Extending the UNIFAC model for ionic liquid–solute systems by combining experimental and computational databases

Abstract Considering that the predictive UNIFAC model is highly valuable for the solvent selection, process design and optimization of separation tasks, a large extension of this model to ionic liquid (IL)–solute systems is presented by combining experimental and COSMO‐RS derived databases. The experimental infinite dilution activity coefficient ( γ ∞ ) data of different solutes in ILs are first collected exhaustively to extend UNIFAC‐IL to cover all involved IL and conventional functional groups. Afterwards, the experimental and COSMO‐RS calculated γ ∞ are compared for different types of solutes to evaluate the potential of using COSMO‐RS predictions as quasi‐experimental data for further UNIFAC‐IL extension. In the cases where COSMO‐RS can provide quantitatively accurate predictions after calibration, additional γ ∞ database is specifically generated to regress more group interaction parameters in the UNIFAC‐IL model. Finally, a large experimental liquid–liquid and vapor–liquid equilibria database is collected and employed to evaluate the predictive performance of the obtained γ ∞ ‐based UNIFAC‐IL model.