Accelerated Quantum Chemical Simulations for Oxygen Evolution Reaction Catalysts Using “PreFerred Potential” (PFP)—A Pathway to Efficient Material Design

PEM water electrolysis is garnering interest as a promising method for converting and storing renewable energy into hydrogen fuel. Designing efficient the oxygen evolution reaction (OER)catalysts that can operate under the acidic conditions of PEM systems is recognized as a significant challenge. An ideal OER catalyst must exhibit not only high reaction activity and electrical conductivity but also exceptional corrosion resistance. However, candidates that satisfy all these criteria are exceedingly rare. Rutile-IrO2 stands out as the leading catalyst for OER within PEM electrolyzers, yet the scarcity of iridium limits its practicality for large-scale industrial applications. To address this gap, we are using state-of-the-art computational chemistry methods to explore OER catalysts with alternating Ir that exhibit both enhanced activity, and durability.<br/>The realm of quantum chemical simulations for heterogeneous catalysis, including OER, has seen remarkable progress due to the relentless contributions of eminent quantum chemists [1-3]. These simulations play a crucial role in propelling computational research forward, aiming to boost catalyst performance. Nonetheless, the substantial computational resources required for such quantum chemical calculations pose a significant hurdle, slowing the advancement of simulation-driven material development.<br/>In this study, we have employed the PreFerred Potential (PFP), a neural network potential which is based on density functional theory datasets [4]. PFP is implemented in MATLANTIS® software and is described as a quasi-atomic potential, which demands fewer computational resources, thus enabling high-precision calculations and remarkably rapid solutions when used for structural relaxation. We have conducted overpotential calculations and screening using computational data for oxygen evolution reaction (OER) catalysts under acidic conditions. Our findings confirm that PFP possesses an interatomic potential with high computational accuracy, comparable to the first-principles calculations, for evaluating OER overpotentials.<br/>Focusing on rutile-RuO2 as, a well-reported candidate material that does not contain Ir, we have performed hetero-metallic doping calculations using PFP. These calculations elucidate the numerical reduction in overpotential due to doping and investigate the appropriate doping levels. Furthermore, we have evaluated the activity of pyrochlore-structured materials containing Ru, identifying better material combinations through overpotential calculations. For each composition, we assessed the surface stability using surface Pourbaix diagrams and compared overpotentials based on adsorption sites, reaction pathways, and molecular orientations [2]. These extensive calculations were made possible by the significant acceleration of structural optimization computations provided by PFP.<br/>Our presentation will suggest effective metal composition ratios for various oxide surfaces, such as rutile, pyrochlore, etc., and demonstrate that PFP is an effective method for rapidly screening potential catalyst compositions. We will illustrate how PFP can be utilized in simulation calculations essential for the theoretical understanding of catalyst activity, thereby offering a valuable tool for the expedited discovery of promising catalyst compositions.<br/>[1] J. Rossmeisl, et al., J. Electroanal. Chem. 607, 83–89 (2007).<br/>[2] H. Hansen, et al., Phys. Chem. Chem. Phys.,10, 3722-3730(2008).<br/>[3] G. T. Gunasooriya and J. K. Nørskov, ACS Energy Lett., 5, 3778−3787(2020).<br/>[4] S. Takamoto, et al. Nat Commun 13, 2991 (2022).