4.7 Article

Fast microextraction of phthalate acid esters from beverage, environmental water and perfume samples by magnetic multi-walled carbon nanotubes

期刊

TALANTA
卷 90, 期 -, 页码 123-131

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.talanta.2012.01.015

关键词

Magnetic solid-phase extraction (MSPE); Magnetic carbon nanotubes (CNTs); Phthalate acid esters (PAEs); Beverages; Water; Perfume; Gas chromatography/mass spectrometry (GC/MS)

资金

  1. Fundamental Research Funds for the Central Universities
  2. National Natural Science Foundation of China [91017013, 31070327, 21005057]
  3. NSFC [20921062]

向作者/读者索取更多资源

In this work, magnetic carbon nanotubes (CNTs) were prepared by mixing the magnetic particles and multi-walled carbon nanotubes dispersed solutions. Due to their excellent adsorption capability towards hydrophobic compounds, the magnetic CNTs were used as adsorbent of magnetic solid-phase extraction (MSPE) to extract phthalate acid esters (PAEs), which are widely used in many consumable products with potential carcinogenic properties. By coupling MSPE with gas chromatography/mass spectrometry (GC/MS), a rapid, sensitive and cost-effective method for the analysis of PAEs was established. Our results showed that the limits of detection (LODs) of 16 PAEs ranged from 4.9 to 38 ng L-1, which are much lower compared to the previously reported methods. And good linearities of the detection method were obtained with correlation coefficients (R-2) between 0.9821 and 0.9993. In addition, a satisfying reproducibility was achieved by evaluating the intra- and inter-day precisions with relative standard deviations (RSDs) less than 11.7% and 14.6%, respectively. Finally, the established MSPE-GC/MS method was successfully applied to the determination of PAEs from bottled beverages, tap water and perfume samples. The recoveries of the 16 PAEs from the real samples ranged from 64.6% to 125.6% with the RSDs less than 16.5%. Taken together, the MSPE-GC/MS method developed in current study provides a new option for the detection of PAEs from real samples with complex matrices. (C) 2012 Elsevier B.V. All rights reserved.

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