4.6 Article

Automated multisyringe stir bar sorptive extraction using robust montmorillonite/epoxy-coated stir bars

期刊

JOURNAL OF CHROMATOGRAPHY A
卷 1445, 期 -, 页码 10-18

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.chroma.2016.03.081

关键词

Montmorillonite; Epoxy resin; Stir bar sorptive extraction; Multisyringe flow injection analysis; High performance liquid chromatography; Chlorophenols

资金

  1. Spanish Ministerio de Economia y Competitividad (MINECO)
  2. European Funds for Regional Development (FEDER) [CTQ2013-47461-R]
  3. Ministry of Science of Iran
  4. Isfahan University of Technology
  5. Government of the Balearic Islands
  6. European Social Fund
  7. Accio [AAEE/35]

向作者/读者索取更多资源

Herein we present a simple, rapid and low cost strategy for the preparation of robust stir bar coatings based on the combination of montmorillonite with epoxy resin. The composite stir bar was implemented in a novel automated multisyringe stir bar sorptive extraction system (MS-SBSE), and applied to the extraction of four chlorophenols (4-chlorophenol, 2,4-dichlorophenol, 2,4,6-trichlorophenol and pentachlorophenol) as model compounds, followed by high performance liquid chromatography-diode array detection. The different experimental parameters of the MS-SBSE, such as sample volume, selection of the desorption solvent, desorption volume, desorption time, sample solution pH, salt effect and extraction time were studied. Under the optimum conditions, the detection limits were between 0.02 and 0.34 mu g L-1. Relative standard deviations (RSD) of the method for the analytes at 10 mu g L-1 concentration level ranged from 3.5% to 4.1% (as intra-day RSD) and from 3.9% to 43% (as inter-day RSD at 50 mu g L-1 concentration level). Batch-to-batch reproducibility for three different stir bars was 4.6-5.1%. The enrichment factors were between 30 and 49. In order to investigate the capability of the developed technique for real sample analysis, well water, wastewater and leachates from a solid waste treatment plant were satisfactorily analyzed. (C) 2016 Elsevier B.V. All rights reserved.

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