Citation: Zhongshan Chen, Jianen Li, Qiao Ma, Xishi Tai, Jiehong Lei, Xiangke Wang. Covalent-organic frameworks: An intelligent platform for photocatalytic uranium reduction and separation[J]. Chinese Chemical Letters, ;2026, 37(9): 112485. doi: 10.1016/j.cclet.2026.112485 shu

Covalent-organic frameworks: An intelligent platform for photocatalytic uranium reduction and separation

Zhongshan Chen ^a ,
Jianen Li ^a ,
Qiao Ma ^a ,
Xishi Tai ^{b, *,} ,
Jiehong Lei ^{c, d, *,} ,
Xiangke Wang ^{a, *,}

a.
College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
b.
College of Chemistry and Chemical Engineering, Weifang University, Weifang 261061, China
c.
School of Physics and Astronomy, China West Normal University, Nanchong 637002, China
d.
Nuclear Medicine and Radiation Safety Key Laboratory of Sichuan Province, Nanchong 637002, China

taixs@wfu.edu.cn

leijiehong@cwnu.edu.cn

xkwang@ncepu.edu.cn

Received Date: 25 November 2025
Revised Date: 22 January 2026
Accepted Date: 30 January 2026
Available Online: 31 January 2026

Figures(4)

Covalent-organic frameworks (COFs) have attracted growing interest as photocatalytic materials for uranium extraction because of their tunable structures and adjustable optoelectronic properties. This perspective summarizes recent progress in COF-based systems for the selective capture and photoreduction of U(Ⅵ), with a focus on molecular design strategies such as band-structure regulation, donor-acceptor framework construction, and interfacial functionalization to improve visible-light utilization and charge separation. Key mechanistic aspects of photoinduced uranium conversion, including electron-transfer pathways, uranium valence evolution, and interfacial reaction kinetics, are discussed. Current challenges, such as uncertainty in reduction products, incomplete mechanistic understanding, and limited cycling stability, are also addressed by highlighting the role of in situ characterization combined with theoretical analysis. Finally, the potential of artificial intelligence-assisted design and the development of macroscopic COF forms, such as aerogels and membranes, are briefly discussed as routes toward practical uranium extraction.
- Covalent-organic frameworks,
- Photocatalytic adsorption-reduction,
- Uranium extraction,
- Electron-hole separation,
- Artificial intelligence (AI)
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