Dual Roles of High-Valence Mo Cation on the Enhanced Electrocatalytic OER Performance of Mixed Multimetal (FeCoNiZrMo) Compounds: Experiment and DFT Insights

The incorporation of high-valence metals into FeCoNi-based oxides is a well-established strategy to enhance the alkaline oxygen evolution reaction (OER). However, the intrinsic mechanism by which high-valence metal cations improve the catalytic activity in materials remains poorly understood. This study explores the dual roles of high-valence Mo cations in boosting the electrocatalytic OER performance of FeCoNiZrMo-based materials (denoted as MMC-Mo<i><sub>n</sub></i>, with <i>n</i> = 0.0, 0.5, 1.0, 1.5, and 2.0 mmol MoCl<sub>5</sub> reagent). A combination of selected area electron diffraction, X-ray spectroscopy analyses, and first-principles calculations reveals that Mo cations facilitate phase transformation and electro-dissolution, which effectively modify the local atomic and electronic structures of the Fe, Co, and Ni active sites. These structural modifications led to a substantial improvement in the OER activity. Notably, the optimized MMC-Mo<sub>1.0</sub> specimen exhibited an overpotential of 253 mV at 10 mA/cm<sup>2</sup>, along with a 6-fold enhancement in turnover frequency compared to MMC-Mo<sub>0.0</sub> at 1.53 V. These findings highlight the dual roles of high-valence Mo cations in enhancing catalytic performance and provide valuable insights into the rational design of high-performance electrocatalysts.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-09-23
DOI
https://doi.org/10.1021/acsami.5c11963
Citations
5
Primary Topic
Electrocatalysts for Energy Conversion
Type
article
Field-Weighted Citation Impact
1.82
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article

Dual Roles of High-Valence Mo Cation on the Enhanced Electrocatalytic OER Performance of Mixed Multimetal (FeCoNiZrMo) Compounds: Experiment and DFT Insights

Yinyan Gong, Can Li, Huanhuan Li, Tao Wang et al.
5 citations
ACS Applied Materials & Interfaces
Electrocatalysts for Energy Conversion
1.82
article

Dual Roles of High-Valence Mo Cation on the Enhanced Electrocatalytic OER Performance of Mixed Multimetal (FeCoNiZrMo) Compounds: Experiment and DFT Insights

Yinyan Gong, Can Li, Huanhuan Li, Tao Wang, Lin Dai, Lengyuan Niu
article en
5 citations

Abstract

The incorporation of high-valence metals into FeCoNi-based oxides is a well-established strategy to enhance the alkaline oxygen evolution reaction (OER). However, the intrinsic mechanism by which high-valence metal cations improve the catalytic activity in materials remains poorly understood. This study explores the dual roles of high-valence Mo cations in boosting the electrocatalytic OER performance of FeCoNiZrMo-based materials (denoted as MMC-Mo<i><sub>n</sub></i>, with <i>n</i> = 0.0, 0.5, 1.0, 1.5, and 2.0 mmol MoCl<sub>5</sub> reagent). A combination of selected area electron diffraction, X-ray spectroscopy analyses, and first-principles calculations reveals that Mo cations facilitate phase transformation and electro-dissolution, which effectively modify the local atomic and electronic structures of the Fe, Co, and Ni active sites. These structural modifications led to a substantial improvement in the OER activity. Notably, the optimized MMC-Mo<sub>1.0</sub> specimen exhibited an overpotential of 253 mV at 10 mA/cm<sup>2</sup>, along with a 6-fold enhancement in turnover frequency compared to MMC-Mo<sub>0.0</sub> at 1.53 V. These findings highlight the dual roles of high-valence Mo cations in enhancing catalytic performance and provide valuable insights into the rational design of high-performance electrocatalysts.

ACS Applied Materials & InterfacesVol. 17(40)
China Jiliang University (CN), Optica (US), Zhejiang University (CN)
Openalex Percentile: Top 14%
Electrocatalysts for Energy Conversion
1.82
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Dual Roles of High-Valence Mo Cation on the Enhanced Electrocatalytic OER Performance of Mixed Multimetal (FeCoNiZrMo) Compounds: Experiment and DFT Insights — Yinyan Gong, Can Li, et al. · ACS Applied Materials & Interfaces (2025) | TGRS Research Map | TGRS