.com/scholar?q=SSCHA+10+1088+1361+648X+ac066b" }, { "name": "10_1103_PhysRevB_103_104305.pdf", "path": "Papers_of_Codes/Phonons/5.4_Temperature_Dependent/SSCHA/10_1103_PhysRevB_103_104305.pdf", "doi_url": "https://scholar.google.com/scholar?q=SSCHA+10+1103+PhysRevB+103+104305" }, { "name": "10_1103_PhysRevB_96_014111.pdf", "path": "Papers_of_Codes/Phonons/5.4_Temperature_Dependent/SSCHA/10_1103_PhysRevB_96_014111.pdf", "doi_url": "https://scholar.google.com/scholar?q=SSCHA+10+1103+PhysRevB+96+014111" } ], "paper_placeholder": false, "slug": "SSCHA", "idx": 429, "overview": "SSCHA (Stochastic Self-Consistent Harmonic Approximation) is a code for computing anharmonic phonon properties including structural phase transitions, dynamical instabilities, and temperature-dependent lattice dynamics. The method uses a variational approach with quantum and thermal fluctuations, making it particularly powerful for strongly anharmonic systems, quantum crystals, and materials near structural phase transitions where standard harmonic or perturbative approaches fail." }, { "num": "207", "name": "ALM", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/atztogo/alm (part of ALAMODE)", "note": "", "md_link_text": "ALM.md", "md_link_path": "Phonons/5.2_Anharmonic_Thermal_Transport/ALM.md", "papers": [ { "name": "10_1016_j_cpc_2017_06_023.pdf", "path": "Papers_of_Codes/Phonons/5.2_Anharmonic_Thermal_Transport/ALM/10_1016_j_cpc_2017_06_023.pdf", "doi_url": "https://scholar.google.com/scholar?q=ALM+10+1016+j+cpc+2017+06+023" }, { "name": "10_1103_PhysRevB_92_054301.pdf", "path": "Papers_of_Codes/Phonons/5.2_Anharmonic_Thermal_Transport/ALM/10_1103_PhysRevB_92_054301.pdf", "doi_url": "https://scholar.google.com/scholar?q=ALM+10+1103+PhysRevB+92+054301" } ], "paper_placeholder": false, "slug": "ALM", "idx": 430, "overview": "ALM is the force constant extraction module of the ALAMODE software suite. It extracts harmonic and anharmonic interatomic force constants from first-principles displacement-force datasets using advanced fitting techniques including compressive sensing. ALM can extract 2nd, 3rd, 4th, and higher-order force constants efficiently, making it a key tool for setting up anharmonic lattice dynamics calculations." }, { "num": "208", "name": "thirdorder.py", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "**MODULE** - Part of ShengBTE package.", "note": "", "md_link_text": "thirdorder.py.md", "md_link_path": "Phonons/5.2_Anharmonic_Thermal_Transport/thirdorder.py.md", "papers": [ { "name": "10_1016_j_cpc_2014_02_015.pdf", "path": "Papers_of_Codes/Phonons/5.2_Anharmonic_Thermal_Transport/thirdorder.py/10_1016_j_cpc_2014_02_015.pdf", "doi_url": "https://scholar.google.com/scholar?q=thirdorder.py+10+1016+j+cpc+2014+02+015" } ], "paper_placeholder": false, "slug": "thirdorder.py", "idx": 431, "overview": "thirdorder.py is a Python script for generating displacement patterns and extracting third-order force constants from DFT calculations. It is distributed as part of the ShengBTE package and provides an automated workflow for creating the necessary input files for anharmonic phonon and thermal conductivity calculations. The script handles symmetry and generates minimal sets of displacements." }, { "num": "209", "name": "THERMACOND", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/Romeo-02/thermacond", "note": "", "md_link_text": "THERMACOND.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/THERMACOND.md", "papers": [], "paper_placeholder": true, "slug": "THERMACOND", "idx": 432, "overview": "" }, { "num": "210", "name": "OpenBTE", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/jesan/OpenBTE", "note": "", "md_link_text": "OpenBTE.md", "md_link_path": "Phonons/5.2_Anharmonic_Thermal_Transport/OpenBTE.md", "papers": [ { "name": "OpenBTE_10.48550_arXiv.2106.02764.pdf", "path": "Papers_of_Codes/Phonons/OpenBTE/OpenBTE_10.48550_arXiv.2106.02764.pdf", "doi_url": "https://doi.org/10.48550/arXiv.2106.02764" } ], "paper_placeholder": false, "slug": "OpenBTE", "idx": 433, "overview": "**OpenBTE** is an open-source vibrational transport solver designed to compute **lattice thermal conductivity** and heat transport maps in **multidimensional nanostructures**. Unlike bulk BTE solvers (like ShengBTE), OpenBTE solves the **space-dependent Boltzmann Transport Equation** for phonons, making it capable of modeling size effects, boundary scattering, and heat flow tailored geometries (membranes, porous materials, nanowires)." }, { "num": "213", "name": "epiq", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/ajf396/epiq", "note": "", "md_link_text": "epiq.md", "md_link_path": "Phonons/5.3_Electron_Phonon_Coupling/epiq.md", "papers": [], "paper_placeholder": true, "slug": "epiq", "idx": 434, "overview": "epiq is a Python package for electron-phonon interactions and related quantum transport calculations. The code provides tools for calculating electron-phonon coupling properties and their effects on electronic and thermal transport." }, { "num": "214", "name": "API_Phonons", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/superstar54/API_Phonons", "note": "", "md_link_text": "API_Phonons.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/API_Phonons.md", "papers": [], "paper_placeholder": true, "slug": "API_Phonons", "idx": 435, "overview": "API_Phonons is a Python API and interface for phonon calculations, providing a unified interface to work with phonon data from various sources. The tool aims to simplify phonon calculation workflows through a consistent Python API." }, { "num": "215", "name": "Phonopy-API", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/phonon/phonopy-api (or just Phonopy wrapper)", "note": "", "md_link_text": "Phonopy-API.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/Phonopy-API.md", "papers": [ { "name": "10_7566_JPSJ_92_012001.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/Phonopy-API/10_7566_JPSJ_92_012001.pdf", "doi_url": "https://scholar.google.com/scholar?q=Phonopy-API+10+7566+JPSJ+92+012001" } ], "paper_placeholder": false, "slug": "Phonopy-API", "idx": 436, "overview": "Phonopy-API refers to the Python API of Phonopy, enabling programmatic access to Phonopy's phonon calculation capabilities. The API allows users to integrate Phonopy functionality into custom Python scripts and workflows, providing full control over phonon calculations without command-line interfaces." }, { "num": "216", "name": "Pheasy", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/GroupePhysiqueTheorique/Pheasy", "note": "", "md_link_text": "Pheasy.md", "md_link_path": "Phonons/5.5_Utilities_Interfaces/Pheasy.md", "papers": [], "paper_placeholder": true, "slug": "Pheasy", "idx": 437, "overview": "Pheasy is a robust and user-friendly program for first-principles phonon physics. It accurately reconstructs the potential energy surface of crystalline solids via a Taylor expansion of arbitrarily high order. Developed to enable efficient and accurate extraction of interatomic force constants (IFCs) from force-displacement datasets, it is designed to be parameter-free and high-throughput compatible." }, { "num": "217", "name": "Simphony", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/gabrielelanaro/simphony", "note": "", "md_link_text": "Simphony.md", "md_link_path": "Phonons/5.5_Utilities_Interfaces/Simphony.md", "papers": [], "paper_placeholder": true, "slug": "Simphony", "idx": 438, "overview": "Simphony is a Python package for phonon and vibrational spectroscopy simulations. The tool provides capabilities for calculating and simulating vibrational properties, particularly focused on spectroscopic applications." }, { "num": "218", "name": "ALATDYN", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/ajf396/alatdyn", "note": "", "md_link_text": "ALATDYN.md", "md_link_path": "Phonons/5.4_Temperature_Dependent/ALATDYN.md", "papers": [], "paper_placeholder": true, "slug": "ALATDYN", "idx": 439, "overview": "ALATDYN is a code for anharmonic lattice dynamics calculations. The tool focuses on extracting and analyzing anharmonic effects in phonon systems, providing capabilities for studying temperature-dependent and nonlinear phonon properties." }, { "num": "218a", "name": "CRYSTALpytools", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/crystal-code-tools/CRYSTALpytools", "note": "Python infrastructure for CRYSTAL code with phonon support.", "md_link_text": "CRYSTALpytools.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/CRYSTALpytools.md", "papers": [ { "name": "Dovesi_et_al_2018.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/CRYSTAL/Dovesi_et_al_2018.pdf", "doi_url": "https://scholar.google.com/scholar?q=CRYSTALpytools+Dovesi+et+al+2018" } ], "paper_placeholder": false, "slug": "CRYSTALpytools", "idx": 440, "overview": "CRYSTALpytools is an open-source Python infrastructure for the CRYSTAL quantum chemistry code. It provides a user-friendly interface for pre- and post-processing of CRYSTAL calculations, including phonon calculations, thermodynamics, and visualization tools." }, { "num": "218b", "name": "pwtools", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/elcorto/pwtools", "note": "Python tools for QE phonon post-processing.", "md_link_text": "pwtools.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/pwtools.md", "papers": [], "paper_placeholder": true, "slug": "pwtools", "idx": 441, "overview": "pwtools is a Python package for pre- and post-processing of atomistic calculations, primarily targeted at Quantum ESPRESSO, CPMD, CP2K, and LAMMPS. It provides powerful parsers, data types for storing calculation results, and tools for phonon dispersion analysis." }, { "num": "218c", "name": "elphmod", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/janberges/elphmod", "note": "Python modules for electron-phonon models with phonon support.", "md_link_text": "elphmod.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/elphmod.md", "papers": [], "paper_placeholder": true, "slug": "elphmod", "idx": 442, "overview": "elphmod is a collection of Python modules to handle coupled tight-binding and mass-spring models derived from first principles. It provides interfaces with Quantum ESPRESSO, Wannier90, EPW, RESPACK, and i-PI for electron-phonon calculations." }, { "num": "218d", "name": "latticeDynamics", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/jgwillingham/latticeDynamics", "note": "Python tools for lattice dynamics with rigid ion models.", "md_link_text": "latticeDynamics.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/latticeDynamics.md", "papers": [], "paper_placeholder": true, "slug": "latticeDynamics", "idx": 443, "overview": "latticeDynamics is a Python package for lattice dynamics calculations using rigid ion and shell models. It provides tools for constructing dynamical matrices, calculating phonon dispersions, and analyzing vibrational properties of crystals." }, { "num": "218e", "name": "Phonon-Vibration-Viewer", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/Tingliangstu/Phonon-Vibration-Viewer", "note": "Phonon dispersion visualization for primitive atoms.", "md_link_text": "Phonon-Vibration-Viewer.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/Phonon-Vibration-Viewer.md", "papers": [ { "name": "10_1103_PhysRevLett_78_4063.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_1103_PhysRevLett_78_4063.pdf", "doi_url": "https://scholar.google.com/scholar?q=Phonon-Vibration-Viewer+10+1103+PhysRevLett+78+4063" }, { "name": "10_7566_JPSJ_92_012001.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_7566_JPSJ_92_012001.pdf", "doi_url": "https://scholar.google.com/scholar?q=Phonon-Vibration-Viewer+10+7566+JPSJ+92+012001" }, { "name": "10_1016_j_cpc_2009_03_010.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_1016_j_cpc_2009_03_010.pdf", "doi_url": "https://scholar.google.com/scholar?q=Phonon-Vibration-Viewer+10+1016+j+cpc+2009+03+010" } ], "paper_placeholder": false, "slug": "Phonon-Vibration-Viewer", "idx": 444, "overview": "Phonon-Vibration-Viewer is a Python tool for visualizing lattice vibration information from phonon dispersion calculations. It extracts and displays atomic displacement patterns for primitive atoms from Phonopy calculations." }, { "num": "218f", "name": "mace_phonopy", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/Mofahdi/mace_phonopy", "note": "MACE ML potential to Phonopy force constants bridge.", "md_link_text": "mace_phonopy.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/mace_phonopy.md", "papers": [], "paper_placeholder": true, "slug": "mace_phonopy", "idx": 445, "overview": "mace_phonopy is a code to generate second-order interatomic force constants (IFCs) from MACE machine learning potentials for use with Phonopy. It bridges MACE ML potentials with standard phonon calculation workflows." }, { "num": "218g", "name": "phononplotter", "category_id": "5", "category": "PHONONS", "subcategory_id": "5.1", "subcategory": "Harmonic Phonons", "confidence": "VERIFIED", "official_url": "https://github.com/warda-rahim/phononplotter", "note": "Phonon band structure and DOS plotting tool.", "md_link_text": "phononplotter.md", "md_link_path": "Phonons/5.1_Harmonic_Phonons/phononplotter.md", "papers": [ { "name": "10_1103_PhysRevLett_78_4063.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_1103_PhysRevLett_78_4063.pdf", "doi_url": "https://scholar.google.com/scholar?q=phononplotter+10+1103+PhysRevLett+78+4063" }, { "name": "10_7566_JPSJ_92_012001.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_7566_JPSJ_92_012001.pdf", "doi_url": "https://scholar.google.com/scholar?q=phononplotter+10+7566+JPSJ+92+012001" }, { "name": "10_1016_j_cpc_2009_03_010.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_1016_j_cpc_2009_03_010.pdf", "doi_url": "https://scholar.google.com/scholar?q=phononplotter+10+1016+j+cpc+2009+03+010" } ], "paper_placeholder": false, "slug": "phononplotter", "idx": 446, "overview": "phononplotter is a Python tool for plotting phonon band structures and density of states from Phonopy calculations. It provides publication-quality plots with customization options for phonon dispersion visualization." }, { "num": "219", "name": "i-PI", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://ipi-code.org/", "note": "", "md_link_text": "i-PI.md", "md_link_path": "Dynamics/6.2_Path_Integral_Quantum_Dynamics/i-PI.md", "papers": [ { "name": "10_1016_j_cpc_2013_10_027.pdf", "path": "Papers_of_Codes/Dynamics/6.2_Path_Integral_Quantum_Dynamics/i-PI/10_1016_j_cpc_2013_10_027.pdf", "doi_url": "https://scholar.google.com/scholar?q=i-PI+10+1016+j+cpc+2013+10+027" } ], "paper_placeholder": false, "slug": "i-PI", "idx": 447, "overview": "i-PI is a universal force engine interface that decouples the evolution of nuclear coordinates from the evaluation of the potential energy surface. It acts as a client-server driver for molecular dynamics, enabling advanced quantum nuclear effects (path integral MD), thermodynamic integration, and enhanced sampling techniques using any electronic structure code that supports the i-PI socket interface." }, { "num": "220", "name": "LAMMPS", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://www.lammps.org/", "note": "", "md_link_text": "LAMMPS.md", "md_link_path": "Dynamics/6.1_Classical_MD_Engines/LAMMPS.md", "papers": [ { "name": "10_1006_jcph_1995_1039.pdf", "path": "Papers_of_Codes/Dynamics/6.1_Classical_MD_Engines/LAMMPS/10_1006_jcph_1995_1039.pdf", "doi_url": "https://scholar.google.com/scholar?q=LAMMPS+10+1006+jcph+1995+1039" }, { "name": "10_1016_j_cpc_2021_108171.pdf", "path": "Papers_of_Codes/Dynamics/6.1_Classical_MD_Engines/LAMMPS/10_1016_j_cpc_2021_108171.pdf", "doi_url": "https://scholar.google.com/scholar?q=LAMMPS+10+1016+j+cpc+2021+108171" } ], "paper_placeholder": false, "slug": "LAMMPS", "idx": 448, "overview": "LAMMPS is a classical molecular dynamics code with a focus on materials modeling. It's an acronym for Large-scale Atomic/Molecular Massively Parallel Simulator. LAMMPS has potentials for solid-state materials (metals, semiconductors) and soft matter (biomolecules, polymers) and coarse-grained or mesoscopic systems. It can be used to model atoms or, more generically, as a parallel particle simulator at the atomic, meso, or continuum scale." }, { "num": "221", "name": "PLUMED", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://www.plumed.org/", "note": "", "md_link_text": "PLUMED.md", "md_link_path": "Dynamics/6.4_Enhanced_Sampling_Methods/PLUMED.md", "papers": [ { "name": "10_1016_j_cpc_2013_09_018.pdf", "path": "Papers_of_Codes/Dynamics/6.4_Enhanced_Sampling_Methods/PLUMED/10_1016_j_cpc_2013_09_018.pdf", "doi_url": "https://scholar.google.com/scholar?q=PLUMED+10+1016+j+cpc+2013+09+018" }, { "name": "10_1016_j_cpc_2009_07_007.pdf", "path": "Papers_of_Codes/Dynamics/6.4_Enhanced_Sampling_Methods/PLUMED/10_1016_j_cpc_2009_07_007.pdf", "doi_url": "https://scholar.google.com/scholar?q=PLUMED+10+1016+j+cpc+2009+07+007" } ], "paper_placeholder": false, "slug": "PLUMED", "idx": 449, "overview": "PLUMED is an open-source library for free energy calculations in molecular systems which works together with some of the most popular molecular dynamics engines. It performs enhanced sampling calculations (Metadynamics, Umbrella Sampling, etc.) and analyzes trajectories using a wide range of collective variables. PLUMED can be used as a plugin or a standalone analysis tool." }, { "num": "222", "name": "GROMACS", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://www.gromacs.org/", "note": "", "md_link_text": "GROMACS.md", "md_link_path": "Dynamics/6.1_Classical_MD_Engines/GROMACS.md", "papers": [ { "name": "10.1016_j.softx.2015.06.001.pdf", "path": "Papers_of_Codes/Dynamics/6.1_Classical_MD_Engines/GROMACS/10.1016_j.softx.2015.06.001.pdf", "doi_url": "https://doi.org/10.1016/j.softx.2015.06.001" } ], "paper_placeholder": false, "slug": "GROMACS", "idx": 450, "overview": "GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles. It is primarily designed for biochemical molecules like proteins, lipids, and nucleic acids that have a lot of complicated bonded interactions, but since GROMACS is extremely fast at calculating the nonbonded interactions (that usually dominate simulations), many groups are also using it for research on non-biological systems, e.g. poly" }, { "num": "223", "name": "AMBER", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://ambermd.org/", "note": "", "md_link_text": "AMBER.md", "md_link_path": "Dynamics/6.1_Classical_MD_Engines/AMBER.md", "papers": [ { "name": "10.1002_jcc.20290.pdf", "path": "Papers_of_Codes/Dynamics/6.1_Classical_MD_Engines/Amber/10.1002_jcc.20290.pdf", "doi_url": "https://doi.org/10.1002/jcc.20290" } ], "paper_placeholder": false, "slug": "AMBER", "idx": 451, "overview": "AMBER refers to two things: a set of molecular mechanical force fields for the simulation of biomolecules (which are in the public domain), and a package of molecular simulation programs. The software package includes AmberTools (open source) for setup and analysis, and the AMBER MD engine (pmemd) which is highly optimized for GPU acceleration." }, { "num": "224", "name": "CHARMM", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://www.charmm.org/", "note": "", "md_link_text": "CHARMM.md", "md_link_path": "Dynamics/6.1_Classical_MD_Engines/CHARMM.md", "papers": [ { "name": "10.1002_jcc.21287.pdf", "path": "Papers_of_Codes/Dynamics/6.1_Classical_MD_Engines/CHARMM/10.1002_jcc.21287.pdf", "doi_url": "https://doi.org/10.1002/jcc.21287" } ], "paper_placeholder": false, "slug": "CHARMM", "idx": 452, "overview": "CHARMM is a highly versatile and widely used molecular simulation program with broad application to many-particle systems. It has been developed for over three decades, primarily at Harvard University. It provides a vast set of tools for molecular mechanics, molecular dynamics, free energy calculations, and analysis of biomolecules, polymers, and liquids." }, { "num": "225", "name": "NAMD", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://www.ks.uiuc.edu/Research/namd/", "note": "", "md_link_text": "NAMD.md", "md_link_path": "Dynamics/6.1_Classical_MD_Engines/NAMD.md", "papers": [ { "name": "10.1063_5.0014475.pdf", "path": "Papers_of_Codes/Dynamics/6.1_Classical_MD_Engines/NAMD/10.1063_5.0014475.pdf", "doi_url": "https://doi.org/10.1063/5.0014475" } ], "paper_placeholder": false, "slug": "NAMD", "idx": 453, "overview": "NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. Developed by the Theoretical and Computational Biophysics Group (TCBG) at UIUC, it is renowned for its scalability on massive supercomputers and its ease of use. NAMD is file-compatible with AMBER, CHARMM, and X-PLOR." }, { "num": "226", "name": "DL_POLY", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://www.scd.stfc.ac.uk/Pages/DL_POLY.aspx", "note": "", "md_link_text": "DL_POLY.md", "md_link_path": "Dynamics/6.1_Classical_MD_Engines/DL_POLY.md", "papers": [ { "name": "10.1039_B517931A.pdf", "path": "Papers_of_Codes/Dynamics/6.1_Classical_MD_Engines/DL_POLY/10.1039_B517931A.pdf", "doi_url": "https://doi.org/10.1039/B517931A" } ], "paper_placeholder": false, "slug": "DL_POLY", "idx": 454, "overview": "DL_POLY is a general-purpose classical molecular dynamics simulation package developed at Daresbury Laboratory. It is designed to run on a wide range of computers, from single processor workstations to massively parallel supercomputers. DL_POLY handles a very wide variety of molecular systems including macromolecules, polymers, ionic systems, solutions, and surfaces." }, { "num": "227", "name": "N2P2", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://github.com/CompPhysVienna/n2p2", "note": "", "md_link_text": "N2P2.md", "md_link_path": "Dynamics/6.3_Machine_Learning_Potentials/N2P2.md", "papers": [ { "name": "N2P2_10.1021_acs.jctc.8b00770.pdf", "path": "Papers_of_Codes/Dynamics/N2P2/N2P2_10.1021_acs.jctc.8b00770.pdf", "doi_url": "https://doi.org/10.1021/acs.jctc.8b00770" }, { "name": "n2p2_10.1021_acs.jctc.8b00770.pdf", "path": "Papers_of_Codes/Dynamics/N2P2/n2p2_10.1021_acs.jctc.8b00770.pdf", "doi_url": "https://doi.org/10.1021/acs.jctc.8b00770" } ], "paper_placeholder": false, "slug": "N2P2", "idx": 455, "overview": "N2P2 (Neural Network Potential Package) is a software package for training and using high-dimensional neural network potentials (HDNNP) for atomistic simulations. Developed at the University of Vienna, it implements the Behler-Parrinello symmetry functions to describe atomic environments and train neural networks to reproduce first-principles potential energy surfaces." }, { "num": "228", "name": "DeepMD-kit", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://github.com/deepmodeling/deepmd-kit", "note": "", "md_link_text": "DeepMD-kit.md", "md_link_path": "Dynamics/6.3_Machine_Learning_Potentials/DeepMD-kit.md", "papers": [ { "name": "DeepMD-kit_10.1016_j.cpc.2018.03.016.pdf", "path": "Papers_of_Codes/Dynamics/DeepMD-kit/DeepMD-kit_10.1016_j.cpc.2018.03.016.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2018.03.016" } ], "paper_placeholder": false, "slug": "DeepMD-kit", "idx": 456, "overview": "DeepMD-kit is a deep learning package for many-body potential energy representation and molecular dynamics. It allows users to train a deep neural network potential from ab initio data (DFT) and then use it to perform molecular dynamics simulations with ab initio accuracy but at a cost comparable to classical empirical potentials. It is a core component of the DeepModeling ecosystem." }, { "num": "229", "name": "OpenMD", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://openmd.org/", "note": "", "md_link_text": "OpenMD.md", "md_link_path": "Dynamics/6.1_Classical_MD_Engines/OpenMD.md", "papers": [], "paper_placeholder": true, "slug": "OpenMD", "idx": 457, "overview": "OpenMD is an open source molecular dynamics engine written in C++ that is designed to simulate liquids, proteins, nanoparticles, interfaces, and other complex systems. It focuses on versatility and ease of use, with a particular emphasis on handling non-standard potentials and rigid body dynamics." }, { "num": "230", "name": "IMD", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://imd.mpibpc.mpg.de/", "note": "", "md_link_text": "IMD.md", "md_link_path": "Dynamics/6.1_Classical_MD_Engines/IMD.md", "papers": [ { "name": "IMD_10.1142_S0129183197000990.pdf", "path": "Papers_of_Codes/Dynamics/IMD/IMD_10.1142_S0129183197000990.pdf", "doi_url": "https://doi.org/10.1142/S0129183197000990" } ], "paper_placeholder": false, "slug": "IMD", "idx": 458, "overview": "IMD (ITAP Molecular Dynamics) is a software package for classical molecular dynamics simulations developed at the Institute for Theoretical and Applied Physics (ITAP) of the University of Stuttgart. It is designed for massive parallelism and simulations of very large systems, with a focus on solid state physics, shock waves, and fracture mechanics." }, { "num": "231", "name": "NEB", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "**MODULE** - Implemented in VASP, ASE, etc.", "note": "", "md_link_text": "NEB.md", "md_link_path": "Dynamics/6.4_Enhanced_Sampling_Methods/NEB.md", "papers": [ { "name": "10.1063_1.1323224.pdf", "path": "Papers_of_Codes/Dynamics/6.4_Enhanced_Sampling_Methods/NEB/10.1063_1.1323224.pdf", "doi_url": "https://doi.org/10.1063/1.1323224" } ], "paper_placeholder": false, "slug": "NEB", "idx": 459, "overview": "Nudged Elastic Band (NEB) is a method for finding the minimum energy path (MEP) between two stable states of a system, typically used to determine transition states and activation barriers for chemical reactions, diffusion processes, and phase transitions. It is not a single software code but a method implemented in virtually all major electronic structure and molecular dynamics packages (VASP, ASE, LAMMPS, DFTB+, etc.)." }, { "num": "232", "name": "String methods", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "**MODULE** - Implemented in VASP, ASE, etc.", "note": "", "md_link_text": "String-methods.md", "md_link_path": "Dynamics/6.4_Enhanced_Sampling_Methods/String-methods.md", "papers": [ { "name": "10_1103_PhysRevB_66_052301.pdf", "path": "Papers_of_Codes/materials_science_papers/7_Transition_States_Rare_Events/String_Method/10_1103_PhysRevB_66_052301.pdf", "doi_url": "https://scholar.google.com/scholar?q=String+methods+10+1103+PhysRevB+66+052301" } ], "paper_placeholder": false, "slug": "String-methods", "idx": 460, "overview": "String methods (including the Simplified String Method and Finite Temperature String Method) are a class of chain-of-states methods used to find the minimum energy path (MEP) or transition pathways in complex energy landscapes. Similar to NEB, they evolve a string of images connecting two minima, but with different parametrization and evolution equations, often offering better stability or different convergence properties." }, { "num": "233", "name": "Metadynamics", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "**MODULE** - Implemented in PLUMED, ASE, CP2K.", "note": "", "md_link_text": "Metadynamics.md", "md_link_path": "Dynamics/6.4_Enhanced_Sampling_Methods/Metadynamics.md", "papers": [ { "name": "Metadynamics_10.1073_pnas.202427399.pdf", "path": "Papers_of_Codes/Dynamics/Metadynamics/Metadynamics_10.1073_pnas.202427399.pdf", "doi_url": "https://doi.org/10.1073/pnas.202427399" } ], "paper_placeholder": false, "slug": "Metadynamics", "idx": 461, "overview": "Metadynamics is an enhanced sampling method used to reconstruct free energy surfaces and accelerate rare events in molecular dynamics simulations. It works by adding a history-dependent bias potential (usually Gaussian hills) to selected collective variables (CVs), encouraging the system to explore new regions of phase space." }, { "num": "234", "name": "libAtoms/Quippy", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://github.com/libatoms/libatoms", "note": "", "md_link_text": "libAtoms-Quippy.md", "md_link_path": "Dynamics/6.3_Machine_Learning_Potentials/libAtoms-Quippy.md", "papers": [ { "name": "libAtoms_Quippy_10.1103_PhysRevLett.104.136403.pdf", "path": "Papers_of_Codes/Dynamics/libAtoms_Quippy/libAtoms_Quippy_10.1103_PhysRevLett.104.136403.pdf", "doi_url": "https://doi.org/10.1103/PhysRevLett.104.136403" } ], "paper_placeholder": false, "slug": "libAtoms-Quippy", "idx": 462, "overview": "libAtoms/Quippy is a software package for molecular dynamics and atomistic simulations, primarily known for its implementation of the Gaussian Approximation Potential (GAP) machine learning interatomic potential. The package consists of the QUIP core (written in Fortran) and Quippy (Python bindings), providing a powerful and flexible environment for running simulations with advanced potentials." }, { "num": "235", "name": "MDI drivers", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://molssi-mdi.github.io/", "note": "", "md_link_text": "MDI-MolSSI.md", "md_link_path": "Dynamics/6.7_Interoperability_Drivers/MDI-MolSSI.md", "papers": [ { "name": "MDI_drivers_10.1016_j.cpc.2020.107688.pdf", "path": "Papers_of_Codes/Dynamics/MDI_drivers/MDI_drivers_10.1016_j.cpc.2020.107688.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2020.107688" } ], "paper_placeholder": false, "slug": "MDI-drivers", "idx": 463, "overview": "The MolSSI Driver Interface (MDI) is a standardized API that allows different computational chemistry codes to communicate and exchange data during runtime. It enables interoperability between codes (e.g., a quantum chemistry code and a molecular dynamics driver) without requiring them to be linked into a single executable. MDI drivers facilitate complex workflows like QM/MM, advanced sampling, and machine learning integration." }, { "num": "236d", "name": "RAPTOR", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://github.com/uchicago-voth/raptor", "note": "Multi-scale reactive MD for proton transport (J. Phys. Chem. B 2024)", "md_link_text": "RAPTOR.md", "md_link_path": "Dynamics/6.1_Classical_MD_Engines/RAPTOR.md", "papers": [], "paper_placeholder": true, "slug": "RAPTOR", "idx": 464, "overview": "" }, { "num": "400", "name": "HTST", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://theory.cm.utexas.edu/vtsttools/", "note": "Harmonic Transition State Theory tools from Henkelman group.", "md_link_text": "HTST.md", "md_link_path": "Dynamics/6.4_Enhanced_Sampling/HTST.md", "papers": [ { "name": "10.1063_1.1415500.pdf", "path": "Papers_of_Codes/Dynamics/6.4_Enhanced_Sampling/HTST/10.1063_1.1415500.pdf", "doi_url": "https://doi.org/10.1063/1.1415500" } ], "paper_placeholder": false, "slug": "HTST", "idx": 465, "overview": "" }, { "num": "401", "name": "String_Method", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://theory.cm.utexas.edu/vtsttools/neb.html", "note": "String method for finding minimum energy pathways.", "md_link_text": "String_Method.md", "md_link_path": "Dynamics/6.4_Enhanced_Sampling/String_Method.md", "papers": [ { "name": "10_1103_PhysRevB_66_052301.pdf", "path": "Papers_of_Codes/Dynamics/6.4_Enhanced_Sampling/String_Method/10_1103_PhysRevB_66_052301.pdf", "doi_url": "https://scholar.google.com/scholar?q=String_Method+10+1103+PhysRevB+66+052301" } ], "paper_placeholder": false, "slug": "String_Method", "idx": 466, "overview": "" }, { "num": "402", "name": "molecularGSM", "category_id": "6", "category": "DYNAMICS", "subcategory_id": null, "subcategory": null, "confidence": "VERIFIED", "official_url": "https://github.com/ZimmermanGroup/molecularGSM", "note": "Growing String Method for reaction pathways and transition states.", "md_link_text": "molecularGSM.md", "md_link_path": "Dynamics/6.4_Enhanced_Sampling/molecularGSM.md", "papers": [ { "name": "10_1021_ct400319w.pdf", "path": "Papers_of_Codes/Dynamics/6.4_Enhanced_Sampling/molecularGSM/10_1021_ct400319w.pdf", "doi_url": "https://scholar.google.com/scholar?q=molecularGSM+10+1021+ct400319w" }, { "name": "10_1002_jcc_23271.pdf", "path": "Papers_of_Codes/Dynamics/6.4_Enhanced_Sampling/molecularGSM/10_1002_jcc_23271.pdf", "doi_url": "https://scholar.google.com/scholar?q=molecularGSM+10+1002+jcc+23271" }, { "name": "10_1002_jcc_23833.pdf", "path": "Papers_of_Codes/Dynamics/6.4_Enhanced_Sampling/molecularGSM/10_1002_jcc_23833.pdf", "doi_url": "https://scholar.google.com/scholar?q=molecularGSM+10+1002+jcc+23833" } ], "paper_placeholder": false, "slug": "molecularGSM", "idx": 467, "overview": "" }, { "num": "236", "name": "USPEX", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "CONFIRMED", "official_url": "https://uspex-team.org/", "note": "", "md_link_text": "USPEX.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/USPEX.md", "papers": [ { "name": "Oganov_Glass_2006.pdf", "path": "Papers_of_Codes/StructurePrediction/7.1_Global_Optimization/USPEX/Oganov_Glass_2006.pdf", "doi_url": "https://scholar.google.com/scholar?q=USPEX+Oganov+Glass+2006" } ], "paper_placeholder": false, "slug": "USPEX", "idx": 468, "overview": "USPEX (Universal Structure Predictor: Evolutionary Xtallography) is a method and code for crystal structure prediction using evolutionary algorithms. Developed by Artem Oganov and collaborators, it is the leading tool for predicting stable crystal structures, interfaces, surfaces, and nanoparticles from scratch, requiring only chemical composition. It has led to numerous experimental discoveries of new materials." }, { "num": "237", "name": "XtalOpt", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "https://xtalopt.github.io/", "note": "", "md_link_text": "XtalOpt.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/XtalOpt.md", "papers": [ { "name": "Lonie_Zurek_2011.pdf", "path": "Papers_of_Codes/StructurePrediction/7.1_Global_Optimization/XtalOpt/Lonie_Zurek_2011.pdf", "doi_url": "https://scholar.google.com/scholar?q=XtalOpt+Lonie+Zurek+2011" } ], "paper_placeholder": false, "slug": "XtalOpt", "idx": 469, "overview": "XtalOpt is an open-source evolutionary algorithm for crystal structure prediction. It is implemented as an extension to the Avogadro molecular editor, providing a graphical user interface for setting up and monitoring structure prediction runs. XtalOpt searches for stable crystal structures by optimizing randomly generated structures and evolving them through genetic operations like crossover and mutation." }, { "num": "238", "name": "CALYPSO", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "http://www.calypso.cn/", "note": "", "md_link_text": "CALYPSO.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/CALYPSO.md", "papers": [ { "name": "Wang_et_al_2012.pdf", "path": "Papers_of_Codes/StructurePrediction/7.1_Global_Optimization/CALYPSO/Wang_et_al_2012.pdf", "doi_url": "https://scholar.google.com/scholar?q=CALYPSO+Wang+et+al+2012" } ], "paper_placeholder": false, "slug": "CALYPSO", "idx": 470, "overview": "CALYPSO is a software package for structure prediction using the Particle Swarm Optimization (PSO) algorithm. It can predict the stable structure of materials given only chemical composition and external conditions (pressure). CALYPSO is widely used for predicting crystal structures, 2D layers, clusters, and surfaces, and has been successful in predicting many high-pressure phases." }, { "num": "239", "name": "AIRSS", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "https://airss-docs.github.io/", "note": "", "md_link_text": "AIRSS.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/AIRSS.md", "papers": [ { "name": "10_1088_0953-8984_23_5_053201.pdf", "path": "Papers_of_Codes/StructurePrediction/7.1_Global_Optimization/AIRSS/10_1088_0953-8984_23_5_053201.pdf", "doi_url": "https://scholar.google.com/scholar?q=AIRSS+10+1088+0953+8984+23+5+053201" } ], "paper_placeholder": false, "slug": "AIRSS", "idx": 471, "overview": "AIRSS is a simple yet powerful method and software package for predicting crystal structures. The core idea is to generate random structures (sensibly constrained by density, symmetry, and distances) and relax them using ab-initio forces. Developed by Chris Pickard and collaborators, AIRSS is robust, easy to parallelize, and effective for a wide range of materials, especially under high pressure." }, { "num": "240", "name": "GASP", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "https://github.com/choi-bohyun/GASP", "note": "", "md_link_text": "GASP.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/GASP.md", "papers": [ { "name": "10_1103_PhysRevB_87_184114.pdf", "path": "Papers_of_Codes/StructurePrediction/7.1_Global_Optimization/GASP/10_1103_PhysRevB_87_184114.pdf", "doi_url": "https://scholar.google.com/scholar?q=GASP+10+1103+PhysRevB+87+184114" }, { "name": "10_1007_128_2013_489.pdf", "path": "Papers_of_Codes/StructurePrediction/7.1_Global_Optimization/GASP/10_1007_128_2013_489.pdf", "doi_url": "https://scholar.google.com/scholar?q=GASP+10+1007+128+2013+489" }, { "name": "10_1038_s41929-018-0142-1.pdf", "path": "Papers_of_Codes/StructurePrediction/7.1_Global_Optimization/GASP/10_1038_s41929-018-0142-1.pdf", "doi_url": "https://scholar.google.com/scholar?q=GASP+10+1038+s41929+018+0142+1" } ], "paper_placeholder": false, "slug": "GASP", "idx": 472, "overview": "GASP (Genetic Algorithm for Structure and Phase Prediction) is a Python-based evolutionary algorithm package developed by the Hennig Group (Cornell/University of Florida). It is designed to predict stable crystal structures and phase diagrams by interfacing with ab initio (VASP) or classical (LAMMPS, GULP) energy calculators." }, { "num": "241", "name": "MAISE", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "https://github.com/tamercan/MAISE", "note": "", "md_link_text": "MAISE.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/MAISE.md", "papers": [ { "name": "10_1016_j_cpc_2020_107679.pdf", "path": "Papers_of_Codes/StructurePrediction/7.1_Global_Optimization/MAISE/10_1016_j_cpc_2020_107679.pdf", "doi_url": "https://scholar.google.com/scholar?q=MAISE+10+1016+j+cpc+2020+107679" } ], "paper_placeholder": false, "slug": "MAISE", "idx": 473, "overview": "MAISE is a package for evolutionary structure prediction that emphasizes the use of neural network potentials to accelerate the search. By training interatomic potentials on-the-fly during the evolutionary search, MAISE reduces the number of expensive ab-initio calculations required to find the global minimum." }, { "num": "242", "name": "EVO", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED (paper only, no public code repository)", "official_url": "https://doi.org/10.1016/j.cpc.2013.02.007", "note": "Evolutionary algorithm for CSP; code distributed on request only", "md_link_text": "EVO.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/EVO.md", "papers": [ { "name": "10_1016_j_cpc_2013_01_005.pdf", "path": "Papers_of_Codes/StructurePrediction/7.1_Global_Optimization/EVO/10_1016_j_cpc_2013_01_005.pdf", "doi_url": "https://scholar.google.com/scholar?q=EVO+10+1016+j+cpc+2013+01+005" } ], "paper_placeholder": false, "slug": "EVO", "idx": 474, "overview": "**Status**: \u26a0\ufe0f UNCERTAIN / GENERIC" }, { "num": "243", "name": "FLAME", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "https://github.com/zhang-kai/FLAME", "note": "", "md_link_text": "FLAME.