金属有机骨架
金属
纳米技术
电催化剂
材料科学
化学
组合化学
电化学
冶金
有机化学
电极
物理化学
吸附
作者
KunPeng Yang,Yuanjun Liu,Yingxin Wang,Yuxuan Jiang,Guoxing Zhu,Ran Wang,Huan Pang
出处
期刊:
日期:2025-08-12
卷期号:1 (1)
被引量:6
标识
DOI:10.1007/s44422-025-00006-6
摘要
Electrooxidation reactions play pivotal roles in sustainable energy conversion and environmental remediation. Metal–organic frameworks (MOFs), characterized by highly tunable structures, large surface areas, and atomically dispersed active sites, have demonstrated significant promise as electrocatalysts in these reactions. MOFs are composed of metal ions or clusters coordinated with organic ligands. This review systematically summarizes recent advances in MOF-based and MOF-derived electrocatalysts for electrooxidation reactions. These reactions include oxygen evolution reaction (OER), hydrogen oxidation reaction (HOR), alcohol oxidation reaction (e.g., methanol, glycerol, ethanol), urea oxidation reaction (UOR), and glucose oxidation reaction (GOR). Particular attention is paid to the correlation between MOFs structure and catalytic performance, covering critical aspects such as metal node engineering, ligand functionality modification, and composite formation strategies that promote activity, selectivity, and durability. Mechanistic insights into each reaction system are reviewed, highlighting how reaction pathways vary with conditions and catalyst design. Despite notable achievements, challenges remain, such as insufficient electrochemical stability and difficulties in controlling active site exposure and transformation under operating conditions. We discuss future research directions, including the development of robust MOFs with enhanced conductivity and long-term stability, integration with synergistic materials, and the application of in situ characterization and computational modeling to guide rational catalyst design. This review aims to provide a comprehensive reference for the rational design and practical deployment of MOF-based electrocatalysts in next-generation electrooxidation technologies.
科研通智能强力驱动
Strongly Powered by AbleSci AI