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data-resources-for-materials-science

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A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.

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## The Collection of Database and Dataset Resources in Materials Science
This collection includes the list of online and offline resources of physical, chemical, mechanical and all other properties of materials.

Helping the students or enthusiasts who seek necessary data to practice machine learning techniques is the main motivation of this collection. It is also expected to assist the researchers in the material informatics field.

In the first three sections below, you can find the list of databases and dataset-sharing platforms accessible publicly and the information of the books/handbooks including materials data.

Additionally, in the last section, there are couple of toy datasets shared by researchers for educational purposes of machine learning techniques in materials science.

### Databases in Materials Science

| Database Name | Description |
| ------------- | ----------- |
| [NIST Materials Genome Initiative (MGI)](https://www.nist.gov/mgi) | Several databases for different material classes |
| [NIST Materials Data Curation System (Part of MGI)](https://phasedata.nist.gov/) | Phase transformation temperatures (e.g. melting, solidus, solvus), lattice parameters, thermal expansion, elastic constants, and diffusion coefficients and compositions profiles |
| [NIST Materials Data Repository (Part of MGI)](https://materialsdata.nist.gov/) | Data of different materials shared by researchers |
| [MDR NIMS Materials Data Repository](https://mdr.nims.go.jp/) | Datasets, publications, collections related to all material classes |
| [The NIMS Materials Database (MatNavi)](https://mits.nims.go.jp/en/) | Polymers, inorganic material, metallic material and computational electronic structure |
| [The Novel Materials Discovery (NOMAD) Laboratory](https://nomad-lab.eu/index.php?page=repo-arch) | Input and output files from more than 100 million high-quality calculations. It also includes [notebooks](https://nomad-lab.eu/aitoolkit) for several materials informatics problems with experinece levels from beginner to advanced. |
| [The Materials Data Facility (MDF)](https://materialsdatafacility.org/) | Published data of different materials shared by researchers |
| [The Joint Automated Repository for Various Integrated Simulations (JARVIS)](https://jarvis.nist.gov/) | Materials data for classical force-field, density functional theory and machine learning calculations |
| [Materials Project](https://materialsproject.org/) | Inorganic compounds, nanoporous materials, elastic tensors, piezoelectric tensors, electrode materials |
| [Pauling File](https://paulingfile.com/) and [MPDS](https://mpds.io) | Linked phase diagrams + crystal structures + physical properties of all experimentally known inorganic compounds |
| [NIST Alloy Data](https://trc.nist.gov/metals_data/) | Thermophysical property data with a focus on unary, binary, and ternary metal systems |
| [NIST Structural Ceramics Database (SCD) Database](https://srdata.nist.gov/CeramicDataPortal/scd) | Published data of structural ceramics |
| [Polymer Property Predictor and Database](https://pppdb.uchicago.edu/) | Flory-Huggins Chi (χ) Database, Glass Transition Temperature Database |
| [NIST Standard Reference Data (SRD)](https://www.nist.gov/srd/srd-catalog) | Catalog of several databases |
| [NIST Self-Diffusion Data](https://www.ctcms.nist.gov/~gkl/selfdiffusion.html) | Self and impurity diffusion coefficients; reference collection of pre-exponential factors and activation energies for Arrhenius type of equations |
| [Open Quantum Materials Database (OQMD)](http://oqmd.org/) | Database of DFT calculated thermodynamic and structural properties of 815,654 materials |
| [Automatic Flow for Materials Discovery (AFLOW)](http://www.aflowlib.org/) | Database of 3,466,057 material compounds with over 679,347,172 calculated properties |
| [NRELMatDB](https://materials.nrel.gov/) | DFT (GGA+U) relaxed crystal structures, thermochemical properties, i.e., enthalpies of formation of compounds, the stability ranges in terms of chemical potentials, and enthalpies of decomposition reactions quasiparticle energy calculations in the GW electronic structures |
| [High Throughput Experimental Materials Database (HTEM DB)](https://htem.nrel.gov/) | Composition (37093), structure (47213), optical (26577), and electrical (12849) properties of thin films synthesized using combinatorial methods |
| [Matmatch](https://matmatch.com/) | Data of over 31000 materials |
