This work reports on a novel, decomposition-based approach for integrated optimal solvent and process design. It aims at developing a design methodology for integrated solvent and process synthesis that maintains all the necessary design information at the solvent design stage and utilizes efficient ways of interfacing this information at the process synthesis stage. The approach builds upon multiple objective optimization in order to generate a set of optimal solvent molecules that embeds highly inclusive designs and incorporates comprehensive design information regardless of process economics. Additionally, it proposes and assesses the use of molecular clustering techniques and of a Pareto front model as a means of efficiently incorporating the obtained design information at the process synthesis level. Applications are presented in the simultaneous design of solvents and separation processes for liquid-liquid extraction and gas absorption.
- Computer-aided solvent design
- multi-objective optimization
- solvent and process integration
ASJC Scopus subject areas
- Chemical Engineering(all)
- Computer Science Applications