Awesome Materials & Chemistry Datasets

A curated list of the most useful datasets in materials science and chemistry for training machine learning and AI foundation models. This includes experimental, computational, and literature-mined datasets—prioritizing open-access resources and community contributions.

This project aims to:

• Catalog the best datasets by domain, type, quality, and size
• Support reproducible research in AI for chemistry and materials
• Provide a community-driven resource with contributions from researchers and developers

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Table of Contents

• How to Use
• Contributing
• Datasets
  • Computational (DFT, MD)
  • Experimental
  • LLM Training
  • Literature-mined & Text
  • Physics & Engineering (PDE, CFD)
  • Proprietary
• License
• Acknowledgements

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Contributing

Want to add a new dataset or improve metadata?

1. Fork the repository
2. Edit the appropriate dataset list or add a new entry
3. Submit a pull request with a brief description and download link OR
4. Submit as an issue

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Datasets

Computational Datasets

Dataset	Domain	Size	Type	Format	License	Access
BOOM: Benchmarks for Out-Of-distribution Molecules	Small molecules	10 Out-Of-Distribution Tasks (1M+ entries)	Computational	CSV	Apache 2.0	Open
MSR-ACC/TAE25	Small molecules	77k CCSD(T)/CBS atomization energies	Computational	JSON	CDLA 2.0	Open
OMat24 (Meta)	Inorganic crystals	110M DFT entries	Computational	JSON/HDF5	CC BY 4.0	Open
OMol25 (Meta)	Molecular chemistry	100M+ DFT calculations	Computational	LMDB	CC BY 4.0	Open
OMC25	Molecular crystals	>27M structures	Computational	Zarr	CC BY-NC 4.0	Open
Materials Project (LBL)	Inorganic crystals	500k+ compounds	Computational	JSON/API	CC BY 4.0	Open
Open Catalyst 2020 (OC20)	Catalysis (surfaces)	1.2M relaxations	Computational	JSON/HDF5	CC BY 4.0	Open
AFLOW	Inorganic materials	3.5M materials	Computational	REST API	Open	Open
OQMD	Inorganic solids	1M+ compounds	Computational	SQL/CSV	Open	Open
JARVIS-DFT (NIST)	3D/2D materials	40k+ entries	Computational	JSON/API	Open	Open
Carolina Materials DB	Hypothetical crystals	214k structures	Computational	JSON	CC BY 4.0	Open
NOMAD	Various DFT/MD	>19M calculations	Computational	JSON	CC BY 4.0	Open
MatPES	DFT Potential Energy Surfaces	~400,000 structures from 300K MD simulations	Computational	JSON		Open
Vector-QM24	Small organic and inorganic molecules	836k conformational isomers	Computational	JSON	Placeholder	Open
AIMNet2 Dataset	Non-metallic compounds	20M hybrid DFT calculations	Computational	JSON	Open	Open
RDB7	Barrier height and enthalpy for small organic reactions	12k CCSD(T)-F12 calculations	Computational	CSV	Open	Open
RDB19-Rad	ΔG of activation and of reaction for organic reactions in 40 common solvents	5.6k DFT + COSMO-RS calculations	Computational	CSV	Open	Open
QCML	Small molecules consisting of up to 8 heavy atoms	14.7B Semi-empirical + 33.5M DFT calculations	Computational	TFDS	CC BY-NC 4.0	Open
QM9	Small organic molecules	134k molecules with quantum properties	Experimental	SDF/CSV	CC BY 4.0	Open
QM7/QM7b	Small molecules	7k molecules with atomization energies	Experimental	SDF/CSV	CC BY 4.0	Open
QMugs	Drug-like molecules	665 k mol / 2 M conf	Computational	HDF5	CC BY 4.0	Open
C2DB	2-D materials	~4 000 entries	Computational	JSON/API	CC BY 4.0	Open
ANI-1x / 1ccx	Small organic mol	5 M (DFT) + 0.5 M (CCSD)	Computational	HDF5	CC BY-NC 4.0	Open
CoRE MOF 2019	Metal-organic frameworks	14 763 structures	Computational	CIF/JSON	CC BY 4.0	Open
QMOF Database	Metal-organic frameworks	20k+ structures (DFT)	Computational	CIF/JSON	CC BY 4.0	Open
Catalysis-Hub	Surface reactions	>100 k energies	Computational	JSON/API	CC BY 4.0	Open
ODAC23	MOF + CO₂/H₂O adsorption	38 M DFT calcs	Computational	HDF5	CC BY 4.0	Open
MOFX-DB	Gas adsorption in MOFs	3 M isotherm pts	Computational	CSV/HDF5	CC BY 4.0	Open
LeMat-Bulk	Inorganic materials (bulk)	6.7M structures (5.9M materials)	Computational	HuggingFace Dataset	CC BY 4.0	Open
LeMat-Traj	Inorganic materials (trajectories)	113M structures	Computational	HuggingFace Dataset	CC BY 4.0	Open
NeurIPS Open Polymer Prediction 2025	Polymers	~1,500 test polymers with MD-derived properties	Computational	CSV	Open	Open
Carbon Data	Carbon materials	22.9M atoms, 546 trajectories	Computational	EXTXYZ	Open	Open
MSR-ACC/TAE25	Small molecules (up to Ar)	76,879 total atomization energies	Computational	HDF5/CSV	Open	Open
DFT Solvation Energy Dataset	Small molecules	651,290 solvation energies in 5 solvents	Computational	CSV/JSON	Open	Open
MD Simulated Monomer Properties	Small molecules	410 molecules with thermodynamic properties	Computational	CSV/JSON	Open	Open
Multimodal Spectroscopic Dataset	Molecular spectroscopy	790k molecules with simulated spectra	Computational	HDF5/JSON	Open	Open
PubChemQCR	Small molecules (relaxation)	3.5M trajectories / 300M conformations	Computational	HuggingFace Dataset	Apache-2.0	Open
MP-ALOE	Universal MLIPs (89 elements)	~1M r2SCAN DFT calculations	Computational	JSONL/MACE	Open	Open
Alexandria DB	Inorganic (1D–3D)	>5 M DFT calcs (PBE)	Computational	JSON/OPTIMADE/LMDB	Open	Open
Quantum‑Chemical Bonding DB (LOBSTER)	Solid‑state bonding analysis	1,520 compounds	Computational	JSON	CC BY 4.0	Open
MultixcQM9 (OpenQDC)	Small molecules (QM9, multi‑XC)	133k molecules	Computational	Torch/NumPy	Open	Open
SPICE (OpenQDC)	Drug‑like molecules	1 M conformers (energies & forces)	Computational	Torch/ASE	Open	Open
Matbench v0.1	Benchmarks (13 tasks)	10 datasets	Benchmark/Comp	CSV/HDF5	BSD‑3	Open
Matbench Discovery	Stability, κ, structures	Multiple files	Benchmark/Comp	CSV/ZIP	BSD‑3	Open
Materials Cloud Archives	Various DFT/MD workflows	1,000+ datasets	Computational	HDF5/JSON/CIF	Various CC	Open
MS25	MLIP benchmark (6 material systems)	Multi-system benchmark suite	Computational/Benchmark	HDF5	Open	Open
RadonPy Polymer Properties Data	Polymer	~1070 MD-calculated Properties	Computational	CSV	BSD-3	Open
SHNITSEL Data	Organic Molecules	418,870 Post-HF-calculated Ground- and Excited-states Properties	Computational	XARRAY	CC BY 4.0	Open
Frustrated Lewis Pairs Database	Small Molecules	146 Metal-free FLPs	Computational	HTML	Open	Open

