4.6 Article

Extraction of trace polychlorinated biphenyls in environmental waters by well-dispersed velvet-like magnetic carbon nitride nanocomposites

Journal

JOURNAL OF CHROMATOGRAPHY A
Volume 1491, Issue -, Pages 27-35

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.chroma.2017.02.048

Keywords

Magnetic solid phase extraction; Polychlorinated biphenyls; Velvet-like carbon nitride; Rapid adsorption and desorption

Funding

  1. National Natural Science Foundation of China [21475061, 21507062]
  2. Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry [[2015]1098]
  3. Program of Natural Science Research of Jiangsu Higher Education Institutions of China [16KJB150022]
  4. Priority Academic Program Development of Jiangsu Higher Education Institutions
  5. Jiangsu Collaborative Innovation Center of Biomedical Functional Materials
  6. Chinese National Scholarship for Graduate Students

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A velvet-like magnetic carbon nitride nanocomposites synthesized by chemical co-precipitation was used to develop a highly efficient magnetic solid-phase extraction method for the pre-concentration of trace polychlorinated biphenyls (PCBs) in water samples. The advantages of this nanocomposite such as large surface area, good dispersity, low solvent consumption, rapid analyte adsorption (30s) and reusability make it a good sorbent. Factors affecting extraction efficiency were systematically investigated and optimized by response surface methodology (RSM). Under optimal experimental conditions, the limits of detection (LODs S/N = 3) of the developed method for PCBs investigated were in the range of 9.0 x 10(-6)-5.8 x 10(-5) mu g/mL. This method was then used for the analysis of four real water samples. Good spiked recoveries over the range of 80.1-118.4%, and RSDs (n=5) of 0.02-3.7% were obtained. This work demonstrated the potential of using this nanocomposite for adsorption, pre-concentration, or even removal of different carbon-based aromatic compounds or other hydrophobic pollutants. (C) 2017 Elsevier B.V. All rights reserved.

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