(147c) Interfacial Tensions from SAFT: Connecting Equations of State to Molecular Simulations | AIChE

(147c) Interfacial Tensions from SAFT: Connecting Equations of State to Molecular Simulations


Müller, E. A. - Presenter, Imperial College London
A description of fluid systems with molecular-based algebraic equations of state (EoSs) and by direct molecular simulation is common practice in chemical engineering and the physical sciences, but the two approaches are rarely closely coupled. The key for an integrated representation is through a well-defined force field and Hamiltonian at the molecular level. We discuss the latest developments in a top-down representation of fluids, where we use an accurate EoS to link the macroscopic properties of the fluid and the force-field parameters, with a particular focus on a coarse-grained formulation of the statistical associating fluid theory (SAFT-γ Mie). The EoS is used to estimate the parameters of the Mie force field, which can then be used with confidence in direct molecular simulations to obtain structural and dynamical properties that are otherwise inaccessible from the EoS, including the interfacial tension, which is a property not included in the original parametrization.

A further theoretical framework is developed based on scaling arguments applied to the influence parameter of the van der Waals theory of inhomogeneous fluids. The molecular model stems from the application of the square gradient theory to the SAFT-γ Mie equation of state. The theory is validated against computer simulation results for homonuclear pearl-necklace linear chains made up to six Mie (λ-6) beads with repulsive exponents spanning λ = 8 to 44 by combining the theory with a corresponding states correlation to determine the intermolecular potential parameters. We show how this can be employed to provide a predictive tool to determine interfacial tensions 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%