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Experimental Datasets

Dataset	Domain	Size	Type	Format	License	Access
Crystallography Open Database (COD)	Crystal structures	~525k entries	Experimental	CIF/SMILES	CC0 1.0	Open
NIST ICSD (subset)	Inorganic structures	~290k structures	Experimental	CIF	Proprietary	Restricted
CSD (Cambridge)	Organic crystals	~1.3M structures	Experimental	CIF	Proprietary	Restricted
opXRD	Crystal structures	92552 (2179 labeled)	Experimental	JSON	CC BY 4.0	Open
MDR SuperCon	Superconductivity	legacy superconductor database w/ material composition, structure, properties, and processes	Mixed		CC BY 4.0	Open
ChEMBL	Bioactive molecules	2.3M+ compounds with bioactivity data	Experimental	JSON/SDF	CC BY-SA 3.0	Open
MoleculeNet	Molecular properties	700k+ compounds across 17 datasets	Mixed	CSV/SDF	Various	Open
ESOL	Aqueous solubility	1,128 compounds with solubility data	Experimental	CSV	Open	Open
FreeSolv	Hydration free energy	643 molecules with experimental data	Experimental	CSV	CC BY 4.0	Open
Lipophilicity	Octanol/water distribution	4,200 compounds with logD values	Experimental	CSV	Open	Open
PCBA	Bioassay screening	400k+ compounds, 128 bioassays	Experimental	CSV	Open	Open
HIV	Antiviral screening	41k compounds with HIV inhibition data	Experimental	CSV	Open	Open
BACE	Beta-secretase inhibitors	1,522 compounds with IC50 data	Experimental	CSV	Open	Open
BBBP	Blood-brain barrier permeability	2,053 compounds with permeability data	Experimental	CSV	Open	Open
Tox21	Toxicity screening	8k compounds, 12 toxicity targets	Experimental	CSV	Open	Open
ToxCast	High-throughput toxicity	8k compounds, 600+ assays	Experimental	CSV	Open	Open
SIDER	Drug side effects	1,427 drugs with adverse reactions	Experimental	CSV	Open	Open
ClinTox	Clinical trial toxicity	1,491 compounds with FDA approval status	Experimental	CSV	Open	Open
PDBbind	Protein-ligand binding	19k complexes with binding affinities	Experimental	PDB/SDF	Open	Open
BindingDB	Protein-ligand binding	2.8M+ binding data points	Experimental	CSV/SDF	CC BY 4.0	Open
ProtBENCH	Drug-target interactions	Protein family-specific datasets	Experimental	CSV	GPL-3.0	Open
PDBench	Protein sequence design	595 protein structures, 40 architectures	Experimental	PDB	MIT	Open
PDB-Struct	Structure-based protein design	Comprehensive protein design benchmark	Experimental	PDB	Open	Open
HTEM-DB	Thin-film composition libraries	140 k+ samples	Experimental	JSON/API	CC0	Open
OCx24	Electrocatalyst inks	572 samples (+DFT)	Experimental	CSV	CC BY 4.0	Open
Polymer Genome	Polymers	20 k polymers	Experimental + Comp	CSV/JSON	CC BY 4.0	Open
CoRE MOF 2024	Metal-organic frameworks	40k+ experimental MOFs	Experimental	CIF	Open	Open
SAIR	Protein-ligand binding	1M+ complexes, 5.2M structures, 2.5TB	Experimental	3D/CSV	CC BY-NC-SA 4.0	Open
Anion Solvation DB	Anion solvation	~26k properties	Mixed	CSV	CC BY 4.0	Open
BigSolDB	Organic molecule solubility	~54k exp. values	Experimental	CSV	CC BY 4.0	Open
StarryData2	Experimental properties	Figshare dump (2023/2024)	Experimental	CSV/JSON	CC BY 4.0	Open
CRIPT Polymer Data	Polymers (synthesis, properties)	Growing community DB	Mixed	JSON/API	CC BY 4.0	Open

