Generalized linear solvation energy model applied to solute partition coefficients in ionic liquid–supercritical carbon dioxide systems

Biphasic solvent systems composed of an ionic liquid (IL) and supercritical carbon dioxide (scCO2) have become frequented in synthesis, extractions and electrochemistry. In the design of related applications, information on interphase partitioning of the target organics is essential, and the infinite-dilution partition coefficients of the organic solutes in IL–scCO2 systems can conveniently be obtained by supercritical fluid chromatography. The data base of experimental partition coefficients obtained previously in this laboratory has been employed to test a generalized predictive model for the solute partition coefficients. The model is an amended version of that described before by Hiraga et al. (J. Supercrit. Fluids, in press). Because of difficulty of the problem to be modeled, the model involves several different concepts – linear solvation energy relationships, density-dependent solvent power of scCO2, regular solution theory, and the Flory–Huggins theory of athermal solutions. The model shows a moderate success in correlating the infinite-dilution solute partition coefficients (K-factors) in individual IL–scCO2 systems at varying temperature and pressure. However, larger K-factor data sets involving multiple IL–scCO2 systems appear to be beyond reach of the model, especially when the ILs involved pertain to different cation classes.

► Solute partitioning in IL–scCO2 systems was modeled with a predictive correlation.
► Large set of K-factors obtained by SFC provided a stringent test of the model.
► Reproduction of data from single IL–scCO2 systems was relatively successful.
► Simultaneous fit of data from multiple IL–scCO2 systems was difficult to achieve.