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/FLAME.md", "papers": [ { "name": "10_1063_1_3512900.pdf", "path": "Papers_of_Codes/StructurePrediction/7.1_Global_Optimization/FLAME/10_1063_1_3512900.pdf", "doi_url": "https://scholar.google.com/scholar?q=FLAME+10+1063+1+3512900" }, { "name": "10_1103_PhysRevB_92_045131.pdf", "path": "Papers_of_Codes/StructurePrediction/7.1_Global_Optimization/FLAME/10_1103_PhysRevB_92_045131.pdf", "doi_url": "https://scholar.google.com/scholar?q=FLAME+10+1103+PhysRevB+92+045131" } ], "paper_placeholder": false, "slug": "FLAME", "idx": 475, "overview": "FLAME (Fast Library for Atomistic Modeling Environments) is a software package designed for performing a wide range of atomistic simulations to explore the potential energy surfaces (PES) of complex condensed matter systems. While not exclusively a \"structure predictor\" in the evolutionary sense like USPEX, it includes powerful optimizers (minima hopping, saddle point searches) used for structural search and stability analysis." }, { "num": "243a", "name": "CrySPY", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "https://github.com/Tomoki-YAMASHITA/CrySPY", "note": "", "md_link_text": "CrySPY.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/CrySPY.md", "papers": [ { "name": "CrySPY_10.1080_27660400.2021.1943171.pdf", "path": "Papers_of_Codes/StructurePrediction/CrySPY/CrySPY_10.1080_27660400.2021.1943171.pdf", "doi_url": "https://doi.org/10.1080/27660400.2021.1943171" } ], "paper_placeholder": false, "slug": "CrySPY", "idx": 476, "overview": "CrySPY (pronounced \"crispy\") is a crystal structure prediction tool written in Python. It supports multiple search algorithms including random search (RS), Bayesian optimization (BO), Look Ahead based on Quadratic Approximation (LAQA), and evolutionary algorithms (EA)." }, { "num": "243b", "name": "GAtor", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "https://arxiv.org/abs/1802.08602", "note": "", "md_link_text": "GAtor.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/GAtor.md", "papers": [ { "name": "GAtor_10.1021_acs.jctc.7b01152.pdf", "path": "Papers_of_Codes/StructurePrediction/GAtor/GAtor_10.1021_acs.jctc.7b01152.pdf", "doi_url": "https://doi.org/10.1021/acs.jctc.7b01152" }, { "name": "Gator_10.1002_wcms.1528.pdf", "path": "Papers_of_Codes/StructurePrediction/GAtor/Gator_10.1002_wcms.1528.pdf", "doi_url": "https://doi.org/10.1002/wcms.1528" } ], "paper_placeholder": false, "slug": "GAtor", "idx": 477, "overview": "GAtor is a massively parallel, first-principles genetic algorithm (GA) for molecular crystal structure prediction. Written in Python, it interfaces with the FHI-aims code for local optimizations and energy evaluations using dispersion-inclusive DFT." }, { "num": "243c", "name": "Genarris", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "https://github.com/timcrose/Genarris", "note": "", "md_link_text": "Genarris.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/Genarris.md", "papers": [ { "name": "Genarris_10.1016_j.cpc.2020.107170.pdf", "path": "Papers_of_Codes/StructurePrediction/Genarris/Genarris_10.1016_j.cpc.2020.107170.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2020.107170" } ], "paper_placeholder": false, "slug": "Genarris", "idx": 478, "overview": "Genarris is an open-source Python package for generating random molecular crystal structures with physical constraints. It serves as a structure generator for seeding crystal structure prediction algorithms and training machine learning models." }, { "num": "243d", "name": "PyChemia", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "https://github.com/MaterialsDiscovery/PyChemia", "note": "", "md_link_text": "PyChemia.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/PyChemia.md", "papers": [], "paper_placeholder": true, "slug": "PyChemia", "idx": 479, "overview": "PyChemia is a Python framework for materials structural search, including global optimization methods like minima hopping and soft-computing techniques. It provides tools for structure manipulation, population-based searches, and interfaces to multiple DFT codes." }, { "num": "243e", "name": "AGOX", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "https://github.com/kimrojas/agox", "note": "", "md_link_text": "AGOX.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/AGOX.md", "papers": [], "paper_placeholder": true, "slug": "AGOX", "idx": 480, "overview": "AGOX (Atomistic Global Optimization X) is a Python package for global optimization of atomistic structures. It interfaces with ASE and supports any ASE-compatible calculator, making it highly flexible for various optimization tasks." }, { "num": "243f", "name": "ParetoCSP", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "https://github.com/sadmanomee/ParetoCSP", "note": "", "md_link_text": "ParetoCSP.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/ParetoCSP.md", "papers": [], "paper_placeholder": true, "slug": "ParetoCSP", "idx": 481, "overview": "ParetoCSP is a crystal structure prediction algorithm that combines a multi-objective genetic algorithm (MOGA) with neural network interatomic potentials (M3GNet) to find energetically optimal crystal structures." }, { "num": "243g", "name": "StructOpt", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "https://github.com/uw-cmg/StructOpt_modular", "note": "", "md_link_text": "StructOpt.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/StructOpt.md", "papers": [ { "name": "StructOpt_10.1016_j.commatsci.2018.12.052.pdf", "path": "Papers_of_Codes/StructurePrediction/StructOpt/StructOpt_10.1016_j.commatsci.2018.12.052.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2018.12.052" } ], "paper_placeholder": false, "slug": "StructOpt", "idx": 482, "overview": "StructOpt is a modular structure optimization suite designed for materials with complicated structures. It identifies atomic structures that are energetically stable and consistent with experimental data by combining multiple fitness criteria." }, { "num": "243h", "name": "MGAC", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "https://github.com/MGAC-group/MGAC2", "note": "", "md_link_text": "MGAC.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/MGAC.md", "papers": [], "paper_placeholder": true, "slug": "MGAC", "idx": 483, "overview": "MGAC (Modified Genetic Algorithm for Crystals) is a genetic algorithm package for molecular crystal structure prediction. MGAC2 is the updated version with improved algorithms." }, { "num": "243i", "name": "COPEX", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "npj Comput. Mater. 7, 223 (2021)", "note": "Co-evolutionary crystal structure prediction for complex multicomponent systems", "md_link_text": "COPEX.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/COPEX.md", "papers": [ { "name": "10_1038_s41524-021-00668-5.pdf", "path": "Papers_of_Codes/StructurePrediction/7.1_Global_Optimization/COPEX/10_1038_s41524-021-00668-5.pdf", "doi_url": "https://scholar.google.com/scholar?q=COPEX+10+1038+s41524+021+00668+5" } ], "paper_placeholder": false, "slug": "COPEX", "idx": 484, "overview": "" }, { "num": "384", "name": "BOSS", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.1", "subcategory": "Global Optimization & Evolutionary Algorithms", "confidence": "VERIFIED", "official_url": "https://github.com/mattias-ek/BOSS", "note": "Bayesian Optimization Structure Search for global optimization.", "md_link_text": "BOSS.md", "md_link_path": "StructurePrediction/7.1_Global_Optimization/BOSS.md", "papers": [ { "name": "10.1021_jp970984n.pdf", "path": "Papers_of_Codes/StructurePrediction/7.1_Global_Optimization/BOSS/10.1021_jp970984n.pdf", "doi_url": "https://doi.org/10.1021/jp970984n" } ], "paper_placeholder": false, "slug": "BOSS", "idx": 485, "overview": "" }, { "num": "244", "name": "Basin hopping", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.2", "subcategory": "Basin Hopping & Local Optimization", "confidence": "VERIFIED", "official_url": "**ALGORITHM** - Implemented in ASE, OpenBabel", "note": "", "md_link_text": "Basin-hopping.md", "md_link_path": "StructurePrediction/7.2_Basin_Hopping/Basin-hopping.md", "papers": [ { "name": "Basin_hopping_10.1021_jp970984n.pdf", "path": "Papers_of_Codes/StructurePrediction/Basin_hopping/Basin_hopping_10.1021_jp970984n.pdf", "doi_url": "https://doi.org/10.1021/jp970984n" } ], "paper_placeholder": false, "slug": "Basin-hopping", "idx": 486, "overview": "Basin hopping is a global optimization algorithm used to find the global minimum of a potential energy surface. It transforms the energy landscape into a set of basins of attraction and samples them using Monte Carlo moves followed by local minimization. It is highly effective for cluster structure prediction and finding stable configurations of molecules and defects." }, { "num": "244a", "name": "TGMin", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.2", "subcategory": "Basin Hopping & Local Optimization", "confidence": "VERIFIED", "official_url": "Nano Res. 10, 3407 (2017)", "note": "", "md_link_text": "TGMin.md", "md_link_path": "StructurePrediction/7.2_Basin_Hopping/TGMin.md", "papers": [ { "name": "TGMin_10.1002_jcc.25649.pdf", "path": "Papers_of_Codes/StructurePrediction/TGMin/TGMin_10.1002_jcc.25649.pdf", "doi_url": "https://doi.org/10.1002/jcc.25649" } ], "paper_placeholder": false, "slug": "TGMin", "idx": 487, "overview": "TGMin (Tsinghua Global Minimum) is an efficient global minimum search program for atomic clusters and surfaces. TGMin-2 is the updated version with improved algorithms and broader applicability." }, { "num": "249", "name": "GMIN", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.2", "subcategory": "Basin Hopping & Local Optimization", "confidence": "VERIFIED", "official_url": "https://www-wales.ch.cam.ac.uk/GMIN/", "note": "", "md_link_text": "GMIN.md", "md_link_path": "StructurePrediction/7.2_Basin_Hopping/GMIN.md", "papers": [ { "name": "GMIN_10.1039_C3CP44332A.pdf", "path": "Papers_of_Codes/StructurePrediction/GMIN/GMIN_10.1039_C3CP44332A.pdf", "doi_url": "https://doi.org/10.1039/C3CP44332A" } ], "paper_placeholder": false, "slug": "GMIN", "idx": 488, "overview": "GMIN is a program for finding global minima of potential energy surfaces, developed by the Wales Group at the University of Cambridge. It implements the basin-hopping algorithm (and variants) to locate the lowest energy structures of clusters and molecules. It is a reference implementation for basin-hopping methods." }, { "num": "251", "name": "ASE-BasinHopping", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.2", "subcategory": "Basin Hopping & Local Optimization", "confidence": "VERIFIED", "official_url": "https://wiki.fysik.dtu.dk/ase/ase/optimize.html", "note": "", "md_link_text": "ASE-BasinHopping.md", "md_link_path": "StructurePrediction/7.2_Basin_Hopping/ASE-BasinHopping.md", "papers": [ { "name": "ASE-BasinHopping_10.1021_jp970984n.pdf", "path": "Papers_of_Codes/StructurePrediction/ASE-BasinHopping/ASE-BasinHopping_10.1021_jp970984n.pdf", "doi_url": "https://doi.org/10.1021/jp970984n" } ], "paper_placeholder": false, "slug": "ASE-BasinHopping", "idx": 489, "overview": "ASE-BasinHopping is the implementation of the basin-hopping global optimization algorithm within the Atomic Simulation Environment. It automates the process of finding the global minimum structure by combining Monte Carlo sampling of local minima with local relaxation steps." }, { "num": "245", "name": "HTOCSP", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.3", "subcategory": "Crystal Structure Generation", "confidence": "VERIFIED", "official_url": "https://github.com/MaterSim/HTOCSP", "note": "", "md_link_text": "HTOCSP.md", "md_link_path": "StructurePrediction/7.3_Crystal_Generation/HTOCSP.md", "papers": [ { "name": "10.1038_npjcompumats.2016.28.pdf", "path": "Papers_of_Codes/StructurePrediction/7.3_Crystal_Generation/HTOCSP/10.1038_npjcompumats.2016.28.pdf", "doi_url": "https://doi.org/10.1038/npjcompumats.2016.28" } ], "paper_placeholder": false, "slug": "HTOCSP", "idx": 490, "overview": "HTOCSP is a Python-based framework specifically designed for the automated, high-throughput prediction of organic crystal structures. It integrates various open-source tools to generate, optimize, and rank crystal structures of organic molecules, addressing the challenge of polymorphism in pharmaceutical and organic materials." }, { "num": "246", "name": "PyXtal", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.3", "subcategory": "Crystal Structure Generation", "confidence": "VERIFIED", "official_url": "https://github.com/qzhu2017/PyXtal", "note": "", "md_link_text": "PyXtal.md", "md_link_path": "StructurePrediction/7.3_Crystal_Generation/PyXtal.md", "papers": [ { "name": "10.1016_j.cpc.2020.107810.pdf", "path": "Papers_of_Codes/StructurePrediction/7.3_Crystal_Generation/PyXtal/10.1016_j.cpc.2020.107810.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2020.107810" } ], "paper_placeholder": false, "slug": "PyXtal", "idx": 491, "overview": "PyXtal is a Python library for the generation of crystal structures with specific symmetry constraints. It allows for the random generation of atomic crystal structures, molecular crystals, and 2D/1D/0D systems based on space group symmetry. PyXtal is a core component for structure prediction workflows and materials generation." }, { "num": "247", "name": "PXRDGen", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.3", "subcategory": "Crystal Structure Generation", "confidence": "VERIFIED", "official_url": "https://github.com/TamVNX/PXRDGen", "note": "", "md_link_text": "PXRDGen.md", "md_link_path": "StructurePrediction/7.3_Crystal_Generation/PXRDGen.md", "papers": [], "paper_placeholder": true, "slug": "PXRDGen", "idx": 492, "overview": "PXRDGen is an AI-driven system designed for the automatic determination of crystal structures directly from Powder X-Ray Diffraction (PXRD) data. Unlike traditional structure prediction which starts from composition, PXRDGen conditions the generation on experimental diffraction patterns, significantly narrowing the search space and solving structures that are difficult for traditional Rietveld refinement." }, { "num": "248", "name": "OpenCSP", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.3", "subcategory": "Crystal Structure Generation", "confidence": "VERIFIED", "official_url": "https://github.com/ajf396/OpenCSP", "note": "", "md_link_text": "OpenCSP.md", "md_link_path": "StructurePrediction/7.3_Crystal_Generation/OpenCSP.md", "papers": [], "paper_placeholder": true, "slug": "OpenCSP", "idx": 493, "overview": "OpenCSP is a recently proposed deep learning framework for crystal structure prediction, particularly emphasizing high-pressure phases. It utilizes large-scale pre-trained atomistic models (foundation models) to predict structures without the heavy computational cost of traditional DFT-based evolutionary searches." }, { "num": "250", "name": "ASE-GA", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.3", "subcategory": "Crystal Structure Generation", "confidence": "VERIFIED", "official_url": "https://wiki.fysik.dtu.dk/ase/ase/ga.html", "note": "", "md_link_text": "ASE-GA.md", "md_link_path": "StructurePrediction/7.3_Crystal_Generation/ASE-GA.md", "papers": [ { "name": "ASE-GA_10.1063_1.4886337.pdf", "path": "Papers_of_Codes/StructurePrediction/ASE-GA/ASE-GA_10.1063_1.4886337.pdf", "doi_url": "https://doi.org/10.1063/1.4886337" } ], "paper_placeholder": false, "slug": "ASE-GA", "idx": 494, "overview": "ASE-GA is the genetic algorithm module within the Atomic Simulation Environment (ASE). It provides a flexible framework for performing global optimization of atomic structures, including clusters, crystals, and surfaces. Being part of ASE, it allows users to combine GA search strategies with any calculator (DFT or classical) supported by ASE." }, { "num": "252", "name": "MUSE", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.3", "subcategory": "Crystal Structure Generation", "confidence": "VERIFIED", "official_url": "https://github.com/MUSE-group/MUSE", "note": "", "md_link_text": "MUSE.md", "md_link_path": "StructurePrediction/7.3_Crystal_Generation/MUSE.md", "papers": [ { "name": "MUSE_10.1016_j.cpc.2014.03.017.pdf", "path": "Papers_of_Codes/StructurePrediction/MUSE/MUSE_10.1016_j.cpc.2014.03.017.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2014.03.017" } ], "paper_placeholder": false, "slug": "MUSE", "idx": 495, "overview": "MUSE (Multi-algorithm collaborative Universal Structure-prediction Environment) is a crystal structure prediction package that combines multiple global optimization algorithms\u2014Evolutionary Algorithm, Simulated Annealing, and Basin Hopping\u2014to efficiently locate stable structures. It is designed to leverage the strengths of different search strategies." }, { "num": "254", "name": "PyMetadynamics", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.3", "subcategory": "Crystal Structure Generation", "confidence": "VERIFIED", "official_url": "**MODULE** - Part of PLUMED/ASE ecosystem", "note": "", "md_link_text": "PyMetadynamics.md", "md_link_path": "StructurePrediction/7.3_Crystal_Generation/PyMetadynamics.md", "papers": [], "paper_placeholder": true, "slug": "PyMetadynamics", "idx": 496, "overview": "**Status**: \u2139\ufe0f MODULE / METHOD" }, { "num": "254a", "name": "RandSpg", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.3", "subcategory": "Crystal Structure Generation", "confidence": "VERIFIED", "official_url": "https://github.com/xtalopt/randSpg", "note": "", "md_link_text": "RandSpg.md", "md_link_path": "StructurePrediction/7.3_Crystal_Generation/RandSpg.md", "papers": [ { "name": "RandSpg_10.1016_j.cpc.2016.12.005.pdf", "path": "Papers_of_Codes/StructurePrediction/RandSpg/RandSpg_10.1016_j.cpc.2016.12.005.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2016.12.005" } ], "paper_placeholder": false, "slug": "RandSpg", "idx": 497, "overview": "RandSpg is a random symmetric crystal structure generator that creates structures using Wyckoff positions. It is part of the XtalOpt ecosystem and generates structures with specified space group symmetry." }, { "num": "254b", "name": "SOPRANO", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.3", "subcategory": "Crystal Structure Generation", "confidence": "VERIFIED", "official_url": "https://github.com/CCP-NC/soprano", "note": "", "md_link_text": "SOPRANO.md", "md_link_path": "StructurePrediction/7.3_Crystal_Generation/SOPRANO.md", "papers": [], "paper_placeholder": true, "slug": "SOPRANO", "idx": 498, "overview": "SOPRANO (Simulated Phonon Raman and NMR Observables) is a Python library for crystal structure generation, manipulation, and analysis. It provides tools for handling collections of structures and computing various properties." }, { "num": "254c", "name": "pyocse", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.3", "subcategory": "Crystal Structure Generation", "confidence": "VERIFIED", "official_url": "https://github.com/MaterSim/pyocse", "note": "", "md_link_text": "pyocse.md", "md_link_path": "StructurePrediction/7.3_Crystal_Generation/pyocse.md", "papers": [], "paper_placeholder": true, "slug": "pyocse", "idx": 499, "overview": "pyocse (Python Organic Crystal Simulation Environment) is a Python package for automating organic crystal simulations. It integrates structure generation, force field setup, and property calculations for organic molecular crystals." }, { "num": "254d", "name": "TCSP", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.3", "subcategory": "Crystal Structure Generation", "confidence": "VERIFIED", "official_url": "https://arxiv.org/abs/2111.14049", "note": "", "md_link_text": "TCSP.md", "md_link_path": "StructurePrediction/7.3_Crystal_Generation/TCSP.md", "papers": [], "paper_placeholder": true, "slug": "TCSP", "idx": 500, "overview": "TCSP (Template-based Crystal Structure Prediction) is a fast and accurate algorithm for crystal structure prediction using template structures from known materials databases." }, { "num": "254e", "name": "CrySPR", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.3", "subcategory": "Crystal Structure Generation", "confidence": "VERIFIED", "official_url": "https://github.com/Tosykie/CrySPR", "note": "", "md_link_text": "CrySPR.md", "md_link_path": "StructurePrediction/7.3_Crystal_Generation/CrySPR.md", "papers": [], "paper_placeholder": true, "slug": "CrySPR", "idx": 501, "overview": "CrySPR (Crystal Structure Pre-Relaxation and PRediction) is a Python interface for implementing crystal structure pre-relaxation and prediction using machine-learning interatomic potentials (ML-IAPs)." }, { "num": "254f", "name": "CSPBench", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.3", "subcategory": "Crystal Structure Generation", "confidence": "VERIFIED", "official_url": "https://github.com/usccolumbia/cspbenchmark", "note": "", "md_link_text": "CSPBench.md", "md_link_path": "StructurePrediction/7.3_Crystal_Generation/CSPBench.md", "papers": [], "paper_placeholder": true, "slug": "CSPBench", "idx": 502, "overview": "CSPBench is a benchmark suite for evaluating crystal structure prediction algorithms. It provides standardized datasets, metrics, and evaluation protocols for comparing CSP methods." }, { "num": "255", "name": "MaterialsProject-ML", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.4", "subcategory": "ML-Accelerated Structure Prediction", "confidence": "VERIFIED", "official_url": "https://materialsproject.org/", "note": "", "md_link_text": "MaterialsProject-ML.md", "md_link_path": "StructurePrediction/7.4_ML_Accelerated/MaterialsProject-ML.md", "papers": [ { "name": "10_1038_s41597-020-00637-5.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/Materials Cloud/10_1038_s41597-020-00637-5.pdf", "doi_url": "https://scholar.google.com/scholar?q=MaterialsProject-ML+10+1038+s41597+020+00637+5" }, { "name": "10_1063_1_4812323.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/Materials Cloud/10_1063_1_4812323.pdf", "doi_url": "https://scholar.google.com/scholar?q=MaterialsProject-ML+10+1063+1+4812323" } ], "paper_placeholder": false, "slug": "MaterialsProject-ML", "idx": 503, "overview": "**Status**: \u2139\ufe0f PLATFORM / ECOSYSTEM" }, { "num": "256", "name": "PyXtal-ML", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.4", "subcategory": "ML-Accelerated Structure Prediction", "confidence": "VERIFIED", "official_url": "https://github.com/qzhu2017/PyXtal", "note": "", "md_link_text": "PyXtal-ML.md", "md_link_path": "StructurePrediction/7.4_ML_Accelerated/PyXtal-ML.md", "papers": [ { "name": "10.1016_j.cpc.2020.107810.pdf", "path": "Papers_of_Codes/StructurePrediction/7.3_Crystal_Generation/PyXtal/10.1016_j.cpc.2020.107810.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2020.107810" } ], "paper_placeholder": false, "slug": "PyXtal-ML", "idx": 504, "overview": "**Status**: \u2139\ufe0f MODULE" }, { "num": "257a", "name": "CSPML", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.4", "subcategory": "ML-Accelerated Structure Prediction", "confidence": "VERIFIED", "official_url": "https://github.com/Minoru938/CSPML", "note": "", "md_link_text": "CSPML.md", "md_link_path": "StructurePrediction/7.4_ML_Accelerated/CSPML.md", "papers": [], "paper_placeholder": true, "slug": "CSPML", "idx": 505, "overview": "CSPML (Crystal Structure Prediction with Machine Learning) is a template-based crystal structure prediction method using metric learning for element substitution. It predicts stable structures by selecting templates from known crystal structures." }, { "num": "257b", "name": "CrySPAI", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.4", "subcategory": "ML-Accelerated Structure Prediction", "confidence": "VERIFIED", "official_url": "https://arxiv.org/abs/2501.15838", "note": "", "md_link_text": "CrySPAI.md", "md_link_path": "StructurePrediction/7.4_ML_Accelerated/CrySPAI.md", "papers": [], "paper_placeholder": true, "slug": "CrySPAI", "idx": 506, "overview": "CrySPAI is a crystal structure prediction software based on artificial intelligence that combines evolutionary optimization algorithms (EOA), density functional theory (DFT), and deep neural networks (DNN) for predicting stable crystal structures." }, { "num": "257c", "name": "GNOA", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.4", "subcategory": "ML-Accelerated Structure Prediction", "confidence": "VERIFIED", "official_url": "https://www.nature.com/articles/s41467-022-29241-4", "note": "", "md_link_text": "GNOA.md", "md_link_path": "StructurePrediction/7.4_ML_Accelerated/GNOA.md", "papers": [], "paper_placeholder": true, "slug": "GNOA", "idx": 507, "overview": "GNOA (Graph Network + Optimization Algorithm) is a machine learning approach for crystal structure prediction that combines graph networks for energy prediction with optimization algorithms for structure search." }, { "num": "257d", "name": "PyMCSP", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.4", "subcategory": "ML-Accelerated Structure Prediction", "confidence": "VERIFIED", "official_url": "https://github.com/polbeni/PyMCSP", "note": "", "md_link_text": "PyMCSP.md", "md_link_path": "StructurePrediction/7.4_ML_Accelerated/PyMCSP.md", "papers": [], "paper_placeholder": true, "slug": "PyMCSP", "idx": 508, "overview": "PyMCSP (Python Machine Learning Crystal Structure Prediction) is a Python package for crystal structure prediction using machine learning interatomic potentials (MACE, M3GNet) for fast structure relaxation." }, { "num": "397", "name": "USPEX-ML", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.4", "subcategory": "ML-Accelerated Structure Prediction", "confidence": "VERIFIED", "official_url": "https://uspex-team.org/", "note": "ML-accelerated version of USPEX evolutionary crystal structure prediction.", "md_link_text": "USPEX-ML.md", "md_link_path": "StructurePrediction/7.4_ML_Accelerated/USPEX-ML.md", "papers": [ { "name": "10.1103_PhysRevB.99.064114.pdf", "path": "Papers_of_Codes/StructurePrediction/7.4_ML_Accelerated/USPEX-ML/10.1103_PhysRevB.99.064114.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.99.064114" } ], "paper_placeholder": false, "slug": "USPEX-ML", "idx": 509, "overview": "" }, { "num": "257e", "name": "CDVAE", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.5", "subcategory": "Generative Models", "confidence": "VERIFIED", "official_url": "https://github.com/txie-93/cdvae", "note": "", "md_link_text": "CDVAE.md", "md_link_path": "StructurePrediction/7.5_Generative_Models/CDVAE.md", "papers": [ { "name": "CDVAE_10.48550_arXiv.2110.06197.pdf", "path": "Papers_of_Codes/StructurePrediction/CDVAE/CDVAE_10.48550_arXiv.2110.06197.pdf", "doi_url": "https://doi.org/10.48550/arXiv.2110.06197" } ], "paper_placeholder": false, "slug": "CDVAE", "idx": 510, "overview": "CDVAE (Crystal Diffusion Variational Autoencoder) is an SE(3)-invariant autoencoder for generating periodic crystal structures. It combines variational autoencoders with diffusion models to generate stable materials." }, { "num": "257f", "name": "DiffCSP", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.5", "subcategory": "Generative Models", "confidence": "VERIFIED", "official_url": "https://github.com/jiaor17/DiffCSP", "note": "", "md_link_text": "DiffCSP.md", "md_link_path": "StructurePrediction/7.5_Generative_Models/DiffCSP.md", "papers": [ { "name": "DiffCSP_10.48550_arXiv.2309.04475.pdf", "path": "Papers_of_Codes/StructurePrediction/DiffCSP/DiffCSP_10.48550_arXiv.2309.04475.pdf", "doi_url": "https://doi.org/10.48550/arXiv.2309.04475" } ], "paper_placeholder": false, "slug": "DiffCSP", "idx": 511, "overview": "DiffCSP is a crystal structure prediction method using joint equivariant diffusion on lattice and atomic coordinates. It treats CSP as a conditional generation task given chemical composition." }, { "num": "257g", "name": "MatterGen", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.5", "subcategory": "Generative Models", "confidence": "VERIFIED", "official_url": "https://github.com/microsoft/mattergen", "note": "", "md_link_text": "MatterGen.md", "md_link_path": "StructurePrediction/7.5_Generative_Models/MatterGen.md", "papers": [], "paper_placeholder": true, "slug": "MatterGen", "idx": 512, "overview": "MatterGen is Microsoft's generative diffusion model for inorganic materials design. It generates stable, diverse inorganic materials across the periodic table and can be fine-tuned to steer generation towards specific property constraints." }, { "num": "257h", "name": "GNoME", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.5", "subcategory": "Generative Models", "confidence": "VERIFIED", "official_url": "https://github.com/google-deepmind/materials_discovery", "note": "", "md_link_text": "GNoME.md", "md_link_path": "StructurePrediction/7.5_Generative_Models/GNoME.md", "papers": [], "paper_placeholder": true, "slug": "GNoME", "idx": 513, "overview": "GNoME (Graph Networks for Materials Exploration) is Google DeepMind's deep learning tool for predicting the stability of inorganic crystal structures. It discovered 2.2 million new stable crystals, including 380,000 added to the Materials Project." }, { "num": "257i", "name": "FlowMM", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.5", "subcategory": "Generative Models", "confidence": "VERIFIED", "official_url": "https://github.com/facebookresearch/flowmm", "note": "", "md_link_text": "FlowMM.md", "md_link_path": "StructurePrediction/7.5_Generative_Models/FlowMM.md", "papers": [ { "name": "FlowMM_10.48550_arXiv.2406.04713.pdf", "path": "Papers_of_Codes/StructurePrediction/FlowMM/FlowMM_10.48550_arXiv.2406.04713.pdf", "doi_url": "https://doi.org/10.48550/arXiv.2406.04713" } ], "paper_placeholder": false, "slug": "FlowMM", "idx": 514, "overview": "FlowMM is a generative model for materials using Riemannian flow matching. It generates crystal structures by learning flows on the Riemannian manifold of periodic structures, achieving state-of-the-art performance on CSP tasks." }, { "num": "257j", "name": "CrystalFlow", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.5", "subcategory": "Generative Models", "confidence": "VERIFIED", "official_url": "https://github.com/ixsluo/CrystalFlow", "note": "", "md_link_text": "CrystalFlow.md", "md_link_path": "StructurePrediction/7.5_Generative_Models/CrystalFlow.md", "papers": [ { "name": "Dovesi_et_al_2018.pdf", "path": "Papers_of_Codes/DFT/1.3_Localized_Basis/CRYSTAL/Dovesi_et_al_2018.pdf", "doi_url": "https://scholar.google.com/scholar?q=CrystalFlow+Dovesi+et+al+2018" } ], "paper_placeholder": false, "slug": "CrystalFlow", "idx": 515, "overview": "CrystalFlow is a flow-based generative model for crystalline materials using Continuous Normalizing Flows (CNFs) within the Conditional Flow Matching (CFM) framework. Published in Nature Communications 2025." }, { "num": "257k", "name": "EquiCSP", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.5", "subcategory": "Generative Models", "confidence": "VERIFIED", "official_url": "https://github.com/EmperorJia/EquiCSP", "note": "", "md_link_text": "EquiCSP.md", "md_link_path": "StructurePrediction/7.5_Generative_Models/EquiCSP.md", "papers": [ { "name": "EquiCSP_10.48550_arXiv.2512.07289.pdf", "path": "Papers_of_Codes/StructurePrediction/EquiCSP/EquiCSP_10.48550_arXiv.2512.07289.pdf", "doi_url": "https://doi.org/10.48550/arXiv.2512.07289" } ], "paper_placeholder": false, "slug": "EquiCSP", "idx": 516, "overview": "EquiCSP (Equivariant Diffusion for Crystal Structure Prediction) is a symmetry-aware deep learning model that ensures permutation, rotation, and periodic translation equivariance during the diffusion process for crystal structure prediction." }, { "num": "257l", "name": "SyMat", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.5", "subcategory": "Generative Models", "confidence": "VERIFIED", "official_url": "https://arxiv.org/abs/2307.02707", "note": "", "md_link_text": "SyMat.md", "md_link_path": "StructurePrediction/7.5_Generative_Models/SyMat.md", "papers": [ { "name": "SyMat_10.48550_arXiv.2307.02707.pdf", "path": "Papers_of_Codes/StructurePrediction/SyMat/SyMat_10.48550_arXiv.2307.02707.pdf", "doi_url": "https://doi.org/10.48550/arXiv.2307.02707" } ], "paper_placeholder": false, "slug": "SyMat", "idx": 517, "overview": "SyMat (Symmetry-aware generation of periodic Materials) is a generative model that incorporates crystal symmetry into the generation process. It uses a symmetry-aware probabilistic model in the coordinate diffusion process." }, { "num": "257m", "name": "OMatG", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.5", "subcategory": "Generative Models", "confidence": "VERIFIED", "official_url": "https://github.com/FERMat-ML/OMatG", "note": "", "md_link_text": "OMatG.md", "md_link_path": "StructurePrediction/7.5_Generative_Models/OMatG.md", "papers": [], "paper_placeholder": true, "slug": "OMatG", "idx": 518, "overview": "OMatG (Open Materials Generation) is a state-of-the-art generative model for crystal structure prediction and de novo generation of inorganic crystals using stochastic interpolants." }, { "num": "257n", "name": "AlphaCrystal", "category_id": "7", "category": "STRUCTURE PREDICTION", "subcategory_id": "7.5", "subcategory": "Generative Models", "confidence": "VERIFIED", "official_url": "https://github.com/usccolumbia/AlphaCrystal", "note": "", "md_link_text": "AlphaCrystal.md", "md_link_path": "StructurePrediction/7.5_Generative_Models/AlphaCrystal.md", "papers": [], "paper_placeholder": true, "slug": "AlphaCrystal", "idx": 519, "overview": "AlphaCrystal is a contact map-based deep learning algorithm for crystal structure prediction, inspired by AlphaFold's approach to protein structure prediction. 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Developed by the JuDFT team at Forschungszentrum J\u00fclich, it provides comprehensive support for all-electron full-potential methods." }, { "num": "273", "name": "ElkOpticsAnalyzer", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "Elk optics output analyzer", "note": "", "md_link_text": "ElkOpticsAnalyzer.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/ElkOpticsAnalyzer.md", "papers": [], "paper_placeholder": true, "slug": "ElkOpticsAnalyzer", "idx": 539, "overview": "ElkOpticsAnalyzer is a tool for analyzing optical properties output from the Elk all-electron full-potential linearized augmented-plane wave (FP-LAPW) code, providing visualization of dielectric functions and optical spectra." }, { "num": "274", "name": "aims_DosBand", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "FHI-aims band/DOS plotter", "note": "", "md_link_text": "aims_DosBand.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/aims_DosBand.md", "papers": [], "paper_placeholder": true, "slug": "aims_DosBand", "idx": 540, "overview": "aims_DosBand is a plotting tool for band structures and density of states from FHI-aims calculations, providing publication-quality figures with orbital projections." }, { "num": "275", "name": "aimstools", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "FHI-aims Python analysis toolkit", "note": "", "md_link_text": "aimstools.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/aimstools.md", "papers": [], "paper_placeholder": true, "slug": "aimstools", "idx": 541, "overview": "aimstools is a Python package for analyzing and visualizing FHI-aims calculation results, providing utilities for post-processing electronic structure data." }, { "num": "277", "name": "JARVIS-Tools", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/usnistgov/jarvis", "note": "", "md_link_text": "JARVIS-Tools.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/JARVIS-Tools.md", "papers": [ { "name": "Choudhary_et_al_2020.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/JARVIS/Choudhary_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=JARVIS-Tools+Choudhary+et+al+2020" } ], "paper_placeholder": false, "slug": "JARVIS-Tools", "idx": 542, "overview": "JARVIS-Tools (Joint Automated Repository for Various Integrated Simulations) is a comprehensive open-source Python package for atomistic data-driven materials design developed at NIST. It provides tools for setting up calculations, post-processing, analysis, visualization, and machine learning across multiple simulation codes. The package is tightly integrated with the JARVIS databases containing >100,000 materials." }, { "num": "278", "name": "OrbVis", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/staradutt/OrbVis", "note": "", "md_link_text": "OrbVis.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/OrbVis.md", "papers": [], "paper_placeholder": true, "slug": "OrbVis", "idx": 543, "overview": "OrbVis is a lightweight Python package for plotting orbital-projected band structures and density of states from VASP output files (PROCAR & DOSCAR)." }, { "num": "279", "name": "bands4vasp", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/QuantumMaterialsModelling/bands4vasp", "note": "", "md_link_text": "bands4vasp.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/bands4vasp.md", "papers": [ { "name": "bands4vasp_10.1021_acs.jpcc.1c02318.pdf", "path": "Papers_of_Codes/Post-Processing/bands4vasp/bands4vasp_10.1021_acs.jpcc.1c02318.pdf", "doi_url": "https://doi.org/10.1021/acs.jpcc.1c02318" } ], "paper_placeholder": false, "slug": "bands4vasp", "idx": 544, "overview": "bands4vasp is a post-processing package for the analysis of unfolded eigenstates in VASP. It provides comprehensive tools for band structures, 2D and 3D Fermi surfaces, Fermi vectors, and spectral functions from VASP calculations with the unfolding patch." }, { "num": "280", "name": "matminer", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/hackingmaterials/matminer", "note": "", "md_link_text": "matminer.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/matminer.md", "papers": [ { "name": "10.1016_j.commatsci.2018.05.018.pdf", "path": "Papers_of_Codes/Frameworks/9.1_General_Purpose_Libraries/matminer/10.1016_j.commatsci.2018.05.018.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2018.05.018" }, { "name": "Ward_et_al_2018.pdf", "path": "Papers_of_Codes/Frameworks/9.1_General_Purpose_Libraries/matminer/Ward_et_al_2018.pdf", "doi_url": "https://scholar.google.com/scholar?q=matminer+Ward+et+al+2018" } ], "paper_placeholder": false, "slug": "matminer", "idx": 545, "overview": "matminer is a comprehensive Python library for data mining in materials science, developed at Lawrence Berkeley National Laboratory. It provides tools for extracting features (descriptors) from materials data including compositions, structures, band structures, and density of states for machine learning applications." }, { "num": "281", "name": "blaze2d", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "Rust 2D photonic crystal band solver", "note": "", "md_link_text": "blaze2d.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/blaze2d.md", "papers": [], "paper_placeholder": true, "slug": "blaze2d", "idx": 546, "overview": "blaze2d is a high-performance Rust implementation for 2D photonic crystal band structure calculations, designed to be faster than MIT's MPB." }, { "num": "281a", "name": "DensityTool", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/llodeiro/DensityTool", "note": "Space- and spin-resolved DOS decomposition from VASP", "md_link_text": "DensityTool.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/DensityTool.md", "papers": [], "paper_placeholder": true, "slug": "DensityTool", "idx": 547, "overview": "**DensityTool** is a FORTRAN post-processing program for space- and spin-resolved density of states from VASP. It provides detailed spatial and spin decomposition of the DOS, enabling atom-, shell-, and orbital-projected DOS analysis beyond standard VASP output." }, { "num": "281b", "name": "WOOPs", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/Chengcheng-Xiao/WOOPs", "note": "Wannier Orbital Overlap Population (COOP/COHP in Wannier basis)", "md_link_text": "WOOPs.