Methodology and for accelerating the search of very large configurational spaces based on machine learning accelerated surrogate modeling will be presented. Stability and morphology of catalyst materials can surprisingly accurately be predicted from machine learning models fitted on the fly and integrated with meta-heuristic search algorithms.

Accelerating discovery of catalysts and catalytic morphology

255th National Meeting (2018)

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