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A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.
| Date | Stars |
|---|---|
| 2026-07-31 | 450 |
| 2026-08-05 | 452 |
| 2026-08-06 | 452 |
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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,
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matched fp:a73f35a63c4faad7, llm:Repository description and README: 'A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.' Topics: material-design, material-properties, materials-data, materials-databases, materials-datasets, materials-informatics, materials-science.
matched fp:a73f35a63c4faad7, llm:Repository description and README: 'A list of databases, datasets and books/handbooks where you can find materials properties for machine learning applications.' Topics: material-design, material-properties, materials-data, materials-databases, materials-datasets, materials-informatics, materials-science.