| [MatWeb](http://www.matweb.com/) | Data of material properties including metals, ceramics, polymer and other engineering materials |
| [Materials Cloud](https://www.materialscloud.org/) | Data of several materials |
| [Knowledgebase of Interatomic Models (OpenKIM)](https://openkim.org/) | Interatomic potential repository and an online framework for making molecular simulations |
| [Materials Commons](https://materialscommons.org/) | Published data of several materials |
| [Crystallography Open Database (COD)](http://www.crystallography.net/cod/) | Open-access collection of crystal structures of organic, inorganic, metal-organics compounds and minerals, excluding biopolymers |
| [Organic Materials Database (OMDB)](https://omdb.mathub.io/) | Open-access electronic structure database for 3-dimensional organic crystals |
| [Open Reaction Database (ORD)](https://open-reaction-database.org) | Infrastructure for structuring and sharing organic reaction data from benchtop reactions to automated high-throughput experiments and flow chemistry.|
| [Polymer Genome](https://www.polymergenome.org/) | Data of polymer building blocks and platform for property prediction of polymeric materials |
| [DoITPoMS Micrograph Library](https://www.doitpoms.ac.uk/miclib/index.php) | Data of several materials' micrographs |
| [Python for Glass Genomics (PyGGi)](https://pyggi.iitd.ac.in/) | Database of glass properties and platform for property prediction and optimization of glass materials |
| [The Engineering Toolbox](https://www.engineeringtoolbox.com/material-properties-t_24.html) | Data of material properties for gases, fluids and solids - densities, specific heats, viscosities and more |
| [nanoHUB](https://nanohub.org/publications/datasets) | Published databases of several materials |
| [NanoMine](https://github.com/Duke-MatSci/nanomine) | NanoMine Nanocomposites Data Resource |
| [Topological Quantum Chemistry](https://www.topologicalquantumchemistry.com/#/) | Topological Materials Database |
| [SciGlass](https://github.com/epam/SciGlass) | Glass property database with more than 420 thousand glass compositions |
| [ORNL_AISD-Ex](https://www.osti.gov/biblio/1907919) | Quantum chemical prediction of UV/Vis absorption spectra for over 10 million organic molecules |
| [The Perovskite Database Project](https://www.perovskitedatabase.com/) |Data collected from 16000 perovskite papers published until the end of February 2020 |
| [Polymer Scholar](https://polymerscholar.org/) |Search engine for polymer properties, powered by a large language model querying the journal abstracts |
| [Computational Materials Repository (CMR)](https://cmr.fysik.dtu.dk/index.html) |Several databases and tutorials based on DFT-calculated material properties|
| [Fatigue Database of AM Alloys2022](https://figshare.com/articles/dataset/Fatigue_Database_of_Additively_Manufactured_Alloys/22337629) | Database of fatigue properties of additively manufactured alloys obtained by natural language model from the literature |
| [DigiMOF](https://figshare.com/collections/DigiMOF_A_Database_of_Metal_Organic_Framework_Synthesis_Information_Generated_via_Text_Mining/6652495) | Database of Metal–Organic Framework Synthesis Information Generated via Text Mining |
| [OpenDAC](https://open-dac.github.io/) |40M DFT calculations from 170K DFT relaxations involving Metal Organic Frameworks (MOFs) with carbon dioxide and water adsorbates|
| [Catalysis-Hub.org](https://www.catalysis-hub.org/) |Database of DFT-calculated surface reaction energies and barriers of catalysts with interactive activity maps, Pourbaix Diagrams and other apps|
| [Springer Materials](https://materials.springer.com/) |Database of multiple material classes, property types, and applications, data visualization|
| [BEAST DB](https://beastdb.nrel.gov/) |>24k of electrocatalysis calculations and visualizations of properties that help rationalize observed behavior and design more effective catalysts|
| [COD_HEM](https://codhem.cecas.clemson.edu/login) |Consolidated Database of High Entropy Materials (Paper and explanations are [here](https://www.sciencedirect.com/science/article/abs/pii/S0927025624008097))|
| [Alexandria Databases](https://alexandria.icams.rub.de) |Geometries relaxed by DFT with PBE and PBEsol functionals and their trajectories.|
| [Stress-Strain Properties Database](https://github.com/gh-PankajKumar/chemdataextractorv2.3-stresseng) |A Database of Stress-Strain Properties Auto-generated from the Scientific Literature using ChemDataExtractor.|
| [ICEM Database](https://www.innomat.se/icem) |A thermodynamic database for hardmetals, describing the Co-Ti-W-C-N alloy system.|