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/WOOPs.md", "papers": [], "paper_placeholder": true, "slug": "WOOPs", "idx": 548, "overview": "**WOOPs** (Wannier Orbital Overlap Population) is a Python post-processing tool for calculating Wannier Orbital Overlap Population (WOOP) and Wannier Orbital Position Population (WOPP) from Wannier90 output. It provides bonding analysis in the Wannier function basis, analogous to COOP/COHP in the atomic orbital basis." }, { "num": "281c", "name": "dftscr", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/tangzhao20/dftscr", "note": "Multi-code (VASP/QE/PARSEC) DFT analysis and visualization suite", "md_link_text": "dftscr.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/dftscr.md", "papers": [], "paper_placeholder": true, "slug": "dftscr", "idx": 549, "overview": "**dftscr** (DFT Scripts) is a suite of Python scripts for analyzing and visualizing data from first-principles electronic structure calculations. It includes tools for plotting band structures, converting atomic structures, analyzing density of states, and preparing inputs for calculations with VASP and Quantum ESPRESSO." }, { "num": "281d", "name": "plot4dft", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/Nijatt/plot4dft", "note": "Simple dual-code (VASP/QE) band+DOS+phonon plotting tool", "md_link_text": "plot4dft.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/plot4dft.md", "papers": [], "paper_placeholder": true, "slug": "plot4dft", "idx": 550, "overview": "**plot4dft** is a Python plotting tool for band structure and density of states generated by VASP or Quantum ESPRESSO. It provides a simple command-line interface for creating publication-quality band structure and DOS plots from DFT output files." }, { "num": "281e", "name": "bandplot", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://pypi.org/project/bandplot/", "note": "PyPI-installable band+DOS+phonon plotting from VASPKIT/phonopy output", "md_link_text": "bandplot.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/bandplot.md", "papers": [], "paper_placeholder": true, "slug": "bandplot", "idx": 551, "overview": "**bandplot** is a Python package for electron band structure, DOS, and phonon band structure/DOS plotting from VASPKIT or phonopy results. It provides automated plotting with two main commands: `bandplot` for electronic band structures and `phononplot` for phonon dispersions." }, { "num": "281f", "name": "aiida-kkr", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/JuDFTteam/aiida-kkr", "note": "", "md_link_text": "aiida-kkr.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/aiida-kkr.md", "papers": [ { "name": "10.1038_s41597-020-00638-4.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/AiiDA/10.1038_s41597-020-00638-4.pdf", "doi_url": "https://doi.org/10.1038/s41597-020-00638-4" }, { "name": "Huber_et_al_2020.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/AiiDA/Huber_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=aiida-kkr+Huber+et+al+2020" } ], "paper_placeholder": false, "slug": "aiida-kkr", "idx": 552, "overview": "aiida-kkr is an AiiDA plugin for running KKR (Korringa-Kohn-Rostoker) Green's function calculations, providing workflow automation for KKR-based electronic structure calculations." }, { "num": "282", "name": "aiida-fleur", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/JuDFTteam/aiida-fleur", "note": "", "md_link_text": "aiida-fleur.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/aiida-fleur.md", "papers": [ { "name": "10.1038_s41597-020-00638-4.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/AiiDA/10.1038_s41597-020-00638-4.pdf", "doi_url": "https://doi.org/10.1038/s41597-020-00638-4" }, { "name": "Huber_et_al_2020.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/AiiDA/Huber_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=aiida-fleur+Huber+et+al+2020" } ], "paper_placeholder": false, "slug": "aiida-fleur", "idx": 553, "overview": "aiida-fleur is an AiiDA plugin for running FLEUR (Full-potential Linearized Augmented Plane Wave) calculations, providing workflow automation for all-electron DFT calculations." }, { "num": "285", "name": "BandUP", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://www.bandupcode.com/", "note": "", "md_link_text": "BandUP.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/BandUP.md", "papers": [ { "name": "10_1103_PhysRevB_89_041407.pdf", "path": "Papers_of_Codes/Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/BandUP/10_1103_PhysRevB_89_041407.pdf", "doi_url": "https://scholar.google.com/scholar?q=BandUP+10+1103+PhysRevB+89+041407" }, { "name": "10_1103_PhysRevB_91_041116.pdf", "path": "Papers_of_Codes/Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/BandUP/10_1103_PhysRevB_91_041116.pdf", "doi_url": "https://scholar.google.com/scholar?q=BandUP+10+1103+PhysRevB+91+041116" } ], "paper_placeholder": false, "slug": "BandUP", "idx": 554, "overview": "BandUP is a code for unfolding the electronic band structure of supercells into the primitive cell Brillouin zone. This technique is essential for analyzing calculations of impurities, defects, alloys, or surfaces, where the translational symmetry of the primitive cell is broken or obscured by the use of a supercell. BandUP recovers the effective band structure (spectral weight) in the primitive representation, making it comparable to ARPES experiments and standard band structures." }, { "num": "286", "name": "fold2Bloch", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/qsnake/fold2Bloch", "note": "", "md_link_text": "fold2Bloch.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/fold2Bloch.md", "papers": [ { "name": "10_1103_PhysRevB_85_085201.pdf", "path": "Papers_of_Codes/Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/fold2Bloch/10_1103_PhysRevB_85_085201.pdf", "doi_url": "https://scholar.google.com/scholar?q=fold2Bloch+10+1103+PhysRevB+85+085201" } ], "paper_placeholder": false, "slug": "fold2Bloch", "idx": 555, "overview": "fold2Bloch is a code for unfolding the band structure of supercells obtained from first-principles calculations. Specifically designed for VASP (and adaptable to other plane-wave codes), it recovers the Bloch character of electronic eigenstates in the primitive Brillouin zone. This allows for the direct comparison of supercell calculations (used for defects, alloys, or magnetic structures) with the band structures of primitive cells and experimental ARPES data." }, { "num": "287", "name": "PyProcar-Unfold", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://pyprocar.readthedocs.io/", "note": "", "md_link_text": "PyProcar-Unfold.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/PyProcar-Unfold.md", "papers": [ { "name": "10_1016_j_cpc_2019_107080.pdf", "path": "Papers_of_Codes/Post-Processing/8.1_Band_Structure_Electronic/8.1.1_Band_DOS_Visualization/pyprocar/10_1016_j_cpc_2019_107080.pdf", "doi_url": "https://scholar.google.com/scholar?q=PyProcar-Unfold+10+1016+j+cpc+2019+107080" } ], "paper_placeholder": false, "slug": "PyProcar-Unfold", "idx": 556, "overview": "PyProcar-Unfold refers to the band unfolding module within the PyProcar package. It provides functionality to unfold the electronic band structure of supercells into the primitive cell Brillouin zone. This is particularly useful for studying the effective band structure of systems with broken translational symmetry, such as defects, interfaces, and alloys, using VASP or other supported DFT codes." }, { "num": "288", "name": "easyunfold", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/SMTG-Bham/easyunfold", "note": "", "md_link_text": "easyunfold.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/easyunfold.md", "papers": [ { "name": "easyunfold_10.21105_joss.05974.pdf", "path": "Papers_of_Codes/Post-Processing/easyunfold/easyunfold_10.21105_joss.05974.pdf", "doi_url": "https://doi.org/10.21105/joss.05974" } ], "paper_placeholder": false, "slug": "easyunfold", "idx": 557, "overview": "easyunfold is a Python package for band structure unfolding, making it easy to obtain effective band structures (EBS) from supercell calculations. It properly accounts for symmetry-breaking by sampling necessary additional k-points and averaging spectral weights appropriately. The package supports multiple DFT codes and provides publication-ready visualizations." }, { "num": "289", "name": "banduppy", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/band-unfolding/banduppy", "note": "", "md_link_text": "banduppy.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/banduppy.md", "papers": [ { "name": "10_1103_PhysRevB_89_041407.pdf", "path": "Papers_of_Codes/Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/BandUP/10_1103_PhysRevB_89_041407.pdf", "doi_url": "https://scholar.google.com/scholar?q=banduppy+10+1103+PhysRevB+89+041407" }, { "name": "10_1103_PhysRevB_91_041116.pdf", "path": "Papers_of_Codes/Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/BandUP/10_1103_PhysRevB_91_041116.pdf", "doi_url": "https://scholar.google.com/scholar?q=banduppy+10+1103+PhysRevB+91+041116" } ], "paper_placeholder": false, "slug": "banduppy", "idx": 558, "overview": "banduppy is a Python implementation of the BandUP code for band structure unfolding from supercell calculations. It provides modern support for Quantum ESPRESSO and other DFT codes, using the irrep library for wavefunction reading. banduppy enables extraction of effective band structures from supercell calculations containing defects, alloys, or interfaces." }, { "num": "290", "name": "VaspBandUnfolding", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/QijingZheng/VaspBandUnfolding", "note": "", "md_link_text": "VaspBandUnfolding.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/VaspBandUnfolding.md", "papers": [ { "name": "Kresse_Furthmuller_1996.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/Kresse_Furthmuller_1996.pdf", "doi_url": "https://scholar.google.com/scholar?q=VaspBandUnfolding+Kresse+Furthmuller+1996" }, { "name": "Kresse_Hafner_1993.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/Kresse_Hafner_1993.pdf", "doi_url": "https://scholar.google.com/scholar?q=VaspBandUnfolding+Kresse+Hafner+1993" }, { "name": "10.1016_0927-0256(96)00008-0.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/10.1016_0927-0256%2896%2900008-0.pdf", "doi_url": "https://doi.org/10.1016/0927-0256(96)00008-0" } ], "paper_placeholder": false, "slug": "VaspBandUnfolding", "idx": 559, "overview": "VaspBandUnfolding is a Python toolkit for VASP band unfolding from supercell calculations, providing WAVECAR parsing and spectral weight calculation with well-documented tutorials." }, { "num": "291", "name": "vasp_unfold", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/tomkeus/vasp_unfold", "note": "", "md_link_text": "vasp_unfold.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/vasp_unfold.md", "papers": [ { "name": "Kresse_Furthmuller_1996.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/Kresse_Furthmuller_1996.pdf", "doi_url": "https://scholar.google.com/scholar?q=vasp_unfold+Kresse+Furthmuller+1996" }, { "name": "Kresse_Hafner_1993.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/Kresse_Hafner_1993.pdf", "doi_url": "https://scholar.google.com/scholar?q=vasp_unfold+Kresse+Hafner+1993" }, { "name": "10.1016_0927-0256(96)00008-0.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/10.1016_0927-0256%2896%2900008-0.pdf", "doi_url": "https://doi.org/10.1016/0927-0256(96)00008-0" } ], "paper_placeholder": false, "slug": "vasp_unfold", "idx": 560, "overview": "vasp_unfold is a Python tool for unfolding VASP band structures using PROCAR files with phase information (LORBIT=12), providing spectral weight calculation for supercell systems." }, { "num": "292", "name": "fold2Bloch-VASP", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/rubel75/fold2Bloch-VASP", "note": "", "md_link_text": "fold2Bloch-VASP.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/fold2Bloch-VASP.md", "papers": [ { "name": "10_1103_PhysRevB_85_085201.pdf", "path": "Papers_of_Codes/Post-Processing/8.1_Band_Structure_Electronic/8.1.2_Band_Unfolding/fold2Bloch/10_1103_PhysRevB_85_085201.pdf", "doi_url": "https://scholar.google.com/scholar?q=fold2Bloch-VASP+10+1103+PhysRevB+85+085201" } ], "paper_placeholder": false, "slug": "fold2Bloch-VASP", "idx": 561, "overview": "fold2Bloch-VASP is a Fortran utility for unfolding supercell band structures from VASP calculations into primitive cell representation, computing effective band structures with Bloch spectral weights." }, { "num": "293", "name": "FermiSurfer", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://fermisurfer.osdn.jp/", "note": "", "md_link_text": "FermiSurfer.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.3_Fermi_Surface/FermiSurfer.md", "papers": [ { "name": "10_1016_j_cpc_2019_01_017.pdf", "path": "Papers_of_Codes/Post-Processing/8.1_Band_Structure_Electronic/8.1.3_Fermi_Surface/FermiSurfer/10_1016_j_cpc_2019_01_017.pdf", "doi_url": "https://scholar.google.com/scholar?q=FermiSurfer+10+1016+j+cpc+2019+01+017" } ], "paper_placeholder": false, "slug": "FermiSurfer", "idx": 562, "overview": "FermiSurfer is a visualization tool for Fermi surfaces. It can display Fermi surfaces with color plots of physical quantities (such as Fermi velocity, superconducting gap, spin character) on the surface. It is designed to be lightweight, fast, and easy to use, supporting input from major first-principles codes." }, { "num": "294", "name": "AutoBZ.jl", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/JuliaQuantum/AutoBZCore.jl", "note": "", "md_link_text": "AutoBZ.jl.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.3_Fermi_Surface/AutoBZ.jl.md", "papers": [ { "name": "AutoBZ.jl_10.21105_joss.07080.pdf", "path": "Papers_of_Codes/Post-Processing/AutoBZ.jl/AutoBZ.jl_10.21105_joss.07080.pdf", "doi_url": "https://doi.org/10.21105/joss.07080" } ], "paper_placeholder": false, "slug": "AutoBZ.jl", "idx": 563, "overview": "AutoBZ.jl is a Julia package for constructing and integrating Brillouin zone (BZ) quantities. It provides a flexible and efficient framework for defining the BZ, discretizing it (using various quadrature rules), and calculating properties like density of states, Fermi surfaces, and transport coefficients. It is designed to be highly modular and composable with other Julia packages in the electronic structure ecosystem." }, { "num": "295", "name": "IFermi", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/fermisurfaces/IFermi", "note": "", "md_link_text": "IFermi.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.3_Fermi_Surface/IFermi.md", "papers": [ { "name": "IFermi_10.21105_joss.03089.pdf", "path": "Papers_of_Codes/Post-Processing/IFermi/IFermi_10.21105_joss.03089.pdf", "doi_url": "https://doi.org/10.21105/joss.03089" } ], "paper_placeholder": false, "slug": "IFermi", "idx": 564, "overview": "IFermi is a Python package for Fermi surface generation, analysis, and visualization from ab initio calculations. It provides tools for extracting Fermi surfaces from DFT band structures, computing Fermi surface properties, and creating publication-quality 2D and 3D visualizations. Developed by the Materials Project team, it integrates seamlessly with pymatgen." }, { "num": "296", "name": "py_FS", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/TheoWeinberger/py_FS", "note": "", "md_link_text": "py_FS.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.3_Fermi_Surface/py_FS.md", "papers": [], "paper_placeholder": true, "slug": "py_FS", "idx": 565, "overview": "**py_FS** is a Python script for plotting Fermi surfaces from BXSF files. It provides 3D visualization using PyVista." }, { "num": "297", "name": "PyARPES", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://arpes.github.io/PyARPES/", "note": "", "md_link_text": "PyARPES.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.4_ARPES_Photoemission/PyARPES.md", "papers": [ { "name": "PyARPES_10.1016_j.softx.2020.100472.pdf", "path": "Papers_of_Codes/Post-Processing/PyARPES/PyARPES_10.1016_j.softx.2020.100472.pdf", "doi_url": "https://doi.org/10.1016/j.softx.2020.100472" } ], "paper_placeholder": false, "slug": "PyARPES", "idx": 566, "overview": "PyARPES is a Python-based analysis framework for Angle-Resolved Photoemission Spectroscopy (ARPES) data. It provides tools for loading, processing, visualizing, and analyzing multidimensional ARPES datasets. PyARPES aims to streamline the workflow from raw data to publication-quality figures, supporting data from various synchrotrons and lab-based systems." }, { "num": "298", "name": "ARPESGUI", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "MATLAB GUI for SX-ARPES analysis", "note": "", "md_link_text": "ARPESGUI.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.4_ARPES_Photoemission/ARPESGUI.md", "papers": [], "paper_placeholder": true, "slug": "ARPESGUI", "idx": 567, "overview": "**ARPESGUI** is a MATLAB-based graphical user interface for analyzing soft X-ray angle-resolved photoemission spectroscopy (SX-ARPES) data." }, { "num": "299", "name": "fuller", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "ML-based band structure reconstruction", "note": "", "md_link_text": "fuller.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.4_ARPES_Photoemission/fuller.md", "papers": [], "paper_placeholder": true, "slug": "fuller", "idx": 568, "overview": "**fuller** is a machine learning-based tool for band structure reconstruction from photoemission spectroscopy data. It uses deep learning to extract electronic band structures from ARPES measurements." }, { "num": "300", "name": "mpes", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "Multidimensional photoemission spectroscopy toolkit", "note": "", "md_link_text": "mpes.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.4_ARPES_Photoemission/mpes.md", "papers": [ { "name": "mpes_10.1038_s41597-020-00769-8.pdf", "path": "Papers_of_Codes/Post-Processing/mpes/mpes_10.1038_s41597-020-00769-8.pdf", "doi_url": "https://doi.org/10.1038/s41597-020-00769-8" } ], "paper_placeholder": false, "slug": "mpes", "idx": 569, "overview": "mpes is a Python toolkit for multidimensional photoemission spectroscopy data analysis. It provides comprehensive tools for processing, calibrating, and analyzing time-resolved and angle-resolved photoemission data, with support for modern data formats and parallel processing." }, { "num": "301", "name": "peaks", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "Modern Python ARPES analysis framework", "note": "", "md_link_text": "peaks.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.4_ARPES_Photoemission/peaks.md", "papers": [], "paper_placeholder": true, "slug": "peaks", "idx": 570, "overview": "**peaks** is a modern Python framework for ARPES (Angle-Resolved Photoemission Spectroscopy) data analysis. It provides comprehensive tools for processing and analyzing photoemission data." }, { "num": "301a", "name": "arpespythontools", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/pranabdas/arpespythontools", "note": "Lightweight ARPES data analysis with momentum conversion and curvature analysis", "md_link_text": "arpespythontools.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.4_ARPES_Photoemission/arpespythontools.md", "papers": [], "paper_placeholder": true, "slug": "arpespythontools", "idx": 571, "overview": "**arpespythontools** is a Python library for exploring, analyzing, and visualizing ARPES (Angle-Resolved Photoemission Spectroscopy) data. It provides tools for loading experimental ARPES data, momentum conversion, Fermi level alignment, band mapping, and curvature analysis." }, { "num": "301b", "name": "erlabpy", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/kmnhan/erlabpy", "note": "Complete ARPES workflow with self-energy analysis and interactive visualization", "md_link_text": "erlabpy.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.4_ARPES_Photoemission/erlabpy.md", "papers": [], "paper_placeholder": true, "slug": "erlabpy", "idx": 572, "overview": "**erlabpy** is a complete Python workflow for angle-resolved photoemission spectroscopy (ARPES) experiments. It provides tools to handle, manipulate, and visualize data from ARPES experiments with comprehensive analysis capabilities including momentum conversion, Fermi surface mapping, and band structure analysis." }, { "num": "302", "name": "effectivemass", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/aflow/effectivemass", "note": "", "md_link_text": "effectivemass.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.5_Effective_Mass/effectivemass.md", "papers": [ { "name": "10_1103_PhysRevB_99_085207.pdf", "path": "Papers_of_Codes/Post-Processing/8.1_Band_Structure_Electronic/8.1.5_Effective_Mass/effectivemass/10_1103_PhysRevB_99_085207.pdf", "doi_url": "https://scholar.google.com/scholar?q=effectivemass+10+1103+PhysRevB+99+085207" } ], "paper_placeholder": false, "slug": "effectivemass", "idx": 573, "overview": "effmass is a Python package for calculating the effective mass of charge carriers (electrons and holes) from electronic band structures. It supports both parabolic and non-parabolic definitions of effective mass and provides tools for selecting band segments extrema. effmass is designed to work with outputs from major DFT codes like VASP, FHI-aims, CASTEP, and Quantum ESPRESSO." }, { "num": "303", "name": "SeeK-path", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://seekpath.readthedocs.io/", "note": "", "md_link_text": "SeeK-path.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.5_Effective_Mass/SeeK-path.md", "papers": [ { "name": "SeeK-path_10.1016_j.commatsci.2016.10.015.pdf", "path": "Papers_of_Codes/Post-Processing/SeeK-path/SeeK-path_10.1016_j.commatsci.2016.10.015.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2016.10.015" } ], "paper_placeholder": false, "slug": "SeeK-path", "idx": 574, "overview": "SeeK-path is a python module and online tool for obtaining the standardized primitive cell and high-symmetry k-points path for band structure calculations. It automatically detects the space group of a crystal structure, converts it to a standard representation, and suggests a path through the Brillouin zone that captures all relevant features of the electronic bands." }, { "num": "304", "name": "effmass", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/lucydot/effmass", "note": "", "md_link_text": "effmass.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.5_Effective_Mass/effmass.md", "papers": [ { "name": "effmass_10.21105_joss.00797.pdf", "path": "Papers_of_Codes/Post-Processing/effmass/effmass_10.21105_joss.00797.pdf", "doi_url": "https://doi.org/10.21105/joss.00797" } ], "paper_placeholder": false, "slug": "effmass", "idx": 575, "overview": "effmass is a Python package for calculating effective masses from ab initio band structure calculations. It provides tools for extracting carrier effective masses using various models including parabolic approximation and Kane's non-parabolic model. The package automatically identifies band extrema and handles multiple valleys." }, { "num": "305", "name": "Effective-mass-fitting", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "PyQt parabolic band fitting app", "note": "", "md_link_text": "Effective-mass-fitting.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.5_Effective_Mass/Effective-mass-fitting.md", "papers": [ { "name": "10_1103_PhysRevB_99_085207.pdf", "path": "Papers_of_Codes/Post-Processing/8.1_Band_Structure_Electronic/8.1.5_Effective_Mass/effectivemass/10_1103_PhysRevB_99_085207.pdf", "doi_url": "https://scholar.google.com/scholar?q=Effective-mass-fitting+10+1103+PhysRevB+99+085207" } ], "paper_placeholder": false, "slug": "Effective-mass-fitting", "idx": 576, "overview": "**Effective-mass-fitting** is a PyQt-based application for parabolic band fitting to extract effective masses from DFT calculations." }, { "num": "306", "name": "mstar", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/rubel75/mstar", "note": "Effective mass via perturbation theory from WIEN2k (conductivity, DOS, cyclotron)", "md_link_text": "mstar.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.5_Effective_Mass/mstar.md", "papers": [], "paper_placeholder": true, "slug": "mstar", "idx": 577, "overview": "**mstar** is a tool for calculating effective masses with DFT using perturbation theory. It computes conductivity, density-of-states, and cyclotron effective masses from WIEN2k band structures using the k\u00b7p perturbation theory approach, providing more accurate effective masses than finite-difference methods." }, { "num": "307", "name": "emc", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/afonari/emc", "note": "Effective Mass Calculator (finite difference) for VASP/QE, anisotropic tensor", "md_link_text": "emc.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.5_Effective_Mass/emc.md", "papers": [ { "name": "Stanton_Gauss_1995.pdf", "path": "Papers_of_Codes/Post-Processing/8.1_Band_Structure_Electronic/8.1.5_Effective_Mass/EMC/Stanton_Gauss_1995.pdf", "doi_url": "https://scholar.google.com/scholar?q=emc+Stanton+Gauss+1995" } ], "paper_placeholder": false, "slug": "emc", "idx": 578, "overview": "**emc** (Effective Mass Calculator) is a program for calculating effective masses at band extrema in semiconductors using the finite difference method. Available in both FORTRAN and Python versions, it works with VASP and Quantum ESPRESSO outputs to compute anisotropic effective mass tensors." }, { "num": "308", "name": "pysktb", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "Slater-Koster tight-binding topological solver", "note": "", "md_link_text": "pysktb.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.6_Tight_Binding/pysktb.md", "papers": [], "paper_placeholder": true, "slug": "pysktb", "idx": 579, "overview": "pysktb is a Python package for Slater-Koster tight-binding calculations with a focus on topological materials analysis. It provides tools for constructing tight-binding Hamiltonians using the two-center Slater-Koster approximation and calculating topological invariants like Berry phases and Chern numbers." }, { "num": "310", "name": "TightBinding.jl", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "Julia high-performance TB package", "note": "", "md_link_text": "TightBinding.jl.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.6_Tight_Binding/TightBinding.jl.md", "papers": [], "paper_placeholder": true, "slug": "TightBinding.jl", "idx": 580, "overview": "TightBinding.jl is a high-performance Julia package for tight-binding calculations, leveraging Julia's speed and just-in-time compilation for large-scale electronic structure simulations. It provides tools for constructing tight-binding Hamiltonians and computing band structures efficiently." }, { "num": "311", "name": "NanoNet", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "TB for nanostructures", "note": "", "md_link_text": "NanoNet.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.6_Tight_Binding/NanoNet.md", "papers": [ { "name": "NanoNet_10.1016_j.cpc.2020.107676.pdf", "path": "Papers_of_Codes/Post-Processing/NanoNet/NanoNet_10.1016_j.cpc.2020.107676.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2020.107676" }, { "name": "NanoNET_10.1016_j.cpc.2020.107676.pdf", "path": "Papers_of_Codes/Post-Processing/NanoNet/NanoNET_10.1016_j.cpc.2020.107676.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2020.107676" } ], "paper_placeholder": false, "slug": "NanoNet", "idx": 581, "overview": "NanoNet is a tight-binding package designed for electronic structure calculations of nanostructures including nanowires, quantum dots, and heterostructures. It provides tools for building atomistic models and computing electronic properties using the tight-binding method with focus on semiconductor nanostructures." }, { "num": "312", "name": "UltimateEPM", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "Empirical pseudopotential method", "note": "", "md_link_text": "UltimateEPM.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.6_Tight_Binding/UltimateEPM.md", "papers": [], "paper_placeholder": true, "slug": "UltimateEPM", "idx": 582, "overview": "**UltimateEPM** is an implementation of the Empirical Pseudopotential Method (EPM) for calculating electronic band structures of semiconductors." }, { "num": "313", "name": "elphem", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "Electron-phonon with empty lattice", "note": "", "md_link_text": "elphem.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.6_Tight_Binding/elphem.md", "papers": [], "paper_placeholder": true, "slug": "elphem", "idx": 583, "overview": "**elphem** is a tool for electron-phonon calculations using the empty lattice (free electron) model, providing a simplified approach to electron-phonon coupling." }, { "num": "314", "name": "kgrid", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/WMD-group/kgrid", "note": "", "md_link_text": "kgrid.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.7_K_Path_BZ/kgrid.md", "papers": [], "paper_placeholder": true, "slug": "kgrid", "idx": 584, "overview": "kgrid is a Python tool for calculating the required k-point density from input geometry for periodic quantum chemistry calculations. It uses a length cutoff approach to determine appropriate Monkhorst-Pack grids, ensuring consistent k-point density across different cell sizes and shapes." }, { "num": "315", "name": "KpLib", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://gitlab.com/muellergroup/kplib", "note": "", "md_link_text": "KpLib.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.7_K_Path_BZ/KpLib.md", "papers": [ { "name": "KpLib_10.1016_j.commatsci.2020.110100.pdf", "path": "Papers_of_Codes/Post-Processing/KpLib/KpLib_10.1016_j.commatsci.2020.110100.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2020.110100" } ], "paper_placeholder": false, "slug": "KpLib", "idx": 585, "overview": "KpLib is a k-point grid generation library providing optimal k-point meshes for DFT calculations based on the Mueller group's research at Johns Hopkins University. It generates generalized regular grids that are more efficient than standard Monkhorst-Pack grids while maintaining the same accuracy." }, { "num": "316", "name": "Brillouin-zone-navigator", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "Interactive BZ visualization", "note": "", "md_link_text": "Brillouin-zone-navigator.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.7_K_Path_BZ/Brillouin-zone-navigator.md", "papers": [], "paper_placeholder": true, "slug": "Brillouin-zone-navigator", "idx": 586, "overview": "**Brillouin-zone-navigator** is an interactive tool for visualizing and navigating Brillouin zones of crystal structures." }, { "num": "317", "name": "pawpyseed", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/kylebystrom/pawpyseed", "note": "", "md_link_text": "pawpyseed.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.8_Wavefunction_Analysis/pawpyseed.md", "papers": [ { "name": "pawpyseed_10.48550_arXiv.1904.11572.pdf", "path": "Papers_of_Codes/Post-Processing/pawpyseed/pawpyseed_10.48550_arXiv.1904.11572.pdf", "doi_url": "https://doi.org/10.48550/arXiv.1904.11572" } ], "paper_placeholder": false, "slug": "pawpyseed", "idx": 587, "overview": "pawpyseed is a parallel C/Python package for numerical analysis of PAW (Projector Augmented Wave) DFT wavefunctions from VASP calculations. It enables reconstruction of all-electron wavefunctions from pseudo-wavefunctions and PAW projectors, essential for accurate defect analysis and wavefunction overlap calculations." }, { "num": "317a", "name": "VASPBERRY", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/Infant83/VASPBERRY", "note": "Berry curvature and Chern number from VASP WAVECAR using Fukui's method", "md_link_text": "VASPBERRY.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.8_Wavefunction_Analysis/VASPBERRY.md", "papers": [ { "name": "Kresse_Furthmuller_1996.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/Kresse_Furthmuller_1996.pdf", "doi_url": "https://scholar.google.com/scholar?q=VASPBERRY+Kresse+Furthmuller+1996" }, { "name": "Kresse_Hafner_1993.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/Kresse_Hafner_1993.pdf", "doi_url": "https://scholar.google.com/scholar?q=VASPBERRY+Kresse+Hafner+1993" }, { "name": "10.1016_0927-0256(96)00008-0.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/10.1016_0927-0256%2896%2900008-0.pdf", "doi_url": "https://doi.org/10.1016/0927-0256(96)00008-0" } ], "paper_placeholder": false, "slug": "VASPBERRY", "idx": 588, "overview": "**VASPBERRY** is a post-processing tool for computing Berry curvature and Chern numbers from VASP WAVECAR output. It uses Fukui's method to calculate Berry curvature and Chern numbers directly from the Bloch wavefunction information stored in VASP's WAVECAR file." }, { "num": "317b", "name": "pyvaspwfc", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.1", "subcategory": "Band Structure & Electronic Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/liming-liu/pyvaspwfc", "note": "WAVECAR parsing with real-space wavefunction visualization and band unfolding", "md_link_text": "pyvaspwfc.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/8.1.8_Wavefunction_Analysis/pyvaspwfc.md", "papers": [], "paper_placeholder": true, "slug": "pyvaspwfc", "idx": 589, "overview": "**pyvaspwfc** is a Python class for dealing with VASP pseudo-wavefunction file WAVECAR. It can extract planewave coefficients of any Kohn-Sham orbital, perform band unfolding, and visualize wavefunctions in real space via 3D Fourier transform." }, { "num": "318", "name": "irvsp", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/zjwang11/irvsp", "note": "", "md_link_text": "irvsp.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.1_Irreducible_Representations/irvsp.md", "papers": [ { "name": "irvsp_10.1016_j.cpc.2020.107760.pdf", "path": "Papers_of_Codes/Post-Processing/irvsp/irvsp_10.1016_j.cpc.2020.107760.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2020.107760" } ], "paper_placeholder": false, "slug": "irvsp", "idx": 590, "overview": "irvsp is a program to compute the irreducible representations (irrep) of electronic states in VASP calculations. It determines the symmetry of Bloch wavefunctions at high-symmetry points in the Brillouin zone, which is crucial for identifying topological phases of matter, enforcing selection rules, and analyzing band connectivity." }, { "num": "319", "name": "IrRep", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/stepan-tsirkin/irrep", "note": "", "md_link_text": "IrRep.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.1_Irreducible_Representations/IrRep.md", "papers": [ { "name": "10_1016_j_cpc_2021_108226.pdf", "path": "Papers_of_Codes/TightBinding/4.4_Topological_Analysis/IrRep/10_1016_j_cpc_2021_108226.pdf", "doi_url": "https://scholar.google.com/scholar?q=IrRep+10+1016+j+cpc+2021+108226" } ], "paper_placeholder": false, "slug": "IrRep", "idx": 591, "overview": "IrRep is a Python code for calculating the irreducible representations of Bloch states in ab-initio calculations. It interfaces with Quantum ESPRESSO, VASP, and Abinit to determine the symmetry properties of electronic bands, which is essential for identifying topological invariants, enforcing selection rules, and understanding band connectivity." }, { "num": "320", "name": "SpaceGroupIrep", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/goodluck1982/SpaceGroupIrep", "note": "Mathematica package for space group irreps (BC convention)", "md_link_text": "SpaceGroupIrep.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.1_Irreducible_Representations/SpaceGroupIrep.md", "papers": [ { "name": "SpaceGroupIrep_10.1016_j.cpc.2021.107993.pdf", "path": "Papers_of_Codes/Post-Processing/SpaceGroupIrep/SpaceGroupIrep_10.1016_j.cpc.2021.107993.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2021.107993" } ], "paper_placeholder": false, "slug": "SpaceGroupIrep", "idx": 592, "overview": "SpaceGroupIrep is a Mathematica program package providing a comprehensive database and tool set for irreducible representations (IRs) of space groups in the Bradley-Cracknell (BC) convention. It enables calculation of character tables, representation matrices, and compatibility relations for all 230 space groups." }, { "num": "321", "name": "spgrep", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/spglib/spgrep", "note": "On-the-fly space-group irrep generator (JOSS published)", "md_link_text": "spgrep.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.1_Irreducible_Representations/spgrep.md", "papers": [ { "name": "spgrep_10.21105_joss.05269.pdf", "path": "Papers_of_Codes/Post-Processing/spgrep/spgrep_10.21105_joss.05269.pdf", "doi_url": "https://doi.org/10.21105/joss.05269" } ], "paper_placeholder": false, "slug": "spgrep", "idx": 593, "overview": "spgrep is a Python package for on-the-fly generation of space-group irreducible representations. It computes irreducible representations (irreps) and their characters for any space group at arbitrary k-points, without relying on pre-tabulated databases. This enables flexible symmetry analysis for band structure calculations." }, { "num": "322", "name": "qeirreps", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/mizoguche/qeirreps", "note": "Quantum ESPRESSO irreducible representations (CPC published)", "md_link_text": "qeirreps.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.1_Irreducible_Representations/qeirreps.md", "papers": [ { "name": "qeirreps_10.1016_j.cpc.2021.107948.pdf", "path": "Papers_of_Codes/Post-Processing/qeirreps/qeirreps_10.1016_j.cpc.2021.107948.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2021.107948" } ], "paper_placeholder": false, "slug": "qeirreps", "idx": 594, "overview": "qeirreps is an open-source program that computes irreducible representations of Bloch wavefunctions from Quantum ESPRESSO output. It analyzes the symmetry character of electronic bands at high-symmetry k-points, enabling topological classification and symmetry-based materials analysis." }, { "num": "323", "name": "spgrep-modulation", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/phonopy/spgrep-modulation", "note": "Collective atomic modulation analysis with irreps", "md_link_text": "spgrep-modulation.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.1_Irreducible_Representations/spgrep-modulation.md", "papers": [], "paper_placeholder": true, "slug": "spgrep-modulation", "idx": 595, "overview": "spgrep-modulation is a Python package for collective atomic modulation analysis using irreducible space-group representations. It enables systematic study of structural phase transitions, phonon instabilities, and order parameter analysis through group-theoretical methods integrated with phonopy." }, { "num": "324", "name": "WannSymm", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/ccao/WannSymm", "note": "Symmetry analysis and symmetrization for Wannier orbitals (CPC 2022)", "md_link_text": "WannSymm.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.1_Irreducible_Representations/WannSymm.md", "papers": [], "paper_placeholder": true, "slug": "WannSymm", "idx": 596, "overview": "WannSymm is a symmetry analysis code for Wannier orbitals. It analyzes the symmetry properties of Wannier functions obtained from Wannier90 calculations and can symmetrize tight-binding Hamiltonians to restore exact crystallographic symmetry that may be broken due to numerical errors." }, { "num": "325", "name": "BerryPI", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/stepan-tsirkin/berryphase", "note": "", "md_link_text": "BerryPI.