Ranking of dispersive-extraction solvents pairs with TOPSIS for the extraction of mifepristone in water samples using dispersive liquid-liquid microextraction

Abstract

TOPSIS, known as Technique for Order of Preference by Similarity to Ideal Solution, is an example of a multi-criteria decision analysis (MCDA) tools useful for decision making for ranking or selecting alternatives based on multiple criteria. In this study, rankings of dispersive-extraction solvents used in DLLME for the extraction of mifepristone in tap water samples was performed to assess their greenness. Two TOPSIS methods based on the objective mean weight (TOPSIS-MW) and entropy (TOPSIS-Entropy) weighting methods were proposed. Criteria were divided into three main categories describing different analytical perspectives: analytical performance, solvents greenness, and combination of analytical performance and solvent greenness. The properties and safety data of the solvents, mean detector response and coefficient of variance were considered as attributes to rank the greener solvent pairs from the combination of sixteen different extraction and disperser solvents as alternatives. The best overall analytical performance for mifepristone was for dichloroethane-acetone and chlorobenzene-tetrahydrofuran pair of solvents, weighted by mean and entropy weights, respectively. The assessment of solvents greenness showed that chloroform-acetone was the most favourable option in terms of green chemistry. The first rank in the combination of the two group of assessment criteria was also achieved by chloroform-acetone solvents. The performance of TOPSIS-MW and TOPSIS-Entropy was evaluated against that of simple additive weighting (SAW) weighted by mean and entropy in terms of the performance of LC-QTOF-MS. The methods were found to be closely correlated with some leading precisely to similar ranking observations.