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LLM Training Datasets

Dataset	Domain	Size	Type	Format	License	Access
ChemPile	Chemistry	75B+ tokens	LLM Training	Mixed	Open	Open
SmolInstruct	Small molecules	3.3M samples	LLM Training	JSON	CC BY 4.0	Open
CAMEL	Chemistry	20K problem-solution pairs	LLM Training	JSON	Open	Open
ChemNLP	Chemistry	Extensive, many combined datasets	LLM Training	JSON	Open	Open
ChemQA	Chemistry	Multimodal QA dataset	LLM Training	JSON	Open	Open
ChemLLMBench	Chemistry	8 chemistry tasks benchmark	LLM Training	JSON	Open	Open
ChemistryQA	Chemistry	4,500 questions across 200 topics	LLM Training	JSON	Open	Open
MaScQA	Materials Science	640 QA pairs	LLM Training	XLSX	Open	Open
SciCode	Research Coding in Physics, Math, Material Science, Biology, and Chemistry	338 subproblems	LLM Training	JSON	Open	Open
ChemData 700K	Chemistry (9 core tasks)	730K Q-A instruction pairs	LLM Training	JSON	CC BY-NC 4.0	Open
MatSci-Instruct (HoneyBee)	Materials science	≈55K verified instructions	LLM Training	JSON	CC BY 4.0	Open
MoleculeQA	Molecular properties & safety	62K multiple-choice QA pairs	LLM Training	JSON	MIT	Open
BioInstruct 25K	Biomedical / biochemistry	25K GPT-4 generated instructions	LLM Training	JSON	MIT	Open
Lab-Bench	Biology	2,400+ questions for biology agents	LLM Training	JSON	Open	Open
ChemBench 4K	Chemistry competency benchmark	4,100 single-choice questions	LLM Training	JSON	CC BY-NC 4.0	Open
GPQA Diamond	Biology, Physics, Chemistry	448 multiple-choice questions	LLM Training	JSON	Open	Open
MaCBench	Chemistry and materials science	Vision-language tasks	LLM Training	JSON	Open	Open
ChemBench	Chemistry	2,700+ question-answer pairs	LLM Training	JSON	Open	Open
MatText	Materials property prediction	2M structures	LLM Training	HuggingFace Dataset	Open	Open
SciAssess	Scientific literature analysis	Benchmark for LLMs in science	LLM Training	JSON	Open	Open
ZINC20-ML	Drug-like molecules (SMILES)	≈1B molecules	LLM Training	SMILES	ZINC License	Open
PMC Open Access Subset	Biomedical full-text	3.4M+ articles	LLM Training	XML	Various CC	Open
MatScholar Task-Schema QA (MatSci-NLP)	Materials science (7 NLP tasks)	Tens of thousands of examples	LLM Training	JSON	CC BY 4.0	Open
Mol-Instructions	Chemistry	molecular, protein, and biochemical instructions	LLM Training	HuggingFace Dataset	Open	Open
USPTO-LLM	Chemical reactions	247K reactions	LLM Training	JSON/Graph	CC BY 4.0	Open
ChemRxivQuest	Chem literature QA	970 QA pairs	LLM Training	JSON	CC BY 4.0	Open
USPTO-Lowe	Patent reactions	1.8 M reactions	Literature-mined	RXN/SMILES	CC BY 4.0	Open
MolTextNet	Small molecules with text	2.5M molecule-text pairs	LLM Training	HuggingFace Dataset	Open	Open
MolOpt-Instructions	Molecule optimization	1.18M instruction-based optimization tasks	LLM Training	HuggingFace Dataset	Open	Open
TextEdge	Crystal properties	Crystal text descriptions with properties	LLM Training	JSON	Open	Open
LAMBench-TrainingSet-v1	Materials structures	19.8M structures for Large Atom Models	LLM Training	Various	Open	Open
LLM4Mat	Materials property prediction	1.9M crystal structures, 45 properties, 3 modalities	LLM Training	Various	Open	Open
LLM-EO	Transition metal complexes / Optimization	1.37M TMC space explored	LLM Training	GitHub	Apache-2.0	Open
Flavor Analysis and Recognition Transformer	Molecular taste prediction	Multi-class taste classification dataset	LLM Training	SMILES/JSON	Open	Open
SCQA (Solar Cell QA)	Solar cells	47K QA pairs	LLM Training	JSON	Open	Open
ScienceQA	K–12 science, multimodal MCQs w/ lectures & explanations	21,208 Qs	LLM Training/Eval	JSON	MIT	Open
SciBench	College-level scientific problem solving (math/chem/phys)	Open & closed sets	LLM Eval	PDF/JSON	Open	Open
MegaScience	Scientific reasoning (7 disciplines)	1.25M instances (650k reasoning questions from 12k textbooks)	LLM Training	HuggingFace Dataset	Open	Open

