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Issue 7, 2017
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Preparation of molecularly imprinted polymeric microspheres based on distillation–precipitation polymerization for an ultrasensitive electrochemical sensor

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Abstract

A highly sensitive electrochemical sensor based on a carbon paste electrode (CPE) modified with molecularly imprinted polymeric microspheres (MIPMSs) was developed for the determination of bisphenol A (BPA). For the first time BPA-imprinted MIPMSs were prepared via distillation precipitation polymerization, and then the polymeric microspheres were involved in producing the MIPMS-modified CPE (MIPMS/CPE). The polymers obtained were observed via a scanning electron microscope and its dynamic and static adsorption performances were investigated. Cyclic voltammetry and electrochemical impedance spectroscopy were performed to study the preparation process and electrochemical behavior of the modified carbon paste electrodes with [Fe(CN)6]3−/4− ions acting as electrical indicators. Compared with the bulk MIP packed sensor, the MIPMS/CPE exhibits a higher sensing response and better reproducibility. The detection linear range for BPA is 1 × 10−11–1 × 10−7 M with a detection limit of 2.8 × 10−12 M (S/N = 3) under the optimal experimental conditions. Moreover, the MIPMS/CPE exhibited good selectivity and stability. The developed sensor can determine BPA in real samples including soil, milk and water rapidly and accurately after simple sample pretreatment.

Graphical abstract: Preparation of molecularly imprinted polymeric microspheres based on distillation–precipitation polymerization for an ultrasensitive electrochemical sensor

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Publication details

The article was received on 11 Jan 2017, accepted on 23 Feb 2017 and first published on 27 Feb 2017


Article type: Paper
DOI: 10.1039/C7AN00059F
Citation: Analyst, 2017,142, 1091-1098
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    Preparation of molecularly imprinted polymeric microspheres based on distillation–precipitation polymerization for an ultrasensitive electrochemical sensor

    Y. Liu, L. Zhang, N. Zhao, Y. Han, F. Zhao, Z. Peng and Y. Li, Analyst, 2017, 142, 1091
    DOI: 10.1039/C7AN00059F

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