324 citations · 348 across the 6 of their papers we have counts for
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cond-mat.mtrl-sci2025
MatterTune: An Integrated, User-Friendly Platform for Fine-Tuning Atomistic Foundation Models to Accelerate Materials Simulation and Discovery
Lingyu Kong, Nima Shoghi, Guoxiang Hu +2
Geometric machine learning models such as graph neural networks have achieved remarkable success in recent years in chemical and materials science research for applications such as…
cond-mat.mtrl-sci2022★ 324 cited
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…