Litcius/Paper detail

Accelerating materials discovery for electrocatalytic water oxidation <i>via</i> center-environment deep learning in spinel oxides

Yihang Li, Xinying Zhang, Tao Li, Yingying Chen, Yi Liu, Lingyan Feng

2024Journal of Materials Chemistry A22 citationsDOI

Abstract

Using DFT and machine learning, we evaluated 5329 spinel oxides and identified 14 promising OER electrocatalysts. Experimentally, MoAg 2 O 4 showed superior performance, achieving 10 mA cm −2 at 284 mV overpotential, surpassing commercial RuO 2 .

Topics & Concepts

OverpotentialSpinelOxygen evolutionMaterials scienceCenter (category theory)Water splittingChemical engineeringComputer scienceCatalysisMetallurgyElectrochemistryChemistryPhysical chemistryCrystallographyEngineeringElectrodePhotocatalysisBiochemistryElectrocatalysts for Energy ConversionMachine Learning in Materials ScienceAdvanced Photocatalysis Techniques