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.2_Topological_Invariants/BerryPI.md", "papers": [ { "name": "10_1103_PhysRevB_63_155107.pdf", "path": "Papers_of_Codes/Post-Processing/8.2_Topological_Symmetry/8.2.2_Topological_Invariants/BerryPI/10_1103_PhysRevB_63_155107.pdf", "doi_url": "https://scholar.google.com/scholar?q=BerryPI+10+1103+PhysRevB+63+155107" } ], "paper_placeholder": false, "slug": "BerryPI", "idx": 597, "overview": "BerryPI is a Python software for calculating Berry phases and related properties from first-principles wavefunctions. It specifically focuses on the modern theory of polarization and the calculation of the spontaneous electric polarization in crystalline solids. It interfaces with VASP to extract the necessary Bloch functions." }, { "num": "326", "name": "Chern-Number", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/stepan-tsirkin/chern-number", "note": "", "md_link_text": "Chern-Number.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.2_Topological_Invariants/Chern-Number.md", "papers": [], "paper_placeholder": true, "slug": "Chern-Number", "idx": 598, "overview": "Chern-Number is a code for calculating the Chern number, a topological invariant, using the discretized Berry curvature on a grid. It post-processes output from Wannier90 or tight-binding models to determine the topological character of 2D band structures and detect topological phase transitions." }, { "num": "327", "name": "Berry-Phase", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "**METHOD** - Implemented in VASP, ABINIT, etc.", "note": "", "md_link_text": "Berry-Phase.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.2_Topological_Invariants/Berry-Phase.md", "papers": [ { "name": "10_1103_PhysRevB_63_155107.pdf", "path": "Papers_of_Codes/Post-Processing/8.2_Topological_Symmetry/8.2.2_Topological_Invariants/BerryPI/10_1103_PhysRevB_63_155107.pdf", "doi_url": "https://scholar.google.com/scholar?q=Berry-Phase+10+1103+PhysRevB+63+155107" } ], "paper_placeholder": false, "slug": "Berry-Phase", "idx": 599, "overview": "berry is a Python code for the differentiation of Bloch wavefunctions from DFT calculations. It calculates Berry connections, Berry curvature, and topological invariants (Chern numbers, Z2) by unwinding the phase of the Bloch states. It also computes nonlinear optical properties like second harmonic generation (SHG) and anomalous Hall conductivity." }, { "num": "328", "name": "BerryEasy", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "arXiv:2312.13051", "note": "GPU-enabled nth-order and spin-resolved topology", "md_link_text": "BerryEasy.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.2_Topological_Invariants/BerryEasy.md", "papers": [ { "name": "BerryEasy_10.48550_arXiv.2312.13051.pdf", "path": "Papers_of_Codes/Post-Processing/BerryEasy/BerryEasy_10.48550_arXiv.2312.13051.pdf", "doi_url": "https://doi.org/10.48550/arXiv.2312.13051" } ], "paper_placeholder": false, "slug": "BerryEasy", "idx": 600, "overview": "BerryEasy is a GPU-enabled Python package for diagnosis of nth-order and spin-resolved topology in the presence of fields and effects. It provides efficient computation of nested Wilson loops, spin-resolved Wilson loops, and various topological invariants using GPU acceleration for performance." }, { "num": "329", "name": "WloopPHI", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "Comput. Phys. Commun. 270, 108147 (2022)", "note": "WIEN2k Wilson loop for Weyl semimetals", "md_link_text": "WloopPHI.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.2_Topological_Invariants/WloopPHI.md", "papers": [ { "name": "WloopPHI_10.1016_j.cpc.2021.108147.pdf", "path": "Papers_of_Codes/Post-Processing/WloopPHI/WloopPHI_10.1016_j.cpc.2021.108147.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2021.108147" } ], "paper_placeholder": false, "slug": "WloopPHI", "idx": 601, "overview": "WloopPHI is a Python code that expands the features of WIEN2k by enabling characterization of Weyl semimetals through Wilson loop calculations. It computes the winding of hybrid Wannier charge centers to identify and characterize Weyl points, nodal lines, and other topological features in the band structure." }, { "num": "330", "name": "topo_2bands", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/jameclear/topo_2bands", "note": "Two-band topological invariant calculator", "md_link_text": "topo_2bands.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.2_Topological_Invariants/topo_2bands.md", "papers": [], "paper_placeholder": true, "slug": "topo_2bands", "idx": 602, "overview": "topo_2bands is a program for calculating typical topological invariants based on minimum two-band tight-binding models. It computes Berry phase, winding number, Chern number, and Z2 invariant, as well as edge states and Fermi arc states in 2D and 3D gapless systems." }, { "num": "331", "name": "TIM", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/Hugo-loio/TIM", "note": "C++ Topological Insulator Models", "md_link_text": "TIM.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.2_Topological_Invariants/TIM.md", "papers": [], "paper_placeholder": true, "slug": "TIM", "idx": 603, "overview": "Topological Insulator Models (TIM) provides C++ classes for tight-binding models of topological insulators. It offers efficient implementations for studying various topological phases including topological insulators, Weyl semimetals, and related systems with a focus on performance and flexibility." }, { "num": "332", "name": "WIEN2k-Topo", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "arXiv:2303.16306, CPC 2023", "note": "CherN/wcc modules for Chern and Z2 invariants in WIEN2k", "md_link_text": "WIEN2k-Topo.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.2_Topological_Invariants/WIEN2k-Topo.md", "papers": [ { "name": "Blaha_et_al_2020.pdf", "path": "Papers_of_Codes/DFT/1.2_All-Electron/WIEN2k/Blaha_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=WIEN2k-Topo+Blaha+et+al+2020" } ], "paper_placeholder": false, "slug": "WIEN2k-Topo", "idx": 604, "overview": "WIEN2k-Topo comprises two Python modules (CherN.py and wcc.py) that expand the functionalities of the all-electron full-potential WIEN2k package for computing Chern and Z2 topological invariants. These complement the WloopPHI module to provide a complete toolkit for topological characterization." }, { "num": "333", "name": "kdotp-symmetry", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/greschd/kdotp-symmetry", "note": "Symmetry-constrained k\u00b7p Hamiltonian generator (Phys. Rev. Materials)", "md_link_text": "kdotp-symmetry.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.3_KP_Hamiltonians/kdotp-symmetry.md", "papers": [ { "name": "kdotp-symmetry_10.1103_PhysRevMaterials.2.103805.pdf", "path": "Papers_of_Codes/Post-Processing/kdotp-symmetry/kdotp-symmetry_10.1103_PhysRevMaterials.2.103805.pdf", "doi_url": "https://doi.org/10.1103/PhysRevMaterials.2.103805" } ], "paper_placeholder": false, "slug": "kdotp-symmetry", "idx": 605, "overview": "kdotp-symmetry is a Python tool for calculating the general form of a k\u00b7p Hamiltonian under given symmetry constraints. It automatically derives the allowed terms in an effective Hamiltonian near a high-symmetry k-point by analyzing the little group symmetry operations and basis function transformations." }, { "num": "334", "name": "kdotp-generator", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/yjiang-iop/kdotp-generator", "note": "k\u00b7p generator with magnetic space group support", "md_link_text": "kdotp-generator.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.3_KP_Hamiltonians/kdotp-generator.md", "papers": [], "paper_placeholder": true, "slug": "kdotp-generator", "idx": 606, "overview": "kdotp-generator is a tool for automatically generating k\u00b7p effective Hamiltonians, extending the kdotp-symmetry package. It includes support for magnetic space groups and provides pre-computed results for many magnetic and non-magnetic space groups, enabling rapid model development." }, { "num": "335", "name": "DFT2kp", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "SciPost Phys. Codebases 25 (2024), arXiv:2306.08554", "note": "Extract Kane/Luttinger k\u00b7p parameters from Quantum ESPRESSO", "md_link_text": "DFT2kp.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.3_KP_Hamiltonians/DFT2kp.md", "papers": [], "paper_placeholder": true, "slug": "DFT2kp", "idx": 607, "overview": "DFT2kp is a code to explicitly calculate Kane (linear in k) and Luttinger (quadratic in k) parameters of k\u00b7p effective Hamiltonians directly from ab initio wavefunctions provided by Quantum ESPRESSO. It analyzes symmetry transformations to construct optimal symmetry-adapted bases for effective models." }, { "num": "336", "name": "findmagsym", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.2", "subcategory": "Topological & Symmetry Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/yuanlinding/findmagsym", "note": "Web app for magnetic space group determination", "md_link_text": "findmagsym.md", "md_link_path": "Post-Processing/8.2_Topological_Symmetry/8.2.4_Magnetic_Symmetry/findmagsym.md", "papers": [], "paper_placeholder": true, "slug": "findmagsym", "idx": 608, "overview": "findmagsym is a web-based application for finding the magnetic space group of a magnetic crystal structure. It takes a crystal structure with magnetic moments as input and determines the appropriate magnetic space group, generating MCIF (Magnetic CIF) format output files compatible with visualization and analysis tools." }, { "num": "337", "name": "BoltzTraP", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://www.imc.tuwien.ac.at/forschungsbereich_theoretische_chemie/forschungsgruppen/prof_dr_gkh_madsen/the_boltzmann_transport_property_package/", "note": "", "md_link_text": "BoltzTraP.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/BoltzTraP.md", "papers": [ { "name": "10.1016_j.cpc.2006.03.007.pdf", "path": "Papers_of_Codes/Post-Processing/8.3_Transport_Properties/BoltzTraP/10.1016_j.cpc.2006.03.007.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2006.03.007" } ], "paper_placeholder": false, "slug": "BoltzTraP", "idx": 609, "overview": "BoltzTraP (Boltzmann Transport Properties) is a code for calculating electronic transport properties (Seebeck coefficient, electrical conductivity, electronic thermal conductivity) as a function of temperature and chemical potential. It solves the semi-classical Boltzmann transport equation within the constant relaxation time approximation (RTA), using a smoothed Fourier interpolation of the bands." }, { "num": "338", "name": "BoltzTraP2", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/gautierabsi/BoltzTraP2", "note": "", "md_link_text": "BoltzTraP2.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/BoltzTraP2.md", "papers": [ { "name": "10.1016_j.cpc.2018.05.010.pdf", "path": "Papers_of_Codes/Post-Processing/8.3_Transport_Properties/BoltzTraP2/10.1016_j.cpc.2018.05.010.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2018.05.010" } ], "paper_placeholder": false, "slug": "BoltzTraP2", "idx": 610, "overview": "BoltzTraP2 is the modern Python-based successor to the widely used BoltzTraP code. It calculates electronic transport properties (Seebeck coefficient, conductivity, thermal conductivity, Hall coefficient) using the Boltzmann transport equation within the relaxation time approximation. BoltzTraP2 improves upon the original by using a more stable interpolation method, offering a Python API, and providing better integration with modern DFT workflows (via ASE, pymatgen)." }, { "num": "339", "name": "AMSET", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/hackingmaterials/amset", "note": "", "md_link_text": "AMSET.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/AMSET.md", "papers": [ { "name": "10.1038_s41467-021-22440-5.pdf", "path": "Papers_of_Codes/Post-Processing/8.3_Transport_Properties/AMSET/10.1038_s41467-021-22440-5.pdf", "doi_url": "https://doi.org/10.1038/s41467-021-22440-5" } ], "paper_placeholder": false, "slug": "AMSET", "idx": 611, "overview": "" }, { "num": "342", "name": "ElecTra (ELECTRA)", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/PatrizioGraziosi/ELECTRA", "note": "Full-band electronic transport and thermoelectric coefficients from the linearized BTE.", "md_link_text": "ElecTra.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/ElecTra.md", "papers": [ { "name": "ElecTra_(ELECTRA)_10.48550_arXiv.2208.00745.pdf", "path": "Papers_of_Codes/Post-Processing/ElecTra_%28ELECTRA%29/ElecTra_%28ELECTRA%29_10.48550_arXiv.2208.00745.pdf", "doi_url": "https://doi.org/10.48550/arXiv.2208.00745" } ], "paper_placeholder": false, "slug": "ElecTra-ELECTRA", "idx": 612, "overview": "ElecTra (often referenced as ELECTRA) is an open-source code for computing electronic and thermoelectric transport coefficients from a full electronic band structure by solving the linearized Boltzmann transport equation (BTE) under momentum-relaxation-time-type approximations. It targets semiconductor transport where scattering rates can depend on carrier energy, momentum, and band index." }, { "num": "343", "name": "TransOpt", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/yangjio4849/TransOpt", "note": "Electrical transport coefficients (Seebeck, conductivity, electronic thermal conductivity) for VASP users.", "md_link_text": "TransOpt.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/TransOpt.md", "papers": [ { "name": "TransOpt_10.1016_j.commatsci.2020.110074.pdf", "path": "Papers_of_Codes/Post-Processing/TransOpt/TransOpt_10.1016_j.commatsci.2020.110074.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2020.110074" } ], "paper_placeholder": false, "slug": "TransOpt", "idx": 613, "overview": "TransOpt is a transport post-processing package intended for VASP users to compute electrical transport coefficients, including Seebeck coefficients, electrical conductivities, and electronic thermal conductivities. The repository documentation describes two approaches: a momentum-matrix based method and a derivative method similar in spirit to the approach used by BoltzTraP-type workflows." }, { "num": "344", "name": "AICON2", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/Baijianlu/AICON2", "note": "Transport property estimation (electronic and thermal) with fast approximate models.", "md_link_text": "AICON2.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/AICON2.md", "papers": [ { "name": "AICON2_10.1016_j.cpc.2021.108027.pdf", "path": "Papers_of_Codes/Post-Processing/AICON2/AICON2_10.1016_j.cpc.2021.108027.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2021.108027" } ], "paper_placeholder": false, "slug": "AICON2", "idx": 614, "overview": "AICON2 is a program aimed at fast estimation of transport properties, including electronic transport quantities and thermal transport quantities, using approximate models designed for efficiency. It is positioned for applications where rapid screening is needed." }, { "num": "345", "name": "AMMCR", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/anup12352/AMMCR", "note": "Ab initio mobility and conductivity calculation using the Rode algorithm (VASP interface).", "md_link_text": "AMMCR.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/AMMCR.md", "papers": [ { "name": "AMMCR_10.1016_j.cpc.2020.107697.pdf", "path": "Papers_of_Codes/Post-Processing/AMMCR/AMMCR_10.1016_j.cpc.2020.107697.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2020.107697" } ], "paper_placeholder": false, "slug": "AMMCR", "idx": 615, "overview": "AMMCR is a code for computing carrier mobility and conductivity using the Rode algorithm, with inputs prepared from first-principles electronic structure calculations. The repository describes an interface targeting VASP output files." }, { "num": "346", "name": "ThermoElectric", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/ariahosseini/ThermoElectric", "note": "Computational framework to compute electron transport coefficients.", "md_link_text": "ThermoElectric.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/ThermoElectric.md", "papers": [], "paper_placeholder": true, "slug": "ThermoElectric", "idx": 616, "overview": "ThermoElectric is a computational framework that computes electron transport coefficients for thermoelectric analysis. It is intended to streamline evaluation of electronic transport quantities used in thermoelectric studies." }, { "num": "347", "name": "TEprop2D", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/artnugraha/TEprop2D", "note": "Thermoelectric properties of 2D materials using Quantum ESPRESSO and EPW outputs.", "md_link_text": "TEprop2D.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/TEprop2D.md", "papers": [], "paper_placeholder": true, "slug": "TEprop2D", "idx": 617, "overview": "TEprop2D is a lightweight Fortran program to calculate thermoelectric transport properties of 2D materials using outputs produced by Quantum ESPRESSO and EPW. It is designed to compute standard thermoelectric quantities as a function of Fermi level and temperature for 2D systems." }, { "num": "348", "name": "kubocalc", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/janbbeck/kubocalc", "note": "Kubo-Greenwood based Quantum ESPRESSO plugin for electrical/thermal conductivity and Seebeck coefficient.", "md_link_text": "kubocalc.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/kubocalc.md", "papers": [], "paper_placeholder": true, "slug": "kubocalc", "idx": 618, "overview": "kubocalc is a Kubo-Greenwood based plugin/workflow for Quantum ESPRESSO intended to compute electronic transport coefficients such as electrical conductivity, electronic thermal conductivity, and the Seebeck coefficient from first-principles molecular dynamics (or sampled configurations) and electronic structure data." }, { "num": "349", "name": "kg4vasp", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/conodipaola/kg4vasp", "note": "Kubo-Greenwood transport coefficients from first-principles molecular dynamics with VASP.", "md_link_text": "kg4vasp.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/kg4vasp.md", "papers": [], "paper_placeholder": true, "slug": "kg4vasp", "idx": 619, "overview": "kg4vasp is a post-processing workflow for computing transport properties using the generalized Kubo-Greenwood approach from first-principles molecular dynamics with VASP. It is intended for calculating electrical conductivity and related quantities from VASP matrix elements and/or compatible inputs." }, { "num": "350", "name": "LanTraP", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://nanohub.org/resources/lantrap", "note": "Landauer-based thermoelectric transport (distribution of modes) from band structure inputs.", "md_link_text": "LanTraP.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/LanTraP.md", "papers": [ { "name": "LanTraP_10.48550_arXiv.1806.08888.pdf", "path": "Papers_of_Codes/Post-Processing/LanTraP/LanTraP_10.48550_arXiv.1806.08888.pdf", "doi_url": "https://doi.org/10.48550/arXiv.1806.08888" } ], "paper_placeholder": false, "slug": "LanTraP", "idx": 620, "overview": "LanTraP is a tool for calculating semi-classical thermoelectric and electronic transport properties using a Landauer transport formulation expressed in terms of the distribution of modes (DOM). It is conceptually similar to Boltzmann approaches and can be driven by band-structure inputs, enabling band-counting and mode-based analysis of thermoelectric performance." }, { "num": "351", "name": "gkx", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/sirmarcel/gkx", "note": "JAX-based Green-Kubo workflow for anharmonic thermal conductivity.", "md_link_text": "gkx.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/gkx.md", "papers": [], "paper_placeholder": true, "slug": "gkx", "idx": 621, "overview": "gkx is a JAX-based workflow for computing thermal conductivity using Green\u2013Kubo relations, designed to integrate with modern machine-learned interatomic potentials and to support efficient anharmonic thermal transport calculations from molecular dynamics trajectories." }, { "num": "352", "name": "mDCThermalC", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/Baijianlu/mDCThermalC", "note": "Modified Debye-Callaway model for lattice thermal conductivity.", "md_link_text": "mDCThermalC.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/mDCThermalC.md", "papers": [ { "name": "mDCThermalC_10.48550_arXiv.1911.12565.pdf", "path": "Papers_of_Codes/Post-Processing/mDCThermalC/mDCThermalC_10.48550_arXiv.1911.12565.pdf", "doi_url": "https://doi.org/10.48550/arXiv.1911.12565" } ], "paper_placeholder": false, "slug": "mDCThermalC", "idx": 622, "overview": "mDCThermalC is a software tool for fast estimation of lattice thermal conductivity using a modified Debye\u2013Callaway type approach. It targets rapid screening and approximate thermal transport evaluation." }, { "num": "353", "name": "empirical_thermal_conductivity", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/houzf/empirical_thermal_conductivity", "note": "Thermal conductivity estimates from empirical models (Clarke, Cahill-Pohl, Slack).", "md_link_text": "empirical_thermal_conductivity.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/empirical_thermal_conductivity.md", "papers": [], "paper_placeholder": true, "slug": "empirical_thermal_conductivity", "idx": 623, "overview": "empirical_thermal_conductivity is a tool to estimate lattice thermal conductivity using empirical models, including Clarke\u2019s, Cahill\u2013Pohl\u2019s, and Slack\u2019s models. It is designed for quick estimates and comparisons when full phonon-BTE calculations are not required." }, { "num": "354", "name": "Unifiedkappa-phonopy", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/yimavxia/Unifiedkappa-phonopy", "note": "Tools for phonon thermal conductivity analysis (including diagonal and off-diagonal contributions).", "md_link_text": "Unifiedkappa-phonopy.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/Unifiedkappa-phonopy.md", "papers": [], "paper_placeholder": true, "slug": "Unifiedkappa-phonopy", "idx": 624, "overview": "Unifiedkappa-phonopy is a set of scripts and a modified phonopy-related workflow for analyzing lattice thermal conductivity, including separating diagonal and off-diagonal contributions. It is typically used in conjunction with phonon-BTE solvers (e.g., ShengBTE) and phonon workflow data." }, { "num": "355", "name": "topological-insulator-spin-hall", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/smfarzaneh/topological-insulator-spin-hall", "note": "Ab initio spin Hall conductivity workflow using Quantum ESPRESSO and Wannier90.", "md_link_text": "topological-insulator-spin-hall.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/topological-insulator-spin-hall.md", "papers": [ { "name": "topological-insulator-spin-hall_10.1103_PhysRevMaterials.4.114202.pdf", "path": "Papers_of_Codes/Post-Processing/topological-insulator-spin-hall/topological-insulator-spin-hall_10.1103_PhysRevMaterials.4.114202.pdf", "doi_url": "https://doi.org/10.1103/PhysRevMaterials.4.114202" } ], "paper_placeholder": false, "slug": "topological-insulator-spin-hall", "idx": 625, "overview": "This repository provides an ab initio workflow to compute spin Hall conductivity in topological insulators using Quantum ESPRESSO and Wannier90-derived interpolations (as described by the repository). It is a practical implementation-oriented code base for spin Hall transport calculations." }, { "num": "356", "name": "MD-GreenKubo-Thermal-Conductivity", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/erny123/MD-GreenKubo-Thermal-Conductivity", "note": "Green-Kubo thermal conductivity post-processing for molecular dynamics trajectories.", "md_link_text": "MD-GreenKubo-Thermal-Conductivity.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/MD-GreenKubo-Thermal-Conductivity.md", "papers": [], "paper_placeholder": true, "slug": "MD-GreenKubo-Thermal-Conductivity", "idx": 626, "overview": "MD-GreenKubo-Thermal-Conductivity is a set of scripts and examples for computing thermal conductivity from molecular dynamics simulations using the Green\u2013Kubo formalism. It targets the practical workflow of taking heat-flux outputs (e.g., from LAMMPS) and performing correlation/integration analysis." }, { "num": "357", "name": "ElasTool", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/zhongliliu/elastool", "note": "Automated elastic constants and mechanical properties from DFT, finite-temperature", "md_link_text": "ElasTool.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/ElasTool.md", "papers": [], "paper_placeholder": true, "slug": "ElasTool", "idx": 627, "overview": "**ElasTool** is a toolkit for automatic calculation and analysis of elastic constants and mechanical properties of materials using first-principles DFT. It supports both zero-temperature and finite-temperature elastic properties via ab initio molecular dynamics, with VASP as the primary DFT backend." }, { "num": "357a", "name": "pymatgen-analysis-diffusion", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/materialsvirtuallab/pymatgen-analysis-diffusion", "note": "Pymatgen add-on for ionic diffusion and conductivity analysis from MD", "md_link_text": "pymatgen-analysis-diffusion.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/pymatgen-analysis-diffusion.md", "papers": [ { "name": "10.1016_j.commatsci.2012.10.028.pdf", "path": "Papers_of_Codes/Frameworks/9.1_General_Purpose_Libraries/pymatgen-db/10.1016_j.commatsci.2012.10.028.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2012.10.028" } ], "paper_placeholder": false, "slug": "pymatgen-analysis-diffusion", "idx": 628, "overview": "**pymatgen-analysis-diffusion** (formerly pymatgen-diffusion) is an add-on to pymatgen for diffusion analysis. It provides tools for analyzing molecular dynamics trajectories for ionic diffusion, including MSD/MSD analysis, conductivity calculation, and Arrhenius plot generation." }, { "num": "357b", "name": "MechElastic", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/romerogroup/MechElastic", "note": "Comprehensive elastic property analysis (Debye temp, melting temp, anisotropy) from Cij", "md_link_text": "MechElastic.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/MechElastic.md", "papers": [ { "name": "MechElastic_10.1016_j.cpc.2021.108068.pdf", "path": "Papers_of_Codes/Post-Processing/MechElastic/MechElastic_10.1016_j.cpc.2021.108068.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2021.108068" } ], "paper_placeholder": false, "slug": "MechElastic", "idx": 629, "overview": "**MechElastic** is a Python library to calculate physical properties from elastic tensors of all crystalline systems. It computes elastic moduli, melting temperature, Debye temperature, elastic wave velocities, elastic anisotropy, and mechanical stability from the elastic constant tensor." }, { "num": "357c", "name": "mech2d", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.3", "subcategory": "Transport Properties", "confidence": "VERIFIED", "official_url": "https://github.com/haidi-ustc/mech2d", "note": "2D-specific elastic constants and stress-strain with automated VASP workflow", "md_link_text": "mech2d.md", "md_link_path": "Post-Processing/8.3_Transport_Properties/mech2d.md", "papers": [], "paper_placeholder": true, "slug": "mech2d", "idx": 630, "overview": "**mech2d** is a Python package for calculating mechanical properties of two-dimensional materials. It computes elastic constant tensors, stress-strain curves, and related properties for 2D systems with automated VASP workflow for deformation calculations." }, { "num": "277", "name": "Lobster", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://www.cochem2.de/", "note": "", "md_link_text": "Lobster.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/Lobster.md", "papers": [ { "name": "10_1021_jp202489s.pdf", "path": "Papers_of_Codes/Post-Processing/8.4_Chemical_Bonding/Lobster/10_1021_jp202489s.pdf", "doi_url": "https://scholar.google.com/scholar?q=Lobster+10+1021+jp202489s" }, { "name": "10_1002_jcc_24300.pdf", "path": "Papers_of_Codes/Post-Processing/8.4_Chemical_Bonding/Lobster/10_1002_jcc_24300.pdf", "doi_url": "https://scholar.google.com/scholar?q=Lobster+10+1002+jcc+24300" } ], "paper_placeholder": false, "slug": "Lobster", "idx": 631, "overview": "Lobster (Local Orbital Basis Suite Towards Electronic-Structure Reconstruction) is a program for chemical bonding analysis based on projecting plane-wave DFT calculations onto a local basis. It enables the calculation of Crystal Orbital Hamilton Populations (COHP), Crystal Orbital Overlap Populations (COOP), and related bonding descriptors from PAW or pseudopotential calculations." }, { "num": "278", "name": "LobsterPy", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/JaGeo/lobsterpy", "note": "", "md_link_text": "LobsterPy.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/LobsterPy.md", "papers": [ { "name": "10_1021_jp202489s.pdf", "path": "Papers_of_Codes/Post-Processing/8.4_Chemical_Bonding/Lobster/10_1021_jp202489s.pdf", "doi_url": "https://scholar.google.com/scholar?q=LobsterPy+10+1021+jp202489s" }, { "name": "10_1002_jcc_24300.pdf", "path": "Papers_of_Codes/Post-Processing/8.4_Chemical_Bonding/Lobster/10_1002_jcc_24300.pdf", "doi_url": "https://scholar.google.com/scholar?q=LobsterPy+10+1002+jcc+24300" } ], "paper_placeholder": false, "slug": "LobsterPy", "idx": 632, "overview": "LobsterPy is a Python package for analyzing and plotting data from the LOBSTER code (Local Orbital Basis Suite Towards Electronic-Structure Reconstruction). It automates the analysis of chemical bonding information (COHP, COOP) and provides tools for visualizing bonding properties, stability analysis, and extracting key bonding descriptors automatically." }, { "num": "279", "name": "COHP", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "**MODULE** - Part of LOBSTER.", "note": "", "md_link_text": "COHP.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/COHP.md", "papers": [ { "name": "COHP_10.1021_j100135a014.pdf", "path": "Papers_of_Codes/Post-Processing/COHP/COHP_10.1021_j100135a014.pdf", "doi_url": "https://doi.org/10.1021/j100135a014" } ], "paper_placeholder": false, "slug": "COHP", "idx": 633, "overview": "**Status**: METHOD/TOOL - COHP refers to the Crystal Orbital Hamilton Population method, a theoretical framework for analyzing chemical bonding in solids by partitioning the band structure energy into bonding and antibonding contributions. While \"COHP\" is a method, the term is often used to refer to the LOBSTER code (which implements it) or legacy codes like Cray-COHP." }, { "num": "280", "name": "Bader", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "http://theory.cm.utexas.edu/henkelman/code/bader/", "note": "", "md_link_text": "Bader.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/Bader.md", "papers": [ { "name": "10_1016_j_commatsci_2005_04_010.pdf", "path": "Papers_of_Codes/Post-Processing/8.4_Chemical_Bonding/Bader/10_1016_j_commatsci_2005_04_010.pdf", "doi_url": "https://scholar.google.com/scholar?q=Bader+10+1016+j+commatsci+2005+04+010" } ], "paper_placeholder": false, "slug": "Bader", "idx": 634, "overview": "The Henkelman Group Bader code is a widely used software for performing Bader charge analysis. It partitions the charge density of a system into atomic volumes based on zero-flux surfaces of the electron density gradient. By integrating the charge within these Bader volumes, it assigns partial charges to atoms, providing a physically motivated way to define oxidation states and charge transfer." }, { "num": "281", "name": "DDEC", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://sourceforge.net/projects/ddec/", "note": "", "md_link_text": "DDEC.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/DDEC.md", "papers": [ { "name": "10_1039_C6RA04656H.pdf", "path": "Papers_of_Codes/Post-Processing/8.4_Chemical_Bonding/DDEC/10_1039_C6RA04656H.pdf", "doi_url": "https://scholar.google.com/scholar?q=DDEC+10+1039+C6RA04656H" } ], "paper_placeholder": false, "slug": "DDEC", "idx": 635, "overview": "DDEC (Density Derived Electrostatic and Chemical) is a method and software code (`chargemol`) for computing net atomic charges, atomic spin moments, and bond orders from quantum mechanical charge density distributions. The DDEC6 method is designed to reproduce the electrostatic potential outside the molecular charge distribution while maintaining chemical transferability and spherical averaging convergence." }, { "num": "282", "name": "Critic2", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/aoterodelaroza/critic2", "note": "", "md_link_text": "Critic2.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/Critic2.md", "papers": [ { "name": "10_1016_j_cpc_2013_10_026.pdf", "path": "Papers_of_Codes/Post-Processing/8.4_Chemical_Bonding/Critic2/10_1016_j_cpc_2013_10_026.pdf", "doi_url": "https://scholar.google.com/scholar?q=Critic2+10+1016+j+cpc+2013+10+026" } ], "paper_placeholder": false, "slug": "Critic2", "idx": 636, "overview": "Critic2 is a code for the analysis of quantum mechanical electron density and other scalar fields in periodic solids. It implements the Quantum Theory of Atoms in Molecules (QTAIM) and other topological analysis methods (NCI, ELF, etc.) for crystals. It can read output from a wide variety of electronic structure codes (WIEN2k, VASP, QE, Abinit, etc.) and perform critical point finding, basin integration, and chemical bonding analysis." }, { "num": "283", "name": "Hirshfeld", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "**IMPLEMENTATION** - Part of many codes (e.g., *Multiwfn*, *Critic2*).", "note": "", "md_link_text": "Hirshfeld.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/Hirshfeld.md", "papers": [ { "name": "Hirshfeld_10.1007_BF00549096.pdf", "path": "Papers_of_Codes/Post-Processing/Hirshfeld/Hirshfeld_10.1007_BF00549096.pdf", "doi_url": "https://doi.org/10.1007/BF00549096" } ], "paper_placeholder": false, "slug": "Hirshfeld", "idx": 637, "overview": "\"Hirshfeld\" refers to Hirshfeld Charge Analysis (and its variants like Hirshfeld-I, Iterative Hirshfeld), a method for partitioning the electron density of a molecule or crystal into atomic contributions. It assigns partial charges to atoms based on the ratio of the free-atom density to the total molecular density (\"stockholder\" partitioning). The term here likely refers to specific implementations or scripts (e.g., Tonto, or VASP scripts) rather than a single code named \"Hirshfeld\"." }, { "num": "284", "name": "NCIPLOT", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/aoterodelaroza/nciplot", "note": "Non-covalent interaction visualization via reduced density gradient", "md_link_text": "NCIPLOT.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/NCIPLOT.md", "papers": [ { "name": "NCIPLOT_10.1021_ct100641a.pdf", "path": "Papers_of_Codes/Post-Processing/NCIPLOT/NCIPLOT_10.1021_ct100641a.pdf", "doi_url": "https://doi.org/10.1021/ct100641a" } ], "paper_placeholder": false, "slug": "NCIPLOT", "idx": 638, "overview": "NCIPLOT is a program that enables the computation and graphical visualization of inter- and intra-molecular non-covalent interactions (hydrogen bonds, \u03c0-\u03c0 interactions, van der Waals contacts) using the reduced density gradient (RDG) method. It produces 3D isosurfaces that can be visualized with molecular graphics programs." }, { "num": "285", "name": "Chargemol", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://sourceforge.net/projects/ddec/", "note": "DDEC6 atomic charges and bond orders", "md_link_text": "Chargemol.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/Chargemol.md", "papers": [ { "name": "Chargemol_10.1039_C7RA11829E.pdf", "path": "Papers_of_Codes/Post-Processing/Chargemol/Chargemol_10.1039_C7RA11829E.pdf", "doi_url": "https://doi.org/10.1039/C7RA11829E" } ], "paper_placeholder": false, "slug": "Chargemol", "idx": 639, "overview": "Chargemol is a program for computing DDEC (Density Derived Electrostatic and Chemical) atomic charges, atomic spin moments, and bond orders from electron and spin density distributions. It implements DDEC6, the latest version of the DDEC method, providing chemically meaningful atomic charges for molecular simulations." }, { "num": "286", "name": "pybader", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/adam-kerrigan/pybader", "note": "Python implementation of Bader charge analysis", "md_link_text": "pybader.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/pybader.md", "papers": [], "paper_placeholder": true, "slug": "pybader", "idx": 640, "overview": "pybader is a threaded Python implementation of grid-based Bader charge analysis. It provides a fast, pure-Python alternative to the original Bader code, with support for multiple file formats and integration with Python workflows for high-throughput analysis." }, { "num": "287", "name": "ChemTools", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://chemtools.org/", "note": "Conceptual DFT, Fukui functions, reactivity descriptors", "md_link_text": "ChemTools.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/ChemTools.md", "papers": [], "paper_placeholder": true, "slug": "ChemTools", "idx": 641, "overview": "ChemTools is a Python library for interpreting the results of quantum chemistry calculations using conceptual density functional theory (CDFT). It provides tools for computing and visualizing chemical reactivity descriptors including Fukui functions, dual descriptor, electrophilicity, and other local and global reactivity indicators." }, { "num": "288", "name": "AIMAll", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://aim.tkgristmill.com/", "note": "Comprehensive QTAIM analysis (commercial, academic free)", "md_link_text": "AIMAll.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/AIMAll.md", "papers": [ { "name": "AIMAll_10.1515_9783110660074-003.pdf", "path": "Papers_of_Codes/Post-Processing/AIMAll/AIMAll_10.1515_9783110660074-003.pdf", "doi_url": "https://doi.org/10.1515/9783110660074-003" } ], "paper_placeholder": false, "slug": "AIMAll", "idx": 642, "overview": "AIMAll is a comprehensive software package for performing quantitative and visual QTAIM (Quantum Theory of Atoms in Molecules) analyses of molecular systems. It provides accurate atomic properties, bond critical point analysis, delocalization indices, and extensive visualization capabilities for understanding chemical bonding." }, { "num": "289", "name": "TopMod", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://www.lct.jussieu.fr/pagesperso/silvi/topmod_english.html", "note": "ELF topology and basin analysis", "md_link_text": "TopMod.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/TopMod.md", "papers": [], "paper_placeholder": true, "slug": "TopMod", "idx": 643, "overview": "TopMod is a FORTRAN package for topological analysis of the Electron Localization Function (ELF). It calculates the ELF on a 3D grid, assigns basins, and computes basin populations and their variances. This enables quantitative analysis of chemical bonding in terms of core, bonding, and lone pair basins." }, { "num": "290", "name": "ORBKIT", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/orbkit/orbkit", "note": "Python wavefunction analysis and visualization (JCC published)", "md_link_text": "ORBKIT.