Rapid Synthesis of Single-Crystal Covalent Organic Framework with Controllable Crystal Habits DOI
Wenqiang Gao, Ziao Chen, Jiaxin Hong

и другие.

Journal of the American Chemical Society, Год журнала: 2025, Номер 147(18), С. 15459 - 15468

Опубликована: Апрель 28, 2025

Covalent organic frameworks (COFs) linked by poorly reversible covalent bonds lack dynamic formation and cleavage, so the synthesis of their single-crystal structures necessitates slow crystallization rates to mitigate defect formation. This, however, inherently restricts opportunities for facet-selective engineering beyond traditional compositional topological controls. To address this fundamental limitation, we developed an acetal/CH3COOH protocol that paradoxically accelerated while enhancing structural perfection, reducing time 60 μm-sized COF-300 1 h, achieving crystal sizes up 120 μm within 48 300 after 30 days. Capitalizing on platform, systematically interrogated landscapes through multiparameter exploration─modulator chemoselectivity, catalyst dosages, temporal evolution, reactive temperature─to decode possible growth mechanisms COFs. Based these, relationship between reaction conditions size, size distribution, shape, dynamics COFs was trained predicted a machine learning (ML) model.

Язык: Английский

Recent Advances in Room-Temperature Synthesis of Covalent Organic Frameworks DOI Creative Commons
Dongchuang Wu, Ning Gu, Jiafeng Yao

и другие.

Chemical Science, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Room-temperature synthesis bridges the gap between chemistry and practical application of COFs. This review provides an overview characterization technologies COF growth mechanisms recent room-temperature synthetic strategies.

Язык: Английский

Процитировано

1
A Phototautomeric 3D Covalent Organic Framework for Ratiometric Fluorescence Humidity Sensing DOI

Xuan Yao,

Zhang Youchang, Yu Qiu

и другие.

Journal of the American Chemical Society, Год журнала: 2025, Номер unknown

Опубликована: Март 6, 2025

Photoinduced proton transfer is an essential photochemical process for designing photocatalysts, white light emitters, bioimaging, and fluorescence sensing materials. However, deliberate control of the excited/ground states meticulous manipulation excited state intramolecular (ESIPT) pathway constitute a significant challenge in liquids dense solids. Here, we present integration hydronaphthoquinone fluorophore into crystalline, porous, phototautomeric dynamic 3D covalent organic framework (COF) to show guest-induced turn-on, emission redshift enhancement, shortened lifetimes ratiometric humidity sensing. Theoretical spectroscopic studies provide mechanistic insights conformational dynamics, charge coupled with local excitation, ground-state uphill regulation multiple tautomers. We illustrate sensitive, rapid, steady, self-calibrated wide range benefiting from architectural chemical robustness crystallinity such COF. These findings molecular design functional porous materials that integrate host-guest mutual recognition photoelectronic response multiplex environmental monitoring biomedical diagnostics applications.

Язык: Английский

Процитировано

0
Rapid Synthesis of Single-Crystal Covalent Organic Framework with Controllable Crystal Habits DOI
Wenqiang Gao, Ziao Chen, Jiaxin Hong

и другие.

Journal of the American Chemical Society, Год журнала: 2025, Номер 147(18), С. 15459 - 15468

Опубликована: Апрель 28, 2025

Covalent organic frameworks (COFs) linked by poorly reversible covalent bonds lack dynamic formation and cleavage, so the synthesis of their single-crystal structures necessitates slow crystallization rates to mitigate defect formation. This, however, inherently restricts opportunities for facet-selective engineering beyond traditional compositional topological controls. To address this fundamental limitation, we developed an acetal/CH3COOH protocol that paradoxically accelerated while enhancing structural perfection, reducing time 60 μm-sized COF-300 1 h, achieving crystal sizes up 120 μm within 48 300 after 30 days. Capitalizing on platform, systematically interrogated landscapes through multiparameter exploration─modulator chemoselectivity, catalyst dosages, temporal evolution, reactive temperature─to decode possible growth mechanisms COFs. Based these, relationship between reaction conditions size, size distribution, shape, dynamics COFs was trained predicted a machine learning (ML) model.

Язык: Английский

Процитировано

0