OPTIMADE Data Providers

Open-access collection of crystal structures of organic, inorganic, metal-organic compounds and minerals, excluding biopolymers

Description of provider: Automatic FLOW (AFLOW) database for computational materials science. Description of dataset: The AFLOW OPTIMADE endpoint

Description of provider: A collection of databases from the group of Prof Miguel A. L. Marques at Ruhr University Bochum. Description of dataset: A dataset of 2.5m+ stable and metastable materials calculated with the PBE functional

Description of provider: A collection of databases from the group of Prof Miguel A. L. Marques at Ruhr University Bochum. Description of dataset: A new dataset of 415k stable and metastable materials calculated with the PBEsol and SCAN functionals

CMR is a collection of materials repositories from different projects such as C2DB, QPOD and many more

Description of provider: The Material Properties Open Database (MPOD) is a web-based, open access repository of quantitative information about the physical properties of crystalline materials. MPOD is oriented to design engineers, scientists, science teachers and students. Properties are generally treated as tensor magnitudes. In MPOD the compact matrix notation is applied. To bring an intuitive view of tensor properties, so-called longitudinal properties surfaces are displayed. 3D printing of properties surfaces is implemented via creation of stl files. A dictionary of properties definitions is included. Eventually, comments are added. Syntax and notation in MPOD files is oriented towards matching IUCr standards and so tries to comply with CIF format. Description of dataset: MPOD is a web-based, open access repository of quantitative information about the physical properties of crystalline materials.

Material-Property-Descriptor Database (MPDD) of atomic structures. Optimized for the high-throughput deployment of material featurizers and ML models. Maintained by Phases Research Lab (phaseslab.org) at The Pennsylvania State University

Description of provider: Databases contributed by the community to the Materials Cloud Archive. Description of dataset: V. Trinquet et al., Optical materials discovery and design with federated databases and machine learning, Materials Cloud Archive 2024.114 (2024) doi: 10.24435/materialscloud:5p-vq

Description of provider: Databases contributed by the community to the Materials Cloud Archive. Description of dataset: Z. Wang et al., Machine learning-accelerated discovery of A2BC2 ternary electrides with diverse anionic electron densities, Materials Cloud Archive 2023.181 (2023) doi: 10.24435/materialscloud:c8-gy

Description of provider: Databases contributed by the community to the Materials Cloud Archive. Description of dataset: L. Kahle et al., High-throughput computational screening for solid-state Li-ion conductors, Materials Cloud Archive 2024.65 (2024) doi: 10.24435/materialscloud:vg-ya

Description of provider: Databases contributed by the community to the Materials Cloud Archive. Description of dataset: Y. He et al., Machine learning on multiple topological materials datasets, Materials Cloud Archive 2025.32 (2025) doi: 10.24435/materialscloud:zk-gc

Description of provider: A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset: Quantum spin Hall insulator (QSHI) candidates through DFT band structure calculations.

Description of provider: A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset: Tail-corrections in molecular simulations for adsorption of gasses in a diverse set of nanoporous crystalline materials (zeolites, Covalent Organic Framworks (COFs), and Metal Organic Frameworks (MOFs)).

Description of provider: A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset: Validation results of an automated protocol for generating maximally-localized Wannier functions in a high-throughput framework.

Description of provider: A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset: Database of experimentally reported Covalent-Organic Frameworks (COFs), provided with DFT-optimized geometry and DDEC partial charges for molecular simulations.

Description of provider: A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset: Structural, dynamic and electronic characterisation of a novel mixed-metal chalcohalide revealing hidden symmetry breaking and spontaneous polarisation.

Description of provider: A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset: Two-dimensional (2D) materials from high-throughput computational exfoliation of experimentally known compounds.

Description of provider: A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset: Curated set of relaxed three-dimensional crystal structures based on raw CIF data from the experimental databases MPDS, COD, and ICSD.

Description of provider: A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset: Pyrene Metal Organic Frameworks (MOFs).

Description of provider: A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset: Refining random structure searching results of SrTiO3-CeO2 interfaces, and exploring how it can affect ionic conduction. Candidate structures of the DFT validation calculations.

A highly curated Pauling File dataset based on ~0.5M publications and backing up Springer Materials, ICDD PDF, ASM APD, MedeA, Pearson Crystal Data, AtomWork Advanced, etc.

A FAIR data sharing platform for materials science data

Description of provider: A public database of crystal structures mostly derived from ab initio structure prediction from the group of Dr Andrew Morris at the University of Birmingham https://ajm143.github.io. Description of dataset: An OPTIMADE API for the recent dataset released by Google DeepMind containing 340k new on-hull materials, according to PBE.

Description of provider: The Open Materials Database (omdb) is a database of materials properties maintained by the developers of the High-Throughput Toolkit (httk). It enables easy access to useful materials data, in particular via programmatic interaction using this toolkit. Description of dataset: This is the main production version of the Open Materials Database

Description of provider: An open database of computed materials properties to accelerate materials discovery and design. Description of dataset: The Materials Project OPTIMADE endpoint