Force Fields Python Packages

nequip

NequIP is a code for building E(3)-equivariant interatomic potentials

nequip-allegro

Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials

chgnet

Pretrained universal neural network potential for charge-informed atomistic modeling https://chgnet.lbl.gov

kliff

KIM-based Learning-Integrated Fitting Framework for interatomic potentials.

moltemplate

A general cross-platform tool for preparing simulations of molecules and complex molecular assemblies

graph-pes

train and use graph-based ML models of potential energy surfaces

apax

A flexible and performant framework for training machine learning potentials.

openff-toolkit

The Open Forcefield Toolkit provides implementations of the SMIRNOFF format, parameterization engine, and other tools. Documentation available at http://open-forcefield-toolkit.readthedocs.io

pystokes

Phoresis and Stokesian hydrodynamics in Python

acellera-openff-toolkit

The Open Forcefield Toolkit provides implementations of the SMIRNOFF format, parameterization engine, and other tools. Documentation available at http://open-forcefield-toolkit.readthedocs.io

q2mm

Quantum-guided molecular mechanics force field optimization

neoralab-openff-toolkit

OpenFF toolkit distribution maintained by Neoralab

uf3

Ultra-Fast Force Fields for molecular dynamics

nequip-eqx

JAX implementation of the NequIP neural network interatomic potential