SAFT-VR Mie is one of the most recent extensions of Statistical Associating Fluid Theory (SAFT). It is based on the Mie potential, which is a generalized form of the Lennard-Jones potential in which the exponents of the repulsive and attractive terms are allowed to vary from 12 and 6, respectively. In this thesis, the latest formulation of SAFT-VR Mie is implemented to accurately calculate densities and phase equilibria of both associating and non-associating fluid mixtures. The model is subsequently extended to mixtures with strongly dissociating electrolytes in water through the addition of a Born term to account for solvation effects and a Debye-Huckel term for long-range, electrostatic interactions. A single adjustable parameter is assigned to each ionic species (the cross dispersion energy between the ion and solvent) and is optimized against experimental data for electrolyte solution densities and mean ionic activity coefficients using a sequential Nelder-Mead algorithm with a parallel objective function evaluation. Model correlations for the activity coefficients and liquid densities, as well as predictive calculations of vapor pressure, osmotic coefficients and mixed ion properties, show that the model's performance is comparable to that of other recent formulations for electrolyte solutions. Further improvement in a subsequent generation of the proposed equation of state will likely derive from a better description of dielectric phenomena, and adjustments to the parameter optimization strategy.
ETD Chair
Economou, Ioannis Senior Associate Dean for Academic Affairs and Graduate Studies, Texas A&M at Qatar
