(308b) Discovery of Stable and Active Iridium-Molybdenum Oxide Electrocatalyst for the Oxygen Evolution Reaction Using Bayesian Optimization

Electrochemical water splitting is a promising avenue for sustainable hydrogen production.¹ These systems require high efficiency electrocatalysts (ECs) to complete the oxygen and hydrogen evolution half reactions (OER and HER). Designing EC’s for OER presents a complex problem as there are significant tradeoffs between EC activity, stability, and cost, as the best performing electrocatalysts consist of precious Ir- and Ru- based oxides. Doping Ir-based oxides to reduce precious metal content in EC’s while maintaining high performance and stability has garnered significant attention. Identifying dopant materials that provide highly active and stable mixed oxide EC’s; however, has proven to be challenging.²

We developed a comprehensive computational framework for determining which elements will create active and stable OER EC’s when combined with Ir. The framework uses a machine-learning-aided (ML) Bayesian optimization paired with density functional theory (DFT) calculations to assess the stability and activity of Ir-doped mixed oxide materials. Using this analysis, we found that IrMo is a promising mixed-oxide candidate for OER. We fabricated planar samples of this mixed oxide material and tested them to assess the electrocatalytic activity and stability to rigorously compare them to state of the art Ir based electrocatalysts. We found that IrMo is an excellent OER EC as it had a lower overpotential than the conventional Ir control sample, maintained low dissolution values of Ir under reaction conditions, and the dopant material remained well mixed after steady state testing. Computational results show that improved IrMo performance may be attributed to the participation of lattice oxygen on select surfaces of Ir_0.5Mo_0.5O₂ and Ir_0.5Mo_0.5O₃. Overall, this contribution proposes a novel electrocatalyst material and a comprehensive ML-aided computational workflow for evaluating the fitness of transition metal dopants for Ir-based OER EC’s.

1. Reier, T.; et.al . Energy Mat. 2017
2. McCrory, C. C. L.; et al. Am. Chem. Soc. 2015