Awesome Materials Informatics !Awesome (https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg) (https://github.com/sindresorhus/awesome)

!DOI (https://zenodo.org/badge/121643986.svg) (https://doi.org/10.5281/zenodo.7693349)

The novel discipline of _materials informatics_ is a junction of materials, computer, and data sciences. It aims to unite the nowadays competing physics- and data-intensive efforts for the most impactful applied science, that transformed our 
society in the 20th century.

Contributions are very welcome - please follow the guidelines (CONTRIBUTING.md).


Contents

- Software and products (#software-and-products)
- Cloud simulation platforms and AI startups (#cloud-simulation-platforms-and-ai-startups)
- Machine-readable materials datasets (#machine-readable-materials-datasets)
- Standardization initiatives (#standardization-initiatives)
- Similar compilations (#similar-compilations)
- License (#license)


Software and products

- AFLOW (http://materials.duke.edu/AFLOW) - High-Throughput ab-initio Computing (C++).
- AiiDA (http://aiida.net) - Automated Infrastructure and Database for Ab-initio design (Python). !Github Stars (https://img.shields.io/github/stars/aiidateam/aiida-core?style=social) (https://github.com/aiidateam/aiida-core)
- ASE (https://wiki.fysik.dtu.dk/ase) - Atomic Simulation Environment (Python). !Gitlab Stars (https://img.shields.io/gitlab/stars/ase%2Fase) (https://gitlab.com/ase/ase)
- ASR (https://gitlab.com/dtorel/asr) - Atomic Simulation Recipes, based on ASE (Python). !Gitlab Stars (https://img.shields.io/gitlab/stars/dtorel%2Fasr) (https://gitlab.com/dtorel/asr)
- atomate (https://hackingmaterials.github.io/atomate) - Materials science workflows based on FireWorks, developed at LBNL (Python). !Github Stars (https://img.shields.io/github/stars/hackingmaterials/atomate?style=social) 
(https://github.com/hackingmaterials/atomate)
- aviary (https://github.com/CompRhys/aviary) - Predict materials properties using compositions and Wyckoff representations (Python). !Github Stars (https://img.shields.io/github/stars/CompRhys/aviary?style=social) 
(https://github.com/CompRhys/aviary)
- BIOVIA Materials Studio (https://www.3ds.com/products-services/biovia/products/molecular-modeling-simulation/biovia-materials-studio/) - _Proprietary_ simulation infrastructure.
- CAMD (https://github.com/tri-amdd/camd) - Agent-based sequential learning software for materials discovery (Python). !Github Stars (https://img.shields.io/github/stars/tri-amdd/camd?style=social) (https://github.com//tri-amdd/camd)
- cclib (https://cclib.github.io) - Parse and interpret the results of computational chemistry packages (Python). !Github Stars (https://img.shields.io/github/stars/cclib/cclib?style=social) (https://github.com/cclib/cclib)
- cctbx (https://cctbx.github.io) - Computational Crystallography Toolbox (C++). !Github Stars (https://img.shields.io/github/stars/cctbx/cctbx_project?style=social) (https://github.com/cctbx/cctbx_project)
- CDVAE (https://github.com/txie-93/cdvae) - Python Crystal Diffusion Variational AutoEncoder (CDVAE) generates novel stable materials via inverse design. !Github Stars (https://img.shields.io/github/stars/txie-93/cdvae?style=social) 
(https://github.com/txie-93/cdvae)
- CrabNet (https://github.com/anthony-wang/CrabNet) - Predict materials properties using only the composition information. (Python). !GitHub Repo stars (https://img.shields.io/github/stars/anthony-wang/CrabNet?style=social)
- Crystal Toolkit (https://docs.crystaltoolkit.org) - A framework for building web apps for materials science powering the new Materials Project website. !Github Stars 
(https://img.shields.io/github/stars/materialsproject/crystaltoolkit?style=social) (https://github.com/materialsproject/crystaltoolkit)
- Custodian (https://github.com/materialsproject/custodian) - Simple, robust and flexible just-in-time (JIT) job management framework (Python).  !Github Stars (https://img.shields.io/github/stars/materialsproject/custodian?style=social) 
(https://github.com/materialsproject/custodian)
- datamol (https://github.com/datamol-org/datamol) - Molecular Manipulation Made Easy. A light wrapper built on top of RDKit (Python). !Github Stars (https://img.shields.io/github/stars/datamol-org/datamol?style=social) 
(https://github.com/datamol-org/datamol)
