LiuGaoyong/AwesomeMLP

Awesome Machine Learning Interatomic Potentials

39
/ 100
Emerging

This collection helps materials scientists, computational chemists, and drug discovery researchers find software tools for simulating atomistic and molecular systems more efficiently. It curates various machine learning-based interatomic potentials and related toolkits, allowing you to select software that takes molecular structures or atomic configurations as input and predicts properties, forces, or energies. The primary users are researchers focused on advanced simulations in chemistry and materials science.

Use this if you need to find an existing software package to perform atomistic or molecular simulations using machine learning-based interatomic potentials, saving time compared to traditional quantum mechanics methods.

Not ideal if you are looking for general-purpose machine learning frameworks or tools not specifically tailored for atomistic or molecular simulations.

materials-science computational-chemistry drug-discovery atomistic-simulation molecular-dynamics
No Package No Dependents
Maintenance 6 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 12 / 25

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Stars

11

Forks

2

Language

License

GPL-3.0

Last pushed

Dec 28, 2025

Commits (30d)

0

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