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调节铜催化剂的酸硬度性质用于选择性硝酸盐到氨的电还原

Tuning the Acid Hardness Nature of Cu Catalyst for Selective Nitrate-to-Ammonia Electroreduction.

作者信息

Wang Ruhan, Jia Shunhan, Wu Limin, Zhang Libing, Song Xinning, Tan Xingxing, Zheng Chaofeng, Li Weixiang, Ma Xiaodong, Qian Qingli, Kang Xinchen, Zhu Qinggong, Sun Xiaofu, Han Buxing

机构信息

Beijing National Laboratory for Molecular Sciences, CAS Laboratory of Colloid and Interface and Thermodynamics, CAS Research/Education Center for Excellence in Molecular Sciences, Center for Carbon Neutral Chemistry, Institute of Chemistry, Chinese Academy of Sciences, Beijing, 100190, China.

School of Chemical Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China.

出版信息

Angew Chem Int Ed Engl. 2025 Apr 7;64(15):e202425262. doi: 10.1002/anie.202425262. Epub 2025 Feb 9.

DOI:10.1002/anie.202425262
PMID:39853855
Abstract

Electrocatalytic nitrate reduction reaction (NORR) in alkaline electrolyte presents a sustainable pathway for energy storage and green ammonia (NH) synthesis. However, it remains challenging to obtain high activity and selectivity due to the limited protonation and/or desorption processes of key intermediates. Herein, we propose a strategy to regulate the acid hardness nature of Cu catalyst by introducing appropriate modifier. Using density functional theory calculations, we firstly identified that the BaO-modified Cu showed optimal Gibbs free energies for key NORR steps, including the protonation of *NO and the desorption of *NH. Experimentally, the BaO-modified Cu catalyst exhibited 97.3 % Faradaic efficiency (FE) for NH with a yield rate of 356.9 mmol h g . It could also maintain high activity across a wide range of applied potentials and nitrate substrate concentrations. Detailed experimental and theoretical studies revealed that the Ba species could modulate the local electronic states of Cu, enhance the electron transfer rate, and optimize the adsorption/protonation/desorption processes of the N-containing intermediates, leading to the excellent catalytic performance for NO -to-NH.

摘要

碱性电解质中的电催化硝酸盐还原反应(NORR)为能量存储和绿色氨(NH₃)合成提供了一条可持续的途径。然而,由于关键中间体的质子化和/或解吸过程有限,要获得高活性和选择性仍然具有挑战性。在此,我们提出了一种通过引入适当的改性剂来调节铜催化剂酸硬度性质的策略。利用密度泛函理论计算,我们首先确定了BaO修饰的Cu对NORR关键步骤表现出最佳的吉布斯自由能,包括NO的质子化和NH₃的解吸。实验上,BaO修饰的Cu催化剂对NH₃的法拉第效率(FE)为97.3%,产率为356.9 mmol h⁻¹ g⁻¹。它还可以在很宽的外加电位和硝酸盐底物浓度范围内保持高活性。详细的实验和理论研究表明,Ba物种可以调节Cu的局部电子态,提高电子转移速率,并优化含氮中间体的吸附/质子化/解吸过程,从而导致对NO₃⁻到NH₃的优异催化性能。

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