OPTIMADE Providers' Datasets

AFMDB is a centralised collection of Atomic Force Microscopy (AFM) data covering a range of physical and biological materials, hosted within the PSDI Community Data Collections. Each entry includes the original AFM files along with a processed image generated during analysis. Initial examples demonstrate the output from our open-source tool TopoStats which has been used to process images and standardised the data output. By making these datasets openly available, AFMDB supports good data sharing practices and provides high quality, standardised examples that can be used to train and evaluate deep learning methods for enhanced AFM analysis. Researchers are encouraged to contribute AFM data from their publications and to test TopoStats, helping refine the tool through community feedback.

BenchmarkSet1500 is an open-access multireference excited-state database established to provide the first dedicated high-accuracy benchmark set for organic semiconductor research. The repository comprises 1,500 small organic molecules with consistently computed vertical excited-state properties obtained using state-averaged complete active space self-consistent field (SA-CASSCF) and strongly contracted N-electron valence state second-order perturbation theory (SC-NEVPT2), alongside the full reproducible workflow code used to generate the dataset. The dataset focuses on systems where single-reference approaches (e.g. TD-DFT) are known to fail, including molecules exhibiting strong static correlation and inverted singlet-triplet gaps. BenchmarkSet1500 is designed to support rigorous method benchmarking, systematic assessment of theory-level performance, development of predictive models, and screening for technologically relevant organic semiconductors.

Topology, trajectory, and AiiDA data provenance files from molecular dynamics simulations of biomolecules are stored in a repository specifically designed for their preservation and accessibility.

The Catalysis Data Infrastructure (CDI) Data Objects resource provides access to the UK Catalysis Hub (UKCH) published data objects that support research outputs. Through the CDI Portal, PSDI Cross Data Search and PSDI Index search users can search, explore, and reuse these data resources. In the Catalysis Data Infrastructure (CDI) knowledge graph, data objects are linked with researchers, institutions, publications, and research themes, fostering data discovery, highlighting collaborations, and supporting analysis of data-driven research. CDI Data Objects can be extended to include domain-specific data resources such as chemical entities, materials, or analytical methods.

The Catalysis Data Infrastructure (CDI) Publications resource provides access to the UK Catalysis Hub (UKCH) Publications, including peer-reviewed articles, books, and theses. CDI Publications offer a dedicated entry point into the CDI knowledge graph through the CDI Portal. PSDI Cross Data Search and PSDI Index search can be used to explore and analyse research publications. Within CDI, publications are linked to researchers (authors), institutions, research themes, and associated data objects. The linking enhances publication discovery, displays research relationships, and supports insight into research activity. CDI Publications can be expanded to include domain-specific indexes about chemicals, materials, and analysis methods.

Data-to-Knowledge Collections provide curated datasets specifically designed for use in machine learning or generated through machine learning processes. An example is the Machine Learning Interatomic Potentials (MLIPs) data collection, which includes MLIP XYZ files used for training, the trained MLIP models, and, where available, additional metadata such as AIIDA provenance information. By making these datasets accessible, researchers without the resources to generate such data themselves can leverage them for machine learning. Additionally, the MLIP models can be directly applied in modeling tasks, enabling broader exploration and advancements in research.

These datasets focus on solubility-related information, including boiling points, Henry's law constants, LogS, melting points, and mole fractions. The Physical Chemistry Properties Data Collection provides carefully curated and standardized data on key chemical properties, empowering researchers to effectively model, analyze, and drive innovation in the field of physical chemistry.

SimpNMR_DB is a shared collection for ab initio calculations of hyperfine interactions that are used as inputs for SimpNMR. SimpNMR is an open-source python package for analysing paramagnetic NMR data that links Density Functional Theory (DFT) calculations with NMR spectra and helps to assign the peaks and extract the magnetic susceptibility tensor form paramagnetic shifts. This ab initio data is useful for the community involved in computing magnetic properties of molecules due to the difficulty in accurate prediction. It provides access to computational results that are often time consuming to generate, giving researchers a consistent reference point for comparison, method testing, and reproducibility. As the database grows, it will also support benchmarking studies and the development of machine learning models. Therefore we encourage researchers to share their computational files in SimpNMR_DB to benefit the wider community. Note that this repository is currently under rapid and active development.

2DMatpedia, an open computational database of two-dimensional materials from top-down and bottom-up approaches

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

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

The Chemotion Repository is an open repository of well-structured and machine-readable chemical data created by the Karlsruhe Institute of Technology. The focus of the repository is synthetic and analytical chemistry data. It includes data pertaining to reactions, molecules and physical samples. Data in the repository is uploaded by the community, and is subject to peer review.

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 (Materials Cloud): A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset (2D topological insulators): Quantum spin Hall insulator (QSHI) candidates through DFT band structure calculations.

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

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

Description of provider (Materials Cloud): A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset (Hidden spontaneous polarisation in the chalcohalide photovoltaic Sn2SbS2I3): Structural, dynamic and electronic characterisation of a novel mixed-metal chalcohalide revealing hidden symmetry breaking and spontaneous polarisation.

Description of provider (Materials Cloud): A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset (MC2D - Materials Cloud two-dimensional crystals database): Two-dimensional (2D) materials from high-throughput computational exfoliation of experimentally known compounds.

Description of provider (Materials Cloud): A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset (MC3D (PBE-v1) - Materials Cloud 3D Structures Database): Curated set of relaxed three-dimensional crystal structures based on raw CIF data from the experimental databases MPDS, COD, and ICSD.

Description of provider (Materials Cloud): A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset (MC3D (PBEsol-v1) - Materials Cloud 3D Structures Database): Curated set of relaxed three-dimensional crystal structures based on raw CIF data from the experimental databases MPDS, COD, and ICSD.

Description of provider (Materials Cloud): A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset (MC3D (PBEsol-v2) - Materials Cloud 3D Structures Database): Curated set of relaxed three-dimensional crystal structures based on raw CIF data from the experimental databases MPDS, COD, and ICSD.

Description of provider (Materials Cloud): A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset (Pyrene-based metal organic frameworks): Pyrene Metal Organic Frameworks (MOFs).

Description of provider (Materials Cloud): A platform for Open Science built for seamless sharing of resources in computational materials science. Description of dataset (SrTiO3-CeO2 interfaces): 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.

Database of machine learning property predictions for over 31 million hypothetical materials and materials in the Materials Project.

A FAIR data sharing platform for materials science data

Description of provider (open database of xtals): 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 (Google DeepMind's Gnome Dataset): An OPTIMADE API for the recent dataset released by Google DeepMind containing 340k new on-hull materials, according to PBE.

Description of provider (open database of xtals): 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 (Miscellaneous Materials Discovery Data): Miscellaneous Materials Discovery Datasets, hosted as an OPTIMADE API (temporarily).

Description of provider (open database of xtals): 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 (odbx): The Open Database of Xtals is run by the group of Dr Andrew Morris at the universities of Birmingham and Cambridge and is constructed using the matador library.

Description of provider (Open Materials Database): 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 (Open Materials Database (omdb) production database): This is the main production version of the Open Materials Database

STFC Open Data includes data and software records from STFC's experimental facilities, such as the ISIS Neutron and Muon Source and the Central Laser Facility. This data source also features long-tail data shared by researchers in the STFC eData institutional repository. Any data or software record originating from STFC with a DOI is published in DataCite, which serves as the source for the "STFC Open Data" collection in PSDI.

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

Description of provider (The Open Quantum Materials Database (OQMD)): The OQMD is a database of DFT calculated thermodynamic and structural properties of materials. Description of dataset (The OQMD): The Open Quantum Materials Database endpoint

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