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Literature-mined & Text Datasets

Dataset	Domain	Size	Type	Format	License	Access
PubChem	Molecules & data	119M compounds	Literature	SMILES/SDF	Public Domain	Open
Open Reaction Database (ORD)	Synthetic reactions	~1M reactions	Experimental/Lit	JSON	CC BY 4.0	Open
PatCID (IBM)	Chemical image data	81M images / 13M mols	Literature	PNG/SMILES	Open	Open
MatScholar	NLP corpus (materials)	5M+ abstracts	Literature	JSON/Graph	Open	Open
Matbench (metadata/text tasks)	Text/meta ML tasks	13 tasks	Literature/Benchmark	CSV	BSD‑3	Open
OpenQDC Hub	QM molecules & reactions	1.5 B geometries	Literature/Computational	Python API/NPZ	MIT	Open

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🌊 Computational Fluid Dynamics, PDE & Engineering Datasets

Dataset	Domain	Size	Type	Format	License	Access
PDEBench	PDE solving / Scientific ML	Multiple datasets	Benchmark / Simulation	HDF5/PyTorch	Apache-2.0	Open
BLASTNet	Fluid mechanics / Reacting flows	17 TB	Simulation / CFD	HDF5/NPY	Open	Open
Johns Hopkins Turbulence DB (JHTDB)	DNS/LES turbulence (9 canonical flows)	≈ 350 TB	Simulation	Web API / HDF5 cutouts	Public Domain	Open
Airfoil CFD 2k	1,830 airfoils × 25 AoA × 3 Re	~6 GB (250 k cases)	Simulation	HDF5	CC BY 4.0	Open
PDEArena (collection)	2-D Navier–Stokes, Shallow-Water, 3-D Maxwell	≈ 100 GB (4 datasets)	Simulation	Torch / HDF5	MIT	Open
WeatherBench 2	Global weather reanalysis (ERA5, 1979-2023)	≈ 5 TB	Reanalysis	NetCDF/Zarr	MIT	Open
UT Austin Channel-DNS Suite	Incompressible channel flow Reτ 180 – 5200	≈ 10 TB	Simulation	Binary / ASCII	Research-Free	Open
Compressible TPC DNS DB	Compressible channel flow (25 M, Reτ*)	~2 GB	Simulation	TXT tables	CC BY 4.0	Open
Curated RANS ↔ DNS Dataset	29 geometries, 4 RANS models w/ DNS/LES labels	1.1 GB	Simulation	HDF5/CSV	CC BY 4.0	Open
NASA Common Research Model (CRM)	Aircraft CRM geom. + wind-tunnel & CFD results	Multi-GB	Mixed (Exp + Sim)	CAD / CSV / Tecplot	NASA PDL	Open
Darcy-Flow (FNO)	2-D porous-media pressure fields (∇·k∇u = f)	≈ 1 GB (10 k samples)	Simulation	HDF5	Apache-2.0	Open
HiFi-TURB LES/DNS	High-fidelity LES/DNS for complex 3D flows	Multi-case suite	Simulation (DNS/LES)	HDF5/NetCDF	Open	Open
NASA High Lift Prediction Workshop (HLPW)	High-lift aircraft configurations	Multi-GB	Mixed (exp + CFD)	CAD/CSV/Tecplot	NASA PDL	Open
High-Speed TBL DNS DB	Compressible turbulent boundary layers	DNS database	Simulation	HDF5	Open	Access w/ paper
ML Turbulence (Kaggle)	RANS Reynolds stress tensor data	~GB scale	Benchmark/Simulation	CSV/HDF5	CC BY 4.0	Open

