Official Resources
- Source Repository: https://github.com/nanotech-empa/aiida-gaussian
- Documentation: Included in repository
- PyPI: https://pypi.org/project/aiida-gaussian/
- License: Open source (MIT)
Overview
aiida-gaussian is an AiiDA plugin for the Gaussian quantum chemistry code. It enables running Gaussian calculations within the AiiDA framework with full provenance tracking, input management, and output parsing for molecular electronic structure calculations.
Scientific domain: AiiDA plugin for Gaussian quantum chemistry
Target user community: Researchers using Gaussian with AiiDA workflow management
Theoretical Methods
- Gaussian input generation and management
- Gaussian output parsing
- AiiDA workflow integration
- Provenance tracking for Gaussian calculations
- Molecular electronic structure
Capabilities (CRITICAL)
- Gaussian calculation submission via AiiDA
- Input parameter management
- Output parsing (energies, forces, orbitals)
- Workflow automation
- Provenance tracking
Sources: GitHub repository
Key Strengths
Gaussian Integration:
- All Gaussian calculation types
- Input parameter handling
- Output parsing
- Error recovery
Provenance:
- Full calculation tracking
- Reproducibility
- Data management
- Query capabilities
Molecular Focus:
- Geometry optimization
- Frequency calculations
- TD-DFT
- Multi-step molecular workflows
Inputs & Outputs
-
Input formats:
- Gaussian input parameters
- Molecular structure
-
Output data types:
- Parsed Gaussian output
- Energies, forces, frequencies
- Provenance graph
Interfaces & Ecosystem
- AiiDA: Workflow framework
- Gaussian: Quantum chemistry code
- Python: Core language
Performance Characteristics
- Speed: Workflow management (fast)
- Accuracy: Gaussian-level
- System size: Molecular
- Automation: Full
Computational Cost
- Plugin: Negligible
- Gaussian calculations: Hours (separate)
Limitations & Known Constraints
- Gaussian only: No other code support
- AiiDA required: Must have AiiDA
- Gaussian license: Commercial code required
- Molecular systems: Not for periodic
Comparison with Other Codes
- vs aiida-orca: Different quantum chemistry code
- vs Gaussian directly: aiida-gaussian adds provenance
- Unique strength: AiiDA plugin for Gaussian with provenance tracking for molecular calculations
Application Areas
Molecular Workflows:
- Automated Gaussian calculations
- Multi-step molecular workflows
- High-throughput molecular screening
- Conformer search
Mixed-Code:
- Gaussian + DFT periodic codes
- QM/MM workflows
- Multi-level calculations
Best Practices
Setup:
- Install AiiDA and configure Gaussian
- Set up basis set data
- Test with simple calculation
Usage:
- Use workchains for complex workflows
- Validate parsed output
- Use AiiDA query for analysis
Community and Support
- Open source (MIT)
- PyPI installable
- Developed by nanotech-empa
- AiiDA community
Verification & Sources
Primary sources:
- GitHub: https://github.com/nanotech-empa/aiida-gaussian
Confidence: VERIFIED
Verification status: ✅ VERIFIED
- Source code: ACCESSIBLE (GitHub)
- PyPI: AVAILABLE
- Specialized strength: AiiDA plugin for Gaussian quantum chemistry with provenance tracking