Molecular docking sites designed for the generation of highly crystalline covalent organic frameworks

化学 堆积 共价键 结晶度 纳米技术 共价有机骨架 多孔性 有机化学 结晶学 材料科学
作者
Laura Ascherl,Torben Sick,Johannes T. Margraf,Saul H. Lapidus,Mona Calik,Christina Hettstedt,Konstantin Karaghiosoff,Markus Döblinger,Timothy Clark,Karena W. Chapman,Florian Auras,Thomas Bein
出处
期刊:Nature Chemistry [Nature Portfolio]
卷期号:8 (4): 310-316 被引量:479
标识
DOI:10.1038/nchem.2444
摘要

Covalent organic frameworks (COFs) formed by connecting multidentate organic building blocks through covalent bonds provide a platform for designing multifunctional porous materials with atomic precision. As they are promising materials for applications in optoelectronics, they would benefit from a maximum degree of long-range order within the framework, which has remained a major challenge. We have developed a synthetic concept to allow consecutive COF sheets to lock in position during crystal growth, and thus minimize the occurrence of stacking faults and dislocations. Hereby, the three-dimensional conformation of propeller-shaped molecular building units was used to generate well-defined periodic docking sites, which guided the attachment of successive building blocks that, in turn, promoted long-range order during COF formation. This approach enables us to achieve a very high crystallinity for a series of COFs that comprise tri- and tetradentate central building blocks. We expect this strategy to be transferable to a broad range of customized COFs. Covalent organic frameworks (COFs) are attractive multifunctional porous materials that can be generated with atomic precision. However, endowing them with long-range order—desirable for applications—has remained challenging. Now, propeller-shaped building units have been used that allow consecutive layers to lock in position, resulting in highly crystalline COFs.
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
1秒前
卡坦精完成签到,获得积分10
1秒前
斑驳发布了新的文献求助10
2秒前
EMMA发布了新的文献求助30
2秒前
qin完成签到,获得积分10
3秒前
Glngar发布了新的文献求助30
6秒前
梁33完成签到,获得积分10
6秒前
溜溜很优秀完成签到,获得积分10
7秒前
@Hi发布了新的文献求助10
7秒前
zzz完成签到,获得积分10
9秒前
10秒前
丘比特应助科研Cat采纳,获得10
12秒前
1781266完成签到,获得积分10
13秒前
14秒前
Glngar完成签到,获得积分10
15秒前
科研通AI5应助喵咪西西采纳,获得10
16秒前
毕业论文三万字完成签到,获得积分10
17秒前
斯文败类应助zhibaishouhei采纳,获得10
19秒前
孙小雨完成签到,获得积分10
19秒前
研友_VZG7GZ应助EMMA采纳,获得10
23秒前
奋斗蝴蝶完成签到,获得积分10
27秒前
28秒前
sxy完成签到,获得积分10
28秒前
28秒前
科研通AI5应助郄建茹采纳,获得10
28秒前
NexusExplorer应助@Hi采纳,获得10
29秒前
bill完成签到,获得积分10
29秒前
冰美式发布了新的文献求助10
30秒前
77发布了新的文献求助10
32秒前
李爱国应助Tammy采纳,获得20
33秒前
喵咪西西发布了新的文献求助10
35秒前
你的完成签到 ,获得积分10
40秒前
40秒前
40秒前
SS完成签到,获得积分10
42秒前
FashionBoy应助简单山水采纳,获得10
42秒前
高兴的蜻蜓完成签到,获得积分10
44秒前
ckl发布了新的文献求助10
44秒前
45秒前
高分求助中
All the Birds of the World 4000
Production Logging: Theoretical and Interpretive Elements 3000
Les Mantodea de Guyane Insecta, Polyneoptera 2000
Machine Learning Methods in Geoscience 1000
Resilience of a Nation: A History of the Military in Rwanda 888
Musculoskeletal Pain - Market Insight, Epidemiology And Market Forecast - 2034 666
Crystal Nonlinear Optics: with SNLO examples (Second Edition) 500
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 3735903
求助须知:如何正确求助?哪些是违规求助? 3279592
关于积分的说明 10016324
捐赠科研通 2996292
什么是DOI,文献DOI怎么找? 1644012
邀请新用户注册赠送积分活动 781709
科研通“疑难数据库(出版商)”最低求助积分说明 749425