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二维 MOF 上通过 NO 还原进行电化学氨合成。

Electrochemical Ammonia Synthesis via NO Reduction on 2D-MOF.

机构信息

School of Chemistry, Biology and Materials Science, East China University of Technology, Nanchang, 330031, China.

State Key Laboratory of Silicate Materials for Architectures, Wuhan University of Technology, Wuhan, 430070, China.

出版信息

Chemphyschem. 2022 Feb 16;23(4):e202100785. doi: 10.1002/cphc.202100785. Epub 2022 Jan 12.

DOI:10.1002/cphc.202100785
PMID:34845837
Abstract

Developing new catalysts that effectively promote electrocatalytic NO reduction (ENOR) is a very important industrial field. A two-dimensional (2D) metal-organic framework (MOF) with hexaaminobenzene (HAB) ligands (TM-HAB MOF, TM=Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Mo, Ru, Rh and Pd) as an electrocatalyst for ENOR was systematically explored in this work by means of well-defined density functional theory (DFT) calculations. We predicted the impact of the coordination structure of different MOFs on its catalytic performance and found that the suitable candidates are Co- and Rh-HAB MOFs due to moderate binding strength between NO and substrates. Further calculations indicated that Co-HAB MOF has the best ENOR catalytic activity with a limiting potential of - 0.26 V toward NH production at low NO coverage, yet NO reduction to N O at high NO coverage was limited due to high limiting potential. The scaling relationship with a good correlation coefficient between several electronic properties and the adsorption Gibbs free energy change of *NO (ΔG ) were found, which implies that ΔG can be used as a simple descriptor for screening out suitable electrocatalysts. This work offers a new paradigm for ENOR toward NH production under ambient conditions.

摘要

开发能有效促进电催化 NO 还原(ENOR)的新型催化剂是一个非常重要的工业领域。本工作通过明确的密度泛函理论(DFT)计算,系统地研究了具有六亚甲基苯(HAB)配体的二维(2D)金属有机骨架(MOF)作为 ENOR 的电催化剂(TM-HAB MOF,TM=Ti、V、Cr、Mn、Fe、Co、Ni、Cu、Mo、Ru、Rh 和 Pd)。我们预测了不同 MOF 的配位结构对其催化性能的影响,发现 Co- 和 Rh-HAB MOF 是合适的候选者,因为 NO 和底物之间的结合强度适中。进一步的计算表明,Co-HAB MOF 在低 NO 覆盖度下对 NH3 生成具有最佳的 ENOR 催化活性,其极限电势为-0.26 V,但由于高极限电势,NO 还原为 N O 的反应受到限制。我们发现几个电子性质与*NO(ΔG)吸附吉布斯自由能变化之间存在良好相关性的标度关系,这表明ΔG 可用作筛选合适电催化剂的简单描述符。这项工作为在环境条件下实现氨的 ENOR 提供了一个新的范例。

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引用本文的文献

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Nanoengineering Metal-Organic Frameworks and Derivatives for Electrosynthesis of Ammonia.用于电合成氨的纳米工程金属有机框架及其衍生物
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2
Fundamentals, rational catalyst design, and remaining challenges in electrochemical NO reduction reaction.电化学NO还原反应的基础、合理的催化剂设计及尚存的挑战
iScience. 2023 Jul 20;26(8):107410. doi: 10.1016/j.isci.2023.107410. eCollection 2023 Aug 18.
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Descriptors and graphical construction for design of efficient and selective single atom catalysts for the eNRR.
用于电化学氮还原反应(eNRR)的高效且选择性单原子催化剂设计的描述符和图形构建
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