Multidimensional Electrochemistry Decodes the Operando Mechanism of Hydrogen Oxidation

化学 机制(生物学) 电化学 解码 无机化学 物理化学 电极 计算机科学 物理 解码方法 量子力学 电信
作者
Kaicong Yang,Hualong Ma,Renjie Ren,Li Xiao,Wenyong Jiang,Yu Xie,Gongwei Wang,Juntao Lu,Lin Zhuang
出处
期刊:Angewandte Chemie [Wiley]
卷期号:63 (24) 被引量:2
标识
DOI:10.1002/anie.202318389
摘要

Being an efficient approach to the utilization of hydrogen energy, the hydrogen oxidation reaction (HOR) is of particular significance in the current carbon-neutrality time. Yet the mechanistic picture of the HOR is still blurred, mostly because the elemental steps of this reaction are rapid and highly entangled, especially when deviating from the thermodynamic equilibrium state. Here we report a strategy for decoding the HOR mechanism under operando conditions. In addition to the wide-potential-range I-V curves obtained using gas diffusion electrodes, we have applied the AC impedance spectroscopy to provide independent and complementary kinetic information. Combining multidimensional data sources has enabled us to fit, in mathematical rigor, the core kinetic parameter set in a 5-D data space. The reaction rate of the three elemental steps (Tafel, Heyrovsky, and Volmer reactions), as a function of the overpotential, can thus be distilled individually. Such an undocumented kinetic picture unravels, in detail, how the HOR is controlled by the elemental steps on polarization. For instance, at low polarization region, the Heyrovsky reaction is relatively slow and can be ignored; but at high polarization region, the Heyrovsky reaction will surpass the Tafel reaction. Additionally, the Volmer reaction has been the fastest within overpotentials of interest. Our findings not only offer a better understanding of the HOR mechanism, but also lay the foundation for the development of improved hydrogen energy utilization systems.
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
1秒前
2秒前
南瓜咸杏完成签到,获得积分10
2秒前
陈甸甸完成签到,获得积分10
2秒前
韦威风发布了新的文献求助10
3秒前
3秒前
king完成签到,获得积分10
3秒前
qweerrtt发布了新的文献求助10
4秒前
余三浪完成签到,获得积分10
4秒前
5秒前
lixoii发布了新的文献求助20
5秒前
豌豆射手发布了新的文献求助10
6秒前
科研通AI2S应助k7采纳,获得10
6秒前
wszldmn完成签到,获得积分10
6秒前
坚定的亦绿完成签到,获得积分10
7秒前
7秒前
yurh完成签到,获得积分10
7秒前
小朋友完成签到,获得积分10
8秒前
华仔应助小王采纳,获得10
8秒前
彭于晏应助乔乔采纳,获得10
8秒前
8秒前
1199完成签到,获得积分10
8秒前
8秒前
南瓜完成签到 ,获得积分10
9秒前
eric曾完成签到,获得积分10
10秒前
11秒前
11秒前
12秒前
韦威风完成签到,获得积分10
12秒前
请叫我风吹麦浪应助cc采纳,获得30
12秒前
所所应助Ll采纳,获得10
12秒前
阳光的道消完成签到,获得积分10
13秒前
13秒前
13秒前
豌豆射手完成签到,获得积分10
14秒前
14秒前
桑桑发布了新的文献求助10
14秒前
领导范儿应助幸福胡萝卜采纳,获得10
15秒前
明理的小甜瓜完成签到,获得积分10
16秒前
16秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527742
求助须知:如何正确求助?哪些是违规求助? 3107867
关于积分的说明 9286956
捐赠科研通 2805612
什么是DOI,文献DOI怎么找? 1540026
邀请新用户注册赠送积分活动 716884
科研通“疑难数据库(出版商)”最低求助积分说明 709762