Hydrogen has emerged as a promising energy source for low-carbon and sustainable mobility purposes. However, its applications are still limited by modest conversion efficiency in the electrocatalytic oxygen reduction reaction (ORR) within fuel cells. The complex nature of the ORR 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. Here, we present a state-of-the-art study that combines classical and quantum computational approaches to investigate ORR on platinum-based 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 great potentiality of quantum computers in solving notoriously difficult systems with strongly correlated electronic structures and suggest platinum/cobalt as ideal candidate for showcasing quantum advantage in future applications.

氢气已成为一种很有前途的低碳和可持续交通能源。然而，其应用仍然受到燃料电池内电催化氧还原反应 （ORR） 中适度转换效率的限制。ORR 的复杂性和强电子相关性的存在对使用经典计算机的原子建模提出了挑战。此方案为实施新型量子计算工作流开辟了新途径。在这里，我们提出了一项最先进的研究，该研究结合了经典和量子计算方法来研究铂基表面的 ORR。我们的研究首次证明了在 H1 系列囚禁离子量子计算机上实施该工作流程的可行性，并确定了该反应的量子化学建模的挑战。结果突出了量子计算机在解决具有强相关电子结构的众所周知的困难系统方面的巨大潜力，并表明铂/钴是在未来应用中展示量子优势的理想候选者。