The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts. (arXiv:2206.08917v2 [cond-mat.mtrl-sci] UPDATED)

The development of machine learning models for electrocatalysts requires a
broad set of training data to enable their use across a wide variety of
materials. One class of materials that currently lacks sufficient training data
is oxides, which are critical for the development of Oxygen Evolution Reaction
(OER) catalysts. To address this, we developed the Open Catalyst 2022 (OC22)
dataset, consisting of 62,331 Density Functional Theory (DFT) relaxations
(~9,854,504 single point calculations) across a range of oxide materials,
coverages, and …

arxiv challenges dataset open catalyst