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/ORBKIT.md", "papers": [ { "name": "ORBKIT_10.1002_jcc.24358.pdf", "path": "Papers_of_Codes/Post-Processing/ORBKIT/ORBKIT_10.1002_jcc.24358.pdf", "doi_url": "https://doi.org/10.1002/jcc.24358" } ], "paper_placeholder": false, "slug": "ORBKIT", "idx": 644, "overview": "ORBKIT is a parallel Python program package for post-processing wavefunction data from quantum chemical programs. It computes grid-based quantities (molecular orbitals, electron density, electrostatic potential) and non-grid-based quantities (Mulliken charges, bond orders) from various quantum chemistry output formats." }, { "num": "291", "name": "DGrid", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "MPI CPfS Dresden (M. Kohout)", "note": "ELI-D electron localizability indicator analysis", "md_link_text": "DGrid.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/DGrid.md", "papers": [ { "name": "DGrid_10.1515_9783110660074-004.pdf", "path": "Papers_of_Codes/Post-Processing/DGrid/DGrid_10.1515_9783110660074-004.pdf", "doi_url": "https://doi.org/10.1515/9783110660074-004" } ], "paper_placeholder": false, "slug": "DGrid", "idx": 645, "overview": "DGrid is a program for calculating and analyzing electron localizability indicators (ELI-D) and performing topological analysis of electron density in molecules and crystals. It provides detailed chemical bonding information through position-space analysis of pair densities and localization functions." }, { "num": "292", "name": "denspart", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/theochem/denspart", "note": "ISA/MBIS charge partitioning Python package", "md_link_text": "denspart.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/denspart.md", "papers": [], "paper_placeholder": true, "slug": "denspart", "idx": 646, "overview": "denspart is a Python package for atoms-in-molecules density partitioning. It implements various stockholder-type partitioning schemes including Iterative Stockholder Atoms (ISA), Minimal Basis Iterative Stockholder (MBIS), and Gaussian Iterative Stockholder (GISA) methods for computing atomic charges and multipole moments." }, { "num": "292a", "name": "TOPOND", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://www.crystal.unito.it/topond.html", "note": "QTAIM/topological electron-density analysis within CRYSTAL for molecules and periodic solids", "md_link_text": "TOPOND.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/TOPOND.md", "papers": [], "paper_placeholder": true, "slug": "TOPOND", "idx": 647, "overview": "TOPOND is a topological analysis program for electron density and related scalar fields, developed for use with CRYSTAL calculations. It implements Bader-style Quantum Theory of Atoms in Molecules for molecules and periodic solids, with particular strength for crystalline materials and charge-density analysis in the solid state." }, { "num": "292b", "name": "DensToolKit", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/jmsolano/denstoolkit", "note": "Open-source electron-density and QTAIM topology analysis toolkit", "md_link_text": "DensToolKit.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/DensToolKit.md", "papers": [ { "name": "DensToolKit_10.1016_j.cpc.2015.07.005.pdf", "path": "Papers_of_Codes/Post-Processing/DensToolKit/DensToolKit_10.1016_j.cpc.2015.07.005.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2015.07.005" } ], "paper_placeholder": false, "slug": "DensToolKit", "idx": 648, "overview": "DensToolKit is an open-source suite of programs for analyzing molecular electron density and derivative scalar and vector fields. In addition to field evaluation and visualization support, it includes topology analysis tools for locating critical points and tracing bond paths in the framework of QTAIM." }, { "num": "292c", "name": "TopChem2", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://www.lct.jussieu.fr/pagesperso/pilme/topchempage.html", "note": "Standalone QTAIM, ELF, NCI, and Fukui analysis from WFN/WFX and cube data", "md_link_text": "TopChem2.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/TopChem2.md", "papers": [], "paper_placeholder": true, "slug": "TopChem2", "idx": 649, "overview": "TopChem2 is a standalone quantum chemical topology program for analyzing electron density and related descriptors from wavefunction and cube data. It supports QTAIM analysis together with ELF, NCI, and Fukui-function style descriptors, making it a broad molecular bonding-analysis environment." }, { "num": "292d", "name": "JANPA", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://janpa.sourceforge.net/", "note": "Open-source natural population analysis, NAOs, and Wiberg-Mayer bond indices", "md_link_text": "JANPA.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/JANPA.md", "papers": [ { "name": "JANPA_10.1016_j.comptc.2014.10.002.pdf", "path": "Papers_of_Codes/Post-Processing/JANPA/JANPA_10.1016_j.comptc.2014.10.002.pdf", "doi_url": "https://doi.org/10.1016/j.comptc.2014.10.002" } ], "paper_placeholder": false, "slug": "JANPA", "idx": 650, "overview": "JANPA is an open-source cross-platform implementation of Natural Population Analysis on the Java platform. It provides natural atomic orbital construction, natural population analysis, and Wiberg-Mayer bond index evaluation from suitable wavefunction-derived inputs." }, { "num": "292e", "name": "IGMPlot", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "http://igmplot.univ-reims.fr/", "note": "IGM/IGMH-based interaction analysis from weak non-covalent to strong bonding regimes", "md_link_text": "IGMPlot.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/IGMPlot.md", "papers": [], "paper_placeholder": true, "slug": "IGMPlot", "idx": 651, "overview": "IGMPlot is a program for identifying, characterizing, and quantifying molecular interactions using the Independent Gradient Model. It supports analysis of interactions ranging from weak non-covalent contacts to stronger covalent or coordinative interactions, with graphical interpretation based on promolecular or quantum-mechanical density." }, { "num": "292f", "name": "EDDB", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "http://aromaticity.uj.edu.pl/eddb.html", "note": "Electron Density of Delocalized Bonds method for aromaticity and delocalization analysis", "md_link_text": "EDDB.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/EDDB.md", "papers": [ { "name": "EDDB_10.1039_C7CP06114E.pdf", "path": "Papers_of_Codes/Post-Processing/EDDB/EDDB_10.1039_C7CP06114E.pdf", "doi_url": "https://doi.org/10.1039/C7CP06114E" } ], "paper_placeholder": false, "slug": "EDDB", "idx": 652, "overview": "EDDB is the Electron Density of Delocalized Bonds method for quantifying and visualizing electron delocalization in molecular systems. It is especially useful for aromaticity analysis, conjugation studies, and interpretation of local or global delocalized bonding patterns." }, { "num": "292g", "name": "AIM-UC", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://sourceforge.net/projects/facyt-quimicomp/files/aim-uc/", "note": "Free QTAIM application for CUBE, GRD, and CHGCAR density files", "md_link_text": "AIM-UC.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/AIM-UC.md", "papers": [ { "name": "AIM-UC_10.3233_JCM-140491.pdf", "path": "Papers_of_Codes/Post-Processing/AIM-UC/AIM-UC_10.3233_JCM-140491.pdf", "doi_url": "https://doi.org/10.3233/JCM-140491" } ], "paper_placeholder": false, "slug": "AIM-UC", "idx": 653, "overview": "AIM-UC is a free application for QTAIM analysis that calculates properties and generates drawings related to Bader's Atoms in Molecules theory. It is designed around grid-based electron-density inputs and supports common formats such as Gaussian cube files, DMol grids, and VASP CHGCAR files." }, { "num": "292h", "name": "AIMPAC", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/qtaim/aimpac", "note": "Classic foundational QTAIM reference implementation", "md_link_text": "AIMPAC.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/AIMPAC.md", "papers": [], "paper_placeholder": true, "slug": "AIMPAC", "idx": 654, "overview": "AIMPAC is a historic reference implementation of Bader-style Quantum Theory of Atoms in Molecules analysis. It is one of the classic software packages for extracting topological information, atomic properties, and bonding descriptors from wavefunction data and remains important as foundational QTAIM software." }, { "num": "292i", "name": "AIM2000", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "http://www.aim2000.de/", "note": "QTAIM analysis and visualization program for AIM data", "md_link_text": "AIM2000.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/AIM2000.md", "papers": [ { "name": "AIM2000_10.1002_jcc.10085.pdf", "path": "Papers_of_Codes/Post-Processing/AIM2000/AIM2000_10.1002_jcc.10085.pdf", "doi_url": "https://doi.org/10.1002/jcc.10085" } ], "paper_placeholder": false, "slug": "AIM2000", "idx": 655, "overview": "AIM2000 is a program to analyze and visualize Atoms in Molecules data. It provides a graphical environment for QTAIM analysis and visualization, helping users inspect critical points, bond paths, and related topological features derived from molecular electron density." }, { "num": "292j", "name": "Molden2AIM", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/zorkzou/Molden2AIM", "note": "Converts Molden files to AIM-WFN/WFX and NBO-47 for downstream bonding analysis", "md_link_text": "Molden2AIM.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/Molden2AIM.md", "papers": [], "paper_placeholder": true, "slug": "Molden2AIM", "idx": 656, "overview": "Molden2AIM is a utility program that converts Molden files into AIM-WFN, AIM-WFX, and NBO-47 files. It is an interoperability tool for feeding downstream chemical-bonding and QTAIM programs, and it also supports output relevant to generalized Wiberg bond-order workflows." }, { "num": "292k", "name": "PAMoC", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://www.pamoc.it/", "note": "Electron-density analysis environment for theoretical and experimental charge-density studies", "md_link_text": "PAMoC.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/PAMoC.md", "papers": [], "paper_placeholder": true, "slug": "PAMoC", "idx": 657, "overview": "PAMoC is an electron-density analysis environment devoted to the analysis of experimental and theoretical charge-density distributions. It provides tools for Bader-style topological analysis, bond-path analysis, and related post-processing of electron-density data with an emphasis on extracting extensive information from charge-density studies." }, { "num": "292l", "name": "NBO", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://nbo7.chem.wisc.edu/", "note": "Natural Bond Orbital program for orbital-based chemical bonding and population analysis", "md_link_text": "NBO.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/NBO.md", "papers": [ { "name": "NBO_10.1002_jcc.25873.pdf", "path": "Papers_of_Codes/Post-Processing/NBO/NBO_10.1002_jcc.25873.pdf", "doi_url": "https://doi.org/10.1002/jcc.25873" } ], "paper_placeholder": false, "slug": "NBO", "idx": 658, "overview": "NBO is the Natural Bond Orbital program for analyzing localized and delocalized chemical bonding in wavefunctions. It provides a broad set of orbital, population, donor-acceptor, and bond-character descriptors that are widely used across computational chemistry for chemically intuitive interpretation of molecular electronic structure." }, { "num": "292m", "name": "Bondalyzer", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/MolecularTheoryGroup/BondalyzerTecplotAddon", "note": "Bondalyzer and gradient bundle decomposition algorithms implemented as a Tecplot addon", "md_link_text": "Bondalyzer.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/Bondalyzer.md", "papers": [], "paper_placeholder": true, "slug": "Bondalyzer", "idx": 659, "overview": "Bondalyzer is a chemical-bonding analysis package implemented as a Tecplot 360 addon. It provides Bondalyzer and gradient bundle decomposition algorithms for analyzing chemically meaningful regions of electron density and related topological features." }, { "num": "292n", "name": "TopIso3D Viewer", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "http://www.topiso3d.ufpb.br/", "note": "Free GUI for 3D QTAIM/topological descriptor isosurfaces, especially for CRYSTAL/TOPOND workflows", "md_link_text": "TopIso3D-Viewer.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/TopIso3D-Viewer.md", "papers": [], "paper_placeholder": true, "slug": "TopIso3D-Viewer", "idx": 660, "overview": "TopIso3D Viewer is a free graphical program for generating three-dimensional maps of descriptors based on the Quantum Theory of Atoms in Molecules. It is aimed especially at CRYSTAL and TOPOND users and provides an interactive way to inspect electron density, Laplacian, ELF-style maps, and related topological descriptors in periodic and nonperiodic systems." }, { "num": "292o", "name": "QuantVec", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/srk/QuantVec", "note": "Successor to AIMPAC2 and modular open QTAIM/QCT tool suite with molecular-graph utilities", "md_link_text": "QuantVec.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/QuantVec.md", "papers": [], "paper_placeholder": true, "slug": "QuantVec", "idx": 661, "overview": "QuantVec is the successor to AIMPAC2 and is being developed as an open suite of QTAIM and Quantum Chemical Topology tools. The repository describes Python-based, pip-installable tools, example datasets, utilities, and a `topviz` molecular-graph visualization GUI for QTAIM-related analysis workflows." }, { "num": "292p", "name": "IGMpython", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/bertadenes/IGMpython", "note": "Python implementation of IGM using QM cube densities and VMD-ready outputs", "md_link_text": "IGMpython.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/IGMpython.md", "papers": [], "paper_placeholder": true, "slug": "IGMpython", "idx": 662, "overview": "IGMpython is a Python implementation of the Independent Gradient Model that uses quantum-mechanical molecular densities provided as cube files. It is designed to reveal and visualize chemical interactions using full and fragment density data, and it produces cube outputs together with a VMD visualization state." }, { "num": "292q", "name": "PyMol-QTAIM", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/popelier-group/PyMol-QTAIM", "note": "PyMOL plugin for visualization of QTAIM basins from AIMAll outputs", "md_link_text": "PyMol-QTAIM.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/PyMol-QTAIM.md", "papers": [], "paper_placeholder": true, "slug": "PyMol-QTAIM", "idx": 663, "overview": "PyMol-QTAIM is a PyMOL visualizer plugin for displaying Quantum Theory of Atoms in Molecules atomic basins and related visualization outputs. It is intended to work with AIMAll-generated files and provides a convenient graphical route for inspecting QTAIM surfaces inside the PyMOL environment." }, { "num": "292r", "name": "QTAIM.wl", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/ecbrown/QTAIM.wl", "note": "Wolfram Language implementation of QTAIM analysis and graphics workflows", "md_link_text": "QTAIM-wl.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/QTAIM-wl.md", "papers": [], "paper_placeholder": true, "slug": "QTAIM.wl", "idx": 664, "overview": "QTAIM.wl is a Wolfram Language implementation of the Quantum Theory of Atoms in Molecules. It is intended for research and teaching use cases, especially customized graphics and interactive exploration of common QTAIM tasks in a high-level Mathematica environment." }, { "num": "292s", "name": "AdNDP", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://zenodo.org/records/3252298", "note": "Adaptive Natural Density Partitioning code for localized and multicenter bonding analysis", "md_link_text": "AdNDP.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/AdNDP.md", "papers": [ { "name": "AdNDP_10.1039_C9CP00379G.pdf", "path": "Papers_of_Codes/Post-Processing/AdNDP/AdNDP_10.1039_C9CP00379G.pdf", "doi_url": "https://doi.org/10.1039/C9CP00379G" } ], "paper_placeholder": false, "slug": "AdNDP", "idx": 665, "overview": "AdNDP is the Adaptive Natural Density Partitioning method for revealing intuitive chemical bonding patterns, including both localized Lewis-like bonds and multicenter delocalized bonding. The publicly archived AdNDP 2.0 code supports modern bonding analysis workflows and was explicitly released alongside a publication on excited-state bonding analysis." }, { "num": "292t", "name": "MolBO", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/zorkzou/MolBO", "note": "Generates NBO-47 files from MOLPRO output and calculates Mayer bond orders", "md_link_text": "MolBO.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/MolBO.md", "papers": [], "paper_placeholder": true, "slug": "MolBO", "idx": 666, "overview": "MolBO is a utility program for generating NBO-47 files from MOLPRO output and for calculating Mayer bond orders. It is a practical bridge between MOLPRO calculations and downstream bonding-analysis workflows that use NBO-compatible data." }, { "num": "292u", "name": "ESI-3D", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://quantchemdev.github.io/resources.html", "note": "Electron sharing and aromaticity indices code using overlap matrices from Hilbert-space or QTAIM partitions", "md_link_text": "ESI-3D.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/ESI-3D.md", "papers": [], "paper_placeholder": true, "slug": "ESI-3D", "idx": 667, "overview": "ESI-3D is a program for calculating electron sharing and delocalization descriptors used in chemical bonding and aromaticity analysis. It evaluates two-center and multicenter electron sharing indices and a range of aromaticity indicators from atomic overlap matrices derived from Hilbert-space or real-space partitions such as QTAIM." }, { "num": "292v", "name": "ESIpy", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/jgrebol/ESIpy", "note": "Python package for electron-sharing and aromaticity analysis across multiple Hilbert-space partitions", "md_link_text": "ESIpy.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/ESIpy.md", "papers": [], "paper_placeholder": true, "slug": "ESIpy", "idx": 668, "overview": "ESIpy is a Python package for calculating population-analysis and aromaticity indicators from different Hilbert-space partitions. It extends the electron-sharing-index ecosystem with a modern Python workflow and can also generate AIMAll-format atomic overlap matrices readable by both ESIpy and the older ESI-3D code." }, { "num": "292w", "name": "APOST3D", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://github.com/mgimferrer/APOST3D", "note": "Open-source wavefunction-analysis code for bond orders, local spin, and effective oxidation states", "md_link_text": "APOST3D.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/APOST3D.md", "papers": [], "paper_placeholder": true, "slug": "APOST3D", "idx": 669, "overview": "APOST3D is an open-source Fortran-based code developed at the Universitat de Girona for extracting chemical concepts from wavefunction analysis. It provides a broad set of chemically motivated descriptors, including atomic populations, bond orders, local spin analysis, and effective oxidation states." }, { "num": "292x", "name": "Chemissian", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://www.chemissian.com/", "note": "GUI-based bond-order, overlap-population, and fragment-bond analysis tool", "md_link_text": "Chemissian.md", "md_link_path": "Post-Processing/8.4_Chemical_Bonding/Chemissian.md", "papers": [], "paper_placeholder": true, "slug": "Chemissian", "idx": 670, "overview": "Chemissian is a graphical electronic-structure analysis program that includes explicit tools for chemical-bonding analysis, such as quantum-chemical bond order indexes, overlap populations, generalized bonds between fragments, and valence-style analysis. Although broader than a single-purpose bonding code, it directly supports practical bond interpretation from the outputs of multiple quantum chemistry packages." }, { "num": "292y", "name": "QMForge", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.4", "subcategory": "Chemical Bonding Analysis", "confidence": "VERIFIED", "official_url": "https://sourceforge.net/projects/qmforge/", "note": "GPL Python GUI for QC result analysis (population, MO, vibrations); cclib-based", "md_link_text": "QMForge.md", "md_link_path": "Post-Processing/8.1_Band_Structure_Electronic/QMForge.md", "papers": [], "paper_placeholder": true, "slug": "QMForge", "idx": 671, "overview": "" }, { "num": "284", "name": "FEFF", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://feffproject.org/", "note": "", "md_link_text": "FEFF.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/FEFF.md", "papers": [ { "name": "10.1039_B926434E.pdf", "path": "Papers_of_Codes/Post-Processing/8.5_Spectroscopy/FEFF/10.1039_B926434E.pdf", "doi_url": "https://doi.org/10.1039/B926434E" } ], "paper_placeholder": false, "slug": "FEFF", "idx": 672, "overview": "FEFF is an automated program for ab initio multiple scattering calculations of X-ray Absorption Fine Structure (XAFS), X-ray Absorption Near-Edge Structure (XANES), and various other spectroscopies for clusters of atoms. Developed at the University of Washington, FEFF uses a real-space Green's function approach, making it highly effective for non-periodic systems, nanoparticles, and defects, as well as crystals." }, { "num": "286", "name": "xspectra", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "**MODULE** - Part of Quantum ESPRESSO.", "note": "", "md_link_text": "xspectra.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/xspectra.md", "papers": [ { "name": "xspectra_10.1103_PhysRevB.80.075102.pdf", "path": "Papers_of_Codes/Post-Processing/xspectra/xspectra_10.1103_PhysRevB.80.075102.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.80.075102" } ], "paper_placeholder": false, "slug": "xspectra", "idx": 673, "overview": "XSpectra is a code for calculating X-ray Absorption Spectra (XAS) at the K-edge (and L-edge) using the Projector Augmented Wave (PAW) method or Pseudopotentials. It is part of the Quantum ESPRESSO distribution (`xspectra.x`). It avoids the explicit calculation of empty states by using the Lanczos recursion algorithm to compute the continued fraction representation of the Green's function." }, { "num": "287", "name": "exciting-XS", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "**MODULE** - Part of exciting.", "note": "", "md_link_text": "exciting-XS.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/exciting-XS.md", "papers": [ { "name": "10_1088_0953-8984_26_36_363202.pdf", "path": "Papers_of_Codes/TDDFT/2.2_Linear-Response_TDDFT/exciting/10_1088_0953-8984_26_36_363202.pdf", "doi_url": "https://scholar.google.com/scholar?q=exciting-XS+10+1088+0953+8984+26+36+363202" } ], "paper_placeholder": false, "slug": "exciting-XS", "idx": 674, "overview": "exciting-XS refers to the X-ray spectroscopy capabilities within the **exciting** code. It is a full-potential all-electron DFT code based on the linearized augmented plane-wave (LAPW) method. It can calculate core-level spectra (XAS, XES, EELS) using the Bethe-Salpeter Equation (BSE) or Time-Dependent DFT (TDDFT), providing highly accurate descriptions of core excitations including excitonic effects." }, { "num": "288", "name": "FDMNES", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://fdmnes.neel.cnrs.fr/", "note": "", "md_link_text": "FDMNES.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/FDMNES.md", "papers": [ { "name": "FDMNES_10.1103_PhysRevB.63.125120.pdf", "path": "Papers_of_Codes/Post-Processing/FDMNES/FDMNES_10.1103_PhysRevB.63.125120.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.63.125120" } ], "paper_placeholder": false, "slug": "FDMNES", "idx": 675, "overview": "FDMNES is a code for simulating X-ray Absorption Spectroscopy (XAS) including XANES and EXAFS, X-ray Emission Spectroscopy (XES), and Resonant Inelastic X-ray Scattering (RIXS). It employs both Finite Difference Method (FDM) and Multiple Scattering Theory (MST) to calculate excited states in clusters or periodic systems. It is particularly powerful for handling low-symmetry systems and core-hole effects." }, { "num": "289", "name": "CRYSOL", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://www.embl-hamburg.de/biosaxs/crysol.html", "note": "", "md_link_text": "CRYSOL.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/CRYSOL.md", "papers": [ { "name": "CRYSOL_10.1107_S0021889895007047.pdf", "path": "Papers_of_Codes/Post-Processing/CRYSOL/CRYSOL_10.1107_S0021889895007047.pdf", "doi_url": "https://doi.org/10.1107/S0021889895007047" } ], "paper_placeholder": false, "slug": "CRYSOL", "idx": 676, "overview": "CRYSOL is a program for evaluating the solution scattering (SAXS/SANS) from macromolecules with known atomic structure and fitting it to experimental data. It uses multipole expansion of the scattering amplitudes to calculate the spherically averaged scattering pattern, taking into account the hydration shell and solvent density. It is part of the ATSAS software suite." }, { "num": "291", "name": "ezSpectra", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/ezspectra/ezspectra", "note": "", "md_link_text": "ezSpectra.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/ezSpectra.md", "papers": [ { "name": "ezSpectra_10.1002_wcms.1546.pdf", "path": "Papers_of_Codes/Post-Processing/ezSpectra/ezSpectra_10.1002_wcms.1546.pdf", "doi_url": "https://doi.org/10.1002/wcms.1546" } ], "paper_placeholder": false, "slug": "ezSpectra", "idx": 677, "overview": "**Note**: Two distinct software packages share this name: 1. **ezSpectra Suite (Krylov Group)**: Toolkit for electronic spectroscopy (photoelectron, absorption) with vibronic structure via Franck-Condon factors. 2. **ezSpectra (Mosey Group)**: Python package for vibrational spectra from MD trajectories." }, { "num": "292", "name": "Libwfa", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/libwfa/libwfa", "note": "", "md_link_text": "Libwfa.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/Libwfa.md", "papers": [ { "name": "Libwfa_10.1002_wcms.1595.pdf", "path": "Papers_of_Codes/Post-Processing/Libwfa/Libwfa_10.1002_wcms.1595.pdf", "doi_url": "https://doi.org/10.1002/wcms.1595" } ], "paper_placeholder": false, "slug": "Libwfa", "idx": 678, "overview": "Libwfa is an open-source C++ library for wavefunction analysis of electronic excitations. It implements various methods for analyzing excited state calculations (e.g., from TD-DFT, ADC, CC, EOM-CC) by computing state difference density matrices, natural transition orbitals (NTOs), and charge-transfer descriptors. It provides tools to visualize and quantify the character of electronic transitions." }, { "num": "293", "name": "DP", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "http://dp-code.org/", "note": "", "md_link_text": "DP.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/DP.md", "papers": [ { "name": "10_1103_PhysRevB_73_045112.pdf", "path": "Papers_of_Codes/Post-Processing/8.5_Spectroscopy/DP/10_1103_PhysRevB_73_045112.pdf", "doi_url": "https://scholar.google.com/scholar?q=DP+10+1103+PhysRevB+73+045112" } ], "paper_placeholder": false, "slug": "DP", "idx": 679, "overview": "DP is a code for calculating the linear response dielectric properties of periodic systems. It uses Time-Dependent Density Functional Theory (TDDFT) in the frequency domain with a plane-wave basis set. It computes the macroscopic dielectric function, Electron Energy Loss Spectra (EELS), and Inelastic X-ray Scattering (IXS) spectra." }, { "num": "294", "name": "Larch", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/xraypy/xraylarch", "note": "Python XAS/XAFS analysis library (J. Synchrotron Rad.)", "md_link_text": "Larch.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/Larch.md", "papers": [ { "name": "Larch_10.1088_1742-6596_430_1_012007.pdf", "path": "Papers_of_Codes/Post-Processing/Larch/Larch_10.1088_1742-6596_430_1_012007.pdf", "doi_url": "https://doi.org/10.1088/1742-6596_430_1_012007" } ], "paper_placeholder": false, "slug": "Larch", "idx": 680, "overview": "Larch is an open-source Python library and set of applications for processing and analyzing X-ray absorption spectroscopy (XAS) data from synchrotron beamlines. It provides comprehensive tools for XAFS (X-ray Absorption Fine Structure), including XANES (near-edge) and EXAFS (extended) analysis, as well as XRF (X-ray fluorescence) mapping and analysis." }, { "num": "295", "name": "Demeter", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://bruceravel.github.io/demeter/", "note": "Athena/Artemis XAS data processing and EXAFS fitting", "md_link_text": "Demeter.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/Demeter.md", "papers": [ { "name": "Demeter_10.1107_S0909049505012719.pdf", "path": "Papers_of_Codes/Post-Processing/Demeter/Demeter_10.1107_S0909049505012719.pdf", "doi_url": "https://doi.org/10.1107/S0909049505012719" } ], "paper_placeholder": false, "slug": "Demeter", "idx": 681, "overview": "Demeter is a comprehensive software package for processing and analyzing X-ray Absorption Spectroscopy (XAS) data. It includes three main programs: Athena (data processing), Artemis (EXAFS fitting with FEFF), and Hephaestus (periodic table and X-ray data). Built on the IFEFFIT library, Demeter provides a complete workflow for XAS analysis." }, { "num": "298", "name": "Phonopy-Spectroscopy", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/skelton-group/Phonopy-Spectroscopy", "note": "IR and Raman spectra from Phonopy", "md_link_text": "Phonopy-Spectroscopy.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/Phonopy-Spectroscopy.md", "papers": [ { "name": "10_1103_PhysRevLett_78_4063.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_1103_PhysRevLett_78_4063.pdf", "doi_url": "https://scholar.google.com/scholar?q=Phonopy-Spectroscopy+10+1103+PhysRevLett+78+4063" }, { "name": "10_7566_JPSJ_92_012001.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_7566_JPSJ_92_012001.pdf", "doi_url": "https://scholar.google.com/scholar?q=Phonopy-Spectroscopy+10+7566+JPSJ+92+012001" }, { "name": "10_1016_j_cpc_2009_03_010.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_1016_j_cpc_2009_03_010.pdf", "doi_url": "https://scholar.google.com/scholar?q=Phonopy-Spectroscopy+10+1016+j+cpc+2009+03+010" } ], "paper_placeholder": false, "slug": "Phonopy-Spectroscopy", "idx": 682, "overview": "Phonopy-Spectroscopy is a Python package that extends Phonopy to simulate infrared (IR) and Raman spectra of crystalline materials. It calculates IR intensities from Born effective charges and Raman activities from polarizability tensors computed using VASP, enabling direct comparison with experimental vibrational spectra." }, { "num": "299", "name": "MRSimulator", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/deepanshs/mrsimulator", "note": "Solid-state NMR simulation (JCP published)", "md_link_text": "MRSimulator.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/MRSimulator.md", "papers": [], "paper_placeholder": true, "slug": "MRSimulator", "idx": 683, "overview": "MRSimulator is a fast, versatile, and open-source Python package for simulating one- and higher-dimensional solid-state NMR spectra. It supports static, magic-angle spinning (MAS), and variable-angle spinning (VAS) conditions for nuclei experiencing chemical shift and quadrupolar coupling interactions." }, { "num": "300", "name": "EasySpin", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://easyspin.org/", "note": "EPR/ESR simulation MATLAB toolbox (JMR published)", "md_link_text": "EasySpin.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/EasySpin.md", "papers": [ { "name": "EasySpin_10.1016_j.jmr.2005.08.013.pdf", "path": "Papers_of_Codes/Post-Processing/EasySpin/EasySpin_10.1016_j.jmr.2005.08.013.pdf", "doi_url": "https://doi.org/10.1016/j.jmr.2005.08.013" } ], "paper_placeholder": false, "slug": "EasySpin", "idx": 684, "overview": "EasySpin is a comprehensive MATLAB toolbox for simulating and fitting Electron Paramagnetic Resonance (EPR/ESR) spectra. It supports continuous-wave (CW) EPR, pulse EPR, and ENDOR experiments, handling complex spin systems with multiple unpaired electrons and nuclei." }, { "num": "301", "name": "CTM4XAS", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://anorg.chem.uu.nl/CTM4XAS/", "note": "Charge transfer multiplet XAS simulation", "md_link_text": "CTM4XAS.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/CTM4XAS.md", "papers": [ { "name": "CTM4XAS_10.1016_j.micron.2010.06.005.pdf", "path": "Papers_of_Codes/Post-Processing/CTM4XAS/CTM4XAS_10.1016_j.micron.2010.06.005.pdf", "doi_url": "https://doi.org/10.1016/j.micron.2010.06.005" } ], "paper_placeholder": false, "slug": "CTM4XAS", "idx": 685, "overview": "CTM4XAS (Charge Transfer Multiplet for X-ray Absorption Spectroscopy) is a program for simulating L-edge and M-edge X-ray absorption spectra of transition metal compounds using atomic multiplet theory and charge transfer effects. It provides a user-friendly interface for calculating XAS and EELS spectra." }, { "num": "302", "name": "HyperSpy", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/hyperspy/hyperspy", "note": "EELS/EDS analysis Python library", "md_link_text": "HyperSpy.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/HyperSpy.md", "papers": [ { "name": "HyperSpy_10.1017_S1431927617001751.pdf", "path": "Papers_of_Codes/Post-Processing/HyperSpy/HyperSpy_10.1017_S1431927617001751.pdf", "doi_url": "https://doi.org/10.1017/S1431927617001751" } ], "paper_placeholder": false, "slug": "HyperSpy", "idx": 686, "overview": "HyperSpy is an open-source Python library for multi-dimensional data analysis, with particular focus on electron microscopy data including EELS (Electron Energy Loss Spectroscopy), EDS (Energy Dispersive X-ray Spectroscopy), and other spectroscopic imaging techniques. It provides tools for data visualization, processing, and quantitative analysis." }, { "num": "303", "name": "Crispy", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/mretegan/crispy", "note": "GUI for Quanty XAS/RIXS simulations (ESRF)", "md_link_text": "Crispy.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/Crispy.md", "papers": [], "paper_placeholder": true, "slug": "Crispy", "idx": 687, "overview": "Crispy is a modern graphical user interface for calculating core-level spectra using the semi-empirical multiplet approaches implemented in Quanty. It enables simulation of XAS (X-ray Absorption Spectroscopy), XES (X-ray Emission Spectroscopy), RIXS (Resonant Inelastic X-ray Scattering), and XPS spectra for transition metal and rare earth compounds." }, { "num": "303a", "name": "Quanty", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://www.quanty.org/", "note": "Many-body script language (Lua) for XAS, XES, RIXS, NIXS, XPS multiplet calculations", "md_link_text": "Quanty.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/Quanty.md", "papers": [], "paper_placeholder": true, "slug": "Quanty", "idx": 688, "overview": "**Quanty** is a many-body script language based on Lua designed for the calculation of X-ray spectroscopy including XAS, XES, RIXS, NIXS, and XPS. It uses exact diagonalization and Lanczos methods to compute multiplet spectra for correlated materials, ranging from crystal field theory to ligand field theory and post-DFT treatments." }, { "num": "303b", "name": "StoBe", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://www.fz-juelich.de/pgi/pgi-1/DE/Home/home_node.html", "note": "DFT code with transition potential method for molecular XAS, XES, XPS", "md_link_text": "StoBe.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/StoBe.md", "papers": [], "paper_placeholder": true, "slug": "StoBe", "idx": 689, "overview": "**StoBe** (Stockholm-Berlin) is a DFT code based on Gaussian-type orbitals (GTO) specifically designed for the simulation of core-level X-ray spectroscopy including XAS, XES, and XPS. It uses the transition potential (TP) method and half/core-hole approaches for accurate core excitation and emission calculations." }, { "num": "303c", "name": "Multiplety", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/gfabbris/multiplety", "note": "Python multiplet XAS/RIXS calculations using Cowan's atomic code", "md_link_text": "Multiplety.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/Multiplety.md", "papers": [], "paper_placeholder": true, "slug": "Multiplety", "idx": 690, "overview": "**Multiplety** is a Python package for multiplet calculations of X-ray absorption (XAS) and resonant inelastic X-ray scattering (RIXS) spectra using the Cowan's atomic code and Racer programs. It provides a Jupyter notebook-based interface for setting up and running multiplet calculations for transition metal and rare-earth systems." }, { "num": "303d", "name": "ThermoPW", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/dalcorso/thermo_pw", "note": "QE driver for automated IR, Raman, dielectric, elastic, and thermodynamic properties", "md_link_text": "ThermoPW.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/ThermoPW.md", "papers": [], "paper_placeholder": true, "slug": "ThermoPW", "idx": 691, "overview": "**ThermoPW** is a Fortran driver for Quantum ESPRESSO that enables parallel and automated computation of material thermodynamic and spectroscopic properties. It leverages QE routines for calculating dielectric properties, infrared spectra, Raman spectra, elastic constants, and thermodynamic quantities in a streamlined, high-throughput workflow." }, { "num": "303e", "name": "QERaman", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/nguyen-group/QERaman", "note": "First-order resonance Raman spectroscopy from Quantum ESPRESSO", "md_link_text": "QERaman.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/QERaman.md", "papers": [], "paper_placeholder": true, "slug": "QERaman", "idx": 692, "overview": "**QERaman** is an open-source program for computing first-order resonance Raman spectroscopy based on Quantum ESPRESSO. It calculates resonance Raman intensities by evaluating the derivative of the frequency-dependent dielectric function with respect to phonon normal mode coordinates, enabling simulation of Raman spectra under resonant conditions." }, { "num": "303f", "name": "ramannoodle", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/wolearyc/ramannoodle", "note": "ML-accelerated off-resonance Raman spectra from VASP", "md_link_text": "ramannoodle.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/ramannoodle.md", "papers": [], "paper_placeholder": true, "slug": "ramannoodle", "idx": 693, "overview": "**ramannoodle** is a Python package for efficiently computing off-resonance Raman spectra from first-principles calculations (e.g., VASP) using polynomial models and machine learning. It dramatically accelerates Raman spectrum computation by replacing expensive finite-difference dielectric tensor derivatives with ML-based surrogate models." }, { "num": "303g", "name": "VASP-Raman", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/raman-sc/VASP", "note": "Off-resonance Raman activity using VASP dielectric tensor (finite displacement)", "md_link_text": "VASP-Raman.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/VASP-Raman.md", "papers": [ { "name": "Kresse_Furthmuller_1996.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/Kresse_Furthmuller_1996.pdf", "doi_url": "https://scholar.google.com/scholar?q=VASP-Raman+Kresse+Furthmuller+1996" }, { "name": "Kresse_Hafner_1993.