Molecular Engineering of CoII Porphyrins with Asymmetric Architecture for Improved Electrochemical CO2 Reduction

电化学 卟啉 催化作用 堆积 位阻效应 共轭体系 密度泛函理论 化学 二氧化碳电化学还原 碳纳米管 材料科学 纳米技术 电极 光化学 计算化学 立体化学 物理化学 有机化学 一氧化碳 聚合物
作者
Wenwen Bao,Senhe Huang,Diana Tranca,Boxu Feng,Feng Qiu,F. Rodríguez-Hernández,Changchun Ke,Sheng Han,Xiaodong Zhuang
出处
期刊:Chemsuschem [Wiley]
卷期号:15 (8) 被引量:3
标识
DOI:10.1002/cssc.202200090
摘要

The electrochemical reduction of carbon dioxide (CO2 ) based on molecular catalysts has attracted more attention, owing to their well-defined active sites and rational structural design. Metal porphyrins (PorMs) have the extended π-conjugated backbone with different transition metals, endowing them with unique CO2 reduction properties. However, few works focus on the investigation of symmetric architecture of PorMs as well as their aggregation behavior to CO2 reduction. In this work, a series of CoII porphyrins (PorCos) with symmetric and asymmetric substituents were used as model of molecular catalysts for CO2 reduction. Owing to the electron donating effect of 2,6-dimethylbenzene (DMB), bandgaps of the complexes became narrower with the increasing number of DMB. As electrocatalysts, all PorCos exhibited promising electrocatalytic CO2 reduction performance. Among the three molecules, asymmetric CoII porphyrin (as-PorCo) showed the lowest onset potential of -288 mV and faradaic efficiencies exceeding 93 % at -0.6 V vs. reversible hydrogen electrode, which is highly competitive among the reported state-of-art porphyrin-based electrocatalysts. The CO2 reduction performance depended on π-π stacking between PorCo with carbon nanotubes (CNTs) and adjacent PorCos, which could be readily controlled by atomically positioned DMB in PorCo. Density functional theory calculations also suggested that the charge density between PorCo and CNT was highest due to the weak steric hindrance in as-PorCo, providing the new insight into molecular design of catalysts for efficient electrochemical CO2 reduction.
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
小安完成签到,获得积分10
刚刚
红星路吃饼子的派大星完成签到 ,获得积分10
刚刚
苹果完成签到,获得积分10
刚刚
domkps完成签到 ,获得积分10
1秒前
小奥奥完成签到,获得积分10
1秒前
fzzf完成签到,获得积分10
2秒前
ww33发布了新的文献求助10
2秒前
成就的冰绿完成签到,获得积分10
2秒前
3秒前
3秒前
noii发布了新的文献求助10
3秒前
河豚完成签到,获得积分10
3秒前
YYDS发布了新的文献求助10
4秒前
Lucas应助简单平蓝采纳,获得10
6秒前
小星星bulingbuling完成签到,获得积分10
6秒前
万年wannian完成签到,获得积分10
6秒前
7秒前
7秒前
独特的豌豆完成签到,获得积分10
7秒前
跳跃凡桃完成签到 ,获得积分10
8秒前
a3979107完成签到,获得积分10
8秒前
8秒前
9秒前
当女遇到乔完成签到 ,获得积分10
9秒前
coolkid应助俏皮的惜灵采纳,获得10
10秒前
waive完成签到,获得积分10
10秒前
Gorge完成签到,获得积分10
10秒前
jade完成签到,获得积分10
10秒前
动听的谷秋完成签到 ,获得积分10
11秒前
自觉沛文完成签到,获得积分10
11秒前
11秒前
阿宅完成签到,获得积分10
11秒前
lxl1996完成签到,获得积分10
11秒前
淡然冬灵应助科研通管家采纳,获得30
12秒前
12秒前
12秒前
科研通AI5应助科研通管家采纳,获得10
12秒前
思源应助科研通管家采纳,获得30
12秒前
天天快乐应助科研通管家采纳,获得10
12秒前
打打应助科研通管家采纳,获得30
13秒前
高分求助中
Thinking Small and Large 500
Algorithmic Mathematics in Machine Learning 500
Getting Published in SSCI Journals: 200+ Questions and Answers for Absolute Beginners 300
The Monocyte-to-HDL ratio (MHR) as a prognostic and diagnostic biomarker in Acute Ischemic Stroke: A systematic review with meta-analysis (P9-14.010) 240
The Handbook of Medicinal Chemistry: Principles and Practice 200
Interpretability and Explainability in AI Using Python 200
SPECIAL FEATURES OF THE EXCHANGE INTERACTIONS IN ORTHOFERRITE-ORTHOCHROMITES 200
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3834097
求助须知:如何正确求助?哪些是违规求助? 3376554
关于积分的说明 10493831
捐赠科研通 3096024
什么是DOI,文献DOI怎么找? 1704828
邀请新用户注册赠送积分活动 820115
科研通“疑难数据库(出版商)”最低求助积分说明 771868