Assessment of COSMO-RS for Predicting Liquid–Liquid Equilibrium in Systems Containing Deep Eutectic Solvents

Abstract

Deep eutectic solvents (DESs) have gained significant attention as green solvents for liquid–liquid extraction applications. Predictive thermodynamic models can identify suitable DESs for a specific separation problem. To this end, we conducted a comprehensive evaluation of the conductor-like screening model for real solvents (COSMO-RS) to predict liquid–liquid equilibrium (LLE) in systems containing DESs. The TZVP and TZVPD-FINE parameter sets of COSMO-RS were considered, and the salts were modeled as associated or fully dissociated ions. The results showed that COSMO-RS predicted LLE in all systems with an average root mean square deviations (RMSDs) below 10% and represented lower average RMSD in systems with nonsalt DESs than salt-based DESs. COSMO-RS predictions using the TZVPD-FINE parameter set were slightly better than the TZVP parameter set. Nevertheless, the COSMO-RS predictions of the solute distribution between the phases were not accurate enough compared to experimental data using either of the parameter sets. COSMO-RS largely overestimated the solute partition coefficients for aromatic and heterocyclic solutes in systems containing alkanes and salt-based DES. On the other hand, acceptable RMSDs and reliable predictions of partition coefficients were observed for alcohol solutes in systems containing alkanes and salt-based DESs. Given the complexity of describing the interactions and LLE in quaternary systems containing salts, further improvements in the COSMO-RS model are still needed. This study highlighted the potential and shortcomings of COSMO-RS as a tool to utilize DES for liquid–liquid extraction applications.