sumo

Official Resources

• Homepage: https://smtg-ucl.github.io/sumo/
• Documentation: https://sumo.readthedocs.io/
• Source Repository: https://github.com/SMTG-UCL/sumo
• License: MIT License

Overview

sumo (Seebeck Utility and Materials characterisation Organizer) is a Python toolkit for publication-quality plotting and analysis of ab initio calculation data, with particular focus on VASP outputs. It provides command-line tools for band structure, DOS, optical properties, and phonon plotting.

Scientific domain: Materials visualization, electronic structure analysis
Target user community: Materials scientists needing publication-quality plots from VASP

Theoretical Methods

sumo is a visualization/analysis tool, not a calculation method. It processes outputs from:

• VASP DFT calculations
• Band structures
• Density of states
• Optical properties
• Phonon calculations

Capabilities (CRITICAL)

• Publication-quality band structure plotting
• Density of states (DOS, PDOS) visualization
• Optical absorption spectra plotting
• Phonon band structure and DOS plotting
• Effective mass calculations
• Band gap analysis
• Orbital contribution visualization
• Spin-polarized and spin-orbit calculations
• Customizable plot styling
• High-symmetry k-path generation
• Command-line interface for automation
• Python API for custom workflows
• Export to publication formats (PDF, PNG, SVG)

Sources: Official sumo documentation, cited in 6/7 source lists

Inputs & Outputs

• Input formats:

  • vasprun.xml (VASP output)
  • EIGENVAL, DOSCAR, PROCAR
  • Phonopy outputs (phonopy.yaml, mesh.yaml)
  • POSCAR for structure info

• Output data types:

  • Publication-quality plots (PDF, PNG, SVG)
  • Data files for further analysis
  • Matplotlib figures
  • Effective mass data

Interfaces & Ecosystem

• VASP integration:

  • Direct reading of VASP outputs via pymatgen
  • Automatic k-path detection

• Phonopy integration:

  • Phonon band structure plotting
  • Phonon DOS visualization

• pymatgen backend:

  • Structure analysis
  • Data parsing
  • Built on pymatgen infrastructure

Limitations & Known Constraints

• VASP-focused: Primarily designed for VASP outputs
• pymatgen dependency: Requires pymatgen installation
• Python 3: Requires Python 3.6+
• Platform: Cross-platform (Linux, macOS, Windows)
• Matplotlib backend: Plot customization via matplotlib
• Documentation: Good but assumes VASP familiarity

Verification & Sources

Primary sources:

1. Official website: https://smtg-ucl.github.io/sumo/
2. Documentation: https://sumo.readthedocs.io/
3. GitHub repository: https://github.com/SMTG-UCL/sumo
4. A. M. Ganose et al., J. Open Source Softw. 3, 717 (2018) - sumo paper

Secondary sources:

1. sumo tutorials and examples
2. SMTG group publications using sumo
3. Materials science visualization guides
4. Confirmed in 6/7 source lists (claude, g, gr, k, m, q)

Confidence: CONFIRMED - Appears in 6 of 7 independent source lists

Verification status: ✅ VERIFIED

• Official homepage: ACCESSIBLE
• Documentation: COMPREHENSIVE and ACCESSIBLE
• Source code: OPEN (GitHub)
• Community support: Active (GitHub issues)
• Academic citations: >100
• Active development: Regular updates, well-maintained