Oxygen Reduction Reaction: Rapid Prediction of Mass Activity of Nanostructured Platinum Electrocatalysts

Abstract

Tailored Pt nanoparticle catalysts are promising candidates to accelerate the oxygen reduction reaction (ORR) in fuel cells. However, the search for active nanoparticle catalysts is hindered by the laborious effort of experimental synthesis and measurements. On the other hand, density functional theory-based approaches are still time-consuming and often not efficient. In this study, we introduce a computational model which enables rapid catalytic activity calculation of unstrained pure Pt nanoparticle electrocatalysts. Regarding particle size effects on Pt nanoparticles, experimental catalytic mass activities from previous studies are accurately reproduced by our computational model. Moreover, beyond available experiments, our computational model identifies potential enhancement in mass activity up to 190% over the experimentally detected maximum. Importantly, the rapid activity calculation enabled by our computational model may pave the way for extensive nanoparticle screening to expedite the search for improved electrocatalysts.