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

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

JARVIS-Tools: an open-source software package for data-driven atomistic materials design. Publications: https://scholar.google.com/citations?user=3w6ej94AAAAJ https://www.youtube.com/@dr_k_choudhary

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

Generate input parameters and coordinates for atomistic and coarse-grained simulations of polymers, ssDNA, and carbohydrates

Code for automated fitting of machine learned interatomic potentials.

Python tool to manipulate Gaussian cube files

Training and evaluating machine learning models for atomistic systems.

A Python Package to Automate Thermodynamic Integration Calculations for Free Energy

A collection of simulation recipes for the atomic-scale modeling of materials and molecules

Grand canonical optimization of grain boundary phases.

Toolkit using the Atomistic Simulation Environment (ASE)

Utilities for ab initio modeling suite CRYSTAL, developed in Turin University

Input file writers and output file readers for the density functional theory code CASTEP.

Library for handling atomistic graph datasets focusing on transformer-based implementations, with utilities for training various models, experimenting with different pre-training tasks, and a suite of pre-trained models with huggingface integrations

A python package for fast building amorphous solids and liquid mixtures from @materialsproject computed structures and machine learning interatomic potentials

Bottom-up topology maker for LAMMPS

Build atomistic structures such as grain boundaries with Python

A collection of Python code for setting up and harvesting results from CASTEP and LAMMPS simulations.

A python interface for SIMPSON