A Simplified Molecular Imprinting Strategy Through Electrospinning of Polyacrylonitrile for Thin Film Microextraction of Selected Pesticides

Abstract

Molecularly imprinted polymers (MIPs) have been extensively used as selective extractive phases for sample preparation because of their analyte-selective binding sites. However, MIP preparation requires optimized monomer-template interactions and long polymerization reactions. In this study, a novel and simple method of MIP preparation was proposed based on electrospinning. Instead of preparing analyte-monomer complexes before polymerization, model analytes (trifluralin and carbaryl) were directly dissolved in a polyacrylonitrile (PAN) solution, then electrospun into nanofibrous mats. This allowed for a means of preparation of highly crystalline, template-imprinted nanostructures with minimal synthetic complexity. Following the characterization studies for the new material, the extraction properties of the imprinted and nonimprinted electrospun mats were investigated in thin film microextraction (TFME) studies by extracting trifluralin and carbaryl from water samples, followed by gas chromatography-mass spectrometry (GC–MS) analysis. The optimization results showed that samplers containing 10.0 mg of MIP sorbents made by electrospinning of a solution containing 5.0 mg of template in 1.0 mL of PAN solution resulted in approximately 4 and 7 times enhanced extraction recoveries for carbaryl and trifluralin compared to samplers made of non-imprinted bulk PAN. Moreover, the cross-reactivity testing performed with non-template analytes (malathion and diazinon) suggested a more specific extraction towards trifluralin compared to carbaryl. The proposed new technique was also validated using computational methodology, which supported the experimental finding about higher selectivity towards trifluralin. This may signify a probability for structural orientation of partially charged trifluralin under an electrical field in electrospun PAN creating favorable extraction sites. © 2025 Elsevier B.V.