A new structure-based model for estimation of true critical volume of multi-component mixtures

Abstract

In this study, a new quantitative structure–property relationship (QSPR) has been proposed to estimate true vapor–liquid critical volume of multi-component mixtures. In developing this model, 598 experimental data on true critical volume for 110 different binary mixtures were applied. The mixture molecular descriptors were computed according to the molecular descriptors of pure components involved in the mixture and their molar fractions. Enhanced replacement method (ERM), as an effective tool for subset variable selection, was utilized. The proposed model is simple multivariate linear equations with six variables. The prediction capability of the proposed model for different families of compounds was critically analyzed. Besides, the capability of the proposed model has been tested by predicting true critical volume of 7 different multi-component mixtures containing 40 experimental data points. The average absolute relative deviation of the proposed QSPR model over all experimental data is 9.7% and 8.7% for binary mixtures and multi-component mixtures, respectively.