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Inorganic nanocrystal-dynamic porous polymer assemblies with effective energy transfer for sensitive diagnosis of urine copper
Authors:Xujiao Ma  Yajie Yang  Rongchen Ma  Yunfeng Zhang  Xiaoqin Zou  Shoujun Zhu  Xin Ge  Ye Yuan  Wei Zhang  Guangshan Zhu
Institution:Key Laboratory of Polyoxometalate Science of Ministry of Education, Northeast Normal University, Changchun 130024 China.; State Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130012 China ; Key Laboratory of Automobile Materials MOE, School of Materials Science & Engineering, Electron Microscopy Center, International Center of Future Science, Jilin University, Changchun 130012 China,
Abstract:Despite their remarkable mechanical, optical, and electrical properties, inorganic particles and dynamic polymer assemblies encounter difficulties in their compatibility with regards to structural order and complexity. Here, covalent organic frameworks (COFs) constructed through reversible coupling reactions were exploited as dynamic porous polymers to prepare inorganic nanocrystal-polymer assemblies. Under an in situ growth process, carbon quantum dots (CDs) were gradually prepared in the COF cavity, with a narrow size distribution (2 ± 0.5 nm). The well-established assemblies achieve effective energy transfer from the inorganic to the organic part (efficiency > 80%), thus rendering a ∼130% increase in quantum yield compared with the pristine COF network. Notably, the hybrid material realizes a simple, selective, and sensitive diagnostic tool for urine copper, surpassing the detection limit of COF solid by 150 times. Beyond the scientific and fundamental interests, such hybrid assemblies are attractive from technological perspectives as well, for example, in energy storage, electronics, catalysis, and optics.

Despite their remarkable mechanical, optical, and electrical properties, inorganic particles and dynamic polymer assemblies encounter difficulties in their compatibility with regards to structural order and complexity.
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