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Current Green Chemistry

Editor-in-Chief

ISSN (Print): 2213-3461
ISSN (Online): 2213-347X

Research Article

Sample Treatment in Organic Compound Determination: A Green Chemistry Perspective

Author(s): Noemí M. Fernández, Ana M. Coto-García, Raquel Gonzalo-Lumbreras, Jon Sanz-Landaluze, Concepción Pérez-Conde and Carmen Cámara

Volume 3, Issue 2, 2016

Page: [133 - 144] Pages: 12

DOI: 10.2174/2213346103666160526130744

Price: $65

Abstract

Background: Analysis of organic compounds in several complex matrices is a growing need and great efforts have been made to achieve analytical characteristics for their quantification or identification in small samples. Sample treatment in terms of time spent, and the use of large amounts of solvents, generating considerable amounts of wastes are the most limiting aspects of an analytical method.

Methods: Here, we review the features of different extraction and cleaning techniques for organic compound determination from a green chemistry perspective.

Results: The large number of techniques discussed in this review implies a great advance in comparison to conventional extraction techniques in terms of solvent consumption, extraction time or automation. The current trend of miniaturization of the extraction process is a viable alternative from a Green Chemistry perspective. Miniaturization involves reduction of amounts of organic solvents and wastes, and also the contamination risk or analyte losses. Thus, automation of the whole analytical process is facilitated. Final decision regarding the extraction technique to choose in each analysis will depend on the type of compounds to be determined, the type of sample or matrix and their concentration. Combination of microextraction techniques with novel extractants or new sorbents will open the door either to improve current extraction techniques or to develop new ones aiming to diminish environmental damage and enabling the automation of the process.

Keywords: Miniaturized, sample treatment, organic compounds, environmental samples.

Graphical Abstract

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