(381b) Interfacial Tensions of Industrial Fluids from a Molecular-Based Square Gradient Theory

Several correlations exist which, based on semi-empirical corresponding states principia or otherwise, allow the calculation of the interfacial tension (IFT) of industrially relevant fluids. However, their application is typically restricted to the chemical family used to fix the constants involved. In this work we combine a molecular thermodynamic theory and molecular simulations to obtain faithful description of the tensiometry of molecular models of fluids and a mapping of it to experimental data. Specifically, this work combines a theoretical approach based on the statistical associating fluid theory (SAFT) SAFT-VR Mie EoS with the square gradient theory (SGT) and molecular dynamics simulations (MD). This approach is based on the description of the interfacial properties for short flexible chains composed of 2, 3, 4, 5, and 6 freely-jointed tangent spheres through a Mie λ - 6 (λ= 8, 10, 12, 20) potential. From the MD results, a simple, flexible and accurate expression for the correlation of the influence parameter in SGT is obtained. This expression provides a route to calculate the influence parameters for pure chain fluids by only using the molecular characteristics of the model fluid (m_s, ε, Ï?, λ). By combining this approach with previous mappings of the Mie potential to pure fluids (Mejía, A. Herdes, C. and Müller EA. Force fields for coarse-grained molecular simulations from a corresponding states correlation. Ind Eng Chem Res. 2014; 53:4131â??4141) one can effectively predict the bulk and interfacial properties of pure fluids from the knowledge of only three widely available properties: the critical temperature, the acentric factor, and a liquid density. A key aspect of the methodology is the internal consistency of the molecular model, that is, both the theory and the simulations are based on the same set of unique force field descriptors. We provide a predictive tool to determine IFTs for a wide range of molecules including hydrocarbons, fluorocarbons, polar molecules, among others. The proposed methodology is tested against comparable existing correlations in the literature, proving to be vastly superior, exhibiting an average absolute deviation of 2.2%.