Computational Insights on Structural Sensitivity of Cobalt in NO Electroreduction to Ammonia and Hydroxylamine

化学 羟胺 氨生产 选择性 催化作用 质子化 吸附 无机化学 电子转移 金属 光化学 物理化学 有机化学 离子
作者
Pu Guo,Dong Luan,Huan Li,Lin Li,Shaoxue Yang,Jianping Xiao
出处
期刊:Journal of the American Chemical Society [American Chemical Society]
卷期号:146 (20): 13974-13982 被引量:61
标识
DOI:10.1021/jacs.4c01986
摘要

It has been reported that it was selective to produce ammonia on metallic cobalt in the electrocatalytic nitric oxide reduction reaction (eNORR), where hexagonal close-packed (hcp) cobalt outperforms face-centered cubic (fcc) cobalt. However, hydroxylamine is more selectively produced on a cobalt single-atom catalyst (Co-SAC). Herein, we uncover the structural sensitivity over hcp-Co, fcc-Co, and Co-SAC in eNORR by employing a recently developed constant potential simulation method and microkinetic modeling. It was found that the superior activity for ammonia production on hcp-Co can be attributed to its facile electron and proton transfer and a stronger lateral suppression effect from NO* over fcc-Co. The exceptional hydroxylamine selectivity on Co-SAC is due to the modified electronic structure, namely, a positively charged active center. It was found that it is more favorable to produce NOH* over hcp-Co and fcc-Co, while HNO* is more preferable on Co-SAC, which are firmly correlated with the vertical and strong NO adsorption on the former and the moderate adsorption on the latter. In other words, a key factor for selectivity control is the first step of NO* protonation. Therefore, the local structure and electronic structure of the catalysts can be critical in regulating the activity and selectivity in eNORR.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
李健应助科研通管家采纳,获得10
刚刚
刚刚
酷波er应助科研通管家采纳,获得10
刚刚
刚刚
刚刚
烟花应助科研通管家采纳,获得10
刚刚
1秒前
Hello应助yan采纳,获得10
1秒前
1秒前
Hello应助义气溪流采纳,获得10
1秒前
研友_VZGVzn发布了新的文献求助20
3秒前
3秒前
多多发布了新的文献求助10
3秒前
the_coco应助123采纳,获得80
3秒前
BanghaoWei完成签到,获得积分10
4秒前
老温完成签到,获得积分10
4秒前
YY发布了新的文献求助30
4秒前
Tinger完成签到,获得积分10
5秒前
Renaissance完成签到 ,获得积分10
5秒前
寒冷的慕晴完成签到,获得积分10
6秒前
6秒前
SHHG完成签到,获得积分10
7秒前
朱昕民发布了新的文献求助10
8秒前
8R60d8应助felix采纳,获得10
8秒前
Ryin发布了新的文献求助10
9秒前
踏实的代曼完成签到,获得积分10
9秒前
Quriky完成签到 ,获得积分10
10秒前
77完成签到 ,获得积分10
10秒前
烟里戏完成签到,获得积分10
11秒前
阿秋菊发布了新的文献求助10
11秒前
12秒前
13秒前
平常汉堡完成签到,获得积分10
13秒前
14秒前
15秒前
懵懂的冰凡完成签到 ,获得积分10
15秒前
16秒前
17秒前
18秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Essentials of Carbohydrate Chemistry and Biochemistry, 4th Edition 600
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Rosenblum, Global Change Biology 500
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 化学工程 工程类 有机化学 物理 复合材料 生物化学 内科学 细胞生物学 基因 遗传学 免疫学 冶金 光电子学 癌症研究
热门帖子
关注 科研通微信公众号,转发送积分 7771510
求助须知:如何正确求助?哪些是违规求助? 9314249
关于积分的说明 20337899
捐赠科研通 7356891
什么是DOI,文献DOI怎么找? 3316706
关于科研通互助平台的介绍 2465322
邀请新用户注册赠送积分活动 2331700