Abstract

For design of ionic liquid (IL) solvents for a specific separation process, a computer-aided ionic liquid design (CAILD) method based on multi-scale simulations is presented. A new group contribution based approach GC-COSMO for ILs is established for estimating the σ-profiles and cavity volumes of cations, where ILs are structured by three parts, i.e., one anion, one cation skeleton, and substituents on cation skeleton. Prediction models, including the COSMO-SAC model for thermodynamic properties and semi-empirical models for physical properties, are integrated into a computational IL design framework. A mixed-integer nonlinear programming (MINLP) problem is then formulated to optimize the separation performance combing the constraints of structural feasibility and physical properties. The optimal IL solvents are identified using a deterministic optimization method with branch and bound algorithm. The CAILD method is successfully tested for two typical separation examples, i.e. extraction of benzene from cyclohexane and post-combustion CO2 capture.

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