Quantifying Uncertainty in Activity Volcano Relationships for Oxygen Reduction Reaction

Abstract

The oxygen reduction reaction (ORR) is an important electrochemical reaction and a major bottleneck for fuel cells. Due to the existence of a scaling relation between the adsorption energies of two key intermediates involved in ORR, OOH*, and OH*, the electrocatalytic activity for the ORR, to a first approximation, is determined by a single descriptor. This descriptor-based approach has been used to screen for electrocatalyst materials that have an optimal binding energy of oxygen intermediates. However, given that this descriptor-based search relies on several approximations, it is crucial to determine the overall predictability of the descriptor-based model to determine the activity of a catalyst. In this work, we develop a formalism for estimating uncertainty for the activity of a catalyst in an electrocatalytic reaction scheme and apply this framework to determine errors involved in describing the ORR activity. We perform density functional theory calculations using the Bayesian Error Estimation Funct...