Dynamic ligand-vacancy engineering drives metal dimerization for efficient urea electrooxidation

The electrochemical urea oxidation reaction offers environmental benefits by enabling hydrogen generation and nitrogen recycling. However, catalyst instability caused by surface reconstruction remains a challenge. Here, we develop a heteronuclear vacancy-to-bond strategy that achieves both catalytic activation and structural preservation via atomic-level self-optimization. Using Fe-doped bimetallic frameworks, we construct a self-adaptive coordination microenvironment that dynamically generates controllable ligand vacancies while promoting metal dimerization, leading to shortened interatomic distances. The resulting ligand-vacancy-mediated stabilization delivers an low potential of 1.222 V @ 10 mA cm<sup>-2</sup> (188 mV lower than IrO<sub>2</sub>) with 87.7% Faradaic efficiency for nitrogen oxides. Spectroscopic analysis and theoretical calculations reveal that ligand-deficient structure reduces the C-N cleavage energy from 1.33 eV to 0.75 eV and shifts the rate-determining step from chemical C-N cleavage to potential-dependent *NO oxygenation, lowering the overall energy requirement. In industrial-scale electrolyzers, the catalyst sustains 1 A cm<sup>-2</sup> for 100 h with negligible degradation, achieving 13% energy savings over conventional water splitting. This work investigates a dynamic vacancy-to-bond conversion mechanism, offering insights into the design of adaptive electrocatalysts for sustainable energy applications.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2026-03-23
DOI
https://doi.org/10.1038/s41467-026-70919-w
Primary Topic
Electrocatalysts for Energy Conversion
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dynamic ligand-vacancy engineering drives metal dimerization for efficient urea electrooxidation

Yuanyuan Luo, Xiaoya Zhan, Xun Cui, Junjie Zheng et al.
Nature Communications
Electrocatalysts for Energy Conversion
article

Dynamic ligand-vacancy engineering drives metal dimerization for efficient urea electrooxidation

Yuanyuan Luo, Xiaoya Zhan, Xun Cui, Junjie Zheng, Mingjie Wu, Jian Luo, Yingkui Yang
article en

Abstract

The electrochemical urea oxidation reaction offers environmental benefits by enabling hydrogen generation and nitrogen recycling. However, catalyst instability caused by surface reconstruction remains a challenge. Here, we develop a heteronuclear vacancy-to-bond strategy that achieves both catalytic activation and structural preservation via atomic-level self-optimization. Using Fe-doped bimetallic frameworks, we construct a self-adaptive coordination microenvironment that dynamically generates controllable ligand vacancies while promoting metal dimerization, leading to shortened interatomic distances. The resulting ligand-vacancy-mediated stabilization delivers an low potential of 1.222 V @ 10 mA cm<sup>-2</sup> (188 mV lower than IrO<sub>2</sub>) with 87.7% Faradaic efficiency for nitrogen oxides. Spectroscopic analysis and theoretical calculations reveal that ligand-deficient structure reduces the C-N cleavage energy from 1.33 eV to 0.75 eV and shifts the rate-determining step from chemical C-N cleavage to potential-dependent *NO oxygenation, lowering the overall energy requirement. In industrial-scale electrolyzers, the catalyst sustains 1 A cm<sup>-2</sup> for 100 h with negligible degradation, achieving 13% energy savings over conventional water splitting. This work investigates a dynamic vacancy-to-bond conversion mechanism, offering insights into the design of adaptive electrocatalysts for sustainable energy applications.

Nature Communications
Wuhan Textile University (CN)
Openalex Percentile: Top 15%
Electrocatalysts for Energy Conversion
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.