### Datasets in Materials Science

| Resource Name | Description |
| ------------- | ----------- |
| [Figshare](https://figshare.com/) | Scientific research repository |
| [Zenodo](https://zenodo.org/) | Scientific research repository |
| [NIST Materials Resource Registry](https://materials.registry.nist.gov/explore/keyword/) | Datasets of several materials |
| [Mendeley Data](https://data.mendeley.com/) | Scientific research repository |
| [Materials Cloud](https://www.materialscloud.org/) | Curated research data sets |
| [Materials Commons](https://materialscommons.org/) | Datasets of several materials |
| [OPoly26](https://huggingface.co/facebook/OMol25#open-polymers-2026-opoly26-dataset) | >6.35M DFT calculations on up to 360 atom clusters derived from polymeric systems|
| [OMol25 (The Open Molecules 2025)](https://huggingface.co/facebook/OMol25) | >101M DFT calculations of biomolecules, metal complexes, electrolytes, and community datasets, generated at the ω B97M-V/def2-TZVPD level of theory |
| [OC25 (The Open Catalyst 2025)](https://huggingface.co/facebook/OC25) | Dataset and Models for Solid-Liquid Interfaces |
| [OMat24](https://fair-chem.github.io/inorganic_materials/datasets/omat24.html) |Total energy, force and stress calculations of non-relaxed structures and their trajectories.|
| [OCx24](https://fair-chem.github.io/catalysts/datasets/ocx24.html) |X-ray fluorescence (XRF), X-ray diffraction (XRD), and electrochemical testing results of catalyst materials.|
| [ODAC23](https://fair-chem.github.io/dac/datasets/odac.html) |single-point DFT calculations on >8,000 MOFs, including a total of >176,000 adsorption energies with COsub>2</sub> and/or Hsub>2</sub>O|
| [AQCat25](https://huggingface.co/datasets/SandboxAQ/aqcat25-dataset) |13.5M DFT calculation trajectories, encompassing approximately 5K materials and 47K intermediate-catalyst systems (including critical spin-polarized systems).|
| [QCML](https://zenodo.org/records/14859804) |Quantum chemistry reference data from 33.5M DFT and 14.7B semi-empirical calculations|
| [QM9Star](https://doi.org/10.6084/m9.figshare.27002905) |2M DFT-computed Equilibrium Structures for Ions and Radicals with Atomic Information|
| [Work function and cleavage energy dataset](https://zenodo.org/records/10703249) | Work function and cleavage energy calculation results of 58,332 surface configurations by DFT|
| [MatPES](https://matpes.ai/) | A Foundational Potential Energy Surface Dataset for Materials|
| [MAD-1.5](https://archive.materialscloud.org/records/18tke-tt476) | Highly curated dataset designed explicitly for training broadly applicable atomistic models across the periodic table at high levels of theory|
| [MSR-ACC/TAE25](https://zenodo.org/records/17629321) | 73k accurate total atomization energies (TAE) of small molecules with up to 5 non-hydrogen elements up to argon, excluding only rare-gas atoms.|
| [MatSyn25](https://huggingface.co/datasets/MatSynAI/MatSyn25) | Large-scale dataset of 2D material synthesis processes extracted from 85,160 research papers. The dataset contains 163,240 synthesis records covering graphene, MXenes, transition metal dichalcogenides, layered double hydroxides, and related materials |
| [AM26](https://github.com/vldgroup/AM26) | Benchmark dataset of amorphous materials comprising 5 amorphous systems, together with reference density-functional theory (DFT) energies and forces |
| [MOFs_CO2N2O2_ML](https://github.com/hasancangulbalkan/MOFs_CO2N2O2_ML) | ~3.9M data points for all synthesized and hypothetical MOFs’ structural, chemical, and energetic features (1.9M), their gas adsorption properties (1.2M), and adsorption-based selectivities (0.8M) computed atdifferent conditions|
| [sysTEm](https://github.com/tankylz/sysTEm_dataset) | A materials dataset for elastomeric foam impact mitigating materials |
| [Ductile Cast Iron Project](https://www.ductilecastironproject.com/) | Dataset of fatigue, mechanical, corrosion and thermal properties and microstructures of ductile cast iron from over 40 scientific papers |
| [nanoHUB](https://nanohub.org/publications/datasets) | Published datasets of several materials |
| [CHiMAD NIST (TDDFT)](https://acdc.alcf.anl.gov/mdf/detail/kononov_firstprinciples_simulation_graphene_v1.1/) | TDDFT simulations of light-ion irradiated graphene performed with Qbox/Qb@ll |
| [Mechanical-MNIST](https://github.com/elejeune11/Mechanical-MNIST) | Mechanical-MNIST is a benchmark dataset for mechanical meta-models |
| [Elastomeric Foam Materials](https://acdc.alcf.anl.gov/mdf/detail/foam_db_v1.1/) | A materials dataset for elastomeric foam impact mitigating materials |
| [Polyinfo](https://polymer.nims.go.jp/) |Polymer Database "PoLyInfo" systematically provides various data required for polymeric material design.|
| [GNoME](https://github.com/google-deepmind/materials_discovery?tab=readme-ov-file#dataset) |Compositions and total energies calculated by DFT with the r²SCAN functional from Google DeepMind.|
| [MP_ALOE](https://figshare.com/articles/dataset/MP-ALOE_An_r2SCAN_dataset_for_universal_machine_learning_interatomic_potentials/29452190) | An r2SCAN dataset for universal machine learning interatomic potentials |
| [Peregrine](https://doi.ccs.ornl.gov/dataset/96b7da99-07e1-562d-88d5-d7e079acfef7) | In-situ monitoring and training dataset for laser powder bed fusion and binder jet printers |
| [BOS-TMC Dataset](https://zenodo.org/records/19410245) | Structures and properties for the BOS-TMC dataset of 159k transition metal complexes in multiple charge and spin states. |

