Datasets for Accelerating Catalysts Screening via Machine-learned Local Coordination Graph Representations

Hieu A. Doan, Chenyang Li, Logan Ward, Mingxia Zhou, Larry A. Curtiss & Rajeev S. Assary
A priori catalyst designs from reliable first principles simulations and emerging artificial intelligence tools are desired to accelerate materials development. In the context of upgrading biomass materials via deoxygenation reaction to value-added chemicals, molybdenum carbides (Mo2C) have been considered among the best and economically viable catalysts. One of the bottlenecks related to longer term stability of Mo2C catalysts is the susceptibility to surface oxidation, which requires the use of excess hydrogen for active site regeneration....
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