(354c) Mutual Diffusion of Binary Liquid Mixtures Containing Methanol, Ethanol, Acetone, Benzene, Cyclohexane, Toluene and Carbon Tetrachloride

Nowadays, modern rate-based methods, which involve mass and energy transfer models, are employed to solve complex macroscopic modelling and simulation issues in the chemical engineering field. These non-equilibrium methods require not only diffusion data, but also other transport coefficients like shear viscosity and thermal conductivity for pure components as well as mixtures. Thus, there is a growing need for accurate transport properties and better methods for their prediction. Owing to the rapid development of computing power, molecular modelling and simulation has emerged as an alternative for such predictions, especially when dealing with hazardous substances or challenging thermodynamic conditions.

We present the results of a comprehensive study on the prediction of mutual diffusion coefficients in binary mixtures on the basis of molecular dynamics simulations and the Green-Kubo formalism. The diffusion coefficients of all 20 binary liquid mixtures that can be formed out of methanol, ethanol, acetone, benzene, cyclohexane, toluene and carbon tetrachloride without a miscibility gap at ambient conditions of temperature and pressure are assessed in the entire composition range. The considered mixtures show a varying mixing behavior from almost ideal to strongly non-ideal. Radial distribution functions are analyzed to gain an understanding of the liquid structure influencing the diffusion processes. It is shown that cluster formation in mixtures containing one alcoholic component has a significant impact on the diffusion process. The estimation of the thermodynamic factor from experimental vapor-liquid equilibrium data is investigated, considering three excess Gibbs energy models, i.e. Wilson, NRTL and UNIQUAC. It is found that the Wilson model yields the thermodynamic factor that best suits the simulation results for the prediction of the Fick diffusion coefficient. Four semi-empirical methods for the prediction of the self-diffusion coefficients and nine predictive equations for the Fick diffusion coefficient are assessed and it is found that methods based on local composition models are more reliable. Finally, the shear viscosity and thermal conductivity are predicted and in most cases favorably compared with experimental literature values.