- ElMD (https://github.com/lrcfmd/ElMD) - Quantify the chemical similarity between two compositions using the Element Movers Distance. !Github Stars (https://img.shields.io/github/stars/lrcfmd/ElMD?style=social) (https://github.com/lrcfmd/ElMD/)
- FireWorks (https://materialsproject.github.io/fireworks) - Workflow engine developed at LBNL (Python). !Github Stars (https://img.shields.io/github/stars/materialsproject/fireworks?style=social) (https://github.com/materialsproject/fireworks)
- Granta MI (https://www.grantadesign.com/products/mi) - _Proprietary_ enterprise infrastructure for the materials data.
- Grobid superconductors (https://github.com/lfoppiano/grobid-superconductors) - Open source Grobid (https://github.com/kermitt2/grobid) module for extracting superconductor material and related properties
- httk (https://httk.openmaterialsdb.se) - High-throughput toolkit (Python). !Github Stars (https://img.shields.io/github/stars/rartino/httk?style=social) (https://github.com/rartino/httk)
- ICMD (https://www.questek.com/software) - A digital materials design platform in the cloud from QuesTek Innovations LLC (_proprietary_).
- ioChem-BD (https://www.iochem-bd.org) - Solution to manage computational chemistry Big Data (Java).
- MAST-ML (https://github.com/uw-cmg/MAST-ML) - An open-source Python package designed to broaden and accelerate the use of machine learning in materials science research (Python). !Github Stars 
(https://img.shields.io/github/stars/uw-cmg/MAST-ML?style=social) (https://github.com/uw-cmg/MAST-ML)
- matador (https://github.com/ml-evs/matador) - A library for aggregation and analysis of high-throughput DFT (Python). !Github Stars (https://img.shields.io/github/stars/ml-evs/matador?style=social) (https://github.com/ml-evs/matador)
- matbench (https://github.com/materialsproject/matbench) - Matbench: Benchmarks for materials science property prediction (Python). !Github Stars (https://img.shields.io/github/stars/materialsproject/matbench?style=social) 
(https://github.com/materialsproject/matbench)
- matbench-genmetrics (https://github.com/sparks-baird/matbench-genmetrics) - Generative materials benchmarking metrics, inspired by guacamol (https://www.benevolent.com/guacamol) and CDVAE (https://github.com/txie-93/cdvae) (Python). !Github 
Stars (https://img.shields.io/github/stars/sparks-baird/matbench-genmetrics?style=social) (https://github.com/sparks-baird/matbench-genmetrics)
- matminer (https://github.com/hackingmaterials/matminer) - A library for data mining in materials science (Python). !Github Stars (https://img.shields.io/github/stars/hackingmaterials/matminer?style=social) 
(https://github.com/hackingmaterials/matminer)
- MatSciBERT (https://huggingface.co/m3rg-iitd/matscibert) - A Materials Domain Language Model for Text Mining and Information Extraction (Python).!GitHub Repo stars (https://img.shields.io/github/stars/M3RG-IITD/MatSciBERT?style=social)
- mat_discover (https://sparks-baird.github.io/mat_discover/) - Find high-performance candidates in chemical spaces, composition-only (Python). !GitHub Repo stars (https://img.shields.io/github/stars/sparks-baird/mat_discover?style=social)
- MDCS (https://github.com/usnistgov/MDCS) - Materials Data Curation System (Python). !Github Stars (https://img.shields.io/github/stars/usnistgov/MDCS?style=social) (https://github.com/usnistgov/MDCS)
- MedeA (https://www.materialsdesign.com/medea-software) - _Proprietary_ computational Tcl environment by Materials Design, Inc.
- MODNet (https://github.com/ppdebreuck/modnet) - Select optimal descriptions and build models for predicting materials properties (Python). !Github Stars (https://img.shields.io/github/stars/ppdebreuck/modnet?style=social) 
(https://github.com/ppdebreuck/modnet)
- mp-time-split (https://github.com/sparks-baird/mp-time-split) - Use time-based cross-validation splits from Materials Project for generative modeling benchmarking (Python). !Github Stars 
(https://img.shields.io/github/stars/sparks-baird/mp-time-split?style=social) (https://github.com/sparks-baird/mp-time-split)
- NOMAD Oasis (https://nomad-lab.eu/nomad-lab/nomad-oasis.html) - A web-based software to manage and share materials data (Python/javascript). !Github Stars (https://img.shields.io/github/stars/nomad-coe/nomad?style=social) 
(https://github.com/nomad-coe/nomad)
- OACIS (https://crest-cassia.github.io/oacis/en/) - Job management software for simulation studies using a Ruby on Rails webserver. !Github Stars (https://img.shields.io/github/stars/crest-cassia/oacis?style=social) 
(https://github.com/crest-cassia/oacis)
