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Integrating Molecular Dynamics Simulations and Experimental Data for Azeotrope Predictions in Binary Mixtures
Xiaoyu Wang, Bingqing Cheng
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An azeotrope is a constant boiling point mixture, and its behavior is important for fluid separation processes. Predicting azeotropes from atomistic simulations is difficult, due to the complexities and convergence problems in Monte Carlo and free-energy perturbation techniques. Here, we present a methodology for predicting the azeotropes of binary mixtures, which computes the compositional dependence of chemical potentials from molecular dynamics simulations using the S0 method, and employs experimental boiling point and vaporization enthalpy data. Using this methodology, we reproduce the azeotropes or the lack of in five case studies, including ethanol/water, ethanol/isooctane, methanol/water, hydrazine/water, and acetone/chloroform mixtures. We find that it is crucial to use the experimental boiling point and vaporization enthalpy for reliable azeotrope predictions, as empirical force fields are not accurate enough for these quantities. Finally, we use regular solution models to rationalize the azeotropes, and reveal that they tend to form when the mixture components have similar boiling points and strong interactions.
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