A predictive approach for thermodynamic modeling of solubility in supercritical fluids using genetic algorithm

The interaction parameter kij used in various mixing rules is not always available. The present work deals with its determination using a group contribution approach which itself is based on group interaction parameters. To date the interaction parameters matrix concerns twelve groups only. Therefore new parameters were determined by optimizing a well defined objective function by means of the genetic algorithm (GAs) and using the Predictive Soave Equation of State (PSEOS) with the van der Waals mixing rule (VDW MR), considering the solubility of organic solutes in supercritical carbon dioxide at elevated pressure ranging from 60 to 350 bar.