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Title
Preparation of a novel stir bar coating based on montmorillonite doped polypyrrole/nylon-6 nanocomposite for sorptive extraction of organophosphorous pesticides in aqueous samples
Type of Research Article
Keywords
Stir bar sorptive extraction; montmorillonite; polypyrrole; nylon-6; central composite design; organophosphorous pesticides; gas chromatography-mass spectrometry
Abstract
In the present work, a novel nanocomposite (NC) was prepared by reinforcing montmorillonite (MMT) into polypyrrole-nylon-6 (PPy- N6) hybrid through in situ oxidative polymerisation of PPy in the MMT-N6 mixture. The prepared novel NC was deposited as a thin layer coating on the stir bar substrate by solvent exchange method. Fourier transform infrared spectroscopy, scanning electron microscopy, X-ray diffraction and energy dispersive X-ray spectroscopy were applied to characterise the prepared NCs. The prepared stir bar based on MMT/PPy/N6 NC was applied for sorptive extraction of some organophosphorous pesticides (OPPs) in river water samples with detection by gas chromatography- mass spectrometry (GC-MS). The effect of MMT doping level in the NC and also the effect of PPy hybridation with N6 on the coating extraction capability were studied. Central composite design was used to optimise and study the effects of influencing factors on the stir bar sorptive extraction efficiency such as salt content, pH, extraction time, desorption time, desorption solvent and its volume. The method optimisation step was performed using gas chromatography-flame ionisation detector, while the method validation was conducted using GC-MS. Limits of detection of the developed method are in the range of 0.05–0.3 μg L−1 and the linear dynamic ranges are in the range of 0.3–1000 and 1–1000 μg L−1, respectively. The intra-day precision (RSD %) of developed method with four replicates varied between 5.4 and 8.2% for distilled water spiked at 100 μg L−1. The applicability of the developed method was examined by extraction and determination of OPP compounds in river water samples, indicating the relative recoveries in the range of 80.3–95.3%.
Researchers Zahra Ayazi (First Researcher)، Mehri Pourvali (Second Researcher)، Amir Abbas Matin (Third Researcher)