🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.

NWChem: Open Source High-Performance Computational Chemistry

Density-functional toolkit

DFTB+ general package for performing fast atomistic simulations

Deep neural networks for density functional theory Hamiltonian.

The official github mirror of the Abinit repository. We welcome bug fixes and improvements. Note that most of the active developments are hosted on our https://un5q025qp35vj3nhtp8f6wr.julianrbryant.com/ server. Before embarking on making significant changes, please contact the Abinit group. Note that questions will NOT be treated on github, please use the ABINIT Forum.

An electronic structure package based on either plane wave basis or numerical atomic orbitals.

nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset

Electronic structure Python package for post analysis and large scale tight-binding DFT/NEGF calculations

QUICK: A GPU-enabled ab intio quantum chemistry software package

FeOs - A Framework for Equations of State and Classical Density Functional Theory

Notes and tutorials on Density Functional Theory calculation using Quantum ESPRESSO.

Domain specific library for electronic structure calculations

DFT-FE: Real-space DFT calculations using Finite Elements

p4vasp, the VASP Visualization Tool

Open-source library for analyzing the results produced by ABINIT

Plane wave density functional theory using Julia programming language

Differentiable Quantum Chemistry (only Differentiable Density Functional Theory and Hartree Fock at the moment)

GradDFT is a JAX-based library enabling the differentiable design and experimentation of exchange-correlation functionals using machine learning techniques.

Materials Learning Algorithms. A framework for machine learning materials properties from first-principles data.