Search Packages

sisl

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

zinq

Implementations of electronic structure methods and mathematical algorithms in Zig, focusing on clarity, simplicity, and modern system programming.

abipy

Open-source library for analyzing the results produced by ABINIT

feos

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

aarontools

Python tools for automating routine tasks encountered when running quantum chemistry computations.

masci-tools

Post-processing toolkit for electronic structure calculations

esse

JSON schemas and examples representing structural data, characteristic properties, modeling workflows and related data about materials standardizing the diverse landscape of information

mdkits

kits for cp2k and abinit

aiida-kkr

AiiDA plugin of the high-performance density functional theory code JuKKR (www.judft.de) for high-throughput electronic structure calculations.

aiida-fleur

AiiDA Plugin for running the FLEUR code and its input generator. Also includes high-level workchains and utilities

pyfock

A simplistic and efficient pure-python quantum chemistry library from Phys Whiz.

grogupy

Python package calculating relativistic magnetic interactions for the generalised Heisenberg model.

asedftk

DFTK-based calculator for ASE

pydft

Python-based localized-orbital Density Functional Theory code for educational purposes.

atomec

Python-based average-atom code for simulations of high energy density phenomena such as in warm dense matter.

dfttoolbox

A toolbox for quickly build inputs and analyze results of DFT codes

mdtool

kits for cp2k and abinit

deepx-dock

DeepH-dock seamlessly integrates deep learning with first-principles calculations. It serves as a modular and extensible bridge, functioning both as the dedicated interface for the DeepH-pack suite and as a standalone tool for coupling deep learning models with computational materials science workflows.

castep-parse

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

ramannoodle

Efficiently compute off-resonance Raman spectra from first principles calculations (e.g. VASP) using polynomial models and machine learning..

materials-learning-algorithms

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

koopmans

Koopmans spectral functional calculations with python and Quantum ESPRESSO

qeview

Tool to help you analyze and visualize the results from Quantum Espresso (Band structure BS, DOS, pDOS) and Wannier90

gamenet-uq

Graph Neural Network with uncertainty quantification for adsorption energy prediction