Predicting and rationalizing the Soret coefficient of binary Lennard-Jones mixtures in the liquid state

Thermodiffusion is a coupled heat and mass transport process, in which a temperature gradient initiates the separation of components in a mixture. It occurs in many natural and technical processes, but experimental measurements are indirect and expensive. Therefore, molecular simulations are valuable to quickly predict transport properties such as the Soret coefficient and provide insights into the underlying mechanisms on the molecular level. In the present work, the thermodiffusion behavior of binary Lennard-Jones mixtures in the liquid state was 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. A detailed analysis of the Soret coefficient suggests a straightforward dependency on thermodynamic properties, whereas its dependence on dynamic properties such as the Onsager coefficients is by 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 use model parameters of the simulated systems instead of simulation outputs. 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.