Co–Fe–P Nanosheet Arrays as a Highly Synergistic and Efficient Electrocatalyst for Oxygen Evolution Reaction

电催化剂 塔菲尔方程 析氧 过电位 纳米片 化学 双金属片 分解水 化学工程 电解水 电解 电化学 催化作用 制氢 纳米技术 无机化学 电极 材料科学 物理化学 有机化学 电解质 光催化 工程类
作者
Yanyu Xie,Huanfeng Huang,Zhuodi Chen,Zhujie He,Zhixiang Huang,Shunlian Ning,Yanan Fan,Mihail Bãrboiu,Jianying Shi,Dawei Wang,Cheng‐Yong Su
出处
期刊:Inorganic Chemistry [American Chemical Society]
卷期号:61 (21): 8283-8290 被引量:27
标识
DOI:10.1021/acs.inorgchem.2c00727
摘要

The rational design and synthesis of highly efficient electrocatalysts for oxygen evolution reaction (OER) is of critical importance to the large-scale production of hydrogen by water electrolysis. Here, we develop a bimetallic, synergistic, and highly efficient Co–Fe–P electrocatalyst for OER, by selecting a two-dimensional metal–organic framework (MOF) of Co-ZIF-L as the precursor. The Co–Fe–P electrocatalyst features pronounced synergistic effects induced by notable electron transfer from Co to Fe, and a large electrochemical active surface area achieved by organizing the synergistic Co–Fe–P into hierarchical nanosheet arrays with disordered grain boundaries. Such features facilitate the generation of abundant and efficiently exposed Co 3+ sites for electrocatalytic OER and thus enable Co–Fe–P to deliver excellent activity (overpotential and Tafel slope as low as 240 mV and 36 mV dec –1, respectively, at a current density of 10 mA cm –2 in 1.0 M KOH solution). The Co–Fe–P electrocatalyst also shows great durability by steadily working for up to 24 h. Our work thus provides new insight into the development of highly efficient electrocatalysts based on nanoscale and/or electronic structure engineering.
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
CipherSage应助闲出屁国公主采纳,获得10
刚刚
大模型应助青塘龙仔采纳,获得10
1秒前
诗谙完成签到,获得积分20
1秒前
可爱的函函应助青塘龙仔采纳,获得10
2秒前
FashionBoy应助青塘龙仔采纳,获得10
2秒前
CipherSage应助青塘龙仔采纳,获得10
2秒前
ChemPu发布了新的文献求助10
2秒前
上官若男应助青塘龙仔采纳,获得10
2秒前
小马甲应助青塘龙仔采纳,获得10
2秒前
3秒前
sugar应助青塘龙仔采纳,获得10
3秒前
爆米花应助青塘龙仔采纳,获得10
3秒前
aimme应助青塘龙仔采纳,获得10
3秒前
赘婿应助青塘龙仔采纳,获得10
3秒前
4秒前
研友_VZG7GZ应助2y采纳,获得10
4秒前
应然忆完成签到 ,获得积分10
5秒前
5秒前
ZhangLetian完成签到,获得积分10
5秒前
6秒前
lalalxx完成签到,获得积分10
9秒前
9秒前
9秒前
斯文败类应助春风十里采纳,获得10
9秒前
10秒前
10秒前
健壮的秋寒完成签到,获得积分10
10秒前
10秒前
GT发布了新的文献求助10
11秒前
11秒前
11秒前
知性的冰棍完成签到,获得积分10
11秒前
11秒前
12秒前
12秒前
youyuguang发布了新的文献求助10
12秒前
molihuakai应助舒适沛珊采纳,获得10
13秒前
光头强发布了新的文献求助10
13秒前
14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
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The Effective Clinical Neurologist 3ed 500
The Great Hymn to Šamaš 500
Moody's Ratings Rising AI spending narrows the gap, but US hyperscalers retain edge over Chinese peers 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 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 7696327
求助须知:如何正确求助?哪些是违规求助? 9256459
关于积分的说明 20002785
捐赠科研通 7270631
什么是DOI,文献DOI怎么找? 3292686
关于科研通互助平台的介绍 2448337
邀请新用户注册赠送积分活动 2298383