- optimade-python-tools (https://github.com/Materials-Consortia/optimade-python-tools) - Tools for OPTIMADE APIs (https://www.optimade.org) in Python. !Github Stars 
(https://img.shields.io/github/stars/Materials-Consortia/optimade-python-tools?style=social) (https://github.com/Materials-Consortia/optimade-python-tools)
- piro (https://github.com/TRI-AMDD/piro) - Software for evaluating pareto-optimal synthesis pathways (Python). !Github Stars (https://img.shields.io/github/stars/TRI-AMDD/piro?style=social) (https://github.com/TRI-AMDD/piro)
- pyiron (https://github.com/pyiron) - Integrated development environment (IDE) for computational materials science (Python). !Github Stars (https://img.shields.io/github/stars/pyiron/pyiron?style=social) (https://github.com/pyiron/pyiron)
- pymatflow (https://github.com/DeqiTang/pymatflow) - Toolbox for (high-throughput) DFT modeling of materials (Python). !Github Stars (https://img.shields.io/github/stars/deqitang/pymatflow?style=social) (https://github.com/deqitang/pymatflow)
- Pymatgen (https://pymatgen.org) - A robust, open-source Python library for materials analysis. !Github Stars (https://img.shields.io/github/stars/materialsproject/pymatgen?style=social) (https://github.com/materialsproject/pymatgen)
- Pymatviz (https://github.com/janosh/pymatviz) - A toolkit for visualizations in materials informatics. !Github Stars (https://img.shields.io/github/stars/janosh/pymatviz?style=social) (https://github.com/janosh/pymatviz)
- pymks (https://pymks.org) - Materials Knowledge System (Python). !Github Stars (https://img.shields.io/github/stars/materialsinnovation/pymks?style=social) (https://github.com/materialsinnovation/pymks)
- QMForge (https://sourceforge.net/projects/qmforge/) - Python framework and GUI for analyzing results of quantum chemistry codes.
- QMflows (https://github.com/SCM-NV/qmflows) - Python library for input generation and task handling in computational chemistry. !Github Stars (https://img.shields.io/github/stars/SCM-NV/qmflows?style=social) (https://github.com/SCM-NV/qmflows)
- qmpy (https://pythonhosted.org/qmpy) - Python backend creating and running the Open Quantum Materials Database. !Github Stars (https://img.shields.io/github/stars/wolverton-research-group/qmpy?style=social) 
(https://github.com/wolverton-research-group/qmpy)
- quacc (https://github.com/arosen93/quacc) - Python platform for high-throughput, database-driven computational materials science and quantum chemistry !Github Stars (https://img.shields.io/github/stars/arosen93/quacc?style=social) 
(https://github.com/arosen93/quacc)
- RDKit (https://github.com/rdkit/rdkit) - A collection of cheminformatics and machine-learning software written in C++ and Python. !Github Stars (https://img.shields.io/github/stars/rdkit/rdkit?style=social) (https://github.com/rdkit/rdkit)
- SEAMM (https://molssi-seamm.github.io/) - Simulation Environment for Atomistic and Molecular Modeling (Python). !Github Stars (https://img.shields.io/github/stars/molssi-seamm/seamm?style=social) (https://github.com/molssi-seamm/seamm)
- SuperCon2 (https://github.com/lfoppiano/supercon2) - A user interface for curating Superconductors materials and properties extracted by grobid-superconductors (https://github.com/lfoppiano/grobid-superconductors)
- SLAMD (https://github.com/BAMresearch/WEBSLAMD) - An open source web app for data driven acceleration of cement and concrete development through digital lab twin and AI optimization (Python/javascript). !Github Stars 
(https://img.shields.io/github/stars/BAMresearch/WEBSLAMD?style=social) (https://github.com/BAMresearch/WEBSLAMD)
- tilde (https://github.com/tilde-lab/tilde) - Python framework for ab initio data repositories. !Github Stars (https://img.shields.io/github/stars/tilde-lab/tilde?style=social) (https://github.com/tilde-lab/tilde)
- XenonPy (https://github.com/yoshida-lab/XenonPy) - A Python library that implements a comprehensive set of machine learning tools for materials informatics. !Github Stars (https://img.shields.io/github/stars/yoshida-lab/XenonPy?style=social) 
(https://github.com/yoshida-lab/XenonPy)
- xtal2png (https://github.com/sparks-baird/xtal2png) - Python package for invertibly representing crystal structures as PNG images for screening state-of-the-art image-processing generative models. !Github Stars 
(https://img.shields.io/github/stars/sparks-baird/xtal2png?style=social) (https://github.com/sparks-baird/xtal2png)


