Hybrid Particle Swarm-Ant Colony Algorithm to Describe the Phase Equilibrium of Systems Containing Supercritical Fluids with Ionic Liquids

Based on biologically inspired algorithms, a thermodynamic model to describe the vapor-liquid equilibrium of binary complex mixtures containing supercritical fluids and ionic liquids, is presented. The Peng-Robinson equation of state with the Wong-Sandler mixing rules are used to evaluate the fugacity coefficient on the systems. Then, a hybrid particle swarm-ant colony optimization was used to minimize the difference between calculated and experimental bubble pressure, and calculate the binary interaction parameters for the excess Gibbs free energy of all systems used. Simulations are carried out in nine systems with imidazolium-based ionic liquids. The results show that the bubble pressures were correlated with low deviations between experimental and calculated values. These deviations show that the proposed hybrid algorithm is the preferable method to describe the phase equilibrium of these complex mixtures, and can be used for other similar systems.