There are 31 repositories under density-functional-theory topic.
🏆 A ranked list of awesome atomistic machine learning projects ⚛️🧬💎.
Density-functional toolkit
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://gitlab.abinit.org/ server. Before embarking on making significant changes, please contact the Abinit group.
Electronic structure Python package for post analysis and large scale tight-binding DFT/NEGF calculations
nablaDFT: Large-Scale Conformational Energy and Hamiltonian Prediction benchmark and dataset
An electronic structure package based on either plane wave basis or numerical atomic orbitals.
Domain specific library for electronic structure calculations
DFT-FE: Real-space DFT calculations using Finite Elements
Notes and tutorials on Density Functional Theory calculation using Quantum ESPRESSO.
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.
Python package to analyse electron density & electrostatic potential grids
Optimized Norm-Conserving Vanderbilt Pseudopotential for Quantum Espresso in UPF format
Berry curvature and Chern number calculations with the output (WAVECAR) of VASP code
Interactive Jupyter Notebooks for learning the fundamentals of Density-Functional Theory (DFT)
Document and code of python and PySCF approach XYG3 type of density functional 2nd-derivative realization
Some python workbooks with various topics from Computational Physics
This repository contains example codes for the book: Quantum ESPRESSO Course for Solid‑State Physics, Jenny Stanford Publishing, New York, 372 Pages (2022) by N. T. Hung, A. R. T. Nugraha and R. Saito.
Thermo_pw is a driver of quantum-ESPRESSO routines for the automatic computation of ab-initio material properties.
Python tools for automating routine tasks encountered when running quantum chemistry computations.