Official Resources
- Source Repository: https://github.com/Chengcheng-Xiao/WOOPs
- Documentation: Included in repository
- License: Open source
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.
Scientific domain: Wannier function bonding analysis, COOP/COHP in Wannier basis
Target user community: Researchers analyzing chemical bonding using Wannier functions from Wannier90
Theoretical Methods
- Wannier Orbital Overlap Population (WOOP)
- Wannier Orbital Position Population (WOPP)
- COOP/COHP analog in Wannier basis
- Wannier90 Hamiltonian analysis
- Bonding/antibonding decomposition
- Projected Crystal Orbital Hamilton Population
Capabilities (CRITICAL)
- WOOP calculation (Wannier COOP analog)
- WOPP calculation (Wannier position population)
- Bonding analysis in Wannier basis
- Wannier90 interface
- Energy-resolved bonding/antibonding
- Pair analysis between Wannier functions
Sources: GitHub repository
Key Strengths
Wannier-Based Bonding:
- Bonding analysis in Wannier basis
- More localized than atomic orbital COOP
- Directly from Wannier90 output
- Systematic and well-defined
COOP/COHP Analogy:
- Familiar bonding analysis framework
- Energy-resolved contributions
- Bonding vs antibonding decomposition
- Quantitative bonding metrics
Wannier90 Integration:
- Direct interface with Wannier90
- Uses hr.dat, centers, spreads
- Consistent with Wannier90 workflow
- Supports multiple DFT codes via Wannier90
Inputs & Outputs
-
Input formats:
- Wannier90 hr.dat (Hamiltonian)
- Wannier90 output files
- Structure files
-
Output data types:
- WOOP vs energy
- WOPP vs energy
- Bonding/antibonding contributions
- ICOOP (integrated WOOP)
Interfaces & Ecosystem
- Wannier90: Primary interface
- Python: Core language
- NumPy: Numerical computation
Performance Characteristics
- Speed: Fast (post-processing)
- Accuracy: Wannier-level
- System size: Limited by Wannier90 Hamiltonian
- Memory: Moderate
Computational Cost
- WOOP calculation: Seconds to minutes
- Wannier90 pre-requisite: Hours (separate)
- Typical: Very efficient
Limitations & Known Constraints
- Wannier90 dependency: Requires Wannier90 output
- WOPP alpha: Position population still in testing
- Limited documentation: Research code
- Small community: Research group code
Comparison with Other Codes
- vs LOBSTER: WOOPs is Wannier-based, LOBSTER is PAW-based COHP
- vs LobsterPy: WOOPs is Wannier, LobsterPy is LOBSTER wrapper
- vs COHP: WOOPs extends COHP concept to Wannier basis
- Unique strength: Bonding analysis (COOP/COHP) in Wannier function basis from Wannier90
Application Areas
Chemical Bonding:
- Bonding analysis in Wannier basis
- Energy-resolved bonding character
- Bonding vs antibonding decomposition
- Quantitative bonding metrics
Materials Science:
- Bonding in complex materials
- Wannier-level bonding analysis
- Comparison with atomic orbital COHP
- Bonding trend analysis
Wannier Function Analysis:
- Wannier function quality assessment
- Wannier localization and bonding
- Wannier overlap populations
- Wannier position populations
Best Practices
Wannier90 Setup:
- Use well-localized Wannier functions
- Check Wannier spread convergence
- Include sufficient bands
- Validate Wannier interpolation against DFT
WOOP Analysis:
- Focus on relevant Wannier pairs
- Compare with COHP/COOP results
- Use energy-resolved plots
- Integrate for total bonding character
Community and Support
- Open source on GitHub
- Developed by C. Xiao
- Research code
- Limited documentation
Verification & Sources
Primary sources:
- GitHub: https://github.com/Chengcheng-Xiao/WOOPs
Confidence: VERIFIED
Verification status: ✅ VERIFIED
- Source code: ACCESSIBLE (GitHub)
- Documentation: Included in repository
- Active development: Research code
- Specialized strength: Bonding analysis (COOP/COHP) in Wannier function basis from Wannier90