Prediction of the McAllister model parameters by using the group-contribution method:: n-alkane liquid systems

The McAllister model is considered to be the best correlating technique for viscosity-composition data. In a series of publications, Asfour et al. and Nhaesi and Asfour successfully converted the McAllister model into a predictive model which requires only the viscosities of the pure components and the molecular parameters of the constituents of a liquid mixture. They validated the model for the cases of n-alkane and regular liquid systems by using data on a large number of liquid mixtures at different temperatures. In this paper, we propose a novel technique for predicting the McAllister model parameters, for n-alkane systems, by the group-contribution method. The predictive capability of the McAllister model in this case is shown, for n-alkane binary and multicomponent systems, to be better or at least as good as the techniques reported earlier. The main advantage of the technique we are proposing here is that we expect it to be able to successfully and reliably predict more classes of liquid solutions than earlier methods.