Open Catalyst Project
Hunting clean-energy catalysts with AI
Latest: Open Catalyst Experiments 2024 (OCx24, Nov 2024); models and demo now served via fairchem/UMA
Collaboration between FAIR and Carnegie Mellon using AI to find catalysts for renewable-energy storage. The OC20 dataset (2020) — over 1.2 million DFT relaxations — plus OC22 and the experimental OCx24 release (November 2024) turned catalysis into a benchmark-driven ML field, with public leaderboards and NeurIPS competitions.
Why it matters
Turned catalyst discovery into a benchmark-driven machine-learning field: OC20's 1.2 million DFT relaxations, public leaderboards and NeurIPS competitions gave ML researchers a concrete climate problem, and OCx24 in 2024 closed the loop with real experiments. Its models now live on in fairchem and UMA.
Facts
- OC20 remains one of the largest chemistry ML datasets ever released; the project's open demo lets anyone simulate adsorption energies in the browser instead of running days of DFT.
Try it yourself
Project site ↗ OC20 leaderboard ↗ Interactive Open Catalyst demo ↗
Lineage
Sources
arXiv ↗Meta AI blog ↗opencatalystproject.org ↗