matador
matador: a Python library for analysing, curating and performing high-throughput density-functional theory calculations - Published in JOSS (2020)
smol
smol: A Python package for cluster expansions and beyond - Published in JOSS (2022)
SMACT
SMACT: Semiconducting Materials by Analogy and Chemical Theory - Published in JOSS (2019)
spgrep
spgrep: On-the-fly generator of space-group irreducible representations - Published in JOSS (2023)
f3dasm
f3dasm: Framework for Data-Driven Design and Analysis of Structures and Materials - Published in JOSS (2024)
A Python Library for Pre- and Post-Processing of DAMASK Simulations
A Python Library for Pre- and Post-Processing of DAMASK Simulations - Published in JOSS (2025)
Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science
Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science - Published in JOSS (2024)
ThermoParser
ThermoParser: Streamlined Analysis of Thermoelectric Properties - Published in JOSS (2024)
PyTASER
PyTASER: Simulating transient absorption spectroscopy (TAS) for crystals from first principles - Published in JOSS (2024)
RustBCA
RustBCA: A High-Performance Binary-Collision-Approximation Code for Ion-Material Interactions - Published in JOSS (2021)
xtal2png
xtal2png: A Python package for representing crystal structure as PNG files - Published in JOSS (2022)
SAMBA
SAMBA: A Trainable Segmentation Web-App with Smart Labelling - Published in JOSS (2024)
polypy - Analysis Tools for Solid State Molecular Dynamics and Monte Carlo Trajectories
polypy - Analysis Tools for Solid State Molecular Dynamics and Monte Carlo Trajectories - Published in JOSS (2021)
UnlockNN
UnlockNN: Uncertainty quantification for neural network models of chemical systems - Published in JOSS (2022)
pylattica
pylattica: a package for prototyping lattice models in chemistry and materials science - Published in JOSS (2024)
PyZFS
PyZFS: A Python package for first-principles calculations of zero-field splitting tensors - Published in JOSS (2020)
deepmd-kit
A deep learning package for many-body potential energy representation and molecular dynamics
Kanapy
Kanapy: A Python package for generating complex synthetic polycrystalline microstructures - Published in JOSS (2019)
Ising_OPV v4.0
Ising_OPV v4.0: Experimental Tomography Data Import, Interpretation, and Analysis - Published in JOSS (2018)
https://github.com/mir-group/allegro
Allegro is an open-source code for building highly scalable and accurate equivariant deep learning interatomic potentials
Express
Express: a high-level, extensible workflow framework for accelerating ab initio calculations for the materials science community
QuantumESPRESSOBase
Provides basic data structures and helpful functions for manipulating structures, generating input files, pre-running error checks, etc.
Chemiscope
Chemiscope: interactive structure-property explorer for materials and molecules - Published in JOSS (2020)
reaction-network
Reaction Network is a Python package for predicting likely inorganic chemical reaction pathways using graph theoretical methods. Project led by @mattmcdermott (formerly at Berkeley Lab).
sqsgenerator
A command line tool written in Python/C++ for finding optimized SQS structures
pycrystal
Utilities for ab initio modeling suite CRYSTAL, developed in Turin University
yascheduler
Yet another cloud computing scheduler for the high-throughput cloud scientific simulations
optimade
Isomorphic TypeScript / JavaScript client to aggregate all the official Optimade providers
pymatgen
Python Materials Genomics (pymatgen) is a robust materials analysis code that defines classes for structures and molecules with support for many electronic structure codes. It powers the Materials Project.
https://github.com/lukasturcani/stk
A Python library which allows construction and manipulation of complex molecules, as well as automatic molecular design and the creation of molecular databases.
https://github.com/materialsvirtuallab/m3gnet
Materials graph network with 3-body interactions featuring a DFT surrogate crystal relaxer and a state-of-the-art property predictor.
https://github.com/tilde-lab/quantum_esperanto
Very fast parser for the XML logs produced with the VASP, Vienna Ab initio Simulation Package
https://github.com/hackingmaterials/robocrystallographer
Automatic generation of crystal structure descriptions.
https://github.com/sparks-baird/self-driving-lab-demo
Software and instructions for setting up and running a self-driving lab (autonomous experimentation) demo using dimmable RGB LEDs, an 8-channel spectrophotometer, a microcontroller, and an adaptive design algorithm, as well as extensions to liquid- and solid-based color matching demos.
https://github.com/bin-cao/bgolearn
[Materials & Design 2024 | NPJ com mat 2024] Offical implement of Bgolearn
pybaselines
A Python library of algorithms for the baseline correction of experimental data.
