Recent advances in understanding surface reconstruction for oxygen evolution reaction electrocatalysts: insights from...

Area of Science:

• Materials Science
• Electrochemistry
• Computational Chemistry

Background:

• Oxygen evolution reaction (OER) electrocatalysts often operate via dynamically transformed interfacial phases, not their as-synthesized structures.
• Surface reconstruction under anodic conditions is a critical phenomenon influencing OER performance.
• Density functional theory (DFT) has become indispensable for understanding these complex surface transformations.

Purpose of the Study:

• To review recent advancements in DFT modeling of OER-related surface reconstruction.
• To elucidate the factors initiating and governing surface reconstruction pathways.
• To highlight the shift from static catalyst screening to understanding dynamic surface evolution.

Main Methods:

• Review of DFT studies on OER energetics, adsorbate evolution, and lattice-oxygen mechanisms.
• Analysis of reconstruction initiation factors: high-valence states, covalency, defects, ion mobility, and environment.
• Examination of reconstruction pathways across various material classes (non-oxides, oxides, oxyhydroxides).

Main Results:

• DFT successfully links adsorption thermodynamics, electronic structure, defects, and dissolution to reconstructed active surfaces.
• Reconstruction is driven by coupled factors like high-valence states, metal-oxygen covalency, oxygen vacancies, and ion mobility.
• DFT distinguishes precursor materials from the true operative surfaces and reveals mechanistic shifts.

Conclusions:

• Surface reconstruction is a fundamental aspect of OER electrocatalysis, significantly altering material behavior.
• DFT provides crucial insights into the mechanisms and driving forces of surface reconstruction.
• Future DFT modeling should focus on dynamic, realistic OER conditions for predictive catalyst design.