Official Resources
- GitHub: https://github.com/QijingZheng/VaspBandUnfolding
- Tutorial: http://staff.ustc.edu.cn/~zqj/posts/Band-unfolding-tutorial/
- License: MIT License
Overview
VaspBandUnfolding is a Python toolkit for VASP band unfolding from supercell calculations, providing WAVECAR parsing and spectral weight calculation with well-documented tutorials.
Scientific domain: Band unfolding, VASP post-processing
Target user community: VASP users studying supercell systems
Capabilities (CRITICAL)
- Band Unfolding: Supercell band structure unfolding
- WAVECAR Parsing: Read VASP wavefunction files
- Spectral Functions: Calculate spectral weights
- K-path Generation: Create unfolding k-paths
Key Strengths
- WAVECAR reading utilities
- Spectral weight calculation
- Well-documented tutorials
- Based on Popescu & Zunger methodology
Inputs & Outputs
- Input formats: VASP WAVECAR, POSCAR
- Output data types: Unfolded band structures, spectral functions
Installation
git clone https://github.com/QijingZheng/VaspBandUnfolding.git
cd VaspBandUnfolding
pip install -e .
Limitations & Known Constraints
- VASP-specific: Only processes VASP WAVECAR files
- Memory: Large WAVECAR files need substantial RAM
- Documentation: Tutorial-based, less formal documentation
Comparison with Other Tools
- vs easyunfold: VaspBandUnfolding more manual, easyunfold more automated
- vs BandUP: Different implementation approaches
- vs fold2Bloch: Both VASP unfolding, different interfaces
- Unique strength: Well-documented tutorials, WAVECAR parsing utilities
Verification & Sources
Confidence: VERIFIED
Verification status: ✅ VERIFIED
- Source code: OPEN (GitHub, MIT)
- Developer: Qijing Zheng (USTC)