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Proprietary Datasets (for reference)

Dataset	Domain	Size	Access	Use Case Notes
CAS Registry	Chemical substances	250M+ substances	Proprietary	Industry standard for molecule indexing
Reaxys (Elsevier)	Reactions & properties	Millions of reactions	Proprietary	Rich curated literature reaction data
Citrine Informatics DB	Experimental materials	Private	Proprietary	Materials ML platform w/ industry data
CSD (Cambridge)	Organic crystals	1.3M+	Proprietary	Gold-standard X-ray structures
PoLyInfo	Polymers & properties	500k+ data points / Experimental	Proprietary	Polymer properties from literature sources

Dataset Resources

• The Materials Data Facility - Over 100 TB of open materials data. #TODO list some of these in the tables above
• Foundry-ML search Foundry - 61 structured datasets ready for download through a Python client #TODO list some of these in the tables above

TODO

• Add all OpenQDC datasets https://www.openqdc.io/datasets
• A dataset on solubilities of gases in polymers (15 000 experimental measurements of 79 gases' uptakes (0.01–50 wt%) in 102 different polymers, pressures from 1 × 10−3 to 7 × 102 bar and temperatures from 233 to 508 K, includes nearly 500 solvent–polymer systems). Optimized structures of various repeating units are included. Should it be of interest for you, it is available here: Data
• Add Materials Cloud Datasets
• Classify Atomly. A bit challenging with non-English
• Look into adding NOMAD for experimental data as well
• Add A Quantum-Chemical Bonding Database for Solid-State Materials Part 1: https://zenodo.org/records/8091844 Part 2: https://zenodo.org/records/8092187
• Add QM datasets. http://quantum-machine.org/datasets/
• Find link for | ChemRxivQuest | Chemistry literature QA | 970 curated QA pairs | LLM Training | JSON | CC BY 4.0 | Open | ChemRxivQuest |
• Find new link for USPTO-Reactions | USPTO Reactions | Organic reactions | 1.8M reactions | Literature | RXN/SMILES | Open | Open |
• Find dataset link for | SciCUEval | Multidomain scientific comprehension (bio/chem/phys/matsci) | 10 sub-datasets | LLM Eval | JSON/PDF | Open | Open |
• Find dataset for | MatSciKB | Materials science KB | 38.5k entries (20k papers, 3.6k Wikipedia, 1.9k textbooks, 10.5k datasets) | Literature | Structured text | Open | Open |

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Other Links

• Awesome Materials Informatics

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License

This project is licensed under the MIT License. Each dataset listed has its own license, noted in the table. Always check the source's license before using the data in your project.

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Acknowledgements

Thanks to the open data and research communities including:

• Meta AI FAIR
• The Materials Data Facility / Foundry-ML
• NIST JARVIS and Materials Project
• LBL, MIT, CCDC, FIZ Karlsruhe
• Contributors to Open Catalyst, PubChem, ORD, and AFLOW
• Developers of open chemistry toolkits (RDKit, Open Babel)

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Citation

If this repository was helpful in your work, feel free to cite or star the repo. You can also reference the underlying dataset publications linked above.

Changelog

This Changelog is autogenerated, there may be errors.

August 2025

Enhanced scientific reasoning capabilities and machine learning interatomic potential benchmarking with 6 new high-quality datasets for AI scientists and materials researchers.

🧮 Computational Datasets (3 datasets)

• OMC25: A collection of over 27 million molecular crystal structures containing 12 elements and up to 300 atoms in the unit cell. The dataset was generated from dispersion-inclusive density functional theory (DFT) relaxation trajectories of over 230,000 randomly generated molecular crystal structures of around 50,000 organic molecules.
• MS25: Comprehensive benchmark dataset for evaluating machine learning interatomic potentials (MLIPs) across 6 diverse materials systems including MgO surfaces, liquid water, zeolites, catalytic Pt surface reactions, high-entropy alloys, and disordered Zr-oxides. Evaluates 5 MLIP architectures (MACE, NequIP, Allegro, MTP, Torch-ANI) with focus on derived physical observables beyond traditional energy/force metrics. Demonstrates that equivariant MLIPs offer 1.5-2× improvements over nonequivariant models in complex systems, while highlighting the importance of explicit validation of physical properties rather than relying solely on error metrics.
• Added the * Frustrated Lewis Pairs Database ** of 146 Metal-free FLPs

📚 LLM Training Datasets (4 datasets)

