Platinum-based Catalysts for Oxygen Reduction Reaction simulated with a Quantum Computer

TL;DR

This paper explores the use of quantum computing to model the oxygen reduction reaction on platinum-based catalysts, addressing complex electronic correlations that challenge classical methods, and demonstrates initial feasibility on a trapped-ion quantum computer.

Contribution

It introduces a novel hybrid classical-quantum workflow for simulating ORR on platinum catalysts and demonstrates its implementation on a trapped-ion quantum computer for the first time.

Findings

Feasibility of quantum workflow on H1-series quantum computer

Identification of strongly correlated species in cobalt catalysts

Potential for quantum advantage in catalysis simulations

Abstract

Hydrogen has emerged as a promising energy source, holding the key to achieve low-carbon and sustainable mobility. However, its applications are still limited by modest conversion efficiency in the electrocatalytic oxygen reduction reaction (ORR) within fuel cells. Consequently, the development of novel catalysts and a profound understanding of the underlying reactions have become of paramount importance. The complex nature of the ORR potential energy landscape and the presence of strong electronic correlations present challenges to atomistic modelling using classical computers. This scenario opens new avenues for the implementation of novel quantum computing workflows to address these molecular systems. Here, we present a pioneering study that combines classical and quantum computational approaches to investigate the ORR on pure platinum and platinum/cobalt surfaces. Our research demonstrates, for the first time, the feasibility of implementing this workflow on the H1-series trapped-ion quantum computer and identify the challenges of the quantum chemistry modelling of this reaction. The results highlight the involvement of strongly correlated species in the cobalt-containing catalyst, suggesting their potential as ideal candidates for showcasing quantum advantage in future applications.