Electrode selection framework for oxygen evolution reaction catalysts involving density functional theory and finite element method.

The design of durable and high-performance electrodes for the oxygen evolution reaction (OER) is important for producing green hydrogen water electrolysis. In this work, we present a multiscale modeling framework that effectively integrates Density Functional Theory (DFT) with Finite Element Modeling (FEM) for the electrodes of polymer electrolyte membrane electrolysers. The framework connects atomic-scale mechanisms of the four electrocatalysts with their half-cell-level redox performance. The redox performance of the catalyst was modelled using the FEM. Cyclic voltammograms (CV) of IrO, RuO, Co-Pt, and Ni-Fe are obtained and validated with experimental results. The atomic-scale calculations of all electrocatalysts provide agreeable electronic structure, surface energetics, and reaction intermediates of the electrocatalysts without any experimental input. The half-cell system-level behavior and atomistic characteristics are obtained by linking quantum-level reaction pathways with continuum-scale electrochemical performance of electrodes. The combination of DFT and CV framework helps to compare and identify activity-limiting steps of the catalysts. The cell polarization data obtained using the half-cell studies specific to individual electrode performance are validated with results obtained by the proposed framework. A perovskite-based material is used as a baseline to compare the characteristics of the OER. Our predictive design framework shows RuO as a promising OER catalyst due to its low HOMO-LUMO gap, optimal structure (2.686 Å), acceptable exchange current density (3.3 × 10 A cm) and double layer capacitance (0.36 F m), charge distribution, and enhanced reaction kinetics. The results are in good agreement with the experimental findings reported in the literature.