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Extractive distillation is a widely accepted and commercialized process for separating azeotropic mixtures compared to conventional distillation. The search for high-performing solvents, or entrainers, needed in extractive distillation is a challenging task. The heuristic guideline or experiment-based method for the screening of entrainers is usually not very efficient and limited to the existing, well-known solvents. In this contribution, we propose a multistage theoretical framework to design solvents for extractive distillation. A multiobjective optimization-based computer-aided molecular design (MOO-CAMD) method is developed and used to find a list of Pareto-optimal solvents. In the MOO-CAMD method, two important solvent properties (i.e., selectivity and capacity) that determine the extractive distillation efficiency are simultaneously optimized. The next step involves a further screening of the Pareto-optimal solvents by performing rigorous thermodynamic calculation and analysis. Finally, for each of...

Optimal Solvent Design for Extractive Distillation Processes: A Multiobjective Optimization-Based Hierarchical Framework