Computational insights on potential dependence of electrocatalytic synthesis of ammonia from nitrate

被引:16
|
作者
Jing, Huijuan [1 ,2 ]
Long, Jun [1 ]
Li, Huan [1 ,2 ]
Fu, Xiaoyan [1 ]
Xiao, Jianping [1 ,2 ]
机构
[1] Chinese Acad Sci, Dalian Inst Chem Phys, State Key Lab Catalysis, Dalian Natl Lab Clean Energy, Dalian 116023, Liaoning, Peoples R China
[2] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
来源
CHINESE JOURNAL OF CATALYSIS | 2023年 / 48卷
基金
中国国家自然科学基金;
关键词
Electrochemical ammonia synthesis; Density functional theory calculation; Reaction phase diagram; Activity; Selectivity; TOTAL-ENERGY CALCULATIONS; ELECTROCHEMICAL REDUCTION; FUTURE; SOLIDS; TRENDS; ATOMS; WATER; COHP; GAS;
D O I
10.1016/S1872-2067(23)64413-4
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
Electrochemical nitrate reduction reaction (eNO3RR) has been considered as an alternative route for decentralized ammonia (NH3) synthesis. However, a major challenge is products selectivity at low overpotentials, namely, the competition between nitrite (HNO2) and ammonia. Herein, we em-ployed a single-atom catalyst (FeN4) as model to study the competitive mechanism of NH3 and HNO2 by density functional theory calculations. It was found the optimal paths for ammonia and nitrite productions share a key intermediate (NO2*), whose adsorption structures and preference in the following conversion determines the selectivity. We have incorporated potential-dependent barri-ers and microkinetic modeling to understand the Faradaic efficiency at different potentials. Our results are in good agreement with the experimental trend of Faradaic efficiencies of NH3 and HNO2, which can be rationalized well by the charge transfer coefficient (0) for NO2* protonation to cisH-NO2* with respect to that to HNO2. A low selectivity of ammonia production at small overpotentials can be ascribed to a kinetic issue. The electron localization function and crystal orbital Hamilton population were analyzed on the initial and transition states for NO2* protonation to cisHNO2* and HNO2. The computational mechanistic insights can help to design new catalyst for eNO3RR highly active and selective to NH3.& COPY; 2023, Dalian Institute of Chemical Physics, Chinese Academy of Sciences. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:205 / 213
页数:9
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