Cloud simulation platforms and AI startups

- Absolidix (https://absolidix.com) - An early preview of the on-demand cloud simulations of materials from MPDS (PAULING FILE) with AiiDA framework.
- AiiDAlab (https://www.materialscloud.org/aiidalab) - Web platform & GUI for AiiDA in the Cloud (_cf._ AiiDA framework).
- Ångström AI (https://www.angstrom-ai.com) - Accelerating molecular simulation using generative AI (California, USA).
- Atomic Tessellator (https://atomictessellator.com) - Computational chemistry cloud and AI lab from New Zealand.
- Azure Quantum Elements (https://quantum.microsoft.com) - Microsoft's Quantum Computing including generative chemistry and accelerated DFT.
- Compular (https://compulartech.com) - New materials development cloud from Sweden.
- CuspAI (https://www.cusp.ai) - Combat Climate Change with AI-Designed Materials (Cambridge, UK).
- Dunia Innovations (https://dunia.ai) - A Berlin-based materials discovery startup (Germany).
- Entalpic (https://entalpic.ai) - AI-driven company for discovering new chemical processes and materials (France).
- LMDS (https://lmds.liverpool.ac.uk) - The Liverpool materials discovery server hosts computational tools to help experimental chemists search for new materials.  
- Mat3ra (https://www.mat3ra.com) - Materials Modeling 2.0 (cloud engine from Silicon Valley). !GitHub followers (https://img.shields.io/github/followers/Exabyte-io?style=social) (https://github.com/Exabyte-io)
- MatCloud (http://matcloud.cnic.cn) - Cloud-based computational infrastructure of the Chinese Materials Genome Project (China).
- Materials Square (https://www.materialssquare.com) - Ab initio and CALPHAD simulations cloud (South Korea).
- Matlantis (https://matlantis.com) - Accelerated materials discovery platform (Japan). !GitHub followers (https://img.shields.io/github/followers/matlantis-pfcc?style=social) (https://github.com/matlantis-pfcc)
- Orbital Materials (https://orbitalmaterials.com) - Advanced materials, made with AI (UK).
- Periodic Labs (https://periodiclabs.ai) - A new materials AI startup from OpenAI and Google DeepMind (USA and UK).
- Radical AI (https://www.radical-ai.com) - Accelerating materials R&D (New York, USA).
- Quantistry Lab (https://quantistry.com/en/product) - Cloud-based simulations of syntheses, designing novel materials, computational chemistry (Germany).
- SIT Rolos (https://rolos.com) - Research platform for materials from Schaffhausen Institute of Technology (Switzerland).


