MACE - Machine Learning Force Fields

Overview

MACE is a machine learning software for predicting many-body atomic interactions and generating force fields. It utilizes higher order equivariant message passing for fast and accurate predictions.

Features

• Predicts many-body atomic interactions with high accuracy

• Generates force fields for use in molecular dynamics simulations

• Utilizes higher order equivariant message passing

• Fast and efficient predictions

Getting Started

Documentation

For detailed information on how to use MACE, please refer to the following documentation:

User Guide

• Quick Start
• User Guide
  • Introduction
  • Installation
  • Training
  • Evaluation
  • ASE calculator
  • MACE descriptors
  • OpenMM Interface
  • MACE in LAMMPS

Examples

• Example scripts for training MACE models
  • MD22: large molecules
  • ANI-1x dataset: H, C, N, O transferable FF
  • Liquid water
• Foundation models
  • Pretrained MACE-MP-0 models
  • MACE-OFF23: Transferable Organic Force Fields
  • MACE-ANI-CC: Coupled cluster Accurate Pretrained Model for H, C, N, O elements

Support

If you need help using MACE, please use GitHub Discussions or send an email to ilyes.batatia@ens-paris-saclay.fr