For the selection
of industrially suitable ionic liquids (ILs)
as extraction solvents, a systematic method combining phase equilibrium
calculation, physical property prediction, and process simulation
is presented. The conductor-like screening model for real solvents
is used to predict the liquid–liquid equilibria of the systems
composed of the target mixture to be separated and different ILs at
the specific global composition of interest, thereby prescreening
ILs with higher mass-based distribution coefficient and selectivity
as well as lower solvent loss. Group contribution methods are then
employed to estimate the key physical properties of the prescreened
ILs and further suggest candidates meeting certain physical property
constraints. Afterward, the performance of the top IL candidates in
a continuous process is analyzed by Aspen Plus to identify finally
process-based optimal solvents. The proposed method is illustrated
with an extractive desulfurization case study and two most promising
ILs for this process are consequently determined.
To properly screen and use ionic liquids (ILs) as environmental-friendly solvents in chemical reactors and separation processes, the knowledge of their solubilities with water is essential. In the present work, mutual solubilities of 1500 ILs (50 cations, 30 anions) with water at 298.15 K were predicted by using the conductor-like screening model for real solvents (COSMO-RS) as a thermodynamic model. On the basis of the COSMO-RS calculations, the influence of the types of anion and cation, side chain modifications and substituent groups on the mutual solubility with water was extensively analyzed. The data obtained can be used for the prescreening of ILs as solvent candidates. Moreover, to understand the intrinsic solubility behavior in detail, different types of molecular interactions between ILs and water in solution were compared on the basis of the determination of multiple water−IL interaction energies from COSMO-RS computation. The results confirm that hydrogen bonding interactions between anions and water molecules have the dominant influence on the solubility. Finally, for the purpose of fast solubility estimation and solvent selection, COSMO-RS derived molecular descriptors which indicate the strength of anionic HB acceptors were calculated for typical anions and anion families.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.