Chemical Engineering Journal, Vol.163, No.3, 195-201, 2010
Prediction of infinite-dilution activity coefficients of organic solutes in ionic liquids using temperature-dependent quantitative structure-property relationship method
Ionic liquids (ILs) are a type of potential green solvents, which can be used as a media for reaction and separation. The infinite-dilution activity coefficient is an important parameter to measure the interaction between ILs and solutes. In this work, we proposed a new method to predict infinite-dilution activity coefficients of ILs at different temperatures. A temperature-dependent quantitative structure-property relationship (QSPR) model was developed for a series of organic solutes in the ionic liquid trihexyl(tetradecyl)phosphonium bis(trifluoromethylsulfonyl)imide. By using genetic algorithm-variables subset selection (GA-VSS) and ordinary least-square regression (OLS) methods, six variables, including temperature and five significant molecular descriptors, were selected and used to build the temperature-dependent prediction model. The satisfactory results of the internal and external validations proved the reliability, stability and predictive ability of the built model. (C) 2010 Elsevier B.V. All rights reserved.
Keywords:Ionic liquid;Infinite-dilution activity coefficient;Genetic algorithm-variables subset selection;Ordinary least-square regression;Temperature-dependent quantitative structure property relationship