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

About 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

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

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

A Python Package to Automate Thermodynamic Integration Calculations for Free Energy

Train, fine-tune, and manipulate machine learning models for atomistic systems

Python tool to manipulate Gaussian cube files

Toolkit using the Atomistic Simulation Environment (ASE)

A framework for the analysis of the dynamics of particle trajectories

Grand canonical optimization of grain boundary phases.

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

Chemical intuition for surface science in a package.

A python interface for SIMPSON

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

AiiDA plugin for the ab initio modeling suite CRYSTAL, developed in Turin University

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

Protein chemical shift prediction with PyTorch

A collection of Python scripts for computing physical properties and analyzing trajectories from molecular dynamics simulations.

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