• MaCBench: A comprehensive benchmark for evaluating how vision-language models handle real-world chemistry and materials science tasks across three core aspects: data extraction, experimental understanding, and results interpretation. Reveals fundamental limitations in spatial reasoning and cross-modal information synthesis in leading models.
• ChemBench: A cutting-edge framework to evaluate the chemical knowledge and reasoning capabilities of large language models (LLMs). It includes over 2,700 curated question-answer pairs across diverse chemistry topics and uniquely encodes chemical semantics, enabling models to process and reason about molecules and equations.
• MatText: A comprehensive benchmarking framework spanning multiple representations and model scales, which finds that LLMs consistently fail to capture coordinate information while excelling at category patterns. This geometric blindness persists regardless of model size, dataset scale, or text representation strategy.
• MegaScience: Large-scale scientific reasoning dataset featuring 1.25 million high-quality instances across 7 scientific disciplines. Includes TextbookReasoning component with 650k reasoning questions extracted from 12,000 university-level textbooks, providing truthful reference answers for training AI scientists. Developed through systematic ablation studies and comprehensive evaluation across 15 benchmarks, demonstrating superior performance and training efficiency compared to existing open-source scientific datasets.

July 2025

Expanded the collection into new scientific domains with 31 new datasets, introducing benchmarks for physics-based machine learning, adding comprehensive quantum mechanics datasets, expanding materials science resources, and enhancing scientific evaluation benchmarks.

🌊 Computational Fluid Dynamics, PDE & Engineering Datasets (15 datasets)

• PDEBench: A comprehensive benchmark suite for scientific machine learning featuring a wide range of Partial Differential Equations. It provides large, ready-to-use datasets for challenging physics problems, supporting both forward and inverse modeling.
• BLASTNet: A 17 TB collection of high-fidelity fluid mechanics simulation datasets for ML applications in automotive, propulsion, and energy sectors. It includes code and pre-trained models for tasks like turbulence modeling and spatio-temporal prediction.
• JHTDB: multi-terabyte DNS/LES portal with isotropic, channel, MHD, boundary-layer and atmospheric datasets.
• Airfoil CFD 2k: DOE/NREL benchmark: 1,830 shapes × 250 k RANS simulations; HDF5 + AWS mirror.
• PDEArena: Hugging-Face org offering Navier–Stokes, Shallow-Water & Maxwell tensors; MIT license.
• WeatherBench 2: ERA5-derived Zarr cubes for data-driven medium-range forecasting; MIT.
• UT Austin DNS Suite: public HTTP server with Reτ 180–5200 channel data & statistics.
• Compressible TPC DNS DB: 25 Reynolds–Mach cases, plain-text statistics (Mendeley Data).
• Curated RANS ↔ DNS: Scientific Data descriptor + Kaggle mirror for ML turbulence closures.
• NASA CRM: open CAD, grids, wind-tunnel Cp & force/moment datasets for the community benchmark.
• Darcy Flow (FNO): canonical permeability→pressure dataset used in FNO/PINO papers.
• HiFi-TURB LES/DNS: EU-funded project providing high-fidelity Large Eddy Simulation and Direct Numerical Simulation datasets for complex 3D turbulent flows, supporting advanced turbulence modeling and AI/ML applications in computational fluid dynamics.
• NASA High Lift Prediction Workshop (HLPW): Multi-phase workshop datasets featuring high-lift aircraft configurations with comprehensive experimental validation data, CAD geometries, and CFD solutions for aerodynamic modeling and validation.
• High-Speed TBL DNS DB: Specialized database of Direct Numerical Simulation data for compressible turbulent boundary layers, providing detailed flow field information for high-speed aerodynamic applications and turbulence model development.
• ML Turbulence (Kaggle): Community-contributed dataset featuring RANS Reynolds stress tensor data with ground truth labels, providing a standardized benchmark for machine learning approaches to turbulence modeling.

🧮 Computational Datasets (7 datasets)

• PubChemQCR: A massive dataset of molecular relaxation trajectories for ~3.5 million small molecules, containing over 300 million conformations with energy and force labels. It is the largest public dataset of its kind, designed to accelerate the development of machine learning interatomic potentials (MLIPs).
• MP-ALOE: Nearly 1 million DFT calculations using the accurate r2SCAN meta-generalized gradient approximation, covering 89 elements. Created using active learning and primarily consisting of off-equilibrium structures, MP-ALOE is designed for training universal machine learning interatomic potentials (UMLIPs) with strong performance on thermochemical properties, force prediction, and physical soundness under extreme conditions.
• Alexandria DB: Massive computational materials database containing over 5 million DFT calculations using PBE functional for 1D-3D inorganic materials. Provides OPTIMADE-compliant API access and LMDB format for high-performance materials screening and property prediction workflows.
• Quantum-Chemical Bonding DB (LOBSTER): Specialized dataset providing detailed bonding analysis for 1,520 solid-state compounds using LOBSTER methodology. Enables understanding of chemical bonding in crystalline materials through projected crystal orbital Hamilton populations and related descriptors.
• MultixcQM9 & SPICE (OpenQDC): Enhanced quantum chemistry datasets within the OpenQDC framework. MultixcQM9 provides multi-exchange correlation functional data for 133k small molecules, while SPICE offers 1 million conformers with energies and forces for drug-like molecules, both optimized for machine learning applications.
• Matbench v0.1 & Discovery: Comprehensive benchmarking suites for materials property prediction featuring 13 standardized tasks across 10 datasets. Matbench Discovery specifically targets stability prediction, thermal conductivity, and structure generation with rigorous evaluation protocols.
• Materials Cloud Archives: Centralized repository of over 1,000 computational datasets from various DFT and molecular dynamics workflows. Provides standardized access to diverse materials science calculations with comprehensive metadata and version control.

