4.7 Review

A recent overview of the application of liquid-phase microextraction to the determination of organic micro-pollutants

Journal

TRAC-TRENDS IN ANALYTICAL CHEMISTRY
Volume 108, Issue -, Pages 203-209

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.trac.2018.09.002

Keywords

Organic micro-pollutants; Microextraction; LPME; Green analytical chemistry; Sample preparation

Funding

  1. Brazilian Governmental Agency Conselho Nacional de Desenvolvimento Cientifico e Tecnologioco (CNPq) [303892/2014-5]
  2. Brazilian Governmental Agency Fundacao de Amparo a Pesquisa do Estado de Santa Catarina (FAPESC) [455/2016]
  3. Brazilian Governmental Agency Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior (CAPES) [001]

Ask authors/readers for more resources

Liquid-phase microextraction (LPME) techniques are widely used for sample preparation in a number of analytical determinations involving different matrices. These techniques exhibit unique features including environmentally-friendly aspects, high extraction capacity and low cost. In this study, the application of liquid-phase microextraction for the determination of organic micro-pollutants is explored and reviewed. Very recent developments are discussed and highlighted focusing on the extraction efficiency and analytical performance achieved in each study. Some applications of important developments in alternative and greener extraction solvents, such as ionic liquids (IL), magnetic ionic liquids (MILs), deep eutectic solvents (DES) and supramolecular solvents (SUPRAS), are mentioned. Moreover, the impressive features of microchip devices for LPME and the promising developments of combining two microextraction techniques for the determination of organic micro-pollutants are presented. (c) 2018 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available