化工进展 ›› 2023, Vol. 42 ›› Issue (4): 1797-1810.DOI: 10.16085/j.issn.1000-6613.2022-1042

• 工业催化 • 上一篇    下一篇

电催化氮还原合成氨MOF基催化剂研究进展

郭朋举1,2(), 何小波1,2, 银凤翔1,2()   

  1. 1.常州大学石油化工学院,江苏 常州 213164
    2.江苏省绿色催化材料与技术重点实验室(常州大学),江苏 常州 213164
  • 收稿日期:2022-06-06 修回日期:2022-10-02 出版日期:2023-04-25 发布日期:2023-05-08
  • 通讯作者: 银凤翔
  • 作者简介:郭朋举(1992—),男,博士研究生,研究方向为电催化。E-mail:ppjuguo086@163.com
  • 基金资助:
    国家自然科学基金(22078027)

Research progress in MOF-based catalysts for electrocatalytic nitrogen reduction to ammonia

GUO Pengju1,2(), HE Xiaobo1,2, YIN Fengxiang1,2()   

  1. 1.College of Petrochemical Engineering, Changzhou University, Changzhou 213164, Jiangsu, China
    2.Jiangsu Key laboratory of Advanced Catalytic Materials and Technology, Changzhou University, Changzhou 213164, Jiangsu, China
  • Received:2022-06-06 Revised:2022-10-02 Online:2023-04-25 Published:2023-05-08
  • Contact: YIN Fengxiang

摘要:

室温下电催化氮还原合成氨(nitrogen reduction reaction,NRR)因其较低的能耗而受到广泛关注。到目前为止,设计高效电催化剂以提高NRR性能是研究重点。其中,金属有机骨架(metal organic framework,MOF)及衍生材料因其独特的多孔结构和可控成分等优势促进了其在气体捕获、分离和催化中的应用。本文首先讨论NRR的反应机制,然后重点讨论MOF及衍生材料用作NRR电催化剂的研究进展,最后,对MOF基NRR电催化剂的设计策略、存在问题及NRR催化面临挑战进行了总结与展望。 此外,文中指出:① 自支撑MOF基电催化剂的合理设计对NRR性能有质的提升;② 机器学习、DFT计算及原位测试技术的有效结合对NRR机理、催化剂的高效设计及筛选等具有重要指导意义。因此这些也将成为NRR催化未来研究趋势。

关键词: 电化学, 催化剂, 还原, 合成, 金属-有机框架

Abstract:

The production of ammonia by electrocatalytic nitrogen reduction reaction (NRR) at room temperature has attracted extensive attention due to its low energy consumption. So far, the research focus is to design highly efficient electrocatalysts. Metal organic framework (MOF) and their derivatives have wide applications in gas capture, separation, and catalysis due to their unique porous structure and controllable compositions. This review first discusses the mechanism of NRR, and then focuses on the research progress of NRR electrocatalysts of MOF and the derived materials. Finally, we summarize and prospect the design strategy, existing problems of the MOF based NRR electrocatalysts and the challenges in NRR catalysis. In addition, this review points out that: ① The reasonable design of self-supporting MOF electrocatalyst can substantially improve the NRR performance; ② The effective combination of machine learning, DFT calculation and in situ testing technology has important guiding significance for NRR mechanism study, efficient design and screening of catalysts, etc., which will become the future research trends of NRR catalysis.

Key words: electrochemistry, catalyst, reduction, synthesis, metal organic frameworks

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