cmstatr
cmstatr: An R Package for Statistical Analysis of Composite Material Data - Published in JOSS (2020)
lintf2_ether_ana_postproc
Analysis postprocessing utilities for my molecular dynamics simulations of LiTFSI-Ether mixtures
sumo
sumo: Command-line tools for plotting and analysis of periodic *ab initio* calculations - Published in JOSS (2018)
mattersim
MatterSim: A deep learning atomistic model across elements, temperatures and pressures.
https://github.com/wmd-group/pdyna
Python package to analyse the structural dynamics of perovskites
https://github.com/pycalphad/scheil
A Scheil-Gulliver simulation tool using pycalphad.
https://github.com/pycalphad/pycalphad
CALPHAD tools for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria.
maml
Python for Materials Machine Learning, Materials Descriptors, Machine Learning Force Fields, Deep Learning, etc.
https://github.com/microsoft/mattergen
Official implementation of MatterGen -- a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property constraints.
https://github.com/pycroscopy/atomai
Deep and Machine Learning for Microscopy
https://github.com/pycroscopy/pycroscopy
Scientific analysis of nanoscale materials imaging data
https://github.com/laurentrdc/crystals
Data structures, algorithms, and parsing for crystallography
deepchem
Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology
https://github.com/uf3/uf3
UF3: a python library for generating ultra-fast interatomic potentials
https://github.com/killiansheriff/atomisticreversemontecarlo
OVITO Python modifier to generate bulk crystal structures with target Warren-Cowley parameters.
https://github.com/mpes-kit/fuller
Probabilistic machine learning for reconstruction and parametrization of electronic band sturcture from photoemission spectroscopy data
https://github.com/usnistgov/fipy
FiPy is a Finite Volume PDE solver written in Python
https://github.com/abinit/abipy
Open-source library for analyzing the results produced by ABINIT
libRL
libRL: A Python library for the characterization of microwave absorption - Published in JOSS (2019)
https://github.com/aiida-vasp/aiida-vasp
A plugin to AiiDA for running simulations with VASP
https://github.com/aiidateam/aiida-workgraph
Efficiently design and manage flexible workflows with AiiDA, featuring an interactive GUI, checkpoints, provenance tracking, and remote execution capabilities.
https://github.com/ppdebreuck/modnet
MODNet: a framework for machine learning materials properties
https://github.com/exabyte-io/materials-designer
A standalone React.js/Redux based web application for the design and visualization of atomistic materials structures. Used at Mat3ra.com and can be deployed in standalone mode.
https://github.com/simphony/simphony-osp
A framework that aims to achieve interoperability between software such as simulation engines, databases and data repositories using a knowledge graph as the common language.
https://github.com/sparks-baird/mat_discover
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
https://github.com/singularitti/spglib.jl
A Julia wrapper for the spglib C-API
https://github.com/radonpy/radonpy
RadonPy is a Python library to automate physical property calculations for polymer informatics.
https://github.com/aspuru-guzik-group/olympus
Olympus: a benchmarking framework for noisy optimization and experiment planning
https://github.com/suncat-center/catlearn
A machine learning environment for atomic-scale modeling in surface science and catalysis.
lasp2interface
Interface for on-the-fly training of Machine Learning Interaction Potentials
https://github.com/killiansheriff/warrencowleyparameters
OVITO Python modifier to compute the Warren-Cowley parameters.
https://github.com/pmeal/beatmap
BET surface area analysis from adsorption data
https://github.com/phasesresearchlab/espei
Fitting thermodynamic models with pycalphad - https://doi.org/10.1557/mrc.2019.59
https://github.com/usnistgov/pyprism
A framework for conducting polymer reference interaction site model (PRISM) calculations
https://github.com/singroup/dscribe
DScribe is a python package for creating machine learning descriptors for atomistic systems.
mpes
Distributed data processing routines for multidimensional photoemission spectroscopy (MPES)
https://github.com/sparks-baird/mp-time-split
Use time-splits for Materials Project entries for generative modeling benchmarking.
hextof-processor
Code for preprocessing data from the HEXTOF instrument at FLASH, DESY in Hamburg (DE)
https://github.com/janosh/matterviz
Interactive browser visualizations for materials science: periodic tables, 3d crystal structures, MD trajectories, heatmaps, scatter plots, histograms.
pymicro
A Python package to work with material microstructures and 3d data sets
https://github.com/hyperspy/hyperspyui
A user interface for the hyperspy package. https://hyperspy.org/hyperspyUI
https://github.com/exabyte-io/wode.js
Workflow Definitions for Digital Materials/Chemistry R&D
https://github.com/cedergrouphub/s4
Solid-state synthesis science analyzer. Thermo, features, ML, and more.
https://github.com/muammar/ml4chem
ML4Chem: Machine Learning for Chemistry and Materials