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Post-imprinting modification based on multilevel mesoporous silica for highly sensitive molecularly imprinted fluorescent sensors

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Abstract

When molecularly imprinted fluorescent polymers (MIFPs) are prepared by the doping method (d-MIFPs), the fluorescent nanoparticles are quenched and passivated during the polymerization and elution process, and their detection sensitivity would be reduced. In this study, to overcome this drawback, MIFPs were synthesized by post-imprinting modification based on multilevel mesoporous structured silica. Briefly, multilevel mesoporous-structured BPA-imprinted polymers (MIPs) were prepared at first, and then, CdTe quantum dots were anchored onto the large pores of the MIPs to form p-MIFPs. Due to the well-maintained fluorescence intensity and low background, the sensitivity of the p-MIFPs was two orders of magnitude higher than that of the d-MIFPs. The F0/F − 1 of p-MIFPs was linear with BPA in the range of 0.005 to 4.0 μM with an LOD of 0.57 nM. Furthermore, post-imprinting modification was adopted to achieve ratiometric fluorescent MIPs (p-r-MIFPs) by simultaneously anchoring carbon dots and quantum dots onto the MIPs. The p-MIFPs and p-r-MIFPs were successfully applied to determine BPA in water samples with average recoveries ranging from 96.4% to 102.0% and an RSD below 4.1%. The results prove that post-imprinting modification is an effective method to construct MIFPs with conspicuous sensitivity, and multilevel mesoporous silica is an ideal matrix for the post-imprinting modification.

Graphical abstract: Post-imprinting modification based on multilevel mesoporous silica for highly sensitive molecularly imprinted fluorescent sensors

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Publication details

The article was received on 07 Aug 2019, accepted on 21 Sep 2019 and first published on 23 Sep 2019


Article type: Paper
DOI: 10.1039/C9AN01503E
Analyst, 2019, Advance Article

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    Post-imprinting modification based on multilevel mesoporous silica for highly sensitive molecularly imprinted fluorescent sensors

    H. Lu, D. Wei, R. Zheng and S. Xu, Analyst, 2019, Advance Article , DOI: 10.1039/C9AN01503E

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