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/Kresse_Hafner_1993.pdf", "doi_url": "https://scholar.google.com/scholar?q=VASP-Raman+Kresse+Hafner+1993" }, { "name": "10.1016_0927-0256(96)00008-0.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/10.1016_0927-0256%2896%2900008-0.pdf", "doi_url": "https://doi.org/10.1016/0927-0256(96)00008-0" } ], "paper_placeholder": false, "slug": "VASP-Raman", "idx": 694, "overview": "**VASP-Raman** is a Python program for evaluating off-resonance Raman activity using VASP as the backend. It computes Raman spectra by calculating the derivative of the macroscopic dielectric tensor (polarizability) with respect to phonon normal mode coordinates using finite displacements." }, { "num": "303h", "name": "phonopy-vibspec", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/pierre-24/phonopy-vibspec", "note": "IR and Raman spectra simulation from Phonopy phonon data", "md_link_text": "phonopy-vibspec.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/phonopy-vibspec.md", "papers": [ { "name": "10_1103_PhysRevLett_78_4063.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_1103_PhysRevLett_78_4063.pdf", "doi_url": "https://scholar.google.com/scholar?q=phonopy-vibspec+10+1103+PhysRevLett+78+4063" }, { "name": "10_7566_JPSJ_92_012001.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_7566_JPSJ_92_012001.pdf", "doi_url": "https://scholar.google.com/scholar?q=phonopy-vibspec+10+7566+JPSJ+92+012001" }, { "name": "10_1016_j_cpc_2009_03_010.pdf", "path": "Papers_of_Codes/Phonons/5.1_Harmonic_Phonons/PHON/10_1016_j_cpc_2009_03_010.pdf", "doi_url": "https://scholar.google.com/scholar?q=phonopy-vibspec+10+1016+j+cpc+2009+03+010" } ], "paper_placeholder": false, "slug": "phonopy-vibspec", "idx": 695, "overview": "**phonopy-vibspec** is a Python tool for simulating IR and Raman spectra from Phonopy phonon calculations. It processes phonon eigenvalues and eigenvectors from Phonopy to compute infrared intensities and Raman activities, producing publication-quality vibrational spectra." }, { "num": "303i", "name": "PPSTM", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/Probe-Particle/PPSTM", "note": "Probe-particle model for STM, STS, and IETS simulation (CPC 2024)", "md_link_text": "PPSTM.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/PPSTM.md", "papers": [], "paper_placeholder": true, "slug": "PPSTM", "idx": 696, "overview": "**PPSTM** (Probe-Particle STM) is a simulation code for various scanning tunneling microscopy (STM) techniques, including STM imaging, scanning tunneling spectroscopy (STS), and inelastic electron tunneling spectroscopy (IETS). It uses the probe-particle model to simulate tip-sample interactions with sub-molecular resolution." }, { "num": "303j", "name": "ppafm", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/Probe-Particle/ppafm", "note": "Probe-particle model for HR-AFM, STM, IETS, TERS, KPFM simulation", "md_link_text": "ppafm.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/ppafm.md", "papers": [], "paper_placeholder": true, "slug": "ppafm", "idx": 697, "overview": "**ppafm** (Probe-Particle AFM) is a simple and efficient simulation software for high-resolution atomic force microscopy (HR-AFM) and other scanning probe microscopy (SPM) techniques with sub-molecular resolution. It simulates the deflection of a probe particle (typically CO or Xe) attached to the tip, enabling realistic AFM, STM, IETS, and TERS simulations." }, { "num": "303k", "name": "PyTASER", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/WMD-group/PyTASER", "note": "Transient absorption spectroscopy (TAS/DAS) simulation from DFT", "md_link_text": "PyTASER.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/PyTASER.md", "papers": [ { "name": "PyTASER_10.21105_joss.05999.pdf", "path": "Papers_of_Codes/Post-Processing/PyTASER/PyTASER_10.21105_joss.05999.pdf", "doi_url": "https://doi.org/10.21105/joss.05999" } ], "paper_placeholder": false, "slug": "PyTASER", "idx": 698, "overview": "**PyTASER** is a Python package for simulating differential absorption spectra in crystalline compounds from first-principles calculations, including transient absorption spectroscopy (TAS) and differential absorption spectroscopy (DAS). It predicts spectra for comparison with and interpretation of experimental pump-probe measurements." }, { "num": "303l", "name": "mbxaspy", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/yufengliang/mbxaspy", "note": "XAS simulation using determinant formalism with DFT and many-body extensions", "md_link_text": "mbxaspy.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/mbxaspy.md", "papers": [], "paper_placeholder": true, "slug": "mbxaspy", "idx": 699, "overview": "**mbxaspy** is a Python software package for predicting X-ray spectra using the determinant formalism based on the independent-electron approximation as used in DFT. It interfaces with the ShirleyXAS Fortran package for DFT and XAS calculations at the one-body level, and can also work with tight-binding models for many-body XAS calculations." }, { "num": "303m", "name": "xas-tools", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/atomisticnet/xas-tools", "note": "XAS simulation, analysis, and ML prediction toolkit", "md_link_text": "xas-tools.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/xas-tools.md", "papers": [], "paper_placeholder": true, "slug": "xas-tools", "idx": 700, "overview": "**xas-tools** is a Python toolkit for X-ray absorption spectroscopy (XAS) simulation and analysis, providing tools for generating simulated XAS databases, analyzing XAS spectra, and interfacing with machine learning models for XAS prediction from atomic structure." }, { "num": "303n", "name": "QuantEXAFS", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/kul-group/QuantEXAFS", "note": "Automated EXAFS fitting with DFT structure database integration", "md_link_text": "QuantEXAFS.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/QuantEXAFS.md", "papers": [], "paper_placeholder": true, "slug": "QuantEXAFS", "idx": 701, "overview": "**QuantEXAFS** is a Python-based toolkit for automated fitting of Extended X-ray Absorption Fine Structure (EXAFS) data using X-ray Larch modules. It combines DFT-optimized structure databases with automated EXAFS fitting workflows, enabling quantitative structural analysis from EXAFS measurements." }, { "num": "303o", "name": "XANESNET", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/NewcastleRSE/xray-spectroscopy-ml", "note": "Deep neural network for XANES prediction (J. Chem. Phys. 2022)", "md_link_text": "XANESNET.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/XANESNET.md", "papers": [], "paper_placeholder": true, "slug": "XANESNET", "idx": 702, "overview": "**XANESNET** is a deep neural network for predicting X-ray Absorption Near Edge Structure (XANES) spectra from molecular structure descriptors. It enables fast and accurate prediction of transition metal XAS spectra without requiring expensive first-principles calculations, making it suitable for high-throughput screening and real-time spectral prediction." }, { "num": "303p", "name": "pyFitIt", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/gudasergey/pyFitIt", "note": "ML-accelerated XANES fitting for structural determination", "md_link_text": "pyFitIt.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/pyFitIt.md", "papers": [ { "name": "pyFitIt_10.1016_j.cpc.2019.107064.pdf", "path": "Papers_of_Codes/Post-Processing/pyFitIt/pyFitIt_10.1016_j.cpc.2019.107064.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2019.107064" } ], "paper_placeholder": false, "slug": "pyFitIt", "idx": 703, "overview": "**pyFitIt** is a Python implementation of the FitIt software for fitting X-ray Absorption Near Edge Structure (XANES) and other spectra. It uses machine learning and automatic component analysis to fit theoretical XANES spectra to experimental data, enabling structural determination from XANES measurements." }, { "num": "303q", "name": "MLXANES", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/tnorthey/mlxanes", "note": "Fortran multivariate linear regression for XANES prediction from structure", "md_link_text": "MLXANES.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/MLXANES.md", "papers": [], "paper_placeholder": true, "slug": "MLXANES", "idx": 704, "overview": "**MLXANES** is an OpenMP-parallelized multivariate linear regression Fortran program for predicting X-ray Absorption Near Edge Structure (XANES) spectra from atomic structure (XYZ files). It uses machine learning to establish structure-spectrum relationships, enabling rapid XANES prediction without first-principles calculations." }, { "num": "303r", "name": "qeapp-xps", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/superstar54/qeapp-xps", "note": "AiiDA-QE plugin for XPS spectra using core-hole pseudopotentials", "md_link_text": "qeapp-xps.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/qeapp-xps.md", "papers": [], "paper_placeholder": true, "slug": "qeapp-xps", "idx": 705, "overview": "**qeapp-xps** is an AiiDA plugin for calculating X-ray Photoelectron Spectroscopy (XPS) spectra using the XpsWorkChain of the aiida-quantumespresso package. It provides an automated workflow for computing core-level binding energies using core-hole pseudopotentials within Quantum ESPRESSO." }, { "num": "303s", "name": "pyEELS", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/sindrebilden/pyeels", "note": "EELS simulation from model band structures (PythTB integration)", "md_link_text": "pyEELS.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/pyEELS.md", "papers": [], "paper_placeholder": true, "slug": "pyEELS", "idx": 706, "overview": "**pyEELS** is a Python simulation package for constructing Electron Energy Loss Spectroscopy (EELS) spectra from model band structures. It simulates EELS based on model band structures created using PythTB (Python Tight Binding) or parabolic band models, enabling rapid spectral prediction for materials characterization." }, { "num": "303t", "name": "ShiftML", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/lab-cosmo/ShiftML", "note": "ML prediction of NMR chemical shieldings for organic solids (Chem. Sci. 2021)", "md_link_text": "ShiftML.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/ShiftML.md", "papers": [ { "name": "ShiftML_10.1038_s41467-018-06972-x.pdf", "path": "Papers_of_Codes/Post-Processing/ShiftML/ShiftML_10.1038_s41467-018-06972-x.pdf", "doi_url": "https://doi.org/10.1038/s41467-018-06972-x" } ], "paper_placeholder": false, "slug": "ShiftML", "idx": 707, "overview": "**ShiftML** is a Python package for the prediction of NMR chemical shieldings in organic solids using machine learning. It is trained on a large dataset of chemical shieldings computed with DFT GIPAW and can predict shieldings for a wide range of organic crystals at a fraction of the computational cost." }, { "num": "303u", "name": "cp2k_xas_tool", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.5", "subcategory": "Spectroscopy Simulation", "confidence": "VERIFIED", "official_url": "https://github.com/houzf/cp2k_xas_tool", "note": "CP2K GAPW XAS spectrum broadening with flexible broadening functions", "md_link_text": "cp2k_xas_tool.md", "md_link_path": "Post-Processing/8.5_Spectroscopy/cp2k_xas_tool.md", "papers": [ { "name": "Kuhne_et_al_2020.pdf", "path": "Papers_of_Codes/TDDFT/2.2_Linear-Response_TDDFT/CP2K/Kuhne_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=cp2k_xas_tool+Kuhne+et+al+2020" } ], "paper_placeholder": false, "slug": "cp2k_xas_tool", "idx": 708, "overview": "**cp2k_xas_tool** is a Python tool for broadening XAS (X-ray Absorption Spectroscopy) spectra simulated with CP2K using the GAPW method. It processes CP2K XAS output and applies appropriate broadening to produce smooth, publication-quality XAS spectra." }, { "num": "294", "name": "Magnon codes", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "*VARIOUS* (e.g., SpinW: https://spinw.org/)", "note": "", "md_link_text": "Magnon-codes.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/Magnon-codes.md", "papers": [], "paper_placeholder": true, "slug": "Magnon-codes", "idx": 709, "overview": "This entry serves as a category placeholder for magnon simulation and spin dynamics codes. The primary modern tools for magnon calculations are **Spirit**, **VAMPIRE**, **SpinW**, and **UppASD**. These codes typically perform atomistic spin dynamics (ASD) simulations or linear spin wave theory (LSWT) calculations to determine magnon dispersion relations, lifetimes, and thermodynamic magnetic properties." }, { "num": "295", "name": "Spirit", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://spirit-docs.readthedocs.io/", "note": "", "md_link_text": "Spirit.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/Spirit.md", "papers": [ { "name": "10_1103_PhysRevB_99_224414.pdf", "path": "Papers_of_Codes/Post-Processing/8.6_Magnetism_Spin/Spirit/10_1103_PhysRevB_99_224414.pdf", "doi_url": "https://scholar.google.com/scholar?q=Spirit+10+1103+PhysRevB+99+224414" } ], "paper_placeholder": false, "slug": "Spirit", "idx": 710, "overview": "Spirit is a framework for spin dynamics and calculating energy landscapes of magnetic systems. It allows for atomistic spin dynamics (ASD) simulations and the determination of minimum energy paths and transition states (e.g., for magnetic skyrmion collapse) using the Geodesic Nudged Elastic Band (GNEB) method. Spirit provides a desktop GUI with real-time visualization and a powerful Python API." }, { "num": "296", "name": "VAMPIRE", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://vampire.york.ac.uk/", "note": "", "md_link_text": "VAMPIRE.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/VAMPIRE.md", "papers": [ { "name": "10_1088_0953-8984_26_10_103202.pdf", "path": "Papers_of_Codes/Post-Processing/8.6_Magnetism_Spin/VAMPIRE/10_1088_0953-8984_26_10_103202.pdf", "doi_url": "https://scholar.google.com/scholar?q=VAMPIRE+10+1088+0953+8984+26+10+103202" } ], "paper_placeholder": false, "slug": "VAMPIRE", "idx": 711, "overview": "VAMPIRE is an atomistic spin dynamics (ASD) code designed for the simulation of magnetic materials. It allows for the simulation of magnetic properties at finite temperatures, including magnetization dynamics, hysteresis loops, and Curie temperatures. VAMPIRE uses the Landau-Lifshitz-Gilbert (LLG) equation and Monte Carlo methods to model magnetic systems ranging from single atoms to complex heterostructures." }, { "num": "298", "name": "Mumax3", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://mumax.github.io/", "note": "", "md_link_text": "Mumax3.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/Mumax3.md", "papers": [ { "name": "Mumax3_10.1063_1.4899186.pdf", "path": "Papers_of_Codes/Post-Processing/Mumax3/Mumax3_10.1063_1.4899186.pdf", "doi_url": "https://doi.org/10.1063/1.4899186" } ], "paper_placeholder": false, "slug": "Mumax3", "idx": 712, "overview": "Mumax3 is a GPU-accelerated micromagnetic simulation program. It solves the time-dependent Landau-Lifshitz-Gilbert (LLG) equation using finite difference discretization. It is designed to be highly efficient, running exclusively on NVIDIA GPUs, and provides a rich scripting interface (Go-like syntax) for defining complex geometries, time-dependent fields, and various magnetic interactions." }, { "num": "299", "name": "McPhase", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "http://www.mcphase.de/", "note": "", "md_link_text": "McPhase.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/McPhase.md", "papers": [ { "name": "McPhase_10.1016_j.jmmm.2003.12.1394.pdf", "path": "Papers_of_Codes/Post-Processing/McPhase/McPhase_10.1016_j.jmmm.2003.12.1394.pdf", "doi_url": "https://doi.org/10.1016/j.jmmm.2003.12.1394" } ], "paper_placeholder": false, "slug": "McPhase", "idx": 713, "overview": "McPhase is a software package for calculating magnetic phase diagrams and thermodynamic properties of magnetic materials. It uses a mean-field approximation combined with Monte Carlo simulations to treat localized magnetic moments in crystal fields. It is particularly specialized for rare-earth magnetism, handling crystal electric field (CEF) effects, exchange interactions, and magneto-elastic coupling." }, { "num": "299a", "name": "SpinW", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://spinw.org/", "note": "", "md_link_text": "SpinW.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/SpinW.md", "papers": [ { "name": "SpinW_10.1088_0953-8984_27_16_166002.pdf", "path": "Papers_of_Codes/Post-Processing/SpinW/SpinW_10.1088_0953-8984_27_16_166002.pdf", "doi_url": "https://doi.org/10.1088/0953-8984_27_16_166002" } ], "paper_placeholder": false, "slug": "SpinW", "idx": 714, "overview": "SpinW is a MATLAB library (with upcoming Python/C++ versions) for optimizing magnetic structures and calculating magnetic excitations (magnons) using Linear Spin Wave Theory (LSWT). It is widely used for fitting experimental inelastic neutron scattering (INS) data to spin Hamiltonian models." }, { "num": "299b", "name": "UppASD", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://github.com/UppASD/UppASD", "note": "Atomistic spin dynamics + Monte Carlo + magnon dispersion (Uppsala)", "md_link_text": "UppASD.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/UppASD.md", "papers": [ { "name": "UppASD_10.1088_0953-8984_20_31_315203.pdf", "path": "Papers_of_Codes/Post-Processing/UppASD/UppASD_10.1088_0953-8984_20_31_315203.pdf", "doi_url": "https://doi.org/10.1088/0953-8984_20_31_315203" } ], "paper_placeholder": false, "slug": "UppASD", "idx": 715, "overview": "**UppASD** (Uppsala Atomistic Spin Dynamics) is a simulation tool for atomistic spin dynamics and Monte Carlo simulations of Heisenberg spin systems. It studies magnetization dynamics using the atomistic Landau-Lifshitz-Gilbert (LLG) equation and can compute magnon dispersion via linear spin-wave theory." }, { "num": "299c", "name": "OOMMF", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://math.nist.gov/oommf/", "note": "NIST public domain micromagnetic framework, de facto standard", "md_link_text": "OOMMF.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/OOMMF.md", "papers": [ { "name": "OOMMF_10.1109_TMAG.2015.2503262.pdf", "path": "Papers_of_Codes/Post-Processing/OOMMF/OOMMF_10.1109_TMAG.2015.2503262.pdf", "doi_url": "https://doi.org/10.1109/TMAG.2015.2503262" } ], "paper_placeholder": false, "slug": "OOMMF", "idx": 716, "overview": "**OOMMF** (Object Oriented MicroMagnetic Framework) is a public domain micromagnetic simulation program developed at NIST. It solves the Landau-Lifshitz-Gilbert equation on a finite-difference grid using Tcl/Tk for GUI and C++ for computation, and is the de facto standard for micromagnetic benchmark problems." }, { "num": "299d", "name": "magnum.af", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://github.com/magnum-af/magnum.af", "note": "Finite-difference/FEM micromagnetic simulation with true PBC and spin-torque", "md_link_text": "magnum.af.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/magnum.af.md", "papers": [], "paper_placeholder": true, "slug": "magnum.af", "idx": 717, "overview": "**magnum.af** is a finite-difference/finite-element micromagnetic simulation package that combines CPU and GPU solvers. It supports standard micromagnetic energy terms plus spin-transfer torque, spin-orbit torque, and true periodic boundary conditions for stray field calculation." }, { "num": "299e", "name": "fidimag", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://github.com/computationalmodelling/fidimag", "note": "Dual micromagnetic+atomistic spin simulation with NEB energy barriers", "md_link_text": "fidimag.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/fidimag.md", "papers": [], "paper_placeholder": true, "slug": "fidimag", "idx": 718, "overview": "**fidimag** (Finite DIfference microMAGnetic code) is a Python/Cython/C package for finite-difference micromagnetic and atomistic simulations. It supports both continuum micromagnetic and atomistic spin models, making it suitable for multiscale magnetic simulations." }, { "num": "299f", "name": "MicroMagnetic.jl", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://github.com/MagneticSimulation/MicroMagnetic.jl", "note": "Julia GPU-accelerated spin dynamics (NVIDIA/AMD/Intel/Apple)", "md_link_text": "MicroMagnetic.jl.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/MicroMagnetic.jl.md", "papers": [], "paper_placeholder": true, "slug": "MicroMagnetic.jl", "idx": 719, "overview": "**MicroMagnetic.jl** is a Julia package for classical spin dynamics and micromagnetic simulations with multi-platform GPU support (NVIDIA, AMD, Intel, Apple). It supports atomistic and continuum spin simulations, Monte Carlo, NEB energy barriers, and spin-transfer torque effects." }, { "num": "299g", "name": "mumax+", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://github.com/mumax/plus", "note": "Extensible GPU micromagnetic simulator with Python interface (mumax3 successor)", "md_link_text": "mumax-plus.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/mumax-plus.md", "papers": [], "paper_placeholder": true, "slug": "mumax", "idx": 720, "overview": "**mumax+** (mumax plus) is a versatile and extensible GPU-accelerated micromagnetic simulator written in C++ and CUDA with a Python interface. It is the successor to mumax3, offering more extensibility, Python scripting, and additional physics capabilities beyond standard micromagnetics." }, { "num": "299h", "name": "exchanges", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://github.com/dkorotin/exchanges", "note": "Heisenberg exchange parameters via Green's function from QE (Lichtenstein formula)", "md_link_text": "exchanges.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/exchanges.md", "papers": [], "paper_placeholder": true, "slug": "exchanges", "idx": 721, "overview": "**exchanges** is a Fortran code for calculating Heisenberg exchange parameters for magnetic compounds using the Green's function formalism within Density Functional Theory. It interfaces with Quantum ESPRESSO to compute exchange coupling constants (Jij) from first principles." }, { "num": "299i", "name": "Jx_DMFT", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://github.com/KAIST-ELST/Jx_DMFT", "note": "Exchange parameters with DFT+DMFT for correlated magnets", "md_link_text": "Jx_DMFT.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/Jx_DMFT.md", "papers": [], "paper_placeholder": true, "slug": "Jx_DMFT", "idx": 722, "overview": "**Jx_DMFT** is a software for calculating magnetic exchange parameters (Jx) from the magnetic force theorem, combined with both DFT and dynamical mean-field theory (DMFT). It can compute magnon dispersion and spectral functions from the exchange parameters, including correlation effects beyond DFT." }, { "num": "299j", "name": "MAELAS", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://github.com/pnieves2019/MAELAS", "note": "Magnetostriction and MAE calculation from VASP with non-collinear SOC", "md_link_text": "MAELAS.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/MAELAS.md", "papers": [ { "name": "MAELAS_10.1016_j.cpc.2021.107964.pdf", "path": "Papers_of_Codes/Post-Processing/MAELAS/MAELAS_10.1016_j.cpc.2021.107964.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2021.107964" } ], "paper_placeholder": false, "slug": "MAELAS", "idx": 723, "overview": "**MAELAS** (MAgnetoElastic Anisotropy Simulation) is a software for calculating magnetostriction coefficients and magnetocrystalline anisotropy energy (MAE) from first principles using VASP. It automates the generation of VASP input files for non-collinear magnetic calculations with spin-orbit coupling." }, { "num": "299k", "name": "AtomMag", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://github.com/jhu238/AtomMag", "note": "GPU-parallel atomistic spin dynamics (66x speedup over CPU)", "md_link_text": "AtomMag.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/AtomMag.md", "papers": [], "paper_placeholder": true, "slug": "AtomMag", "idx": 724, "overview": "**AtomMag** is a GPU-parallel atomistic spin dynamics model developed at the University of Wisconsin-Madison. It achieves 66x speedup over CPU implementations and is validated against fidimag and analytical results, supporting large-scale atomistic magnetic simulations." }, { "num": "299l", "name": "Ubermag", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://ubermag.github.io/", "note": "Python DSL for micromagnetics wrapping OOMMF/Mumax3/fidimag, Jupyter-integrated", "md_link_text": "Ubermag.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/Ubermag.md", "papers": [ { "name": "Ubermag_10.1109_TMAG.2021.3078896.pdf", "path": "Papers_of_Codes/Post-Processing/Ubermag/Ubermag_10.1109_TMAG.2021.3078896.pdf", "doi_url": "https://doi.org/10.1109/TMAG.2021.3078896" } ], "paper_placeholder": false, "slug": "Ubermag", "idx": 725, "overview": "**Ubermag** is a Python-based domain-specific language for computational magnetism that provides a Jupyter-integrated workflow for micromagnetic simulations. It wraps multiple micromagnetic solvers (OOMMF, Mumax3, fidimag) with a unified Python interface, enabling interactive simulation, analysis, and visualization in notebooks." }, { "num": "299m", "name": "DarkMAGIC", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.6", "subcategory": "Magnetism & Spin Dynamics", "confidence": "VERIFIED", "official_url": "https://github.com/Griffin-Group/DarkMAGIC", "note": "Ab initio magnon/phonon interaction calculator for dark matter detection", "md_link_text": "DarkMAGIC.md", "md_link_path": "Post-Processing/8.6_Magnetism_Spin/DarkMAGIC.md", "papers": [], "paper_placeholder": true, "slug": "DarkMAGIC", "idx": 726, "overview": "**DarkMAGIC** (Dark Matter Ab initio maGnon/phonon Interaction Calculator) is a Python package for computing dark matter interaction rates with collective excitations (magnons and phonons) based on ab initio calculations of material properties. It supports magnon calculations using ab initio-based spin Hamiltonians." }, { "num": "300", "name": "VESTA", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.7", "subcategory": "Visualization", "confidence": "VERIFIED", "official_url": "https://jp-minerals.org/vesta/en/", "note": "", "md_link_text": "VESTA.md", "md_link_path": "Post-Processing/8.7_Visualization/VESTA.md", "papers": [ { "name": "10.1107_S0021889811038970.pdf", "path": "Papers_of_Codes/Post-Processing/8.7_Visualization/VESTA/10.1107_S0021889811038970.pdf", "doi_url": "https://doi.org/10.1107/S0021889811038970" } ], "paper_placeholder": false, "slug": "VESTA", "idx": 727, "overview": "VESTA is a 3D visualization program for structural models, volumetric data such as electron/nuclear densities, and crystal morphologies. It is one of the most popular tools in materials science for visualizing crystal structures and electronic structure data (charge densities, wavefunctions). VESTA supports a wide range of file formats and provides high-quality rendering for publications." }, { "num": "301", "name": "XCrySDen", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.7", "subcategory": "Visualization", "confidence": "VERIFIED", "official_url": "http://www.xcrysden.org/", "note": "", "md_link_text": "XCrySDen.md", "md_link_path": "Post-Processing/8.7_Visualization/XCrySDen.md", "papers": [ { "name": "10_1016_S0927-02560300104-6.pdf", "path": "Papers_of_Codes/Post-Processing/8.7_Visualization/XCrySDen/10_1016_S0927-02560300104-6.pdf", "doi_url": "https://scholar.google.com/scholar?q=XCrySDen+10+1016+S0927+02560300104+6" } ], "paper_placeholder": false, "slug": "XCrySDen", "idx": 728, "overview": "XCrySDen (X-Window Crystalline Structures and Densities) is a crystalline and molecular structure visualization program capable of displaying isosurfaces and contours from grid data. It is specifically designed for solid-state physics and interfaces seamlessly with major electronic structure codes like WIEN2k, Quantum ESPRESSO, and CRYSTAL. It allows for the interactive selection of k-paths in the Brillouin zone and real-time manipulation of structures." }, { "num": "302", "name": "VMD", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.7", "subcategory": "Visualization", "confidence": "VERIFIED", "official_url": "https://www.ks.uiuc.edu/Research/vmd/", "note": "", "md_link_text": "VMD.md", "md_link_path": "Post-Processing/8.7_Visualization/VMD.md", "papers": [ { "name": "10_1016_0263-78559600018-5.pdf", "path": "Papers_of_Codes/Post-Processing/8.7_Visualization/VMD/10_1016_0263-78559600018-5.pdf", "doi_url": "https://scholar.google.com/scholar?q=VMD+10+1016+0263+78559600018+5" } ], "paper_placeholder": false, "slug": "VMD", "idx": 729, "overview": "VMD is a molecular visualization program for displaying, animating, and analyzing large biomolecular systems using 3D graphics and built-in scripting. While originally designed for biological systems, it is widely used in materials science for visualizing MD trajectories (from LAMMPS, NAMD, GROMACS) and volumetric data (charge densities, orbitals). It supports a vast range of file formats and is highly extensible via Tcl and Python scripting." }, { "num": "303", "name": "Avogadro", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.7", "subcategory": "Visualization", "confidence": "VERIFIED", "official_url": "https://avogadro.cc/", "note": "", "md_link_text": "Avogadro.md", "md_link_path": "Post-Processing/8.7_Visualization/Avogadro.md", "papers": [ { "name": "10_1186_1758-2946-4-17.pdf", "path": "Papers_of_Codes/Post-Processing/8.7_Visualization/Avogadro/10_1186_1758-2946-4-17.pdf", "doi_url": "https://scholar.google.com/scholar?q=Avogadro+10+1186+1758+2946+4+17" } ], "paper_placeholder": false, "slug": "Avogadro", "idx": 730, "overview": "Avogadro is an advanced molecule editor and visualizer designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas. It offers flexible high quality rendering and a powerful plugin architecture. It is widely used for building molecular structures, generating input files for various quantum chemistry codes, and visualizing results." }, { "num": "305", "name": "JMol", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.7", "subcategory": "Visualization", "confidence": "VERIFIED", "official_url": "https://jmol.sourceforge.net/", "note": "", "md_link_text": "JMol.md", "md_link_path": "Post-Processing/8.7_Visualization/JMol.md", "papers": [ { "name": "10_1107_S0021889810030256.pdf", "path": "Papers_of_Codes/Post-Processing/8.7_Visualization/JMol/10_1107_S0021889810030256.pdf", "doi_url": "https://scholar.google.com/scholar?q=JMol+10+1107+S0021889810030256" } ], "paper_placeholder": false, "slug": "JMol", "idx": 731, "overview": "Jmol is a free, open-source Java viewer for chemical structures in 3D. It is designed to be cross-platform, running on Windows, Mac, Linux, and Unix systems. It supports a huge range of file formats and is widely used for teaching, research, and web-based visualization (via JSmol, the HTML5/JavaScript version). It can visualize molecules, crystals, materials, and biomolecules, along with orbitals, surfaces, and vibrations." }, { "num": "306", "name": "PyMOL", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.7", "subcategory": "Visualization", "confidence": "VERIFIED", "official_url": "https://pymol.org/", "note": "", "md_link_text": "PyMOL.md", "md_link_path": "Post-Processing/8.7_Visualization/PyMOL.md", "papers": [], "paper_placeholder": true, "slug": "PyMOL", "idx": 732, "overview": "PyMOL is a molecular visualization system on an open-source foundation, maintained by Schr\u00f6dinger. It is renowned for its high-quality rendering of biomolecules (proteins, nucleic acids) and its powerful Python scripting capabilities. PyMOL excels at creating publication-quality images and movies, and performing structural analysis like superposition and measurement." }, { "num": "307", "name": "OVITO", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.7", "subcategory": "Visualization", "confidence": "VERIFIED", "official_url": "https://ovito.org/", "note": "", "md_link_text": "OVITO.md", "md_link_path": "Post-Processing/8.7_Visualization/OVITO.md", "papers": [ { "name": "OVITO_10.1088_0965-0393_18_1_015012.pdf", "path": "Papers_of_Codes/Post-Processing/OVITO/OVITO_10.1088_0965-0393_18_1_015012.pdf", "doi_url": "https://doi.org/10.1088/0965-0393_18_1_015012" } ], "paper_placeholder": false, "slug": "OVITO", "idx": 733, "overview": "OVITO is a scientific visualization and analysis software for atomistic and particle simulation data. It is widely used in materials science, physics, and chemistry to analyze output from molecular dynamics (LAMMPS, GROMACS), Monte Carlo, and ab-initio simulations. OVITO excels at processing large datasets (millions of atoms) and provides a powerful pipeline architecture for applying analysis modifiers (e.g., dislocation analysis, cluster analysis) non-destructively." }, { "num": "312", "name": "ASE-GUI", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.7", "subcategory": "Visualization", "confidence": "VERIFIED", "official_url": "https://wiki.fysik.dtu.dk/ase/ase/gui/gui.html", "note": "", "md_link_text": "ASE-GUI.md", "md_link_path": "Post-Processing/8.7_Visualization/ASE-GUI.md", "papers": [ { "name": "Larsen_et_al_2017.pdf", "path": "Papers_of_Codes/Post-Processing/8.7_Visualization/ASE-GUI/Larsen_et_al_2017.pdf", "doi_url": "https://scholar.google.com/scholar?q=ASE-GUI+Larsen+et+al+2017" }, { "name": "10_1088_1361-648X_aa680e.pdf", "path": "Papers_of_Codes/Post-Processing/8.7_Visualization/ASE-GUI/10_1088_1361-648X_aa680e.pdf", "doi_url": "https://scholar.google.com/scholar?q=ASE-GUI+10+1088+1361+648X+aa680e" } ], "paper_placeholder": false, "slug": "ASE-GUI", "idx": 734, "overview": "ASE-GUI is the graphical user interface for the Atomic Simulation Environment (ASE). It is a lightweight, Python-based viewer that allows users to visualize, manipulate, and analyze atomic structures. It is integrated directly into ASE and can handle any file format supported by ASE (xyz, cif, POSCAR, trajectory files, etc.). It is particularly useful for quick inspection of structures, setting up constraints, and visualizing MD trajectories or relaxation paths." }, { "num": "312a", "name": "matterviz", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.7", "subcategory": "Visualization", "confidence": "VERIFIED", "official_url": "https://github.com/janosh/matterviz", "note": "Interactive web-based materials science visualization (structures, spectra, phase diagrams)", "md_link_text": "matterviz.md", "md_link_path": "Post-Processing/8.7_Visualization/matterviz.md", "papers": [], "paper_placeholder": true, "slug": "matterviz", "idx": 735, "overview": "**matterviz** is a toolkit for building interactive web UIs for materials science, providing 3D crystal structures, molecules, MD/relaxation trajectories, periodic tables, phase diagrams, convex hulls, spectral data (bands, DOS, XRD), heatmaps, and scatter plots. It is built on modern web technologies for browser-based visualization." }, { "num": "312b", "name": "cif2cell", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.7", "subcategory": "Visualization", "confidence": "VERIFIED", "official_url": "https://github.com/torbjornbjorkman/cif2cell", "note": "CIF to 20+ DFT code input format converter with k-point generation", "md_link_text": "cif2cell.md", "md_link_path": "Post-Processing/8.7_Visualization/cif2cell.md", "papers": [ { "name": "cif2cell_10.1016_j.cpc.2011.01.013.pdf", "path": "Papers_of_Codes/Post-Processing/cif2cell/cif2cell_10.1016_j.cpc.2011.01.013.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2011.01.013" } ], "paper_placeholder": false, "slug": "cif2cell", "idx": 736, "overview": "**cif2cell** is a tool to generate the geometrical setup for various electronic structure codes from a CIF (Crystallographic Information Framework) file. It converts crystallographic data to input formats for DFT codes, bridging experimental crystallography and computational workflows." }, { "num": "312c", "name": "surfaxe", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.7", "subcategory": "Visualization", "confidence": "VERIFIED", "official_url": "https://github.com/SMTG-Bham/surfaxe", "note": "Surface slab analysis (energy, work function, convergence) for VASP", "md_link_text": "surfaxe.md", "md_link_path": "Post-Processing/8.7_Visualization/surfaxe.md", "papers": [ { "name": "surfaxe_10.21105_joss.03171.pdf", "path": "Papers_of_Codes/Post-Processing/surfaxe/surfaxe_10.21105_joss.03171.pdf", "doi_url": "https://doi.org/10.21105/joss.03171" } ], "paper_placeholder": false, "slug": "surfaxe", "idx": 737, "overview": "**surfaxe** is a Python package for dealing with slabs for first principles calculations. It automates surface energy convergence checks, work function calculations, bond length analysis, and slab thickness convergence for surface science DFT calculations with VASP." }, { "num": "312d", "name": "Molara", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.7", "subcategory": "Visualization", "confidence": "VERIFIED", "official_url": "https://github.com/Molara-Lab/Molara", "note": "Open-source 3D visualization for molecules and crystal structures", "md_link_text": "Molara.md", "md_link_path": "Post-Processing/8.7_Visualization/Molara.md", "papers": [], "paper_placeholder": true, "slug": "Molara", "idx": 738, "overview": "" }, { "num": "313", "name": "Nanodcal", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.8", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "https://www.nanodcal.com/", "note": "", "md_link_text": "Nanodcal.md", "md_link_path": "Post-Processing/8.8_Quantum_Transport/Nanodcal.md", "papers": [], "paper_placeholder": true, "slug": "Nanodcal", "idx": 739, "overview": "Nanodcal is a state-of-the-art quantum transport simulation software based on the Non-Equilibrium Green's Function (NEGF) density functional theory (DFT). It is designed to simulate electron transport through nanostructures and devices from first principles. Developed by Nanoacademic Technologies, it handles zero-bias and finite-bias conditions for molecular electronics, spintronics, and nanoscale devices." }, { "num": "314", "name": "Transiesta", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.8", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "**MODULE** - Part of SIESTA.", "note": "", "md_link_text": "Transiesta.md", "md_link_path": "Post-Processing/8.8_Quantum_Transport/Transiesta.md", "papers": [ { "name": "10.1103_PhysRevB.65.165401.pdf", "path": "Papers_of_Codes/Post-Processing/8.8_Quantum_Transport/TranSIESTA/10.1103_PhysRevB.65.165401.