Mathematical representation of solute solubility in binary mixture of supercritical fluids by the Jouyban-Acree model

Abstract

Applicability of a solution model for calculating the solute solubility in binary mixtures of supercritical fluids at different SCIF compositions and pressures was shown using phenanthrene solubility data in supercritical carbon dioxide and supercritical ethane at 313 K and a pressure range of 100-350 bar. The correlation ability of the proposed model was evaluated by fitting all data points and computing error term employing back-calculated solubilities. The prediction capability of the model was assessed by dividing each data set to two subsets, namely training and test subsets. The predicted solubilities using trained models were used to calculate the prediction error term. The results show that both correlative and predictive error terms were less than the experimentally obtained RSD values.