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Frontiers of Chemical Science and Engineering >> 2007, Volume 1, Issue 2 doi: 10.1007/s11705-007-0035-3

Measurement of activity coefficients at infinite dilution for hydrocarbons in imidazolium-based ionic liquids and QSPR model

1.State Key Laboratory of Chemical Resource Engineering, Beijing University of Chemical Technology, Beijing 100029, China; State Key Laboratory of Chemical Engineering, Tsinghua University, Beijing 100084, China; 2.State Key Laboratory of Chemical Engineering, Tsinghua University, Beijing 100084, Chin;

Available online: 2007-06-05

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Abstract

The separations of olefin/paraffin, aromatic/aliphatic hydrocarbons or olefin isomers using ionic liquids instead of volatile solvents have interested many researchers. Activity coefficients γ at infinite dilution of a solute in ionic liquid are generally used in the selection of solvents for extraction or extractive distillation. In fact, the measurement of γ by gas-liquid chromatography is a speedy and cost-saving method. Activity coefficients at infinite dilution of hydrocarbon solutes, such as alkanes, hexenes, alkylbenzenes, styrene, in 1-allyl-3-methylimidazolium tetrafluoroborate ([AMIM][BF]) and 1-butyl-3-methyl imidazolium hexafluorophosphate ([BMIM][PF6]), 1-isobutenyl-3-methylimidazolium tetrafluoroborate ([MPMIM][BF]) and [MPMIM][BF]-AgBF have been determined by gas-liquid chromatography using ionic liquids as stationary phase. The measurements were carried out at different temperatures from 298 to 318 K. The separating effects of these ionic liquids for alkanes/hexane, aliphatic hydrocarbons/benzene and hexene isomers have been discussed. The hydrophobic parameter, dipole element, frontier molecular orbital energy gap and hydration energy of these hydrocarbons were calculated with the PM3 semi-empirical quantum chemistry method. The quantitative relations among the computed structure parameters and activity coefficients at infinite dilution were also developed. The experimental activity coefficient data are consistent with the correlated and predicted results using QSPR models.

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