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.65.165401" } ], "paper_placeholder": false, "slug": "Transiesta", "idx": 740, "overview": "Transiesta is the quantum transport module of the SIESTA density functional theory code. It uses the Non-Equilibrium Green's Function (NEGF) method combined with DFT to calculate electron transport properties of nanoscale systems under finite bias voltage. It enables the simulation of current-voltage characteristics, transmission spectra, and local currents in molecular junctions, nanowires, and interfaces." }, { "num": "315", "name": "Smeagol", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.8", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "**MODULE** - Part of TranSIESTA/SIESTA suite.", "note": "", "md_link_text": "Smeagol.md", "md_link_path": "Post-Processing/8.8_Quantum_Transport/Smeagol.md", "papers": [ { "name": "10.1038_nmat1349.pdf", "path": "Papers_of_Codes/TightBinding/4.3_Quantum_Transport/SMEAGOL/10.1038_nmat1349.pdf", "doi_url": "https://doi.org/10.1038/nmat1349" } ], "paper_placeholder": false, "slug": "Smeagol", "idx": 741, "overview": "Smeagol is a software package for calculating spin-dependent electron transport in nanoscale devices. It interfaces with the SIESTA DFT code to perform Non-Equilibrium Green's Function (NEGF) calculations. Smeagol is specifically designed for spintronics, handling magnetic materials, spin torque, and non-collinear magnetism in transport junctions." }, { "num": "316", "name": "MIKA", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.8", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "https://github.com/MIKA-code/MIKA", "note": "", "md_link_text": "MIKA.md", "md_link_path": "Post-Processing/8.8_Quantum_Transport/MIKA.md", "papers": [], "paper_placeholder": true, "slug": "MIKA", "idx": 742, "overview": "MIKA (Multigrid Instead of K-spAce) is a collection of Matlab/Octave functions and C++ codes for electronic structure calculations using real-space grid methods (finite difference and multigrid). It includes a DFT solver (RMG) and a time-dependent DFT solver. It is designed for solving the Schr\u00f6dinger and Poisson equations on real-space grids, particularly useful for transport and large systems without periodic boundary conditions." }, { "num": "317a", "name": "Gollum", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.8", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "https://github.com/gollumcode/gollum2", "note": "Next-generation quantum transport for molecular junctions, NEGF, thermoelectrics", "md_link_text": "Gollum.md", "md_link_path": "Post-Processing/8.8_Quantum_Transport/Gollum.md", "papers": [ { "name": "10.1088_1367-2630_16_9_093029.pdf", "path": "Papers_of_Codes/TightBinding/4.3_Quantum_Transport/GOLLUM/10.1088_1367-2630_16_9_093029.pdf", "doi_url": "https://doi.org/10.1088/1367-2630_16_9_093029" } ], "paper_placeholder": false, "slug": "Gollum", "idx": 743, "overview": "**Gollum** is a next-generation quantum transport simulation tool for computing transport properties of nanoscale devices using the non-equilibrium Green's function (NEGF) method. It works with tight-binding Hamiltonians and can compute conductance, current-voltage characteristics, and thermoelectric properties." }, { "num": "317b", "name": "Jiezi", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.8", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "https://github.com/Jiezi-negf/Jiezi", "note": "Self-consistent NEGF-Poisson quantum transport with FEM, Python", "md_link_text": "Jiezi.md", "md_link_path": "Post-Processing/8.8_Quantum_Transport/Jiezi.md", "papers": [], "paper_placeholder": true, "slug": "Jiezi", "idx": 744, "overview": "**Jiezi** is an open-source Python software for simulating quantum transport of nanoscale devices. It solves the Schr\u00f6dinger and Poisson equations self-consistently using the non-equilibrium Green's function (NEGF) method with finite element discretization, enabling atomistic-level device simulation." }, { "num": "317c", "name": "DPNEGF", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.8", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "https://github.com/DeePTB-Lab/dpnegf", "note": "ML-accelerated quantum transport with DeePTB-NEGF, DFT accuracy at TB speed", "md_link_text": "dpnegf.md", "md_link_path": "Post-Processing/8.8_Quantum_Transport/dpnegf.md", "papers": [], "paper_placeholder": true, "slug": "DPNEGF", "idx": 745, "overview": "**DPNEGF** (DeePTB-NEGF) is a Python package that integrates the Deep Learning Tight-Binding (DeePTB) approach with the Non-Equilibrium Green's Function (NEGF) method, establishing an efficient quantum transport simulation framework with first-principles accuracy. It enables fast quantum transport calculations using ML-trained tight-binding Hamiltonians." }, { "num": "317d", "name": "GreenCheetah", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.8", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "https://github.com/StxGuy/GreenCheetah", "note": "Fortran/C++ NEGF quantum transport with Armadillo, recursive Green's function", "md_link_text": "GreenCheetah.md", "md_link_path": "Post-Processing/8.8_Quantum_Transport/GreenCheetah.md", "papers": [], "paper_placeholder": true, "slug": "GreenCheetah", "idx": 746, "overview": "**GreenCheetah** is a Non-Equilibrium Green's Function (NEGF) approach for quantum transport implemented in Fortran and C++/Armadillo. It provides efficient computation of quantum transport properties in nanoscale devices using the NEGF formalism." }, { "num": "317e", "name": "PyMoire", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.8", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "https://github.com/mahyar-servati/PyMoire", "note": "TB calculation of twisted bilayer moir\u00e9 systems with Wannier functions", "md_link_text": "PyMoire.md", "md_link_path": "Post-Processing/8.8_Quantum_Transport/PyMoire.md", "papers": [], "paper_placeholder": true, "slug": "PyMoire", "idx": 747, "overview": "**PyMoire** is a Python package for tight-binding calculation of twisted bilayer graphene and other moir\u00e9 systems based on mapped Wannier functions. It calculates band structures and density of states for twisted bilayer systems at any commensurate twist angle." }, { "num": "317f", "name": "RUQT", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.8", "subcategory": "Quantum Transport", "confidence": "VERIFIED", "official_url": "https://github.com/HoyLab-Rowan/RUQT", "note": "NEGF quantum transport with 2-RDM and MCPDFT beyond-DFT methods", "md_link_text": "RUQT.md", "md_link_path": "Post-Processing/8.8_Quantum_Transport/RUQT.md", "papers": [], "paper_placeholder": true, "slug": "RUQT", "idx": 748, "overview": "**RUQT** (Rowan University Quantum Transport) is a Fortran code for performing Landauer NEGF calculations using advanced electronic structure methods, particularly parametric 2-RDM (NEGF-RDM) and multi-configuration pair density functional theory (NEGF-MCPDFT) for quantum transport through molecular junctions." }, { "num": "310", "name": "dbaAutomator", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.9", "subcategory": "Workflow & Automation", "confidence": "VERIFIED", "official_url": "https://github.com/xingyu-alfred-liu/dbaAutomator", "note": "", "md_link_text": "dbaAutomator.md", "md_link_path": "Post-Processing/8.9_Workflow_Automation/dbaAutomator.md", "papers": [ { "name": "10.1103_PhysRevB.90.115148.pdf", "path": "Papers_of_Codes/Post-Processing/8.9_Workflow_Automation/dbaAutomator/10.1103_PhysRevB.90.115148.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.90.115148" } ], "paper_placeholder": false, "slug": "dbaAutomator", "idx": 749, "overview": "dbaAutomator (Double-Bader Analysis Automator) is a Python-based tool designed to assist users of the **BerkeleyGW** package. It automates the workflow for performing **Double-Bader Analysis (DBA)** on excitons in molecular crystals. This analysis characterizes the hole and electron distributions of excitons, quantifying the degree of charge transfer. It also provides functionality to verify the convergence of fine k-point grids for GW-BSE calculations." }, { "num": "311", "name": "gpaw-tools", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.9", "subcategory": "Workflow & Automation", "confidence": "VERIFIED", "official_url": "https://wiki.fysik.dtu.dk/gpaw/", "note": "", "md_link_text": "gpaw-tools.md", "md_link_path": "Post-Processing/8.9_Workflow_Automation/gpaw-tools.md", "papers": [ { "name": "Enkovaara_et_al_2010.pdf", "path": "Papers_of_Codes/TDDFT/2.1_Real-Time_TDDFT/GPAW/Enkovaara_et_al_2010.pdf", "doi_url": "https://scholar.google.com/scholar?q=gpaw-tools+Enkovaara+et+al+2010" } ], "paper_placeholder": false, "slug": "gpaw-tools", "idx": 750, "overview": "gpaw-tools is a collection of Python scripts and modules designed to facilitate the use of the GPAW DFT code. It automates common tasks such as converging calculations, analyzing band structures, plotting density of states (DOS), and calculating optical properties. It acts as a user-friendly wrapper around GPAW and ASE functionality." }, { "num": "311a", "name": "doped", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.9", "subcategory": "Workflow & Automation", "confidence": "VERIFIED", "official_url": "https://github.com/SMTG-Bham/doped", "note": "Automated defect calculation workflow for VASP with corrections and analysis", "md_link_text": "doped.md", "md_link_path": "Post-Processing/8.9_Workflow_Automation/doped.md", "papers": [ { "name": "doped_10.21105_joss.06433.pdf", "path": "Papers_of_Codes/Post-Processing/doped/doped_10.21105_joss.06433.pdf", "doi_url": "https://doi.org/10.21105/joss.06433" } ], "paper_placeholder": false, "slug": "doped", "idx": 751, "overview": "**doped** is a Python software for the generation, simulation, and analysis of defect supercells in solid-state materials. It automates the workflow for point defect calculations using VASP and pymatgen, including symmetry analysis, finite-size corrections, and defect property analysis." }, { "num": "311b", "name": "pymatgen-analysis-defects", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.9", "subcategory": "Workflow & Automation", "confidence": "VERIFIED", "official_url": "https://github.com/materialsproject/pymatgen-analysis-defects", "note": "Pymatgen add-on for defect analysis, Materials Project compatible", "md_link_text": "pymatgen-analysis-defects.md", "md_link_path": "Post-Processing/8.9_Workflow_Automation/pymatgen-analysis-defects.md", "papers": [ { "name": "10.1016_j.commatsci.2012.10.028.pdf", "path": "Papers_of_Codes/Frameworks/9.1_General_Purpose_Libraries/pymatgen-db/10.1016_j.commatsci.2012.10.028.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2012.10.028" } ], "paper_placeholder": false, "slug": "pymatgen-analysis-defects", "idx": 752, "overview": "**pymatgen-analysis-defects** is an add-on package to pymatgen for defect analysis in crystalline materials. It provides tools for generating defect structures, computing formation energies, applying finite-size corrections, and analyzing defect properties from DFT calculations." }, { "num": "311c", "name": "DFTTK", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.9", "subcategory": "Workflow & Automation", "confidence": "VERIFIED", "official_url": "https://github.com/PhasesResearchLab/dfttk", "note": "High-throughput VASP workflow with MongoDB storage, phase diagram focus", "md_link_text": "DFTTK.md", "md_link_path": "Post-Processing/8.9_Workflow_Automation/DFTTK.md", "papers": [], "paper_placeholder": true, "slug": "DFTTK", "idx": 753, "overview": "**DFTTK** (Density Functional Theory Toolkit) is a Python package designed to automate VASP jobs and manage results in MongoDB. It provides high-throughput VASP workflows leveraging Custodian for error handling and PyMongo for data storage, with support for thermodynamic property calculations." }, { "num": "311d", "name": "py-sc-fermi", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.9", "subcategory": "Workflow & Automation", "confidence": "VERIFIED", "official_url": "https://github.com/bjmorgan/py-sc-fermi", "note": "Self-consistent Fermi level and defect concentration calculation, temperature-dependent", "md_link_text": "py-sc-fermi.md", "md_link_path": "Post-Processing/8.9_Workflow_Automation/py-sc-fermi.md", "papers": [ { "name": "10_1002_wcms_1340.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/PySCF/10_1002_wcms_1340.pdf", "doi_url": "https://scholar.google.com/scholar?q=py-sc-fermi+10+1002+wcms+1340" }, { "name": "10_1063_5_0006074.pdf", "path": "Papers_of_Codes/DFT/1.4_Quantum_Chemistry/PySCF/10_1063_5_0006074.pdf", "doi_url": "https://scholar.google.com/scholar?q=py-sc-fermi+10+1063+5+0006074" } ], "paper_placeholder": false, "slug": "py-sc-fermi", "idx": 754, "overview": "**py-sc-fermi** is a materials modelling code for calculating self-consistent Fermi energies and defect concentrations under thermodynamic equilibrium (or quasi-equilibrium) given defect formation energies. It determines the equilibrium Fermi level and defect/carrier concentrations from DFT defect calculations." }, { "num": "311e", "name": "pylada-defects", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.9", "subcategory": "Workflow & Automation", "confidence": "VERIFIED", "official_url": "https://github.com/pylada/pylada-defects", "note": "Automated defect structure generation with corrections, pylada ecosystem", "md_link_text": "pylada-defects.md", "md_link_path": "Post-Processing/8.9_Workflow_Automation/pylada-defects.md", "papers": [ { "name": "pylada-defects_10.1016_j.commatsci.2016.12.040.pdf", "path": "Papers_of_Codes/Post-Processing/pylada-defects/pylada-defects_10.1016_j.commatsci.2016.12.040.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2016.12.040" } ], "paper_placeholder": false, "slug": "pylada-defects", "idx": 755, "overview": "**pylada-defects** is a computational framework to automate point defect calculations. It creates point defect structures (vacancies, interstitials, substitutions) and automates computation of formation energies with finite-size corrections including potential alignment, image-charge correction, and band-filling correction." }, { "num": "311f", "name": "CASCADE", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.9", "subcategory": "Workflow & Automation", "confidence": "VERIFIED", "official_url": "https://github.com/patonlab/CASCADE", "note": "ML-corrected NMR chemical shifts to CCSD(T) quality for organic molecules", "md_link_text": "CASCADE.md", "md_link_path": "Post-Processing/8.9_Workflow_Automation/CASCADE.md", "papers": [], "paper_placeholder": true, "slug": "CASCADE", "idx": 756, "overview": "**CASCADE** (CAlculation of NMR Chemical Shifts using DEep learning) is a tool for predicting NMR chemical shifts using machine learning. It combines DFT-calculated shifts with ML corrections to achieve CCSD(T)-quality predictions at DFT cost, particularly for organic molecules." }, { "num": "311g", "name": "ml4nmr", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.9", "subcategory": "Workflow & Automation", "confidence": "VERIFIED", "official_url": "https://github.com/grimme-lab/ml4nmr", "note": "ML correction of NMR shifts with spin-orbit relativistic effects (\u0394SO^ML)", "md_link_text": "ml4nmr.md", "md_link_path": "Post-Processing/8.9_Workflow_Automation/ml4nmr.md", "papers": [], "paper_placeholder": true, "slug": "ml4nmr", "idx": 757, "overview": "**ml4nmr** is a machine learning-based correction tool for NMR chemical shifts calculated with DFT. It enables correction of 1H and 13C NMR chemical shifts toward CCSD(T) quality (\u0394corrML) and prediction of spin-orbit relativistic contributions to NMR chemical shifts caused by heavy atoms (\u0394SO^ML)." }, { "num": "311h", "name": "vaspup2.0", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.9", "subcategory": "Workflow & Automation", "confidence": "VERIFIED", "official_url": "https://github.com/kavanase/vaspup2.0", "note": "Automated VASP convergence testing with plotting and criteria checking", "md_link_text": "vaspup2.md", "md_link_path": "Post-Processing/8.9_Workflow_Automation/vaspup2.md", "papers": [ { "name": "Kresse_Furthmuller_1996.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/Kresse_Furthmuller_1996.pdf", "doi_url": "https://scholar.google.com/scholar?q=vaspup2.0+Kresse+Furthmuller+1996" }, { "name": "Kresse_Hafner_1993.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/Kresse_Hafner_1993.pdf", "doi_url": "https://scholar.google.com/scholar?q=vaspup2.0+Kresse+Hafner+1993" }, { "name": "10.1016_0927-0256(96)00008-0.pdf", "path": "Papers_of_Codes/DFT/1.1_Plane-Wave_Pseudopotential/VASP/10.1016_0927-0256%2896%2900008-0.pdf", "doi_url": "https://doi.org/10.1016/0927-0256(96)00008-0" } ], "paper_placeholder": false, "slug": "vaspup2.0", "idx": 758, "overview": "**vaspup2.0** is a Python package for VASP convergence testing. It automates energy, k-point, and cutoff convergence tests with automatic job submission, result extraction, and convergence plotting, streamlining the setup of production VASP calculations." }, { "num": "311i", "name": "PyCDT", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.9", "subcategory": "Workflow & Automation", "confidence": "VERIFIED", "official_url": "https://github.com/mbkumar/pycdt", "note": "Comprehensive charged defect corrections with multiple image-charge schemes, VASP workflow", "md_link_text": "PyCDT.md", "md_link_path": "Post-Processing/8.9_Workflow_Automation/PyCDT.md", "papers": [ { "name": "PyCDT_10.1016_j.cpc.2018.01.004.pdf", "path": "Papers_of_Codes/Post-Processing/PyCDT/PyCDT_10.1016_j.cpc.2018.01.004.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2018.01.004" } ], "paper_placeholder": false, "slug": "PyCDT", "idx": 759, "overview": "**PyCDT** (Python Charged Defect Tools) is a Python package for thermodynamic calculations and error corrections for charged defects in semiconductors and insulators using periodic DFT. It generates inputs for required VASP calculations and processes output to compute defect formation energies with finite-size corrections." }, { "num": "311j", "name": "PyDEF", "category_id": "8", "category": "POST-PROCESSING", "subcategory_id": "8.9", "subcategory": "Workflow & Automation", "confidence": "VERIFIED", "official_url": "https://github.com/PyDEF/PyDEF", "note": "Defect formation energy with chemical potential phase diagrams and stability visualization", "md_link_text": "PyDEF.md", "md_link_path": "Post-Processing/8.9_Workflow_Automation/PyDEF.md", "papers": [ { "name": "PyDEF_10.1002_jcc.25543.pdf", "path": "Papers_of_Codes/Post-Processing/PyDEF/PyDEF_10.1002_jcc.25543.pdf", "doi_url": "https://doi.org/10.1002/jcc.25543" } ], "paper_placeholder": false, "slug": "PyDEF", "idx": 760, "overview": "**PyDEF** (Python for Defect Energy Formation) is a scientific software dedicated to defect formation energy calculation using VASP. It computes formation energies of any defect using VASP output files, with support for chemical potential determination and defect phase diagram construction." }, { "num": "318", "name": "ASE", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.1", "subcategory": "General Purpose Libraries", "confidence": "CONFIRMED", "official_url": "https://wiki.fysik.dtu.dk/ase/", "note": "", "md_link_text": "ASE.md", "md_link_path": "Frameworks/9.1_General_Purpose_Libraries/ASE.md", "papers": [ { "name": "Larsen_et_al_2017.pdf", "path": "Papers_of_Codes/Frameworks/9.1_General_Purpose_Libraries/ASE/Larsen_et_al_2017.pdf", "doi_url": "https://scholar.google.com/scholar?q=ASE+Larsen+et+al+2017" }, { "name": "10.1088_1361-648X_aa680e.pdf", "path": "Papers_of_Codes/Frameworks/9.1_General_Purpose_Libraries/ASE/10.1088_1361-648X_aa680e.pdf", "doi_url": "https://doi.org/10.1088/1361-648X_aa680e" } ], "paper_placeholder": false, "slug": "ASE", "idx": 761, "overview": "The Atomic Simulation Environment (ASE) is a set of tools and Python modules for setting up, manipulating, running, visualizing, and analyzing atomistic simulations. It acts as a unified interface to a vast ecosystem of electronic structure codes (calculators), allowing users to write calculator-independent scripts for tasks like geometry optimization, molecular dynamics, and NEB calculations." }, { "num": "319", "name": "pymatgen", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.1", "subcategory": "General Purpose Libraries", "confidence": "CONFIRMED", "official_url": "https://pymatgen.org/", "note": "", "md_link_text": "pymatgen.md", "md_link_path": "Frameworks/9.1_General_Purpose_Libraries/pymatgen.md", "papers": [ { "name": "Ong_et_al_2013.pdf", "path": "Papers_of_Codes/Frameworks/9.1_General_Purpose_Libraries/pymatgen/Ong_et_al_2013.pdf", "doi_url": "https://scholar.google.com/scholar?q=pymatgen+Ong+et+al+2013" } ], "paper_placeholder": false, "slug": "pymatgen", "idx": 762, "overview": "Pymatgen (Python Materials Genomics) is a robust, open-source Python library for materials analysis. It provides a core set of objects to represent materials (e.g., structures, molecules) and a comprehensive suite of tools to generate input files for and parse output files from various electronic structure codes. It is the core analysis code powering the **Materials Project**." }, { "num": "320", "name": "spglib", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.1", "subcategory": "General Purpose Libraries", "confidence": "VERIFIED", "official_url": "https://spglib.github.io/", "note": "", "md_link_text": "spglib.md", "md_link_path": "Frameworks/9.1_General_Purpose_Libraries/spglib.md", "papers": [], "paper_placeholder": true, "slug": "spglib", "idx": 763, "overview": "Spglib is a C library for finding and handling crystal symmetries. It provides algorithms for finding space groups, symmetry operations, and primitive unit cells. Spglib is widely used as the underlying symmetry engine for many major materials science codes (including Phonopy, Phono3py, Pymatgen, ASE, and Quantum ESPRESSO) due to its robustness and efficiency." }, { "num": "321", "name": "matscipy", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.1", "subcategory": "General Purpose Libraries", "confidence": "VERIFIED", "official_url": "https://github.com/libAtoms/matscipy", "note": "Python materials science library for interatomic potentials, elastic constants, fracture", "md_link_text": "matscipy.md", "md_link_path": "Frameworks/9.1_General_Purpose_Libraries/matscipy.md", "papers": [ { "name": "matscipy_10.21105_joss.05668.pdf", "path": "Papers_of_Codes/Frameworks/matscipy/matscipy_10.21105_joss.05668.pdf", "doi_url": "https://doi.org/10.21105/joss.05668" } ], "paper_placeholder": false, "slug": "matscipy", "idx": 764, "overview": "matscipy is a Python library designed for materials science calculations, building upon the Atomic Simulation Environment (ASE). It aims to provide efficient implementations of common tasks in atomistic simulations, often using C extensions for performance. It includes tools for elasticity, fracture mechanics, dislocation analysis, and more. It is likely the intended tool for the entry \"MatPy\"." }, { "num": "352", "name": "pymatgen-analysis", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.1", "subcategory": "General Purpose Libraries", "confidence": "VERIFIED", "official_url": "**MODULE** - Part of pymatgen.", "note": "", "md_link_text": "pymatgen-analysis.md", "md_link_path": "Frameworks/9.1_General_Purpose_Libraries/pymatgen-analysis.md", "papers": [ { "name": "10.1016_j.commatsci.2012.10.028.pdf", "path": "Papers_of_Codes/Frameworks/9.1_General_Purpose_Libraries/pymatgen-db/10.1016_j.commatsci.2012.10.028.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2012.10.028" } ], "paper_placeholder": false, "slug": "pymatgen-analysis", "idx": 765, "overview": "\"pymatgen-analysis\" typically refers to the analysis modules within the main `pymatgen` library or its add-on packages like `pymatgen-analysis-diffusion` or `pymatgen-analysis-defects`. These provide specialized algorithms for analyzing calculation data, such as diffusion paths, defect thermodynamics, and Pourbaix diagrams." }, { "num": "348", "name": "pymatgen-db", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.1", "subcategory": "General Purpose Libraries", "confidence": "VERIFIED", "official_url": "https://github.com/materialsproject/pymatgen-db", "note": "", "md_link_text": "pymatgen-db.md", "md_link_path": "Frameworks/9.1_General_Purpose_Libraries/pymatgen-db.md", "papers": [ { "name": "10.1016_j.commatsci.2012.10.028.pdf", "path": "Papers_of_Codes/Frameworks/9.1_General_Purpose_Libraries/pymatgen-db/10.1016_j.commatsci.2012.10.028.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2012.10.028" } ], "paper_placeholder": false, "slug": "pymatgen-db", "idx": 766, "overview": "pymatgen-db is a tool for managing MongoDB databases of materials data. It works with Pymatgen to parse calculation results (from VASP, Q-Chem, etc.) and insert them into a database with a structured schema. It allows for powerful querying of materials properties using a Python API or CLI." }, { "num": "355", "name": "Jarvis-Tools", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.1", "subcategory": "General Purpose Libraries", "confidence": "VERIFIED", "official_url": "https://github.com/usnistgov/jarvis-tools", "note": "", "md_link_text": "Jarvis-Tools.md", "md_link_path": "Frameworks/9.1_General_Purpose_Libraries/Jarvis-Tools.md", "papers": [ { "name": "Choudhary_et_al_2020.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/JARVIS/Choudhary_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=Jarvis-Tools+Choudhary+et+al+2020" } ], "paper_placeholder": false, "slug": "Jarvis-Tools", "idx": 767, "overview": "jarvis-tools is the open-source Python software package that powers the JARVIS database. It provides a suite of tools for designing, managing, and analyzing atomistic simulations (DFT, MD) and applying machine learning to materials data. It supports VASP, Quantum ESPRESSO, LAMMPS, and other codes." }, { "num": "356c", "name": "XenonPy", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.1", "subcategory": "General Purpose Libraries", "confidence": "VERIFIED", "official_url": "https://github.com/yoshida-lab/XenonPy", "note": "Transfer learning framework for materials with 290+ elemental descriptors", "md_link_text": "XenonPy.md", "md_link_path": "Frameworks/9.1_General_Purpose_Libraries/XenonPy.md", "papers": [], "paper_placeholder": true, "slug": "XenonPy", "idx": 768, "overview": "**XenonPy** is a Python library that implements a comprehensive set of machine learning tools for materials informatics. It provides descriptor calculation, model training, transfer learning, and inverse design capabilities for materials discovery from compositional and structural features." }, { "num": "356d", "name": "pymatviz", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.1", "subcategory": "General Purpose Libraries", "confidence": "VERIFIED", "official_url": "https://github.com/janosh/pymatviz", "note": "Materials-specific publication-quality visualization with automatic ML metrics annotation", "md_link_text": "pymatviz.md", "md_link_path": "Frameworks/9.1_General_Purpose_Libraries/pymatviz.md", "papers": [], "paper_placeholder": true, "slug": "pymatviz", "idx": 769, "overview": "**pymatviz** is a Python toolkit for visualizations in materials informatics. It provides publication-quality plotting functions for common materials science data types including parity plots, histogram plots, crystal structure visualizations, and phase diagrams, built on matplotlib and plotly." }, { "num": "356e", "name": "CatKit", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.1", "subcategory": "General Purpose Libraries", "confidence": "VERIFIED", "official_url": "https://github.com/SUNCAT-Center/CatKit", "note": "Automated adsorption site enumeration and surface generation for catalysis", "md_link_text": "CatKit.md", "md_link_path": "Frameworks/9.1_General_Purpose_Libraries/CatKit.md", "papers": [], "paper_placeholder": true, "slug": "CatKit", "idx": 770, "overview": "**CatKit** (Catalysis Kit) is a Python library for surface generation and catalysis simulations. It provides tools for generating surface slabs, adsorption sites, and surface structures for heterogeneous catalysis research, integrated with the SUNCAT Center workflow." }, { "num": "356f", "name": "MLatom", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.1", "subcategory": "General Purpose Libraries", "confidence": "VERIFIED", "official_url": "https://github.com/dralgroup/mlatom", "note": "AI-enhanced computational chemistry with ML/MM hybrid and active learning", "md_link_text": "MLatom.md", "md_link_path": "Frameworks/9.1_General_Purpose_Libraries/MLatom.md", "papers": [], "paper_placeholder": true, "slug": "MLatom", "idx": 771, "overview": "**MLatom** is an AI-enhanced computational chemistry library that combines machine learning with quantum chemistry methods. It provides ML-accelerated simulations, property predictions, and model training for molecules and materials, supporting ML/MM, ML/Kraken, and various ML models." }, { "num": "356z", "name": "maml", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.1", "subcategory": "General Purpose Libraries", "confidence": "VERIFIED", "official_url": "https://github.com/ml-evs/matador", "note": "Python library for aggregation and analysis of HT-DFT data (MP, OQMD, CASTEP)", "md_link_text": "matador.md", "md_link_path": "Frameworks/9.1_General_Purpose_Libraries/matador.md", "papers": [], "paper_placeholder": true, "slug": "maml", "idx": 772, "overview": "" }, { "num": "322", "name": "AiiDA", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.2", "subcategory": "Workflow & Job Management", "confidence": "VERIFIED", "official_url": "https://aiida.net/", "note": "", "md_link_text": "AiiDA.md", "md_link_path": "Frameworks/9.2_Workflow_Job_Management/AiiDA.md", "papers": [ { "name": "10.1038_s41597-020-00638-4.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/AiiDA/10.1038_s41597-020-00638-4.pdf", "doi_url": "https://doi.org/10.1038/s41597-020-00638-4" }, { "name": "Huber_et_al_2020.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/AiiDA/Huber_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=AiiDA+Huber+et+al+2020" } ], "paper_placeholder": false, "slug": "AiiDA", "idx": 773, "overview": "AiiDA is a sophisticated open-source workflow management system designed for high-throughput computational science. It focuses on reproducibility, provenance tracking, and automation. AiiDA manages the entire lifecycle of a calculation: preparing inputs, submitting jobs to supercomputers (via SLURM, PBS, etc.), parsing outputs, and storing the entire provenance graph (inputs, outputs, and the code that produced them) in a database." }, { "num": "323", "name": "FireWorks", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.2", "subcategory": "Workflow & Job Management", "confidence": "VERIFIED", "official_url": "https://materialsproject.github.io/fireworks/", "note": "", "md_link_text": "FireWorks.md", "md_link_path": "Frameworks/9.2_Workflow_Job_Management/FireWorks.md", "papers": [ { "name": "10.1002_cpe.3505.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/FireWorks/10.1002_cpe.3505.pdf", "doi_url": "https://doi.org/10.1002/cpe.3505" } ], "paper_placeholder": false, "slug": "FireWorks", "idx": 774, "overview": "FireWorks is a workflow software for running, tracking, and managing high-throughput calculations. It is designed to handle complex workflows with dependencies, enabling the automation of large-scale computational tasks. FireWorks uses a centralized database (MongoDB) to store the state of all workflows, allowing for dynamic workflow modification and robust failure recovery." }, { "num": "324", "name": "atomate", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.2", "subcategory": "Workflow & Job Management", "confidence": "VERIFIED", "official_url": "https://hackingmaterials.github.io/atomate/", "note": "", "md_link_text": "atomate.md", "md_link_path": "Frameworks/9.2_Workflow_Job_Management/atomate.md", "papers": [ { "name": "Mathew_et_al_2017.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/atomate/Mathew_et_al_2017.pdf", "doi_url": "https://scholar.google.com/scholar?q=atomate+Mathew+et+al+2017" } ], "paper_placeholder": false, "slug": "atomate", "idx": 775, "overview": "Atomate is a library of pre-defined workflows for computational materials science. It is built on top of Pymatgen, FireWorks, and Custodian. Atomate provides robust, production-ready workflows for running VASP, multiple FEFF, and other calculations, handling everything from input generation to error correction and database insertion." }, { "num": "325", "name": "atomate2", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.2", "subcategory": "Workflow & Job Management", "confidence": "VERIFIED", "official_url": "https://github.com/materialsproject/atomate2", "note": "", "md_link_text": "atomate2.md", "md_link_path": "Frameworks/9.2_Workflow_Job_Management/atomate2.md", "papers": [ { "name": "Mathew_et_al_2017.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/atomate/Mathew_et_al_2017.pdf", "doi_url": "https://scholar.google.com/scholar?q=atomate2+Mathew+et+al+2017" } ], "paper_placeholder": false, "slug": "atomate2", "idx": 776, "overview": "Atomate2 is the next-generation workflow library for computational materials science, succeeding Atomate. It is built on top of `jobflow` (instead of FireWorks directly) and Pymatgen. It offers a more modern, flexible, and easier-to-use API for defining workflows. It supports VASP, CP2K, ForceField (via LAMMPS), and other codes, with a focus on modularity and dynamic workflow generation." }, { "num": "326", "name": "custodian", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.2", "subcategory": "Workflow & Job Management", "confidence": "VERIFIED", "official_url": "https://materialsproject.github.io/custodian/", "note": "", "md_link_text": "custodian.md", "md_link_path": "Frameworks/9.2_Workflow_Job_Management/custodian.md", "papers": [], "paper_placeholder": true, "slug": "custodian", "idx": 777, "overview": "Custodian is a simple, robust, and flexible just-in-time (JIT) job management framework in Python. It is designed to run scientific calculations (like VASP, Q-Chem, NwChem) while simultaneously monitoring them for errors and performing automatic error recovery. It acts as a \"wrapper\" around the executable, checking output files and logs in real-time to intervene if convergence fails or the job crashes." }, { "num": "327", "name": "jobflow", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.2", "subcategory": "Workflow & Job Management", "confidence": "VERIFIED", "official_url": "https://materialsproject.github.io/jobflow/", "note": "", "md_link_text": "jobflow.md", "md_link_path": "Frameworks/9.2_Workflow_Job_Management/jobflow.md", "papers": [ { "name": "jobflow_10.21105_joss.05995.pdf", "path": "Papers_of_Codes/Frameworks/jobflow/jobflow_10.21105_joss.05995.pdf", "doi_url": "https://doi.org/10.21105/joss.05995" } ], "paper_placeholder": false, "slug": "jobflow", "idx": 778, "overview": "Jobflow is a free, open-source library for writing computational workflows. It is intended to be the successor to the workflow primitives in FireWorks. Jobflow separates the definition of the workflow (Jobs and Flows) from the execution engine (JobStore). This allows workflows to be run locally (for development/debugging) or deployed to remote managers like FireWorks without changing the code." }, { "num": "328", "name": "jobflow-remote", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.2", "subcategory": "Workflow & Job Management", "confidence": "VERIFIED", "official_url": "https://github.com/materialsproject/jobflow-remote", "note": "Remote execution backend for jobflow workflows", "md_link_text": "jobflow-remote.md", "md_link_path": "Frameworks/9.2_Workflow_Job_Management/jobflow-remote.md", "papers": [], "paper_placeholder": true, "slug": "jobflow-remote", "idx": 779, "overview": "Jobflow-remote (formerly `jobflow-runners` or similar concepts) is a runner for `jobflow` that enables execution on remote resources (like SLURM clusters) without the full complexity of FireWorks' database-polling model. It is a lightweight alternative for submitting jobflow Flows to HPC queues." }, { "num": "329", "name": "Luigi", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.2", "subcategory": "Workflow & Job Management", "confidence": "VERIFIED", "official_url": "https://luigi.readthedocs.io/", "note": "", "md_link_text": "Luigi.md", "md_link_path": "Frameworks/9.2_Workflow_Job_Management/Luigi.md", "papers": [], "paper_placeholder": true, "slug": "Luigi", "idx": 780, "overview": "Luigi is a Python package that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization, handling failures, command line integration, and much more. 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It allows researchers to build parallel applications composed of Python functions and external components (executables) that can run on arbitrary computing resources, from laptops to supercomputers. It abstracts the execution model, allowing the same script to scale from a single core to thousands of nodes." }, { "num": "331", "name": "MyQueue", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.2", "subcategory": "Workflow & Job Management", "confidence": "VERIFIED", "official_url": "https://myqueue.readthedocs.io/", "note": "", "md_link_text": "MyQueue.md", "md_link_path": "Frameworks/9.2_Workflow_Job_Management/MyQueue.md", "papers": [ { "name": "MyQueue_10.21105_joss.01844.pdf", "path": "Papers_of_Codes/Frameworks/MyQueue/MyQueue_10.21105_joss.01844.pdf", "doi_url": "https://doi.org/10.21105/joss.01844" } ], "paper_placeholder": false, "slug": "MyQueue", "idx": 782, "overview": "MyQueue is a lightweight, frontend-agnostic task scheduler and workflow manager. 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It enables running FHI-aims calculations within the AiiDA framework with provenance tracking, input management, and output parsing." }, { "num": "356p", "name": "aiida-lammps", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.3", "subcategory": "AiiDA Plugins", "confidence": "VERIFIED", "official_url": "https://github.com/aiidaplugins/aiida-lammps", "note": "AiiDA plugin for LAMMPS with potential management and provenance tracking", "md_link_text": "aiida-lammps.md", "md_link_path": "Frameworks/9.3_AiiDA_Plugins/aiida-lammps.md", "papers": [ { "name": "10.1038_s41597-020-00638-4.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/AiiDA/10.1038_s41597-020-00638-4.pdf", "doi_url": "https://doi.org/10.1038/s41597-020-00638-4" }, { "name": "Huber_et_al_2020.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/AiiDA/Huber_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=aiida-lammps+Huber+et+al+2020" } ], "paper_placeholder": false, "slug": "aiida-lammps", "idx": 801, "overview": "**aiida-lammps** is an AiiDA plugin for the LAMMPS molecular dynamics code. It enables running LAMMPS calculations within the AiiDA framework with provenance tracking, potential management, and output parsing for classical MD simulations." }, { "num": "356q", "name": "aiida-abinit", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.3", "subcategory": "AiiDA Plugins", "confidence": "VERIFIED", "official_url": "https://github.com/aiidateam/aiida-abinit", "note": "AiiDA plugin for ABINIT with pseudopotential management", "md_link_text": "aiida-abinit.md", "md_link_path": "Frameworks/9.3_AiiDA_Plugins/aiida-abinit.md", "papers": [ { "name": "10.1038_s41597-020-00638-4.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/AiiDA/10.1038_s41597-020-00638-4.pdf", "doi_url": "https://doi.org/10.1038/s41597-020-00638-4" }, { "name": "Huber_et_al_2020.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/AiiDA/Huber_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=aiida-abinit+Huber+et+al+2020" } ], "paper_placeholder": false, "slug": "aiida-abinit", "idx": 802, "overview": "**aiida-abinit** is an AiiDA plugin for the ABINIT DFT code. It enables running ABINIT calculations within the AiiDA framework with provenance tracking, input management, and output parsing." }, { "num": "356r", "name": "aiida-nwchem", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.3", "subcategory": "AiiDA Plugins", "confidence": "VERIFIED", "official_url": "https://github.com/aiidateam/aiida-nwchem", "note": "AiiDA plugin for NWChem with basis set management and provenance tracking", "md_link_text": "aiida-nwchem.md", "md_link_path": "Frameworks/9.3_AiiDA_Plugins/aiida-nwchem.md", "papers": [ { "name": "10.1038_s41597-020-00638-4.