### Books/Handbooks for Materials Data

+ **Materials Handbook (Handbook)** 15th Edition by George S. Brady (Author), Henry R. Clauser (Author), John A. Vaccari (Author)
+ **Smithells Metals Reference Book** 8th Edition by William F. Gale (Editor), Terry C. Totemeier (Editor)
+ **Materials Science and Engineering Handbook** 3rd Edition by James F. Shackelford (Editor), W. Alexander (Editor)
+ **MMPDS Handbook**
+ **Handbook of Materials Structures, Properties, Processing and Performance** by Lawrence E. Murr (Author)
+ **ASM Handbook Set (38 Volumes)**
+ **CASTI Metals Handbook Nonferrous Metals** 4th Edition by John E. Bringas (Author)
+ **Materials Handbook A Concise Desktop Reference** 2nd Edition by François Cardarelli

### Toy Datasets for Machine Learning Applications in Materials Science
 - [Machine Learning Materials Datasets](https://figshare.com/articles/dataset/MAST-ML_Education_Datasets/7017254)
 - [JARVIS Materials Design – Tools, Notebooks](https://github.com/JARVIS-Materials-Design/jarvis-tools-notebooks)
 - [Machine Learning Lab Module](https://nanohub.org/tools/intromllab)
 - [REMI: REsource for Materials Informatics](https://pages.nist.gov/remi/)

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