📚 LLM Training Datasets (5 datasets)

• LLM-EO (Evolutionary Optimization): A framework that integrates LLMs into evolutionary algorithms for optimizing transition metal complexes. This approach leverages the chemical knowledge of LLMs to surpass traditional genetic algorithms, enabling flexible, multi-objective optimization without complex mathematical formulations.
• Flavor Analysis and Recognition Transformer: A state-of-the-art machine learning model dataset for predicting molecular taste from chemical structures. Built on ChemBERTa transformer architecture, it classifies molecules across four taste categories (sweet, bitter, sour, umami) with >91% accuracy, enabling interpretability through gradient-based visualizations and applications in flavor compound discovery and rational food design.
• SCQA (Solar Cell QA): Domain-specific question-answering dataset containing 47,268 QA pairs about solar cell properties, auto-generated using ChemDataExtractor. Fine-tuning language models on this dataset achieves F1-scores exceeding general-English QA datasets by 10-20%, demonstrating the value of domain-specific training data for specialized scientific applications.
• ScienceQA: Comprehensive K-12 science education dataset with 21,208 multimodal multiple-choice questions including lectures and explanations. Supports development of educational AI systems and scientific reasoning capabilities in language models.
• SciBench: College-level scientific problem-solving benchmark covering mathematics, chemistry, and physics with both open and closed evaluation sets. Enables systematic assessment of LLM performance on advanced scientific reasoning tasks.

🧪 Experimental Datasets (4 datasets)

• Anion Solvation DB: Comprehensive compilation of 26,000+ solvation properties including 8,241 experimental pKa values across 8 solvents, 5,536 computed gas-phase acidities, and over 12,000 solvation energies for anions and neutral compounds computed using COSMO-RS. Bridges experimental and computational approaches for understanding anion behavior in different solvation environments.
• BigSolDB: Extensive experimental solubility database containing 54,273 measured solubility values across temperature range 243.15-403.15 K in various organic solvents and water. Features diverse chemical space coverage with interactive t-SNE exploration tool and comprehensive statistical analysis for QSPR model development.
• StarryData2: Large-scale experimental properties dataset from Figshare spanning 2023-2024, providing comprehensive experimental measurements across diverse materials and chemical systems for machine learning model validation and training.
• CRIPT Polymer Data: Community-driven polymer database featuring synthesis procedures, characterization data, and properties. Enables standardized data sharing and collaborative research in polymer science through structured JSON API access.

June 2025

Added 28 new high-quality datasets spanning polymer science, drug discovery, carbon materials, spectroscopy, MOF databases, foundation model training, and materials knowledge bases:

🧮 Computational Datasets (15 datasets)

• NeurIPS Open Polymer Prediction 2025: Kaggle competition dataset for predicting 5 key polymer properties (Tg, FFV, Tc, density, Rg) from SMILES structures using MD simulation ground truth. Includes ~1,500 test polymers.
• Carbon Data: 22.9 million atom dataset with synthetic energy labels from C-GAP-17 potential, featuring 546 carbon trajectories across diverse densities and temperatures. Captures nanotubes, graphitic films, diamond, and amorphous carbon environments.
• MSR-ACC/TAE25: Microsoft Research's comprehensive dataset of 76,879 total atomization energies computed at CCSD(T)/CBS level using W1-F12 protocol. Exhaustively covers chemical space for elements up to argon with sub-chemical accuracy (±1 kcal/mol).
• DFT Solvation Energy Dataset: 651,290 computed solvation energies for 130,258 molecules from QM9 dataset across 5 solvents (acetone, ethanol, acetonitrile, DMSO, water). Achieves 0.5 kcal/mol MAE for small molecules with accompanying ML models and web interface.
• MD Simulated Monomer Properties: GPU-accelerated molecular dynamics dataset of thermodynamic properties for 410 molecules, generated through active learning pipeline. Includes validation against experimental data and automated simulation workflow.
• Multimodal Spectroscopic Dataset: Comprehensive spectroscopic dataset with simulated 1H-NMR, 13C-NMR, HSQC-NMR, Infrared, and Mass spectra for 790k molecules from patent reactions. Enables multimodal foundation model development for structure elucidation and functional group prediction.
• QMugs: 665k drug-like molecules with ~2M conformers, featuring quantum mechanical properties at both semi-empirical (GFN2-xTB) and DFT (ωB97X-D/def2-SVP) levels.
• C2DB (Computational 2D Materials Database): ~4,000 two-dimensional materials with computed structural, electronic, magnetic, and optical properties.
• ANI-1x / ANI-1ccx: 5 million DFT and 500k CCSD(T) calculations for organic molecules, supporting machine learning potential development.
• CoRE MOF 2019: 14,763 computation-ready metal-organic frameworks with solvent and charge balancing, suitable for high-throughput screening.
• QMOF Database: Comprehensive database of quantum-chemical properties for 20,000+ metal-organic frameworks derived from high-throughput periodic density functional theory calculations.
• Catalysis-Hub Surface Reactions: Over 100,000 adsorption and reaction energies on catalytic surfaces, accessible via a Python/GraphQL API.
• ODAC23 (Open DAC 2023): 38 million DFT calculations of CO₂/H₂O adsorption on 8,400 MOFs, aimed at direct-air-capture sorbent discovery.
• MOFX-DB: Over 3 million simulated adsorption data points across 160,000 MOFs and 286 zeolites for various gases.
• Enhanced QCML dataset entry with more comprehensive description of coverage and properties

