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Automation of static and dynamic non-dispersive liquid phase microextraction. Part 2: Approaches based on impregnated membranes and porous supports

期刊

ANALYTICA CHIMICA ACTA
卷 907, 期 -, 页码 18-30

出版社

ELSEVIER
DOI: 10.1016/j.aca.2015.11.046

关键词

Automation; Miniaturisation; Liquid phase microextraction; Supported liquid membrane microextraction; Chromatomembrane; Hollow-fibre liquid phase microextraction; Static liquid phase microextraction; Dynamic liquid phase microextraction

资金

  1. Charles University Research Centre [UNCE 204026/2012]
  2. Czech Science Foundation [P206/15/10781S]

向作者/读者索取更多资源

A critical overview on automation of modern liquid phase microextraction (LPME) approaches based on the liquid impregnation of porous sorbents and membranes is presented. It is the continuation of part 1, in which non-dispersive LPME techniques based on the use of the extraction phase (EP) in the form of drop, plug, film, or microflow have been surveyed. Compared to the approaches described in part 1, porous materials provide an improved support for the EP. Simultaneously they allow to enlarge its contact surface and to reduce the risk of loss by incident flow or by components of surrounding matrix. Solvent-impregnated membranes or hollow fibres are further ideally suited for analyte extraction with simultaneous or subsequent back-extraction. Their use can therefore improve the procedure robustness and reproducibility as well as it opens the door to the new operation modes and fields of application. However, additional work and time are required for membrane replacement and renewed impregnation. Automation of porous support-based and membrane-based approaches plays an important role in the achievement of better reliability, rapidness, and reproducibility compared to manual assays. Automated renewal of the extraction solvent and coupling of sample pretreatment with the detection instrumentation can be named as examples. The different LPME methodologies using impregnated membranes and porous supports for the extraction phase and the different strategies of their automation, and their analytical applications are comprehensively described and discussed in this part. Finally, an outlook on future demands and perspectives of LPME techniques from both parts as a promising area in the field of sample pretreatment is given. (C) 2015 Elsevier B.V. All rights reserved.

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