Machine-readable materials datasets

- AFLOW (http://www.aflowlib.org) - Flow for Materials Discovery repository (_cf._ AFLOW framework).
- ATB (https://atb.uq.edu.au) - Automated Topology Builder and Repository.
- AtomWork (https://crystdb.nims.go.jp/en) and AtomWork-Adv (https://atomwork-adv.nims.go.jp) - Data platform of NIMS, Japan (based on the PAULING FILE experimental database).
- Baikov Institute of Metallurgy and Materials Science (https://imet-db.ru) - Databases of Russian Academy of Sciences.
- Carolina Materials Database (http://www.carolinamatdb.org) - an ML-DFT database of the University of South Carolina.
- CascadesDB (https://cascadesdb.org) - Molecular dynamics simulations of collision cascades, by the International Atomic Energy Agency.
- Catalysis Hub (https://www.catalysis-hub.org) - Web-platform for sharing data and software for computational catalysis research.
- cccbdb (http://cccbdb.nist.gov) - Computational Chemistry Comparison and Benchmark Database.
- CCDC (https://www.ccdc.cam.ac.uk) - Cambridge Crystallographic Data Centre (partly _proprietary_).
- Citrination (https://citrination.com) - AI-Powered Materials Data Platform (partly _proprietary_).
- CMR (https://wiki.fysik.dtu.dk/cmr) - Computational Materials Repository (_cf._ ASE framework).
- COD (https://www.crystallography.net) - Crystallography Open Database (including theoretical database).
- ESP (http://gurka.fysik.uu.se/ESP) - Electronic Structure Project.
- HybriD3 Materials Database (https://materials.hybrid3.duke.edu/) - A comprehensive collection of experimental and computational materials data for crystalline organic-inorganic compounds.
- ICSD (https://icsd.products.fiz-karlsruhe.de) - Inorganic Crystal Structure Database (partly _proprietary_).
- JARVIS (https://jarvis.nist.gov) - Joint Automated Repository for Various Integrated Simulations (NIST).
- Khazana (https://khazana.gatech.edu) - Repository for data created in atomistic simulations, features also the polymer genome.
- Materials Cloud (https://www.materialscloud.org) - A Platform for Open Materials Science (_cf._ AiiDA framework).
- Materials Genome Engineering Databases of China (https://www.mgedata.cn) - National integration platform (_cf._ MatCloud).
- MaterialsMine (https://materialsmine.org) - An open-source repository for nanocomposite data (NanoMine) and mechanical metamaterials data (MetaMine). 
- Materials Project (https://www.materialsproject.org) - Computed information on known and predicted materials (_cf._ Pymatgen framework).
- MDF (https://materialsdatafacility.org) - Materials Data Facility, a set of data services built specifically to support materials science researchers.
- MolSSI (https://qcarchive.molssi.org) - The MolSSI Quantum Chemistry Archive.
- MPDS (https://mpds.io) - Materials Platform for Data Science (based on the PAULING FILE experimental database, partly _proprietary_).
- MPOD (http://mpod.cimav.edu.mx) - Material Properties Open Database.
- MSE (http://mse.fhi-berlin.mpg.de) - Test Set for Materials Science and Engineering.
- nanoHUB (https://nanohub.org/developer) - Place for computational nanotechnology research, education, and collaboration.
- NOMAD (https://nomad-lab.eu) - Novel Materials Discovery, Repository, and Laboratory (_cf._ NOMAD Oasis).
- NREL MatDB (http://materials.nrel.gov) - Computational database of thermochemical and electronic properties of materials for renewable energy applications
- Organic Materials Database (https://omdb.mathub.io) - Electronic structure database for 3-dimensional organic crystals (Nordita).
- Open Materials Database (http://openmaterialsdb.se) - Materials-genome-type repository from ab-inito calculations (_cf._ httk framework).
- OpenKIM (https://openkim.org) - Repository of interatomic potential implementations and computational protocols for testing them.
- OQMD (http://oqmd.org) - Open Quantum Materials Database (_cf._ qmpy framework).
- Phonon database at Kyoto university (http://phonondb.mtl.kyoto-u.ac.jp) - Computational phonon band structures, density of states and thermal properties.
- Pitt Quantum Repository (https://pqr.pitt.edu) - Molecular properties predicted from quantum mechanics.
- ROD (https://solsa.crystallography.net/rod/) - Raman Open Database.
- SuperMat (https://github.com/lfoppiano/SuperMat) - A dataset of superconductors materials
- Topological Materials Database (https://www.topologicalquantumchemistry.org) - A Complete Catalogue of High-Quality Topological Materials.


