basf/mlipx
Machine-Learned Interatomic Potential eXploration (mlipx) is designed at BASF for evaluating machine-learned interatomic potentials (MLIPs). It offers a growing set of evaluation methods alongside powerful visualization and comparison tools.
This tool helps computational chemists and materials scientists evaluate and compare different machine-learned interatomic potentials (MLIPs). You input material structures (from files, SMILES strings, or Materials Project IDs) and specify the MLIPs you want to test. It then outputs calculated properties, like energy-volume curves or optimized structures, along with powerful visualizations, allowing you to assess an MLIP's suitability for your specific research.
Use this if you need to rigorously test and compare the accuracy and performance of various machine-learned interatomic potentials for your materials science or chemistry research.
Not ideal if you are looking to develop a new MLIP from scratch or perform quantum chemistry calculations without comparing MLIPs.
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96
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7
Language
Python
License
MIT
Category
Last pushed
Jan 28, 2026
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0
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