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The effect of vacuum: an emerging experimental parameter to consider during headspace microextraction sampling

Psyllaki Eleftheria

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/74C5D37E-BC97-4458-B409-3249D46E8B4A
Έτος 2020
Τύπος Δημοσίευση σε Περιοδικό με Κριτές
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά E. Psillakis, “The effect of vacuum: an emerging experimental parameter to consider during headspace microextraction sampling,” Anal. Bioanal. Chem., vol. 412, no. 24, pp. 5989–5997, Sep. 2020. doi: 10.1007/s00216-020-02738-x https://doi.org/10.1007/s00216-020-02738-x
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Περίληψη

The effect of vacuum is an emerging experimental parameter to consider during optimization of a variety of headspace microextraction methodologies. The positive effect of vacuum was initially demonstrated for headspace solid-phase microextraction and was recently expanded to single-drop microextraction and higher capacity sorbents i.e. stir bar sorptive extraction. In all cases, sampling under vacuum greatly accelerated the extraction kinetics of analytes exhibiting long equilibration times under atmospheric pressure. At the same time, the extraction of analytes that reached equilibrium fast was not affected. In all optimized methods, extraction times were greatly reduced and/or sampling temperatures were lower to those reported with the standard methodology under atmospheric pressure. This work succinctly overviews the effect of vacuum on the different headspace microextraction technologies reported so far. The fundamental concepts describing the pressure dependence of each methodology are pulled together and presented in a simplified manner. The latest findings on the combined effects of vacuum and several selected experimental parameters typically examined during method optimization are then presented and the practical aspects of past outcomes are highlighted. The discussion also includes the air-evacuation step and the analysis of complex matrices. This article is intended for readers who are either new to the field of vacuum headspace microextraction sampling or its use and want to exploit this powerful approach.

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