Predicting and Rationalizing the Soret Coefficient of Binary Lennard-Jones Mixtures in the Liquid State

The thermodiffusion behavior of binary Lennard-Jones mixtures in the liquid state is investigated by combining the individual strengths of non-equilibrium molecular dynamics (NEMD) and equilibrium molecular dynamics (EMD) simulations. On the one hand, boundary-driven NEMD simulations are useful to quickly predict Soret coefficients because they are easy to set up and straightforward to analyze. However, careful interpolation is required because the mean temperature in the measurement region does not exactly reach the target temperature. On the other hand, EMD simulations attain the target temperature precisely and yield a multitude of properties that clarify the microscopic origins of Soret coefficient trends. An analysis of the Soret coefficient suggests a straightforward dependence on the thermodynamic properties, whereas its dependence on dynamic properties is far more complex. Furthermore, a limit of applicability of a popular theoretical model, which mainly relies on thermodynamic data, was identified by virtue of an uncertainty analysis in conjunction with efficient empirical Soret coefficient predictions, which rely on model parameters instead of simulation output. Finally, the present study underscores that a combination of predictive models and EMD and NEMD simulations is a powerful approach to shed light onto the thermodiffusion behavior of liquid mixtures.

Automated summary

The study investigates the thermodiffusion behavior of binary Lennard-Jones mixtures in the liquid state by combining NEMD and EMD simulations. It finds that the Soret coefficient has a straightforward dependence on thermodynamic properties, but a more complex dependence on dynamic properties. The study identifies the limit of applicability of a popular theoretical model in thermodiffusion behavior research through uncertainty analysis.