Publish. Discover. Accelerate Science.

The Materials Data Facility (MDF) connects you to high-quality materials science datasets. Publish your findings, discover new data, and build the future of research.

Discover DataPublish Data
Datasets
880+
Data Hosted
600 TB+
ML-Ready Datasets
60+

Discover

Curated datasets for your research

Explore high-quality datasets across materials science, simulations, and ML-ready collections.

Browse all datasets
Publishing

Share your data.
Amplify your impact.

Make your research citable, discoverable, and accessible. MDF provides a streamlined workflow backed by Globus for secure and reliable data publishing.

Mint DOIs for your datasets
Meet data management requirements
Track citations and usage
Start Publishing

Sign up & Join

Create a free Globus account and join the MDF group to unlock publishing capabilities.

Create AccountJoin Group

Prepare Data

Organize your data in open formats. Upload from local storage, Globus endpoints, or Google Drive.

Best Practices

Submit & Publish

Use our guided interface to mint a DOI, add metadata, and share your research with the world.

Publish Now
Foundry ML

ML-Ready Data.
Zero Friction.

Stop spending hours cleaning data. Foundry provides structured, validated datasets that are ready for machine learning. Load them with just a few lines of Python.

Get StartedBrowse ML Datasets
foundry_example.py
1# Import Foundry
2from foundry import Foundry
3f = Foundry()
4
5# Load a dataset by DOI
6doi = '10.18126/qsdl-qj6x'
7ds = f.get_dataset(doi)
8
9# Get data as a dictionary
10X, y = ds.get_as_dict()
11
Spotlight

High-Impact Datasets

OMol25

Electronic Structure Dataset

New Release

Electronic Structure Dataset for Molecular Machine Learning

500 terabytes of electronic densities, wavefunctions, and molecular orbital information from over 4 million high-accuracy DFT calculations.

500 TB4M+ CalculationsQuantum Chemistry
View Dataset

How to Cite

If MDF supports your research, please cite these foundational papers to support the platform.

"The Materials Data Facility: Data services to advance materials science research."

Blaiszik, B., et al. JOM 68, no. 8, 2016: 2045-2052.

View Paper DOI: 10.1007/s11837-016-2001-3

"A data ecosystem to support machine learning in materials science."

Blaiszik, B., et al. MRS Communications 9, no. 4, 2019: 1125-1133.

View Paper DOI: 10.1557/mrc.2019.118

Support

The Center for Hierarchical Materials Design (CHiMaD)

CHiMaD is a NIST-sponsored center of excellence for advanced materials research, focusing on developing new tools and methods for materials design and discovery.

Supported by NIST

The Materials Data Facility

MDF development and operations are supported by NIST, enabling the creation of a national data infrastructure for materials science.

Supported by NIST