Preparation of magnetic molecularly imprinted polymer for rapid determination of bisphenol A in environmental water and milk samples |
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Authors: | Yongsheng Ji Juanjuan Yin Zhigang Xu Chuande Zhao Huayu Huang Haixia Zhang and Chunming Wang |
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Institution: | (1) State Key Laboratory of Applied Organic Chemistry, Lanzhou University, Lanzhou, 730000, China; |
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Abstract: | A magnetic molecularly imprinted polymer (M-MIP) of bisphenol A (BPA) was prepared by miniemulsion polymerization. The morphological
and magnetic characteristics of the M-MIP were characterized by Fourier-transform infrared spectroscopy, transmission electron
microscopy, and vibrating sample magnetometry. The adsorption capacities of the M-MIP and the nonimprinted polymer were investigated
using static adsorption tests, and were found to be 390 and 270 mg g−1, respectively. Competitive recognition studies of the M-MIP were performed with BPA and the structurally similar compound
DES, and the M-MIP displayed high selectivity for BPA. A method based on molecularly imprinted solid-phase extraction assisted
by magnetic separation was developed to extract BPA from environmental water and milk samples. Various parameters such as
the mass of sorbent, the pH of the sample, the extraction time, and desorption conditions were optimized. Under selected conditions,
extraction was completed in 15 min. High-performance liquid chromatography with UV detection was employed to determine BPA
after the extraction. For water samples, the developed method exhibited a limit of detection (LOD) of 14 ng L−1, a relative standard deviation of 2.7% (intraday), and spiked recoveries ranging from 89% to 106%. For milk samples, the
LOD was 0.16 μg L−1, recoveries ranged from 95% to 101%, and BPA was found in four samples at levels of 0.45–0.94 μg L−1. The proposed method not only provides a rapid and reliable analysis but it also overcomes problems with conventional solid-phase
extraction (SPE), such as the packing of the SPE column and the time-consuming nature of the process of loading large-volume
samples. |
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Keywords: | |
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