ArticleAngewandte Chemie (International ed. in English)2025
Self-optimizing Cobalt Tungsten Oxide Electrocatalysts toward Enhanced Oxygen Evolution in Alkaline Media.
Article in Angewandte Chemie (International ed. in English), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Sustainable Ammonia Electrosynthesis Coupled With Glycerol Valorization via an Adaptive Tri-Component Catalyst.Angewandte Chemie (International ed. in English) · 2026Article
- Reductive Nitrogen Species Activation via Pulsed Electrolysis: Recent Advances and Future Prospects.Angewandte Chemie (International ed. in English) · 2025Review
- Self-optimizing Cobalt Tungsten Oxide Electrocatalysts toward Enhanced Oxygen Evolution in Alkaline Media.Angewandte Chemie (International ed. in English) · 2025Article
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Authors and funding
17 authors.
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Abstract
Self-optimizing mixed metal oxides represent a novel class of electrocatalysts for the advanced oxygen evolution reaction (OER). Here, we report self-assembled cobalt tungsten oxide nanostructures on a lab-synthesized copper oxide substrate through a single-step deposition approach. The resulting composite exhibits remarkable self-optimization behavior, shown by significantly reduced overpotentials and enhanced current densities, accompanied with substantial increase in OER kinetics, electrocatalytically active surface area, surface wettability, and electrical conductivity. Under operating conditions, interfacial restructuring of the electrocatalyst reveals the in situ formation of oxidized cobalt species as the true active site. Complementary density functional theory (DFT) calculations further demonstrate the formation of *OOH intermediate as the rate-determining step of OER, and highlight the adaptive binding of oxygen intermediates, which transitions from tungsten to cobalt site during OER process. Our study provides a fundamental understanding of the self-optimization mechanism and advances the knowledge-driven design of efficient water-splitting electrocatalysts.
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