RESEARCH Highlight #2
Featured Article: Selectivity trends in two-electron oxygen reduction: insights from two-dimensional materials
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Using first-principles calculations and descriptor-based screening, we developed a predictive framework that accelerates the discovery of highly selective electrocatalysts for sustainable hydrogen peroxide production.
Highlights
- Developed and validated a thermodynamic selectivity descriptor (螖螖G) for predicting H2O2 selectivity in the two-electron oxygen reduction reaction (2e-ORR).
- Established quantitative selectivity trends by linking adsorption energetics of key ORR intermediates to H2O2 formation.
- Applied high-throughput DFT screening across binary alloys, carbon-based materials, boron nitrides, and single-atom catalysts.
- Screened thousands of active sites to identify catalysts that simultaneously exhibit high activity and high selectivity.
- Revealed that high activity alone does not guarantee H2O2 selectivity, particularly for carbon-based electrocatalysts.
- Discovered only a small subset of active sites capable of achieving both efficient oxygen reduction and selective H2O2 production.
- Established 螖螖G as a predictive descriptor for accelerating computational discovery of next-generation peroxide electrocatalysts.