Inverse gas chromatography was used to obtain the activity coefficients at infinite dilution (γ 13 ∞ ) of several organic solutes and water in the thermotropic ionic liquid crystal phases of both [C 12 mim][BF 4 ] and [C 14 mim][BF 4 ] and their isotropic phases. In the smectic to isotropic transition, a change in the linear representation of the natural logarithm of γ 13 ∞ with the reciprocal temperature was observed for [C 14 mim][BF 4 ], and was more evident for alkanes, alkylbenzenes, esters, and alcohols, that can be related to structural modifications of the stationary phase. Results are interpreted in terms of the enthalpic and entropic contributions of solute-IL interactions. Selectivities and capacities of important separation problems, such as octane/benzene and cyclohexane/ benzene, were calculated and compared with literature values for separating agents such as N-methyl-2-pyrrolidinone, sulfolane, and ionic liquids presenting the [BF 4 ] − anion combined with several imidazolium-based cations. It is shown that to achieve maximum separation efficiency, imidazolium cations with short alkyl chain lengths such as [C 2 mim][BF 4 ] should be used, whereas high capacities require larger alkyl chain lengths.
The Abraham and NRTL-SAC semipredictive models were employed to represent the solubility of (−)-borneol, (1R)-(+)-camphor, L-(−)-menthol, and thymol in water and organic solvents, using data measured in this work and collected from the literature. A reduced set of solubility data was used to estimate the model parameters of the solutes, and global average relative deviations (ARDs) of 27% for the Abraham model and 15% for the NRTL-SAC model were obtained. The predictive capability of these models was tested by estimating the solubilities in solvents not included in the correlation step. Global ARDs of 8% (Abraham model) and 14% (NRTL-SAC model) were obtained. Finally, the predictive COSMO-RS model was used to describe the solubility data in organic solvents, with ARD of 16%. These results show the overall better performance of NRTL-SAC in a hybrid correlation/prediction approach, while COSMO-RS can produce very satisfactory predictions even in the absence of any experimental data.
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