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

Area of Science:

• Materials Science
• Electrochemistry
• Computational Chemistry

Background:

• Durable, high-performance electrodes are essential for efficient water electrolysis and green hydrogen production.
• The oxygen evolution reaction (OER) is a critical bottleneck in water electrolysis.

Purpose of the Study:

• To develop and validate a multiscale modeling framework integrating DFT and FEM for OER electrode design.
• To connect atomic-scale catalyst mechanisms with macro-scale electrochemical performance.
• To identify promising electrocatalysts for OER in polymer electrolyte membrane electrolyzers.

Main Methods:

• Integrated Density Functional Theory (DFT) with Finite Element Modeling (FEM) for multiscale analysis.
• Modeled redox performance of IrO2, RuO2, Co-Pt, and Ni-Fe catalysts using FEM.
• Obtained and validated cyclic voltammograms (CV) against experimental data.
• Linked quantum-level reaction pathways with continuum-scale electrochemical performance.

Main Results:

• The integrated DFT-FEM framework accurately predicted catalyst performance and validated experimental results.
• Atomic-scale calculations provided electronic structure and energetics without experimental input.
• RuO2 demonstrated superior OER catalytic activity due to its favorable electronic and structural properties, including a low HOMO-LUMO gap and high exchange current density.

Conclusions:

• The multiscale modeling framework effectively predicts OER catalyst performance and identifies limiting steps.
• RuO2 is a highly promising electrocatalyst for OER applications, offering enhanced kinetics and durability.
• This predictive approach accelerates the design of efficient electrodes for green hydrogen production.