Litcius/Paper detail

Navigating the unknown with AI: multiobjective Bayesian optimization of non-noble acidic OER catalysts

Ken J. Jenewein, Luca Torresi, Navid Haghmoradi, Attila Kormányos, Pascal Friederich, Serhiy Cherevko

2023Journal of Materials Chemistry A52 citationsDOIOpen Access PDF

Abstract

This study highlighted the effectiveness of AI-driven multiobjective Bayesian optimization for electrocatalysis, accelerating the search for active and stable compositions for the acidic oxygen evolution reaction by 17x.

Topics & Concepts

Bayesian optimizationBayesian probabilityElectrocatalystCatalysisComputer scienceMulti-objective optimizationMathematical optimizationChemistryArtificial intelligenceMachine learningMathematicsBiochemistryElectrodeElectrochemistryPhysical chemistryElectrocatalysts for Energy ConversionMachine Learning in Materials ScienceFuel Cells and Related Materials