journal article·2016-04

Molecularly imprinted polymer silica monolith for the selective extraction of alpha-cypermethrin from soil samples

Mengying Zhao, Xiaodong Ma, Fengjun Zhao, Hongwen Guo

Journal of Materials Science· Volume 51· Issue 7
Publisher page

Abstract

A novel molecularly imprinted polymer silica monolith (MIPSM) was successfully designed and prepared by a two-step procedure. Silica monolith was first synthesized by a sol–gel process. Then molecularly imprinted polymer (MIP) was coated on the surface of the activated silica monolithic column by using γ-methacryloxypropyl trimethoxysilane as a silane coupling agent, methacrylic acid as a functional monomer, ethylene glycol diglycidyl ether as a cross-linker, and alpha-cypermethrin (α-CYP) as a template. The prepared MIPSM, coupled with high-performance liquid chromatography/diode array detection, was used as a solid-phase extraction material for selective enrichment and determination of α-CYP in soil samples. The recovery of MIPSM for α-CYP was 87.0 %, which was significantly higher than that of nonimprinted polymer silica monolith (59.0 %), suggesting that MIPSM has specific recognition ability for template molecule. High selectivity of MIPSM was identified by comparing with the extraction efficiency for structure analog (deltamethrin). The synthesized MIPSM could be used for five times with the recovery maintained in a desirable range (85.4–90.9 %). Combining the advantages of high specificity and selectivity of MIP with the advantages of chromatographic separation of silica monolith, this prepared MIPSM presented a promising method for the pretreatment of trace amount of synthetic pyrethroid insecticides in the soil samples prior to the chromatographic analysis.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Analytical chemistry methods development · Pesticide Residue Analysis and Safety · Electrochemical Analysis and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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