Exploring a bimetallic catalyst family for hydrogen oxidation with insights into superior activity and durability

Anion exchange membrane fuel cells are limited by the slow kinetics of the alkaline hydrogen oxidation reaction (HOR). Aided by density functional theory combined with fine-tuned machine learning interatomic potential, we establish a family of bimetallic catalysts with controlled surface atomic arrangements to identify the optimal catalysts for HOR. Our theoretical analysis successfully predicts the HOR activity rankings of these catalysts, consistent with the experimental results. RuIr exhibits the highest activity, followed by PtRu, AuIr, PtRh, PtIr, PtAu, RhIr, RuRh, AuRu, and AuRh. These trends correlate with the electron-accepting tendencies and the adsorption strengths of H<sub>2</sub> and OH* on the catalysts. Among all candidates, RuIr emerges as the most active and durable bimetallic catalyst. Furthermore, operando X-ray absorption spectroscopy and electrochemical measurements reveal a strong synergistic effect of RuIr, where Ir exhibits superior electron-accepting tendency and strong H<sub>2</sub> adsorption, while Ru demonstrates strong OH* adsorption, accelerating the alkaline HOR process.

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Publication Details

Journal
Nature Communications
Published
2025-11-25
DOI
https://doi.org/10.1038/s41467-025-65503-7
Citations
1
Primary Topic
Electrocatalysts for Energy Conversion
Type
article
Field-Weighted Citation Impact
0.36

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article

Exploring a bimetallic catalyst family for hydrogen oxidation with insights into superior activity and durability

Rui-Tong Kuo, Liang‐Ching Hsu, K. Y. Lee, Lu‐Yu Chueh et al.
1 citations
Nature Communications
Electrocatalysts for Energy Conversion
0.36
article

Exploring a bimetallic catalyst family for hydrogen oxidation with insights into superior activity and durability

Rui-Tong Kuo, Liang‐Ching Hsu, K. Y. Lee, Lu‐Yu Chueh, Jui‐Tai Lin, Hong‐Kang Tian, Yung‐Tin Pan, Chih‐Wen Pao, Chun‐Wei Chang, Tung‐Han Yang, Chia‐Ying Wu, Shang‐Cheng Lin, Yan-Ying Tsai, I‐Ting Kao
article en
1 citations

Abstract

Anion exchange membrane fuel cells are limited by the slow kinetics of the alkaline hydrogen oxidation reaction (HOR). Aided by density functional theory combined with fine-tuned machine learning interatomic potential, we establish a family of bimetallic catalysts with controlled surface atomic arrangements to identify the optimal catalysts for HOR. Our theoretical analysis successfully predicts the HOR activity rankings of these catalysts, consistent with the experimental results. RuIr exhibits the highest activity, followed by PtRu, AuIr, PtRh, PtIr, PtAu, RhIr, RuRh, AuRu, and AuRh. These trends correlate with the electron-accepting tendencies and the adsorption strengths of H<sub>2</sub> and OH* on the catalysts. Among all candidates, RuIr emerges as the most active and durable bimetallic catalyst. Furthermore, operando X-ray absorption spectroscopy and electrochemical measurements reveal a strong synergistic effect of RuIr, where Ir exhibits superior electron-accepting tendency and strong H<sub>2</sub> adsorption, while Ru demonstrates strong OH* adsorption, accelerating the alkaline HOR process.

Nature CommunicationsVol. 16(1)
National Taiwan University of Science and Technology (TW), National Chung Hsing University (TW), National Tsing Hua University (TW), National Synchrotron Radiation Research Center (TW), National Cheng Kung University (TW)
Ministry of Education, India, National Tsing Hua University, National Cheng Kung University, National Science and Technology Council
Openalex Percentile: Top 36%
Electrocatalysts for Energy Conversion
0.36
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