Capturing the solubility minima of n-Alkanes in water by Soft-SAFT

The purpose of this work is twofold: (1) to provide an accurate molecular model for water within the soft-SAFT equation of state [Bias, F. J.; Vega, L. F. Mol. Phys. 1997, 92, 135; Llovell, F., et al. J. Chem. Phys. 2004, 121, 10715] and (2) to check the capability of this molecular-based equation of state for capturing the solubility minima of n-alkanes in water experimentally found at room temperature for these mixtures. Water was modeled as a Lennard-Jones sphere with four associating sites, with parameters obtained by fitting to experimental vapor-liquid equilibrium data. Special care was taken to the value of these parameters depending on the range of applicability of the equation, which turned out to be essential for accurate predictions for mixtures. A correlation available in the literature was used for the molecular parameters of the n-alkane series. The crossover soft-SAFT equation was able to accurately describe the phase behavior of water near to and far from the critical point, up to 350 K. If instead of obtaining an overall good agreement one is interested in a more precise description of the near-ambient conditions, a more refined fitting of the parameters is needed. The model was used to describe the water + methane up to water + n-decane binary mixtures. The equation was able to predict the mutual solubilities in almost quantitative agreement with experimental data, including the presence of the solubility minima at ambient temperature, with a single transferable energy binary parameter, independent of temperature and chain length. Predictions obtained from the soft-SAFT approach are clearly superior than those obtained from the Huang and Radosz version of the SAFT equation [Economou, I. G.; Tsonopoulos, C. Chem. Eng. Sci. 1997, 52, 511], due to the more refined reference term and the more accurate radial distribution function used in the chain and association terms. This is the first time a SAFT approach is able to describe this minima.