An accurate model for the prediction of the glass transition temperature of ammonium based ionic liquids: A QSPR approach

Glass transition temperature is one of the main criteria for the assessment of the potential electrolyte options. In this study, the attention is focused to develop a model to predict this property for ammonium based ionic liquids with the aid of Quantitative Structure–Property Relationship (QSPR) method.To develop a model, the contribution of the both anion and cation parts are considered. This would help to study the effect of structural variation of both ionic segments on the desired physical property.Genetic Function Approximation is applied for model's parameter selection (molecular descriptors) and its development. Consequently, a simple linear predictive model with satisfactory results quantified by the following statistical parameters: absolute average deviations (AAD) of the predicted properties from existing experimental values by the GFA linear equation: 1.98%, linear correlation coefficient squared (R2): 0.9657 and Root Mean Square: 4.3 K.

► A predictive QSPR model is presented for estimation of glass transition temperature of ammonium-based ionic liquids.
► The model is molecular-based and accurate.
► The model can be employed for designing new ionic liquids serving as electrolytes.