🧪 Experimental Datasets (5 datasets)

• SAIR (Structurally Augmented IC50 Repository): Largest public protein–ligand binding dataset with over 1 million complexes and 5.2 million cofolded 3D structures (2.5TB total). Combines experimental binding affinities from ChEMBL/BindingDB with Boltz-1x predicted structures.
• CoRE MOF 2024: Updated database of over 40,000 experimentally reported metal-organic frameworks from literature through early 2024. Includes pre-computed material properties for high-throughput material-process screening and carbon-capture applications.
• HTEM-DB (High-Throughput Experimental Materials Database): More than 140,000 composition–process–property data points from combinatorial sputtering experiments, with optical, electrical, and structural measurements.
• OCx24 (Open Catalyst Experiments 2024): 572 synthesized catalyst inks evaluated with matched XRF/XRD and DFT adsorption energies, bridging the gap between simulation and laboratory data.
• Khazana / Polymer Genome: Approximately 20,000 polymers with DFT-calculated properties and experimental dielectric data, supporting machine learning on soft materials.

📚 LLM Training Datasets (5 datasets)

• MolTextNet: 2.5 million high-quality molecule-text pairs from ChEMBL35, featuring GPT-4o-mini generated descriptions 10x longer than existing datasets. Integrates structural features, computed properties, bioactivity data, and synthetic complexity for multimodal molecular modeling.
• MolOpt-Instructions: 1.18 million instruction-based molecule optimization tasks for fine-tuning LLMs on drug discovery. Supports interactive human-machine dialogue for molecule optimization through the DrugAssist framework, enabling expert feedback integration and iterative refinement.
• TextEdge: Benchmark dataset for predicting crystal properties from natural language text descriptions. Demonstrates superior performance of LLM-based approaches over traditional GNN methods, with improvements of 8% on band gap prediction and 65% on unit cell volume prediction.
• LAMBench-TrainingSet-v1: Massive training dataset for Large Atom Models (LAMs) containing 19.8 million valid structures from the OpenLAM Initiative. Includes 1 million structures on the convex hull for advancing generative modeling and materials science applications.
• LLM4Mat: Comprehensive benchmark dataset for evaluating LLMs in materials property prediction, containing 1.9M crystal structures from 10 data sources with 45 distinct properties. Features three input modalities (crystal composition, CIF, text description) with 4.7M, 615.5M, and 3.1B tokens respectively.

📖 Literature-mined & Text Datasets (3 datasets)

• MatSciKB: Comprehensive materials science knowledge base with 38,469 curated entries across 16 categories. Integrates ArXiv papers (20,384), Wikipedia articles (3,620), textbooks (1,930), datasets (10,473), formulas (57), and GPT-generated examples (2,005) with efficient CRUD operations for research applications.
• ChemRxivQuest: 970 curated question–answer pairs spanning 17 chemistry subfields, designed for retrieval-augmented generation and factuality assessments.
• USPTO-Lowe Reactions (1976–2016): 1.8 million atom-mapped reactions extracted from US patents, serving as a benchmark for reaction prediction and retrosynthesis models.

📚 Enhanced Literature & Benchmark Resources (2 datasets)

• Matbench (metadata/text tasks): Extended benchmarking suite providing 13 standardized tasks for text-based and metadata-driven materials property prediction. Enables systematic evaluation of natural language processing approaches in materials science applications.
• OpenQDC Hub: Comprehensive quantum chemistry database aggregating 1.5 billion molecular geometries and quantum mechanical properties. Provides unified Python API access to diverse quantum chemistry datasets with standardized formats for large-scale machine learning applications.

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Earlier Updates

For changes made earlier than the changelog entries, please see the repository commit history.