Boron–Nitrogen-Embedded Polycyclic Aromatic Hydrocarbon-Based Controllable Hierarchical Self-Assemblies through Synergistic Cation–π and C–H···π Interactions for Bifunctional Photo- and Electro-Catalysis

化学 超分子化学 双功能 催化作用 纳米技术 化学工程 组合化学 有机化学 分子 材料科学 工程类
作者
Zhelin Zhang,Xiao Hu,Shuai Qiu,Junlong Su,Rui Bai,Jian Zhang,Wei Tian
出处
期刊:Journal of the American Chemical Society [American Chemical Society]
被引量:7
标识
DOI:10.1021/jacs.4c00706
摘要

Boron–Nitrogen-embedded polycyclic aromatic hydrocarbons (BN-PAHs) as novel π-conjugated systems have attracted immense attention owing to their superior optoelectronic properties. However, constructing long-range ordered supramolecular assemblies based on BN-PAHs remains conspicuously scarce, primarily attributed to the constraints arising from coordinating multiple noncovalent interactions and the intrinsic characteristics of BN-PAHs, which hinder precise control over delicate self-assembly processes. Herein, we achieve the successful formation of BN-PAH-based controllable hierarchical assemblies through synergistically leveraged cation–π and C–H···π interactions. By carefully adjusting the solvent conditions in two progressive assembly hierarchies, the one-dimensional (1D) supramolecular assemblies with "rigid yet flexible" assembled units are first formed by cation–π interactions, and then they can be gradually fused into two-dimensional (2D) structures under specific C–H···π interactions, thus realizing the precise control of the transformation process from BN-PAH-based 1D primary structures to 2D higher-order assemblies. The resulting 2D-BNSA, characterized by enhanced electrical conductivity and ordered 2D layered structure, provides anchoring and dispersion sites for loading two appropriate nanocatalysts, thus facilitating the efficient photocatalytic CO2 reduction (with a remarkable CH4 evolution rate of 938.7 μmol g–1 h–1) and electrocatalytic acetylene semihydrogenation (reaching a Faradaic efficiency for ethylene up to 98.5%).
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
赘婿应助Su采纳,获得10
1秒前
1秒前
欢呼的雨琴完成签到 ,获得积分10
1秒前
1秒前
吞吞发布了新的文献求助10
2秒前
glass_light发布了新的文献求助10
2秒前
Hello应助张凯茜采纳,获得10
2秒前
舒心的语儿完成签到,获得积分20
3秒前
3秒前
4秒前
铲屎大王发布了新的文献求助10
5秒前
无私谷梦发布了新的文献求助10
6秒前
Anderson发布了新的文献求助10
7秒前
牧青发布了新的文献求助10
7秒前
8秒前
9秒前
10秒前
11秒前
YinLi完成签到,获得积分20
11秒前
13秒前
星辰大海应助橙子采纳,获得10
13秒前
zzz完成签到 ,获得积分10
13秒前
Hd完成签到,获得积分10
13秒前
Anderson完成签到,获得积分10
13秒前
小二郎应助来碗豆腐采纳,获得10
14秒前
15秒前
柚子完成签到,获得积分10
16秒前
Hd发布了新的文献求助30
16秒前
16秒前
17秒前
18秒前
cm发布了新的文献求助10
19秒前
19秒前
22秒前
111发布了新的文献求助10
23秒前
23秒前
来碗豆腐发布了新的文献求助10
23秒前
24秒前
Andone完成签到,获得积分10
24秒前
充电宝应助AHA采纳,获得10
24秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(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
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
ズームレンズの光学設計に関する研究 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
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 7295367
求助须知:如何正确求助?哪些是违规求助? 8913817
关于积分的说明 18873827
捐赠科研通 6961609
什么是DOI,文献DOI怎么找? 3210209
关于科研通互助平台的介绍 2379497
邀请新用户注册赠送积分活动 2186486