Development of a new parameterization strategy and GC parameters of halogenated hydrocarbons for PC-SAFT equation of state

Statistical Associating Fluid Theory (SAFT) equations of state (EoSs) have been extensively used in the prediction of fluid phase equilibria and thermodynamic properties. For each fluid, determining the component-dependent parameters typically involves fitting experimental data with a local optimization algorithm. SAFT-type EoSs are highly nonlinear due to the high-order functions used to describe different contribution terms. This nonlinearity leads to the presence of multiple local optima, making parameter optimization very sensitive to initial values. Hence, it is crucial to determine the starting point for the optimization process, yet little attention has been paid to how initial parameter sets are selected. In this paper, a method based on group contributions to establish an appropriate initial value for the optimization process is proposed and applied to Perturbed-Chain SAFT (PCSAFT). The optimized PC-SAFT parameters for a total of 74 substances from 11 different chemical families have been evaluated. The fitting results for saturated pressure, liquid density, and vapor density showed overall average absolute relative deviations (AARD) of 0.050 %, 0.042 %, and 0.151 %, respectively. This paper also provided group contribution parameters for halogenated hydrocarbons to estimate PC-SAFT parameters. Additionally, an assessment of global and local optimization algorithms was conducted. The results demonstrate that the global algorithm not only requires longer computation time but also exhibits significantly lower accuracy compared to the local algorithm. The overall AARD for the global algorithm is 9.493 %, whereas for the local algorithm, it stands at 0.068 %.