Standardization initiatives

- Blue Obelisk (https://blueobelisk.github.io) - Movement for open data, open source and open standards in chemistry and materials science (by Murray-Rust).
- CIF (https://www.iucr.org/resources/cif) - Crystallographic Information File, a standard for crystallographic information (by IUCr, International Union of Crystallography).
- CML (http://www.xml-cml.org) - Chemical Markup Language: molecules, compounds, reactions, spectra, crystals _etc._ (by Murray-Rust).
- ColabFit (https://colabfit.org) - Collaborative infrastructure for the development and distribution of state-of-the-art data-driven interatomic potentials (DDIPs).
- EMMO (https://github.com/emmo-repo/EMMO) - European Materials Modelling Ontology.
- ESCDF (https://gitlab.com/ElectronicStructureLibrary/escdf/escdf-specifications) - Electronic Structure Common Data Format.
- ESSE (https://github.com/Exabyte-io/esse) - Exabyte Source of Schemas and Examples designed for digital materials science.
- GEMD (https://citrineinformatics.github.io/gemd-docs/) - Graphical Expression of Materials Data (by Citrine), supersedes _PIF_.
- JCAMP-DX (http://www.jcamp-dx.org) - Electronic data standards for chemical and spectroscopy information (by IUPAC).
- KIM API (https://openkim.org/kim-api/) - API standard for connecting molecular simulation codes with interatomic models.
- NOMAD Meta Info (https://nomad-lab.eu/services/metainfo) - Schema for storing results of ab initio and force-field atomistic simulations (by NOMAD Laboratory).
- OPTIMADE (https://www.optimade.org) - Open Databases Integration for Materials Design, a REST API standard for exchanging materials information.
- PIF (https://citrineinformatics.github.io/pif-documentation/index.html) - Physical Information File schema (by Citrine), superseded by _GEMD_.
- Semantic Assets for Materials Science (https://doi.org/10.5281/zenodo.2456346) - Task group within the vocabulary services interest group (https://rd-alliance.org/groups/vocabulary-services-interest-group.html) of the Research Data Alliance.
- Open Force Field Toolkit (https://open-forcefield-toolkit.readthedocs.io) - Specification for encoding molecular mechanics force fields (by Open Force Field Initiative (http://openforcefield.org)).


Similar compilations

- atomistic.software (https://atomistic.software) - a collection of major atomistic simulation engines with citation info
- Best of Atomistic Machine Learning (https://github.com/JuDFTteam/best-of-atomistic-machine-learning) - curated list with 510+ atomistic projects
- Data‐Driven Materials Science: Status, Challenges, and Perspectives (https://doi.org/10.1002/advs.201900808)
- Experimental chemistry and materials science data (https://github.com/neo-chem/awesome-chemical-data)
- European Materials Modelling Council Taxondas (https://emmc.info/taxonda)
- Information Resources on Inorganic Chemistry (http://en.iric.imet-db.ru) - a collection from Baikov Institute of Metallurgy and Materials Science, Russia.
- Materials-Related Databases (https://github.com/blaiszik/Materials-Databases)


License
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materialsinformatics Github: https://github.com/tilde-lab/awesome-materials-informatics