A Python package for estimating diffusion properties from molecular dynamics simulations.

Jupyter notebooks demonstrating the utilization of open-source codes for the study of materials science.

MACE-Field - Fast and accurate machine learning interatomic potentials under an external electric field for predicting dielectric properties.

Torch-native, batchable, atomistic simulations.

Automated Reactions for CO2 Storage

Python library for creating PEG parsers

MatterSim: A deep learning atomistic model across elements, temperatures and pressures.

A code to generate atomic structure with symmetry

All aboard the Coding Train! Choo choo! 🚂🌈❤️

Anharmonic Lattice Dynamics

Data mining for materials science

Automated creation and manipulation of Chemical Reaction Networks (CRNs) in heterogeneous catalysis, allowing the evaluation of species and reaction properties with data-driven ML models and the ne…

Open source IFC library and geometry engine

Graph deep learning library for materials

Python package to interact with high-dimensional representations of the chemical elements

New API client for the Materials Project

datalab is a place to store experimental data and the connections between them.

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

12 Weeks, 24 Lessons, AI for All!

The Temperature Dependent Effective Potentials (TDEP) code

quacc is a flexible platform for computational materials science and quantum chemistry that is built for the big data era.

jobflow is a library for writing computational workflows.

A lightweight python package for reading and writing VASP ML_AB files

Understanding Deep Learning - Simon J.D. Prince

Python bindings for the `buildcell` program for Ab Initio Random Structure Searching (AIRSS)

Ferroelectric/Ferroelastic domain wall builder