4.6 Article

Supramolecular nanosolvent-based hollow fiber liquid phase microextraction as a novel method for simultaneous preconcentration of acidic, basic and amphiprotic pollutants

Journal

RSC ADVANCES
Volume 6, Issue 48, Pages 41825-41834

Publisher

ROYAL SOC CHEMISTRY
DOI: 10.1039/c5ra23488c

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The coextraction of acidic, basic and amphiprotic pollutants from various matrixes is a significant and disputable concept in sample preparation strategies. In this study, for the first time, coextraction of acidic, basic and amphiprotic pollutants was performed using supramolecular nanosolvent-based hollow fiber liquid phase microextraction (SS-HF-LPME) as an efficient method followed by high performance liquid chromatography-photodiode array detection. The supramolecular solvent (SUPRAS) is formed through coacervation of decanoic acid aqueous vesicles in the presence of tetrabutylammonium hydroxide. The results revealed that 40% SUPRAS in 1-decanol has the best extraction efficiency for three selected model analytes (4-nitrophenol, 3-nitroaniline and 1-amino-2-naphthol). The extraction process was accomplished in two-phase mode and the unique interactions between the solvent and polar analytes (hydrophobic, electrostatic, hydrogen bonding and pi-cation interactions) resulted in elevated coextraction efficiency. Central composite design methodology combined with the desirability function approach was applied to develop predictive models for simulation and optimization of the SS-HF-LPME procedure. The optimized conditions were: pH of the sample, 9.0; percentage of SUPRAS in 1-decanol, 40%; extraction time, 30 min; salt concentration, 20% w/v; stirring rate, 1250 rpm. Under the optimum conditions, detection limits and linear dynamic ranges were achieved in the range of 0.1-0.2 mu g L-1 and 0.5-400 mu g L-1, respectively. The percentage extraction recoveries and relative standard deviations (n = 5) were in the range of 56.1-71.1 and 4.1-6.9, respectively. Finally, the applicability of this method was successfully confirmed by analyzing rain, snow, river, dam and wastewater samples.

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