4.2 Article

Synthesis of Fe3O4@PPy-MWCNT nanocomposite and its application for extraction of ultra-trace amounts of PAHs from various samples

期刊

JOURNAL OF THE IRANIAN CHEMICAL SOCIETY
卷 14, 期 3, 页码 623-634

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SPRINGER
DOI: 10.1007/s13738-016-1012-x

关键词

Magnetic solid-phase extraction; ANN modeling; Gas chromatography-mass spectrometry

资金

  1. Tarbiat Modares University (Tehran, Iran)

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In the present study, multi-walled carbon nanotube oxide was immobilized on the pyrrole magnetic nanoparticles. Application of the synthesized material was investigated for the magnetic solid-phase extraction (MSPE) of polycyclic aromatic hydrocarbons (PAHs), from the environmental samples. Determinations of the analytes were performed with gas chromatography-mass spectrometry. The structure and morphology of Fe3O4@PPy-MWCNT were characterized by Fourier transform infrared spectroscopy, scanning electron microscopy, thermal gravimetric analysis, and vibrating sample magnetometer. Performance of MSPE is mainly affected by extraction time, sorbent amount, sample solution volume, and eluent type and volume. In this study, the best possible performance of MSPE has been achieved using a combination of central composite design and Bayesian regularized artificial neural network technique. Under the optimum extraction conditions, linear range between 0.5 and 250 A mu g L-1 (R (2) > 0.994), preconcentration factors from 232 to 403 and limits of detection ranging from 0.1 to 0.3 A mu g L-1 were obtained. Relative standard deviations for intra-day and inter-day precision were 3.3-5.1% and 3.7-5.6%, respectively. In addition, feasibility of the method was demonstrated by extraction and determination of PAHs from some real samples containing tap water, hookah water as well as soil samples, and relative recovery in the range of 85.4-106.8% was obtained. This MSPE method provides several advantages, such as high extraction efficiency, minimum sorbent for extraction of the analytes from high sample volumes, convenient extraction procedure, and short analysis times.

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