793 citations · 1.7k across the 34 of their papers we have counts for
3 papers · 2 filters
AdsorbML: A Leap in Efficiency for Adsorption Energy Calculations using Generalizable Machine Learning Potentials
Janice Lan, Aini Palizhati, Muhammed Shuaibi +6
Computational catalysis is playing an increasingly significant role in the design of catalysts across a wide range of applications. A common task for many computational methods is…
Catlas: an automated framework for catalyst discovery demonstrated for direct syngas conversion
Brook Wander, Kirby Broderick, Zachary W. Ulissi
Catalyst discovery is paramount to support access to energy and key chemical feedstocks in a post fossil fuel era. Exhaustive computational searches of large material design spaces…
The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysts
Richard Tran, Janice Lan, Muhammed Shuaibi +14
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…