The oxygen path mechanism from Ni-OOOO-Fe species in oxygen evolution reaction on NiFe layered double hydroxides

层状双氢氧化物 催化作用 氧气 析氧 机制(生物学) 双层 路径(计算) 化学 材料科学 化学工程 无机化学 冶金 物理 计算机科学 物理化学 有机化学 复合材料 电化学 电极 程序设计语言 量子力学 工程类
作者
Ang Cao,Xu Wang,Han‐Dong Sun,Zheheng Jiang,Fengmei Wang,Yaping Li,Xiaoming Sun
出处
期刊:Molecular Catalysis [Elsevier BV]
卷期号:555: 113864-113864
标识
DOI:10.1016/j.mcat.2024.113864
摘要

The oxygen evolution reaction (OER) with large overpotential is the bottleneck of the whole water electrolysis process. NiFe layered double hydroxide (NiFe-LDH) represent one of the potential catalysts for OER in alkaline media. For the LDH, it was well established that both adsorption evolution mechanism and lattice oxygen mechanism could appear at a single site, but Ni-OOOO-Fe species would provide a different OO path mechanism at dual-O sites due to the complexity and diversity of LDH surface. Here, using first-principles study, tetra-oxygen path mechanism (t-OPM) was proposed to investigate the OER performance of NiFe-LDH by considering surface 2O were as active sites (Oac) and other O as environment O (Oev) with different exposed degrees (0–6). It was found that the optimal performance of the NiFe-LDH surface could be achieved when 2 ∼ 4 Oev were exposed under the explored mechanism in different paths (path 1 and path 2) with overpotential η = 0.07 ∼ 0.35 V, and path 1 was slightly better than path 2. At the same time, the solvation effect (SE) was used to study the effect on the OER performance, the results showed that SE had a little influence on the case of 2 ∼ 4 Oev exposed while had a large effect on the other cases. The detailed analysis of the electronic structure showed a smaller difference Δε between the energy Fe-3d band center and Oac-2p, which imply the stronger the interaction between them. Thus, the t-OPM was feasible in OER on NiFe-LDH. It was anticipated that our work could provide a fresh perspective on the understanding of the excellent OER performance of LDH in alkaline environment, which was complementary to the traditional mechanism to some extent.
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
Owen应助赫赫采纳,获得10
刚刚
daomaihu发布了新的文献求助100
刚刚
cqk123完成签到,获得积分10
1秒前
123发布了新的文献求助10
1秒前
2秒前
云阳发布了新的文献求助10
2秒前
SciGPT应助马昌进采纳,获得10
3秒前
英吉利25发布了新的文献求助10
5秒前
yzy应助胡一菲采纳,获得10
5秒前
脑洞疼应助mouhao1采纳,获得30
5秒前
gqw3505完成签到,获得积分10
5秒前
6秒前
科研通AI6.4应助dom采纳,获得10
6秒前
6秒前
9秒前
11秒前
11秒前
彭于晏应助rain采纳,获得10
11秒前
CCccc完成签到 ,获得积分10
13秒前
大模型应助西西马小茄采纳,获得10
13秒前
科研通AI6.2应助Exhit采纳,获得10
13秒前
义气的博涛完成签到,获得积分10
14秒前
16秒前
打打应助一盏壶采纳,获得10
16秒前
没头发完成签到,获得积分10
16秒前
渡人舟应助空白山采纳,获得10
16秒前
活力甜瓜完成签到,获得积分20
17秒前
开心的中心完成签到 ,获得积分10
18秒前
19秒前
19秒前
20秒前
20秒前
20秒前
Triumph完成签到 ,获得积分10
22秒前
22秒前
22秒前
烟花应助Sofia采纳,获得10
22秒前
22秒前
董晴发布了新的文献求助10
22秒前
JamesPei应助科研通管家采纳,获得10
23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
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
Additive Manufacturing Design and Applications (ASM Handbook, Volume 24A) 500
Variations: A More Diverse Picture of Contemporary Art 400
Induction Heating and Heat Treatment (ASM Handbook, Volume 4C) 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7589064
求助须知:如何正确求助?哪些是违规求助? 9167035
关于积分的说明 19620721
捐赠科研通 7168809
什么是DOI,文献DOI怎么找? 3267111
关于科研通互助平台的介绍 2432031
邀请新用户注册赠送积分活动 2259231