143
Views
5
CrossRef citations to date
0
Altmetric
Original Articles

Retrieval of the Extraction Solvent by Magnetic Particles for Dispersive Liquid–Liquid Microextraction of UV Filters

, , , &
Pages 104-110 | Published online: 02 Oct 2014
 

Abstract

A simple dispersive liquid–liquid microextraction (DLLME) method, based on retrieval of the extraction solvent by magnetic particles and followed by HPLC–UV analysis, was proposed for the determination of UV filters in environmental water samples. The new method uses vortex agitation in the DLLME process to achieve rapid equilibrium. Another feature of the proposed method is that the retrieval of the extraction solvent is accomplished by functionalized magnetic particles rather than by special designed vessels or refrigeration and thawing process associated with DLLME when low-density extraction solvent was used. The parameters that may influence the extraction, including vortex time, volume of extraction solvent, weight of the magnetic particles, volume of desorption solvent, pH, and ionic concentration of the sample solution, were investigated in detail. Under the optimized conditions, the limits of detection for the target UV filters were in range of 0.7–12.3 ng mL−1. The results also demonstrated good linearity and precision, with the regression coefficients above 0.9989 and the RSDs below 4.4%, respectively.

Notes

a Calculated from the sample spiked at a level of 0.35 µg/mL.

Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/ljlc.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 583.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.