Application of particle swarm optimization to model the phase equilibrium of complex mixtures

Based on the conception of biologically inspired algorithms, the particle swarm optimization (PSO) is applied to model the phase equilibrium of complex mixtures containing supercritical carbon dioxide with ionic liquids or biomolecules. A commonly used equation of state with mixing rules is used as a thermodynamic model. Simulations are carried out in five complex mixtures containing ionic liquids, and for another six complex mixtures consisting of biomolecules. Then, PSO algorithm is used to minimize the difference between calculated and experimental values, and calculate the binary interaction parameters for all systems used. The results show that the PSO algorithm provides a good method to optimize the interaction parameters of the phase equilibrium of any mixtures with high accuracy.

► Particle swarm optimization is applied to model the phase equilibrium. ► The Peng–Robinson equation of state with the Wong–Sandler mixing rule are used as thermodynamic model. ► The binary interaction parameters of the eleven mixtures containing CO2 are calculated.