Development of Statistical Associating Fluid Theory for Aqueous Ionic Liquid Solutions by Implementing Monte Carlo Simulations and Ornstein-Zernike Integral Equation

Hao Jiang

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arXiv · 1705.06973

Development of Statistical Associating Fluid Theory for Aqueous Ionic Liquid Solutions by Implementing Monte Carlo Simulations and Ornstein-Zernike Integral Equation

Hao Jiang

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Abstract

A recent version of statistical associating fluid theory (SAFT), namely SAFT2, is coupled with the van der Waals and Platteeuw theory to study the alkane hydrate phase equilibrium conditions. The model is found to provide an accurate representation of the alkane hydrate dissociation conditions with and without inhibitors, such as salts, alcohols, as well as mixed salts and alcohol. Based on SAFT2, a heterosegmented SAFT equation of state is developed to model the thermodynamic properties of aqueous ionic liquid (IL) solutions, which is recently discovered as dual function gas hydrate inhibitors. With transferrable model parameters, the heterosegmented SAFT generally well represents the liquid density, activity coefficient, and osmotic coefficient of aqueous imidazolium IL solutions. The inhibition effects of imidazolium IL on methane hydrate is also studied by the heterosegmented SAFT and the van der Waals and Platteeuw theory. The heterosegmented SAFT is then modified to better represent the thermodynamic properties of aqueous IL solutions with the help of Monte Carlo simulation and the solutions of Ornstein-Zernike integral equation. A simple modification of MSA, referred to as KMSA, is proposed to accurately predict the excess energies of electrolyte system in mixture with neutral component. Monte Carlo simulations are also conducted on flexible charged hard-sphere chain molecules, and a SAFT model which implements either a dimer or a dimer-monomer approach to account for the charged chain connectivity is proposed.

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Hao Jiang. 2017-05-17. Development of Statistical Associating Fluid Theory for Aqueous Ionic Liquid Solutions by Implementing Monte Carlo Simulations and Ornstein-Zernike Integral Equation. https://arxiv.org/abs/1705.06973

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