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 infinitedilution 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 algorithmvariables 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.

Prediction of Infinite-dilution activity coefficients of organic solutes in Ionic Liquids Using Temperature-dependent Quantitative Structure-Property Relationship method,

GRAMATICA, PAOLA
2010

Abstract

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 infinitedilution 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 algorithmvariables 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.
Ionic liquid Infinite-dilution activity coefficient Genetic algorithm-variables subset selection Ordinary least-square regression Temperature-dependent quantitative structure–property relationship
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11383/1718845
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