Applications of Metal–Organic Frameworks and Their Derivatives in Electrochemical CO2 Reduction

电化学 金属有机骨架 纳米技术 材料科学 催化作用 碳纤维 还原(数学) 二氧化碳电化学还原 电解 化学 电极 有机化学 一氧化碳 复合材料 吸附 物理化学 复合数 电解质 数学 几何学
作者
Chengbo Li,Yuan Ji,Youpeng Wang,Chunxiao Liu,Zhaoyang Chen,Jialin Tang,Yawei Hong,Xu Li,Tingting Zheng,Qiu Jiang,Chuan Xia
出处
期刊:Nano-micro Letters [Springer Science+Business Media]
卷期号:15 (1): 113-113 被引量:130
标识
DOI:10.1007/s40820-023-01092-8
摘要

Electrochemically reducing CO2 to more reduced chemical species is a promising way that not only enables the conversion of intermittent energy resources to stable fuels, but also helps to build a closed-loop anthropogenic carbon cycle. Among various electrocatalysts for electrochemical CO2 reduction, multifunctional metal-organic frameworks (MOFs) have been employed as highly efficient and selective heterogeneous electrocatalysts due to their ultrahigh porosity and topologically diverse structures. Up to now, great progress has been achieved in the design and synthesis of highly active and selective MOF-related catalysts for electrochemical CO2 reduction reaction (CO2RR), and their corresponding reaction mechanisms have been thoroughly studied. In this review, we summarize the recent progress of applying MOFs and their derivatives in CO2RR, with a focus on the design strategies for electrocatalysts and electrolyzers. We first discussed the reaction mechanisms for different CO2RR products and introduced the commonly applied electrolyzer configurations in the current CO2RR system. Then, an overview of several categories of products (CO, HCOOH, CH4, CH3OH, and multi-carbon chemicals) generated from MOFs or their derivatives via CO2RR was discussed. Finally, we offer some insights and perspectives for the future development of MOFs and their derivatives in electrochemical CO2 reduction. We aim to provide new insights into this field and further guide future research for large-scale applications.
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
1秒前
胖飞飞发布了新的文献求助10
1秒前
2秒前
朱洪帆完成签到,获得积分20
2秒前
2秒前
Akim应助哈哈采纳,获得10
3秒前
lou关闭了lou文献求助
3秒前
川盈发布了新的文献求助10
4秒前
4秒前
zzz小秦完成签到 ,获得积分10
4秒前
上官若男应助CHA采纳,获得10
4秒前
4秒前
Akim应助LJF采纳,获得10
4秒前
朱洪帆发布了新的文献求助10
5秒前
XQQDD应助YCYD采纳,获得100
5秒前
在水一方应助ewww采纳,获得10
6秒前
6秒前
tao发布了新的文献求助10
6秒前
冰糖葫芦完成签到,获得积分10
6秒前
沉默鱼完成签到,获得积分10
7秒前
maguodrgon发布了新的文献求助10
7秒前
全麦面包完成签到,获得积分10
7秒前
噜啦啦完成签到,获得积分20
8秒前
10秒前
赘婿应助ikea1984采纳,获得10
11秒前
change完成签到 ,获得积分10
11秒前
标点符号完成签到,获得积分10
12秒前
13秒前
英吉利25发布了新的文献求助10
14秒前
Jokerc完成签到,获得积分10
14秒前
14秒前
15秒前
情怀应助蒋彪采纳,获得10
15秒前
15秒前
ip完成签到,获得积分10
16秒前
大模型应助177采纳,获得10
17秒前
欣怡发布了新的文献求助10
17秒前
田様应助俏皮可仁采纳,获得10
17秒前
红涛完成签到,获得积分10
17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
Chemistry and Physics of Carbon Volume 18 800
The Organometallic Chemistry of the Transition Metals 800
The formation of Australian attitudes towards China, 1918-1941 640
Signals, Systems, and Signal Processing 610
全相对论原子结构与含时波包动力学的理论研究--清华大学 500
Elevating Next Generation Genomic Science and Technology using Machine Learning in the Healthcare Industry Applied Machine Learning for IoT and Data Analytics 400
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 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6443142
求助须知:如何正确求助?哪些是违规求助? 8257058
关于积分的说明 17585007
捐赠科研通 5501690
什么是DOI,文献DOI怎么找? 2900830
邀请新用户注册赠送积分活动 1877812
关于科研通互助平台的介绍 1717461