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Magnetically Encoded Luminescent Composite Nanoparticles through Layer‐by‐Layer Self‐Assembly
Authors:Prof?Dr Erqun Song  Weiye Han  Hongyan Xu  Yunfei Jiang  Dan Cheng  Prof?Dr Yang Song  Prof?Dr Mark T Swihart
Institution:1. Key Laboratory of Luminescence and Real‐Time, Analytical Chemistry (Southwest University), Ministry of Education, College of Pharmaceutical Sciences, Southwest University, Chongqing, 400715 (P.R. China), Fax: (+86)?23‐68251048;2. Department of Chemical and Biological Engineering, University at Buffalo, State University of New York, Buffalo, NY 14260 (USA)
Abstract:Sensitive and rapid detection of multiple analytes and the collection of components from complex samples are important in fields ranging from bioassays/chemical assays, clinical diagnosis, to environmental monitoring. A convenient strategy for creating magnetically encoded luminescent CdTe@SiO2@n Fe3O4 composite nanoparticles, by using a layer‐by‐layer self‐assembly approach based on electrostatic interactions, is described. Silica‐coated CdTe quantum dots (CdTe@SiO2) serve as core templates for the deposition of alternating layers of Fe3O4 magnetic nanoparticles and poly(dimethyldiallyl ammonium chloride), to construct CdTe@SiO2@n Fe3O4 (n=1, 2, 3, …?) composite nanoparticles with a defined number (n) of Fe3O4 layers. Composite nanoparticles were characterized by zeta‐potential analysis, fluorescence spectroscopy, vibrating sample magnetometry, and transmission electron microscopy, which showed that the CdTe@SiO2@n Fe3O4 composite nanoparticles exhibited excellent luminescence properties coupled with well‐defined magnetic responses. To demonstrate the utility of these magnetically encoded nanoparticles for near‐simultaneous detection and separation of multiple components from complex samples, three different fluorescently labeled IgG proteins, as model targets, were identified and collected from a mixture by using the CdTe@SiO2@n Fe3O4 nanoparticles.
Keywords:luminescence  magnetic properties  nanoparticles  quantum dots  self‐assembly
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