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/AiiDA/10.1038_s41597-020-00638-4.pdf", "doi_url": "https://doi.org/10.1038/s41597-020-00638-4" }, { "name": "Huber_et_al_2020.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/AiiDA/Huber_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=aiida-nwchem+Huber+et+al+2020" } ], "paper_placeholder": false, "slug": "aiida-nwchem", "idx": 803, "overview": "**aiida-nwchem** is an AiiDA plugin for the NWChem quantum chemistry code. It enables running NWChem calculations within the AiiDA framework with provenance tracking, input management, and output parsing for molecular and periodic electronic structure calculations." }, { "num": "356s", "name": "aiida-bigdft", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.3", "subcategory": "AiiDA Plugins", "confidence": "VERIFIED", "official_url": "https://github.com/siesta-project/aiida_siesta_plugin", "note": "AiiDA plugin for SIESTA with optical calculation support and provenance tracking", "md_link_text": "aiida-siesta.md", "md_link_path": "Frameworks/9.3_AiiDA_Plugins/aiida-siesta.md", "papers": [ { "name": "10.1038_s41597-020-00638-4.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/AiiDA/10.1038_s41597-020-00638-4.pdf", "doi_url": "https://doi.org/10.1038/s41597-020-00638-4" }, { "name": "Huber_et_al_2020.pdf", "path": "Papers_of_Codes/Frameworks/9.2_Workflow_Job_Management/AiiDA/Huber_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=aiida-bigdft+Huber+et+al+2020" } ], "paper_placeholder": false, "slug": "aiida-bigdft", "idx": 804, "overview": "**aiida-siesta** is an AiiDA plugin for the SIESTA DFT code. It enables running SIESTA calculations within the AiiDA framework with provenance tracking, input management, and workflow automation including optical calculations." }, { "num": "340", "name": "Materials Project", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "https://materialsproject.org/", "note": "", "md_link_text": "Materials-Project.md", "md_link_path": "Frameworks/9.4_Materials_Databases/Materials-Project.md", "papers": [ { "name": "10_1038_s41597-020-00637-5.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/Materials Project/10_1038_s41597-020-00637-5.pdf", "doi_url": "https://scholar.google.com/scholar?q=Materials+Project+10+1038+s41597+020+00637+5" }, { "name": "10_1063_1_4812323.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/Materials Project/10_1063_1_4812323.pdf", "doi_url": "https://scholar.google.com/scholar?q=Materials+Project+10+1063+1+4812323" } ], "paper_placeholder": false, "slug": "Materials-Project", "idx": 805, "overview": "The Materials Project (MP) is a major initiative to compute the properties of all known inorganic materials and provide the data freely to the public. It provides a searchable database of calculated properties (band structures, elastic constants, piezoelectricity, etc.) generated using high-throughput DFT (VASP). It also provides an API (MAPIDoc) and a Python client (`mp_api`) for programmatic access." }, { "num": "341", "name": "AFLOW", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "http://www.aflow.org/", "note": "", "md_link_text": "AFLOW.md", "md_link_path": "Frameworks/9.4_Materials_Databases/AFLOW.md", "papers": [ { "name": "Curtarolo_et_al_2012.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/AFLOW/Curtarolo_et_al_2012.pdf", "doi_url": "https://scholar.google.com/scholar?q=AFLOW+Curtarolo+et+al+2012" }, { "name": "10.1016_j.commatsci.2012.02.005.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/AFLOW/10.1016_j.commatsci.2012.02.005.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2012.02.005" } ], "paper_placeholder": false, "slug": "AFLOW", "idx": 806, "overview": "AFLOW (Automatic Flow) is a prominent high-throughput ab initio calculation framework and database. It automates the generation, simulation, and analysis of materials using DFT (primarily VASP). AFLOW manages a massive database of calculated properties (AFLOWlib) and provides tools for convex hull construction, prototype generation, and machine learning (AFLOW-ML)." }, { "num": "342", "name": "OQMD", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "http://oqmd.org/", "note": "", "md_link_text": "OQMD.md", "md_link_path": "Frameworks/9.4_Materials_Databases/OQMD.md", "papers": [ { "name": "10.1007_s11837-013-0755-5.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/OQMD/10.1007_s11837-013-0755-5.pdf", "doi_url": "https://doi.org/10.1007/s11837-013-0755-5" } ], "paper_placeholder": false, "slug": "OQMD", "idx": 807, "overview": "The Open Quantum Materials Database (OQMD) is a high-throughput database of DFT-calculated thermodynamic and structural properties of materials. It focuses heavily on thermodynamics, phase stability, and the discovery of new stable compounds. It is built using the `qmpy` software stack." }, { "num": "343", "name": "NOMAD", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "https://nomad-lab.eu/", "note": "", "md_link_text": "NOMAD.md", "md_link_path": "Frameworks/9.4_Materials_Databases/NOMAD.md", "papers": [ { "name": "10_1088_2515-7639_ab13bb.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/NOMAD/10_1088_2515-7639_ab13bb.pdf", "doi_url": "https://scholar.google.com/scholar?q=NOMAD+10+1088+2515+7639+ab13bb" }, { "name": "10_1088_1361-648X_ab13bb.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/NOMAD/10_1088_1361-648X_ab13bb.pdf", "doi_url": "https://scholar.google.com/scholar?q=NOMAD+10+1088+1361+648X+ab13bb" } ], "paper_placeholder": false, "slug": "NOMAD", "idx": 808, "overview": "NOMAD is a web-based data management platform for materials science. Unlike MP or OQMD which generate their own data, NOMAD is primarily a repository for *archiving* and *sharing* data produced by the community from *any* code. It processes uploaded raw output files (from VASP, QE, etc.), normalizes them into a code-independent format (NOMAD Metainfo), and makes them searchable and analyzable." }, { "num": "344", "name": "Materials Cloud", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "https://www.materialscloud.org/", "note": "", "md_link_text": "Materials-Cloud.md", "md_link_path": "Frameworks/9.4_Materials_Databases/Materials-Cloud.md", "papers": [ { "name": "10_1038_s41597-020-00637-5.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/Materials Cloud/10_1038_s41597-020-00637-5.pdf", "doi_url": "https://scholar.google.com/scholar?q=Materials+Cloud+10+1038+s41597+020+00637+5" }, { "name": "10_1063_1_4812323.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/Materials Cloud/10_1063_1_4812323.pdf", "doi_url": "https://scholar.google.com/scholar?q=Materials+Cloud+10+1063+1+4812323" } ], "paper_placeholder": false, "slug": "Materials-Cloud", "idx": 809, "overview": "Materials Cloud is a web platform for Open Science in computational materials science. Built on top of AiiDA, it enables researchers to FAIRly share their data, calculations, and provenance graphs. It provides interactive tools for visualizing data (structures, bands, phonons) and a \"Work\" section for running simulations in the cloud (AiiDA Lab)." }, { "num": "345", "name": "JARVIS", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "https://jarvis.nist.gov/", "note": "", "md_link_text": "JARVIS.md", "md_link_path": "Frameworks/9.4_Materials_Databases/JARVIS.md", "papers": [ { "name": "Choudhary_et_al_2020.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/JARVIS/Choudhary_et_al_2020.pdf", "doi_url": "https://scholar.google.com/scholar?q=JARVIS+Choudhary+et+al+2020" } ], "paper_placeholder": false, "slug": "JARVIS", "idx": 810, "overview": "JARVIS is an integrated framework and database developed by NIST for data-driven materials design. It consists of the JARVIS-DFT database (DFT calculations), JARVIS-FF (Force fields), and JARVIS-ML (Machine learning). It emphasizes properties relevant to applications (e.g., solar cells, thermoelectrics, dielectrics) and uses high-throughput workflows powered by `jarvis-tools`." }, { "num": "346", "name": "C2DB", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "https://c2db.fysik.dtu.dk/", "note": "", "md_link_text": "C2DB.md", "md_link_path": "Frameworks/9.4_Materials_Databases/C2DB.md", "papers": [ { "name": "C2DB_10.1088_2053-1583_aacfc1.pdf", "path": "Papers_of_Codes/Frameworks/C2DB/C2DB_10.1088_2053-1583_aacfc1.pdf", "doi_url": "https://doi.org/10.1088/2053-1583_aacfc1" } ], "paper_placeholder": false, "slug": "C2DB", "idx": 811, "overview": "C2DB is a highly curated database of two-dimensional materials calculated using the Atomic Simulation Environment (ASE) and the GPAW electronic structure code. It systematically classifies and characterizes thousands of 2D monolayers, calculating a wide range of properties including stability, stiffness, topological invariants, and excited state properties (GW band gaps, excitons)." }, { "num": "347", "name": "2DMatPedia", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "https://www.2dmaterials.org/", "note": "", "md_link_text": "2DMatPedia.md", "md_link_path": "Frameworks/9.4_Materials_Databases/2DMatPedia.md", "papers": [ { "name": "2DMatPedia_10.1038_s41597-019-0097-3.pdf", "path": "Papers_of_Codes/Frameworks/2DMatPedia/2DMatPedia_10.1038_s41597-019-0097-3.pdf", "doi_url": "https://doi.org/10.1038/s41597-019-0097-3" } ], "paper_placeholder": false, "slug": "2DMatPedia", "idx": 812, "overview": "2DMatPedia is a large-scale database of 2D materials generated by exfoliating bulk materials from the Materials Project. It performs high-throughput DFT calculations to identify stable 2D layers and calculate their properties." }, { "num": "349", "name": "qmpy", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "https://github.com/wolverton-research-group/qmpy", "note": "", "md_link_text": "qmpy.md", "md_link_path": "Frameworks/9.4_Materials_Databases/qmpy.md", "papers": [ { "name": "10.1007_s11837-013-0755-5.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/qmpy/10.1007_s11837-013-0755-5.pdf", "doi_url": "https://doi.org/10.1007/s11837-013-0755-5" } ], "paper_placeholder": false, "slug": "qmpy", "idx": 813, "overview": "qmpy is the backend software stack for the Open Quantum Materials Database (OQMD). It provides tools for creating, managing, and analyzing high-throughput DFT calculations. It includes modules for structure manipulation, VASP input generation, job management, and thermodynamic analysis (phase diagrams)." }, { "num": "350", "name": "NCD", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "http://www.nanocrystallography.org/", "note": "", "md_link_text": "NCD.md", "md_link_path": "Frameworks/9.4_Materials_Databases/NCD.md", "papers": [], "paper_placeholder": true, "slug": "NCD", "idx": 814, "overview": "The Nanocrystallography Database (NCD) is a collection of crystal structure data, primarily focused on nanomaterials, minerals, and zeolites. It is closely affiliated with the Crystallography Open Database (COD) and provides an open-access platform for identifying and retrieving crystallographic information (CIF files)." }, { "num": "356a", "name": "teMatDb", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "https://github.com/byungkiryu/teMatDb", "note": "Thermoelectric materials database (literature-extracted) and analysis utilities", "md_link_text": "teMatDb.md", "md_link_path": "Frameworks/9.4_Materials_Databases/teMatDb.md", "papers": [], "paper_placeholder": true, "slug": "teMatDb", "idx": 815, "overview": "teMatDb is a thermoelectric materials database project aimed at consolidating thermoelectric property data extracted from the literature, with accompanying utilities for analysis and handling of the dataset." }, { "num": "356b", "name": "thermo", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "https://github.com/janosh/thermo", "note": "Data-driven analysis and discovery workflow for thermoelectric materials", "md_link_text": "thermo.md", "md_link_path": "Frameworks/9.4_Materials_Databases/thermo.md", "papers": [], "paper_placeholder": true, "slug": "thermo", "idx": 816, "overview": "thermo is a data-driven workflow repository focused on risk-conscious discovery and analysis of thermoelectric materials. It provides code for data analysis, visualization, and modeling targeted at thermoelectric transport-related datasets." }, { "num": "356t", "name": "mp-api", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "https://github.com/materialsproject/api", "note": "Official Python API client for Materials Project with comprehensive data access", "md_link_text": "mp-api.md", "md_link_path": "Frameworks/9.4_Materials_Databases/mp-api.md", "papers": [ { "name": "mp-api_10.1016_j.commatsci.2014.10.037.pdf", "path": "Papers_of_Codes/Frameworks/mp-api/mp-api_10.1016_j.commatsci.2014.10.037.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2014.10.037" } ], "paper_placeholder": false, "slug": "mp-api", "idx": 817, "overview": "**mp-api** is the official Python API client for the Materials Project database. It provides programmatic access to Materials Project data including computed materials properties, phase diagrams, phonon data, and elastic constants, replacing the legacy `pymatgen.ext.matproj` interface." }, { "num": "356u", "name": "OPTIMADE", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "https://github.com/materialsproject/MPContribs", "note": "Platform for contributing and sharing materials data within the Materials Project ecosystem", "md_link_text": "MPContribs.md", "md_link_path": "Frameworks/9.4_Materials_Databases/MPContribs.md", "papers": [ { "name": "10.1038_s41597-021-00974-z.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/OPTIMADE/10.1038_s41597-021-00974-z.pdf", "doi_url": "https://doi.org/10.1038/s41597-021-00974-z" } ], "paper_placeholder": false, "slug": "OPTIMADE", "idx": 818, "overview": "**MPContribs** is a platform and API for contributing computational and experimental data to the Materials Project. It provides tools for uploading, validating, and sharing materials data within the MP ecosystem, enabling community contributions alongside core MP data." }, { "num": "386", "name": "CCDC", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.4", "subcategory": "Materials Databases", "confidence": "VERIFIED", "official_url": "https://www.ccdc.cam.ac.uk/", "note": "Cambridge Crystallographic Data Centre - crystal structure database.", "md_link_text": "CCDC.md", "md_link_path": "Frameworks/9.4_Materials_Databases/CCDC.md", "papers": [ { "name": "Groom_et_al_2016.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/CCDC/Groom_et_al_2016.pdf", "doi_url": "https://scholar.google.com/scholar?q=CCDC+Groom+et+al+2016" } ], "paper_placeholder": false, "slug": "CCDC", "idx": 819, "overview": "" }, { "num": "351", "name": "ASR", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.5", "subcategory": "Specialized Analysis Frameworks", "confidence": "VERIFIED", "official_url": "https://gitlab.com/asr-project/asr", "note": "", "md_link_text": "ASR.md", "md_link_path": "Frameworks/9.5_Specialized_Analysis_Frameworks/ASR.md", "papers": [ { "name": "ASR_10.1016_j.commatsci.2021.110731.pdf", "path": "Papers_of_Codes/Frameworks/ASR/ASR_10.1016_j.commatsci.2021.110731.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2021.110731" } ], "paper_placeholder": false, "slug": "ASR", "idx": 820, "overview": "Atomic Simulation Recipes (ASR) is a Python framework for defining and executing simulation workflows. Developed at DTU, it allows users to define \"recipes\" (workflows) that link calculations (typically using ASE and GPAW) to results. ASR is the engine behind the C2DB database. It emphasizes caching, reproducibility, and automatic presentation of results via a web interface." }, { "num": "356v", "name": "PyLada", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.5", "subcategory": "Specialized Analysis Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/pylada/pylada", "note": "Python Lattice Defect Automation framework for high-throughput DFT", "md_link_text": "PyLada.md", "md_link_path": "Frameworks/9.5_Specialized_Analysis_Frameworks/PyLada.md", "papers": [], "paper_placeholder": true, "slug": "PyLada", "idx": 821, "overview": "PyLada is a Python framework for high-throughput computational materials science. It provides tools for managing DFT calculations (wrapping VASP and Crystal), handling crystal structures, and managing job submission to clusters. It is designed to be lightweight and scriptable." }, { "num": "356w", "name": "emmet", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.5", "subcategory": "Specialized Analysis Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/materialsproject/emmet", "note": "Materials Project data pipeline builder (predecessor to maggma)", "md_link_text": "emmet.md", "md_link_path": "Frameworks/9.5_Specialized_Analysis_Frameworks/emmet.md", "papers": [], "paper_placeholder": true, "slug": "emmet", "idx": 822, "overview": "Emmet is the core library defining the data models and \"Builders\" for the Materials Project. It defines the schema for materials properties (e.g., `MaterialDoc`, `TaskDoc`) and contains the logic to aggregate raw calculation tasks into consolidated material documents." }, { "num": "356x", "name": "maggma", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.5", "subcategory": "Specialized Analysis Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/materialsproject/maggma", "note": "Scientific data processing pipeline framework for databases, blobs, and REST APIs", "md_link_text": "maggma.md", "md_link_path": "Frameworks/9.5_Specialized_Analysis_Frameworks/maggma.md", "papers": [], "paper_placeholder": true, "slug": "maggma", "idx": 823, "overview": "Maggma is a framework for building scientific data pipelines. It provides an abstraction layer (Stores) for various databases (MongoDB, S3, GridFS, Filesystem) and a \"Builder\" pattern for processing data from one store to another. It is the backbone of the Materials Project's new data infrastructure." }, { "num": "356y", "name": "MPWorks", "category_id": "9", "category": "FRAMEWORKS", "subcategory_id": "9.5", "subcategory": "Specialized Analysis Frameworks", "confidence": "VERIFIED", "official_url": "https://github.com/pybamm-team/PyBaMM", "note": "Open-source physics-based battery modeling with comprehensive degradation models", "md_link_text": "PyBaMM.md", "md_link_path": "Frameworks/9.5_Specialized_Analysis_Frameworks/PyBaMM.md", "papers": [ { "name": "10_1002_cpe_3505.pdf", "path": "Papers_of_Codes/materials_science_papers/10.2.2_Specialized_HT_Tools/MPWorks/10_1002_cpe_3505.pdf", "doi_url": "https://scholar.google.com/scholar?q=MPWorks+10+1002+cpe+3505" } ], "paper_placeholder": false, "slug": "MPWorks", "idx": 824, "overview": "**PyBaMM** (Python Battery Mathematical Modelling) is a fast and flexible physics-based battery modeling framework. It provides implementations of battery models (DFN, SPM, SPMe, etc.) with sub-models for electrochemistry, degradation, and thermal effects, for simulating battery performance." }, { "num": "357", "name": "Allegro", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.1", "subcategory": "MLIPs - Message Passing", "confidence": "VERIFIED", "official_url": "https://github.com/mir-group/allegro", "note": "Strictly local equivariant architecture, ACE-like features", "md_link_text": "Allegro.md", "md_link_path": "Niche/10.1_MLIPs_Message_Passing/Allegro.md", "papers": [ { "name": "10_1038_s41467-023-36329-y.pdf", "path": "Papers_of_Codes/Niche/10.1_MLIPs_Message_Passing/Allegro/10_1038_s41467-023-36329-y.pdf", "doi_url": "https://scholar.google.com/scholar?q=Allegro+10+1038+s41467+023+36329+y" } ], "paper_placeholder": false, "slug": "Allegro", "idx": 825, "overview": "Allegro is a strictly local equivariant deep learning interatomic potential. It is built on the same principles as NequIP (E(3)-equivariance) but is designed to be strictly local (no message passing beyond a cutoff) and massively parallel. This allows it to scale to extremely large systems (millions of atoms) while maintaining high accuracy." }, { "num": "358", "name": "m3gnet", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.1", "subcategory": "MLIPs - Message Passing", "confidence": "VERIFIED", "official_url": "https://github.com/materialsvirtuallab/m3gnet", "note": "Materials 3-body graph network for 94 elements", "md_link_text": "m3gnet.md", "md_link_path": "Niche/10.1_MLIPs_Message_Passing/m3gnet.md", "papers": [], "paper_placeholder": true, "slug": "m3gnet", "idx": 826, "overview": "M3GNet is a graph neural network (GNN) potential trained on the massive Materials Project trajectory dataset (>187,000 materials). It serves as a \"universal\" interatomic potential for the periodic table, capable of relaxing structures and performing MD for diverse chemistries. It can also be used as a surrogate model for property prediction." }, { "num": "359", "name": "SchNetPack", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.1", "subcategory": "MLIPs - Message Passing", "confidence": "VERIFIED", "official_url": "https://github.com/atomistic-machine-learning/schnetpack", "note": "Efficient equivariant message passing without spherical harmonics", "md_link_text": "PaiNN.md", "md_link_path": "Niche/10.1_MLIPs_Message_Passing/PaiNN.md", "papers": [ { "name": "SchNetPack_10.1021_acs.jctc.8b00908.pdf", "path": "Papers_of_Codes/Niche/SchNetPack/SchNetPack_10.1021_acs.jctc.8b00908.pdf", "doi_url": "https://doi.org/10.1021/acs.jctc.8b00908" } ], "paper_placeholder": false, "slug": "SchNetPack", "idx": 827, "overview": "**PaiNN** (Polarizable Atom Interaction Neural Network) is an equivariant message passing architecture that uses scalar and vector features. It achieves high accuracy for molecular property prediction with efficient equivariant message passing." }, { "num": "360", "name": "MLIP", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.2", "subcategory": "MLIPs - ACE/Linear", "confidence": "VERIFIED", "official_url": "https://mlip.org/", "note": "Moment Tensor Potential (MTP) with active learning", "md_link_text": "MLIP.md", "md_link_path": "Niche/10.2_MLIPs_ACE_Linear/MLIP.md", "papers": [ { "name": "10_1137_15M1054183.pdf", "path": "Papers_of_Codes/Niche/10.2_MLIPs_ACE_Linear/MLIP/10_1137_15M1054183.pdf", "doi_url": "https://scholar.google.com/scholar?q=MLIP+10+1137+15M1054183" } ], "paper_placeholder": false, "slug": "MLIP", "idx": 828, "overview": "MLIP is a software package for constructing moment tensor potentials (MTP). MTPs are a class of machine learning potentials that use polynomial invariants as descriptors. They are known for being computationally efficient (faster than neural networks) while maintaining accuracy comparable to GAP or NNPs. MLIP includes tools for active learning (generating training sets on the fly)." }, { "num": "361", "name": "n2p2", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.2", "subcategory": "MLIPs - ACE/Linear", "confidence": "VERIFIED", "official_url": "https://github.com/CompPhysVienna/n2p2", "note": "Behler-Parrinello HDNNP with LAMMPS integration", "md_link_text": "n2p2.md", "md_link_path": "Niche/10.2_MLIPs_ACE_Linear/n2p2.md", "papers": [], "paper_placeholder": true, "slug": "n2p2", "idx": 829, "overview": "n2p2 is a C++ library and set of tools for training and using neural network potentials (Behler-Parrinello type). It allows for the training of high-dimensional neural network potentials (HDNNP) and provides a highly efficient interface for LAMMPS. It is known for its performance and parallel scaling." }, { "num": "362", "name": "SIMPLE-NN", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.2", "subcategory": "MLIPs - ACE/Linear", "confidence": "VERIFIED", "official_url": "https://github.com/MDIL-SNU/SIMPLE-NN", "note": "Simple neural network potential with Behler-Parrinello scheme", "md_link_text": "SIMPLE-NN.md", "md_link_path": "Niche/10.2_MLIPs_ACE_Linear/SIMPLE-NN.md", "papers": [ { "name": "10.1016_j.cpc.2019.04.014.pdf", "path": "Papers_of_Codes/Niche/10.2_MLIPs_ACE_Linear/SIMPLE-NN/10.1016_j.cpc.2019.04.014.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2019.04.014" } ], "paper_placeholder": false, "slug": "SIMPLE-NN", "idx": 830, "overview": "SIMPLE-NN (SImple Machine Learning Potential Energy with Neural Networks) is a package for constructing neural network potentials using Behler-Parrinello symmetry functions. It is designed to be easy to use and integrates with LAMMPS for MD simulations." }, { "num": "363", "name": "AMP", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.2", "subcategory": "MLIPs - ACE/Linear", "confidence": "VERIFIED", "official_url": "https://github.com/libAtoms/QUIP", "note": "Pioneering MLIP framework with SOAP descriptors and sparse GP", "md_link_text": "GAP-QUIP.md", "md_link_path": "Niche/10.2_MLIPs_ACE_Linear/GAP-QUIP.md", "papers": [ { "name": "10.1016_j.cpc.2016.05.010.pdf", "path": "Papers_of_Codes/Niche/10.2_MLIPs_ACE_Linear/AMP/10.1016_j.cpc.2016.05.010.pdf", "doi_url": "https://doi.org/10.1016/j.cpc.2016.05.010" } ], "paper_placeholder": false, "slug": "AMP", "idx": 831, "overview": "**GAP** (Gaussian Approximation Potential) with **QUIP** (Quantum Interatomic Potential) is the original MLIP framework using SOAP descriptors and sparse Gaussian processes. It pioneered the field of ML interatomic potentials and remains widely used for element-specific high-accuracy potentials." }, { "num": "395", "name": "SNAP", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.2", "subcategory": "MLIPs - ACE/Linear", "confidence": "VERIFIED", "official_url": "https://www.lammps.org/", "note": "Spectral Neighbor Analysis Potential - ML potential in LAMMPS.", "md_link_text": "SNAP.md", "md_link_path": "Niche/10.2_MLIPs_ACE_Linear/SNAP.md", "papers": [ { "name": "10.1016_j.jcp.2014.12.018.pdf", "path": "Papers_of_Codes/Niche/10.2_MLIPs_ACE_Linear/SNAP/10.1016_j.jcp.2014.12.018.pdf", "doi_url": "https://doi.org/10.1016/j.jcp.2014.12.018" }, { "name": "10.1063_1.5017641.pdf", "path": "Papers_of_Codes/Niche/10.2_MLIPs_ACE_Linear/SNAP/10.1063_1.5017641.pdf", "doi_url": "https://doi.org/10.1063/1.5017641" } ], "paper_placeholder": false, "slug": "SNAP", "idx": 832, "overview": "" }, { "num": "381", "name": "ACE", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.2", "subcategory": "MLIPs - ACE/Linear", "confidence": "VERIFIED", "official_url": "https://github.com/ACEsuit/ACE.jl", "note": "Atomic Cluster Expansion framework for ML interatomic potentials.", "md_link_text": "ACE.md", "md_link_path": "Niche/10.2_MLIPs_ACE_Linear/ACE.md", "papers": [ { "name": "10.1016_j.jcp.2022.110946.pdf", "path": "Papers_of_Codes/Niche/10.2_MLIPs_ACE_Linear/ACE/10.1016_j.jcp.2022.110946.pdf", "doi_url": "https://doi.org/10.1016/j.jcp.2022.110946" }, { "name": "10.1103_PhysRevB.99.014104.pdf", "path": "Papers_of_Codes/Niche/10.2_MLIPs_ACE_Linear/ACE/10.1103_PhysRevB.99.014104.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.99.014104" } ], "paper_placeholder": false, "slug": "ACE", "idx": 833, "overview": "" }, { "num": "364", "name": "AFLOW-ML", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.8", "subcategory": "Niche Tools", "confidence": "VERIFIED", "official_url": "http://www.aflow.org/aflow-ml", "note": "", "md_link_text": "AFLOW-ML.md", "md_link_path": "Niche/10.8_Niche_Tools/AFLOW-ML.md", "papers": [ { "name": "10_1016_j_commatsci_2018_03_075.pdf", "path": "Papers_of_Codes/Niche/10.8_Niche_Tools/AFLOW-ML/10_1016_j_commatsci_2018_03_075.pdf", "doi_url": "https://scholar.google.com/scholar?q=AFLOW-ML+10+1016+j+commatsci+2018+03+075" }, { "name": "Curtarolo_et_al_2012.pdf", "path": "Papers_of_Codes/Niche/10.8_Niche_Tools/AFLOW-ML/Curtarolo_et_al_2012.pdf", "doi_url": "https://scholar.google.com/scholar?q=AFLOW-ML+Curtarolo+et+al+2012" }, { "name": "10.1016_j.commatsci.2012.02.005.pdf", "path": "Papers_of_Codes/Niche/10.8_Niche_Tools/AFLOW-ML/10.1016_j.commatsci.2012.02.005.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2012.02.005" } ], "paper_placeholder": false, "slug": "AFLOW-ML", "idx": 834, "overview": "AFLOW-ML is a machine learning API and library integrated into the AFLOW framework. It provides access to pre-trained machine learning models for predicting materials properties (electronic, thermal, mechanical) based on crystal structure and composition. It allows users to screen materials without performing expensive DFT calculations." }, { "num": "365", "name": "AFLOW-SYM", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.8", "subcategory": "Niche Tools", "confidence": "VERIFIED", "official_url": "http://www.aflow.org/aflow-sym", "note": "", "md_link_text": "AFLOW-SYM.md", "md_link_path": "Niche/10.8_Niche_Tools/AFLOW-SYM.md", "papers": [ { "name": "Curtarolo_et_al_2012.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/AFLOW/Curtarolo_et_al_2012.pdf", "doi_url": "https://scholar.google.com/scholar?q=AFLOW-SYM+Curtarolo+et+al+2012" }, { "name": "10.1016_j.commatsci.2012.02.005.pdf", "path": "Papers_of_Codes/Frameworks/9.4_Materials_Databases/AFLOW/10.1016_j.commatsci.2012.02.005.pdf", "doi_url": "https://doi.org/10.1016/j.commatsci.2012.02.005" } ], "paper_placeholder": false, "slug": "AFLOW-SYM", "idx": 835, "overview": "AFLOW-SYM is a robust symmetry analysis tool integrated into the AFLOW framework. It determines the symmetry of crystals (space group, Pearson symbol, Wyckoff positions) and performs symmetry-based operations like finding the primitive cell or standardization. It is designed to handle noisy experimental data and high-throughput calculations robustly." }, { "num": "366", "name": "CatApp", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.8", "subcategory": "Niche Tools", "confidence": "VERIFIED", "official_url": "https://github.com/SUNCAT-Center/CatApp", "note": "", "md_link_text": "CatApp.md", "md_link_path": "Niche/10.8_Niche_Tools/CatApp.md", "papers": [ { "name": "10_1038_s41597-019-0081-y.pdf", "path": "Papers_of_Codes/Niche/10.8_Niche_Tools/CatApp/10_1038_s41597-019-0081-y.pdf", "doi_url": "https://scholar.google.com/scholar?q=CatApp+10+1038+s41597+019+0081+y" } ], "paper_placeholder": false, "slug": "CatApp", "idx": 836, "overview": "CatApp is a web-based application (and mobile app) providing a database of DFT-calculated reaction energies and activation barriers for surface reactions relevant to heterogeneous catalysis. It allows users to quickly look up activation energies for elementary steps on various metal surfaces." }, { "num": "367", "name": "CatMAP", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.8", "subcategory": "Niche Tools", "confidence": "VERIFIED", "official_url": "https://github.com/SUNCAT-Center/CatMAP", "note": "", "md_link_text": "CatMAP.md", "md_link_path": "Niche/10.8_Niche_Tools/CatMAP.md", "papers": [ { "name": "10_1007_s10562-015-1495-6.pdf", "path": "Papers_of_Codes/Niche/10.8_Niche_Tools/CatMAP/10_1007_s10562-015-1495-6.pdf", "doi_url": "https://scholar.google.com/scholar?q=CatMAP+10+1007+s10562+015+1495+6" } ], "paper_placeholder": false, "slug": "CatMAP", "idx": 837, "overview": "CatMAP is a software package for thermodynamic and kinetic modeling of catalytic reactions. It allows users to create microkinetic models based on DFT-calculated energies. CatMAP automates the solution of the mean-field rate equations to predict turnover frequencies (TOF), coverages, and reaction rates as a function of temperature and pressure." }, { "num": "368", "name": "DataVerse", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.8", "subcategory": "Niche Tools", "confidence": "VERIFIED", "official_url": "https://dataverse.org/", "note": "", "md_link_text": "DataVerse.md", "md_link_path": "Niche/10.8_Niche_Tools/DataVerse.md", "papers": [], "paper_placeholder": true, "slug": "DataVerse", "idx": 838, "overview": "Dataverse is an open-source web application to share, preserve, cite, explore, and analyze research data. It facilitates making data available to others and allows you to replicate others' work more easily. Institutions often host their own Dataverse repositories (e.g., Harvard Dataverse)." }, { "num": "369", "name": "Dual-fermions", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.8", "subcategory": "Niche Tools", "confidence": "VERIFIED", "official_url": "https://github.com/averkulov/dual-fermion", "note": "", "md_link_text": "Dual-fermions.md", "md_link_path": "Niche/10.8_Niche_Tools/Dual-fermions.md", "papers": [ { "name": "10.1103_PhysRevB.77.033101.pdf", "path": "Papers_of_Codes/materials_science_papers/9.3_Specialized_DFT/Dual fermions/10.1103_PhysRevB.77.033101.pdf", "doi_url": "https://doi.org/10.1103/PhysRevB.77.033101" } ], "paper_placeholder": false, "slug": "Dual-fermions", "idx": 839, "overview": "\"Dual Fermions\" refers to a theoretical method (Dual Fermion expansion) for going beyond Dynamical Mean Field Theory (DMFT) to include non-local spatial correlations. While not a single software package, there are specific open-source implementations, most notably **opendf** (developed by the Center for Quantum Materials Physics) and **DFermion**. These codes solve strongly correlated lattice problems (like the Hubbard model) using the dual fermion diagrammatic expansion." }, { "num": "371", "name": "GASpy", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.8", "subcategory": "Niche Tools", "confidence": "VERIFIED", "official_url": "https://github.com/ulissigroup/gaspy", "note": "", "md_link_text": "GASpy.md", "md_link_path": "Niche/10.8_Niche_Tools/GASpy.md", "papers": [ { "name": "10_1038_s41929-018-0142-1.pdf", "path": "Papers_of_Codes/Niche/10.8_Niche_Tools/GASpy/10_1038_s41929-018-0142-1.pdf", "doi_url": "https://scholar.google.com/scholar?q=GASpy+10+1038+s41929+018+0142+1" } ], "paper_placeholder": false, "slug": "GASpy", "idx": 840, "overview": "GASpy is a Python package for automating the generation of adsorption structures on catalyst surfaces for high-throughput DFT calculations. Developed by the Ulissi Group (CMU), it focuses on finding the lowest energy adsorption sites for arbitrary adsorbates on arbitrary surfaces using heuristic algorithms and VASP." }, { "num": "372", "name": "HubbardFermiMatsubara", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.8", "subcategory": "Niche Tools", "confidence": "VERIFIED", "official_url": "https://github.com/HauleGroup/HubbardFermiMatsubara", "note": "", "md_link_text": "HubbardFermiMatsubara.md", "md_link_path": "Niche/10.8_Niche_Tools/HubbardFermiMatsubara.md", "papers": [ { "name": "10_1103_PhysRevB_100_205130.pdf", "path": "Papers_of_Codes/Niche/10.8_Niche_Tools/HubbardFermiMatsubara/10_1103_PhysRevB_100_205130.pdf", "doi_url": "https://scholar.google.com/scholar?q=HubbardFermiMatsubara+10+1103+PhysRevB+100+205130" }, { "name": "10.1098_rspa.1963.0204.pdf", "path": "Papers_of_Codes/Niche/10.8_Niche_Tools/HubbardFermiMatsubara/10.1098_rspa.1963.0204.pdf", "doi_url": "https://doi.org/10.1098/rspa.1963.0204" } ], "paper_placeholder": false, "slug": "HubbardFermiMatsubara", "idx": 841, "overview": "**Status**: \u26a0\ufe0f UNCERTAIN / RESEARCH CODE" }, { "num": "373", "name": "Matbench", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.8", "subcategory": "Niche Tools", "confidence": "VERIFIED", "official_url": "https://matbench.materialsproject.org/", "note": "", "md_link_text": "Matbench.md", "md_link_path": "Niche/10.8_Niche_Tools/Matbench.md", "papers": [ { "name": "10_1038_s41524-020-00406-3.pdf", "path": "Papers_of_Codes/Niche/10.8_Niche_Tools/Matbench/10_1038_s41524-020-00406-3.pdf", "doi_url": "https://scholar.google.com/scholar?q=Matbench+10+1038+s41524+020+00406+3" } ], "paper_placeholder": false, "slug": "Matbench", "idx": 842, "overview": "Matbench is an automated leaderboard and benchmark suite for materials science machine learning. It consists of a curated set of 13 materials datasets (covering properties like band gap, formation energy, elastic moduli) and a python package to simplify testing and submission. It aims to standardize the comparison of ML algorithms in materials science." }, { "num": "374", "name": "OSF", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.8", "subcategory": "Niche Tools", "confidence": "VERIFIED", "official_url": "https://osf.io/", "note": "", "md_link_text": "OSF.md", "md_link_path": "Niche/10.8_Niche_Tools/OSF.md", "papers": [ { "name": "OSF_10.5195_jmla.2017.88.pdf", "path": "Papers_of_Codes/Niche/OSF/OSF_10.5195_jmla.2017.88.pdf", "doi_url": "https://doi.org/10.5195/jmla.2017.88" } ], "paper_placeholder": false, "slug": "OSF", "idx": 843, "overview": "The Open Science Framework (OSF) is a free, open-source project management tool that supports researchers throughout their entire project lifecycle. It functions as a collaboration platform, allowing teams to manage files, data, code, and protocols in one centralized location. It integrates with many other services (GitHub, Dropbox, Google Drive, Dataverse) to act as a hub." }, { "num": "376", "name": "QMCPACK-addons", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.8", "subcategory": "Niche Tools", "confidence": "VERIFIED", "official_url": "https://github.com/QMCPACK/qmcpack-addons", "note": "", "md_link_text": "QMCPACK-addons.md", "md_link_path": "Niche/10.8_Niche_Tools/QMCPACK-addons.md", "papers": [ { "name": "Kim_et_al_2018.pdf", "path": "Papers_of_Codes/DMFT/3.3_QMC/QMCPACK/Kim_et_al_2018.pdf", "doi_url": "https://scholar.google.com/scholar?q=QMCPACK-addons+Kim+et+al+2018" } ], "paper_placeholder": false, "slug": "QMCPACK-addons", "idx": 844, "overview": "Nexus is a workflow management system distributed with QMCPACK. It automates the complex series of steps required for Quantum Monte Carlo (QMC) calculations: generating trial wavefunctions (from DFT codes like QE, VASP), optimizing Jastrow factors, and running DMC. It manages dependencies and job submission." }, { "num": "377", "name": "Stoner", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.8", "subcategory": "Niche Tools", "confidence": "VERIFIED", "official_url": "https://github.com/janosh/stoner", "note": "", "md_link_text": "Stoner.md", "md_link_path": "Niche/10.8_Niche_Tools/Stoner.md", "papers": [], "paper_placeholder": true, "slug": "Stoner", "idx": 845, "overview": "The Stoner package is a Python library containing a collection of utilities for managing and analyzing experimental data, particularly in physics. It provides a `Data` class (subclassing Pandas DataFrame) with metadata handling and specialized plotting/analysis methods useful for experimentalists (e.g., hysteresis loops, IV curves)." }, { "num": "378", "name": "Zenodo", "category_id": "10", "category": "NICHE & ML", "subcategory_id": "10.8", "subcategory": "Niche Tools", "confidence": "VERIFIED", "official_url": "https://zenodo.org/", "note": "", "md_link_text": "Zenodo.md", "md_link_path": "Niche/10.8_Niche_Tools/Zenodo.md", "papers": [], "paper_placeholder": true, "slug": "Zenodo", "idx": 846, "overview": "Zenodo is a general-purpose open-access repository developed under the European OpenAIRE program and operated by CERN. It allows researchers to deposit data sets, research software, reports, and any other research related digital artifacts. For each submission, a persistent identifier (DOI) is minted, making the stored items easily citeable." } ] }