Sustainable framework to develop deep eutectic solvent-based DLLME methodologies using COSMO-RS and RSM: Application to PCB-77 in greywater

M. Villegas, C. Toledo-Neira, G. Merlet, R. Cabezas, J. Romero, E. Villarroel-Utreras, E. Quijada-Maldonado

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This study presents a novel framework that integrates COSMO-RS calculations with Response Surface Methodology (RSM) to develop a dispersive liquid–liquid microextraction (DLLME) method for PCB-77, targeting a more sustainable sample preparation process. Deep eutectic solvents (DES) were employed as green extraction solvents. The methodology involved an initial screening of the most suitable DES for PCB-77 extraction using COSMO-RS, followed by experimental validation. Subsequently, RSM was applied to optimize operational variables, achieving high enrichment factors (EF) and recoveries (REC). COSMO-RS calculations identified lidocaine (Lid) and menthol (Meth)-based DES as having the highest affinity for PCB-77, which was corroborated experimentally. Optimization of DLLME operational conditions through RSM resulted in an EF of 51.6 and a REC of 61.2 % for the extraction of PCB-77 from water. Real greywater samples doped with PCB-77 were analyzed to validate the framework, achieving EF values of 41 and 80.6 for water collected from the first and third rinses of a washing machine cycle, respectively. This framework significantly reduces the number of required experiments, offering a pathway to accelerate the development of green and selective sample preparation techniques. Furthermore, it highlights the potential to quantify emerging pollutants in greywater, which could serve as an alternative water source in regions affected by extreme drought.

Original languageEnglish
Article number126790
JournalJournal of Molecular Liquids
Volume419
DOIs
StatePublished - 1 Feb 2025
Externally publishedYes

Keywords

  • COSMO-RS
  • DES
  • DLLME
  • Experimental design
  • Green analytical chemistry
  • Sample preparation

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