Literature DB >> 25099151

Selective recognition and discrimination of water-soluble azo dyes by a seven-channel molecularly imprinted polymer sensor array.

Zerong Long1, Yi Lu, Mingliang Zhang, Hongdeng Qiu.   

Abstract

A seven-channel molecularly imprinted polymer sensor array was prepared and characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, UV-Vis spectroscopy, and nitrogen physisorption studies. The results revealed that the imprinted polymers have distinct-binding affinities from those of structurally similar azo dyes. Analysis of the UV-Vis spectral response patterns of the seven dye analytes against the imprinted polymer array suggested that the different selectivity patterns of the array were closely connected to the imprinting process. To evaluate the effectiveness of the array format, the binding of a series of analytes was individually measured for each of the seven polymers, made with different templates (including one control polymer synthesized without the use of a template). The response patterns of the array to the selected azo dyes were processed by canonical discriminant analysis. The results showed that the molecularly imprinted array was able to discriminate each analyte with 100% accuracy. Moreover, the azo dyes in two real samples, spiked chrysoidin in smoked bean curd extract and Fanta lime soda (containing tartrazine), were successfully classified by the array.
© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Azo dyes; Canonical discriminant analysis; Molecularly imprinted polymers; Sensor arrays

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Year:  2014        PMID: 25099151     DOI: 10.1002/jssc.201400684

Source DB:  PubMed          Journal:  J Sep Sci        ISSN: 1615-9306            Impact factor:   3.645


  1 in total

1.  Synthesis, column packing and liquid chromatography of molecularly imprinted polymers for the acid black 1, acid black 210, and acid Brown 703 dyes.

Authors:  Faiz Ali; Zuber Shah; Alamgir Khan; Maria Saadia; Zeid A AlOthman; Won Jo Cheong
Journal:  RSC Adv       Date:  2022-07-06       Impact factor: 4.036

  1 in total

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