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An efficient grafting technique for producing molecularly imprinted film via reversible addition–fragmentation chain transfer polymerization

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Abstract

Herein, an efficient approach towards obtaining molecularly imprinted polymer (MIP) film for the detection of 17β-estradiol (E2) with water-compatible properties using a reversible addition–fragmentation chain transfer (RAFT) via photo-initiation is described. 2-Methyl-2-[(dodecylsulfanylthiocarbonyl)sulfanyl]propanoic acid (DDMAT) as the sole control agent in the absence of additional photoinitiators or catalysts was utilized for the synthesis of MIP film. The MIP film was characterized using contact angle measurements, infrared spectroscopy (IR) and scanning electron microscopy (SEM). Analysis of the surface plasmon resonance (SPR) spectra showed that the imprinted film displayed good sensitivity and selectivity to E2 when compared to other competitors and non-imprinted polymer (NIP) film. The response of the E2 ranged from 10−14 to 10−6 mol L−1 with a limit of detection (LOD) of 1.15 × 10−15 mol L−1 (S/N = 3) in PBS buffer (pH 7.4). This sensor showed good reusability and stability, and retained about 84.8% of its original response after 45 days of storage under dry and ambient conditions. Finally, the sensor was applied to determine the concentration of E2 in tap water and underground water samples in the range from 10−13 mol L−1 to 10−7 mol L−1, and the LODs were obtained as 7.4 × 10−15 mol L−1 and 1.12 × 10−14 mol L−1, respectively.

Graphical abstract: An efficient grafting technique for producing molecularly imprinted film via reversible addition–fragmentation chain transfer polymerization

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Publication details

The article was received on 03 Jul 2017, accepted on 11 Aug 2017 and first published on 14 Aug 2017


Article type: Paper
DOI: 10.1039/C7AY01623A
Citation: Anal. Methods, 2017, Advance Article
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    An efficient grafting technique for producing molecularly imprinted film via reversible addition–fragmentation chain transfer polymerization

    Y. Wang, S. Q. Jiao, X. L. Chen and T. X. Wei, Anal. Methods, 2017, Advance Article , DOI: 10.1039/C7AY01623A

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