Design of Solvent Mixtures for Selective Extraction by Quantifying Thermodynamic and Sustainability Aspects

Abstract

The selection of suitable solvents for selective extraction is a challenging task due to expensive experimental studies and heavy reliance on heuristics which introduce errors and biased judgements. The development of computer-aided molecular design (CAMD) has facilitated the search for novel solvents by providing an efficient and systematic computational approach. In this work, a novel CAMD framework for the selection of most suitable solvents or solvent mixtures by quantifying thermodynamics and sustainability aspects has been developed. The overall solvent design methodology can be described via a multi-level approach. The first level involves the prescreening of molecular blocks by introducing a solubility model to identify the promising functional groups. The second level includes the implementation of a rigorous model to determine potential solvents based on phase equilibrium information such as selectivity and capacity. Finally, the third level incorporates safety and health parameters in the formulation of a multi-objective optimization problem. Here, a modified fuzzy algorithm is developed to address the trade-off between thermodynamic and safety and health properties. In cases where the selectivity and capacity show antagonistic behaviour, solvent mixture design is introduced to improve the extraction performance. The developed CAMD framework is illustrated through a case study on the extraction of 1,2-dichloroethane from cyclohexane.