Abstract
Abstract
2-Methyltetrahydrofuran (2-MTHF) and acetonitrile (ACN) are widely used solvents in pharmaceutical manufacturing, but their recovery from waste solvent mixtures is challenging because of the formation of a minimum-boiling azeotrope. Herein, an ionic liquid (IL)-assisted extractive distillation (ED) was developed by integrating molecular-based entrainer screening with process optimization. Eighty candidate ILs were systematically screened using quantum chemical calculations, from which 1-butyl-3-methylpyridinium diethyl phosphate ([BMPY][DEP]) was identified as the optimal entrainer. σ-Profile, electrostatic potential (ESP), and independent gradient model with Hirshfeld partition (IGMH) analyses demonstrated that the preferential interactions of [BMPY][DEP] with ACN arise from stronger hydrogen-bonding and electrostatic interactions than those with 2-MTHF, providing a molecular basis for its separation selectivity. The corresponding thermophysical properties and binary interaction parameters were then incorporated into Aspen Plus V12 to develop and optimize conventional ED and heat-integrated ED (HI-ED) processes. Multiobjective optimization using a genetic algorithm was performed with total annual cost (TAC) and CO2 emissions as the objective functions. The optimized HI-ED process reduced TAC by 14,431 $/year and CO2 emissions by 290 t/year compared with conventional ED, while [BMPY][DEP] showed favorable economic performance relative to conventional organic entrainers. These results demonstrate that the molecularly selected IL can be effectively translated into process-level benefits, highlighting an integrated molecular-to-process strategy for sustainable ACN/2-MTHF recovery.