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Capillary Electrophoresis as a green Alternative Separation Technique

Wuethrich, A and Quirino, JP ORCID: 0000-0002-8275-9672 2017 , 'Capillary Electrophoresis as a green Alternative Separation Technique', in F Pena-Pereira and M Tobiszewski (eds.), The Application of Green Solvents in Separation Processes , Elsevier, Netherlands, pp. 517-532.

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Abstract

Electrokinetic separations or electrodriven separation techniques in microchannels such as capillaries use the electric field to induce analyte separation of mainly nonvolatile molecules by electrophoretic mobility and analyte elution by generation of an electroosmotic flow. The use of additives such as micelles added into the background electrolyte or stationary phases prepared inside the channels transform these approaches to analytical separation methods that parallel that of chromatography. In fact, there are separation modes available in electrodriven separation or capillary electrophoresis modes that function the same way as their traditional chromatographic counterparts. The small scales in which electrodriven separations are performed make this family of techniques a greener alternative to chromatography. For example, reversed phase chromatography uses far larger amounts of mobile phases that contain organic solvents compared to an electrodriven method with the same analytical performance. Although recent developments in chromatography have decreased solvent and materials consumption by using smaller columns, the use of smaller columns however, does not always improve the separation performance. This chapter aims to introduce the chromatographic and electrokinetic separations, which will be useful for readers not familiar with separation techniques, and then compare these separation techniques in terms of their “greenness.”

Item Type: Book Section
Authors/Creators:Wuethrich, A and Quirino, JP
Keywords: capillary electrophoresis, green separation techniques
Publisher: Elsevier
DOI / ID Number: 10.1016/B978-0-12-805297-6.00017-6
Copyright Information:

Copyright 2017 Elsevier Inc.

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