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Maxwell-Stefan diffusivities in liquid mixtures: Using molecular dynamics for testing model predictions

机译：液体混合物中的Maxwell-Stefan扩散率：使用分子动力学测试模型预测

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Multicomponent diffusion is ubiquitous in (bio)chemical processes. The Maxwell-Stefan (M-S) framework provides a sound theoretical basis for describing transport diffusion as it correctly accounts for the gradient in chemical potential as driving force. Unfortunately, M-S diffusivities {Eth}_(ij) cannot be measured directly in experiments. The use of predictive models based on easily measurable quantities like Fick- or self-diffusivities in diluted systems is therefore desirable. In this study, equilibrium molecular dynamics (EMD) simulations are used to study M-S diffusivities in liquid mixtures containing n-hexane, cyclohexane and/or toluene. Predictive models for estimating M-S diffusivities {Eth}ijxk→1 in ternary systems are investigated. The following analysis are carried out. First, these predictive models are used to calculate the self-diffusivity in the infinite dilution limit using the well-known Vignes approximation. The predicted self-diffusivity is compared to the self-diffusivity directly calculated from EMD simulations. Second, we investigated the quality of the Vignes approximation using diffusivities obtained from EMD simulations. Third, we directly compared the predictive models for {Eth}ijxk→1 with EMD simulations. Our results show that: (1) predicted self-diffusivities are not very sensitive to the choice of the predictive model for {Eth}ijxk→1; (2) the Vignes equation results in only reasonable predictions for M-S diffusivities, yielding errors of 13% on average; (3) the interaction between solutes and solvent cannot be neglected in predictive models for {Eth}ijxk→1; (4) present predictive models for calculating {Eth}ijxk→1 from binary data results in errors of 8% for the systems under investigation.
机译：在（生物）化学过程中，多组分扩散无处不在。 Maxwell-Stefan（M-S）框架为描述传输扩散提供了坚实的理论基础，因为它正确地将化学势梯度作为驱动力。不幸的是，无法在实验中直接测量M-S扩散率{Eth} _（ij）。因此，需要在稀释系统中使用基于容易测量的量（如Fick或自扩散率）的预测模型。在这项研究中，平衡分子动力学（EMD）模拟用于研究含正己烷，环己烷和/或甲苯的液体混合物中M-S的扩散率。研究了用于估计三元系统中M-S扩散率{Eth} ijxk→1的预测模型。进行以下分析。首先，这些预测模型用于使用众所周知的Vignes近似来计算无限稀释极限中的自扩散系数。将预测的自扩散系数与直接从EMD仿真计算的自扩散系数进行比较。其次，我们使用从EMD仿真获得的扩散率研究了Vignes近似的质量。第三，我们直接将{Eth} ijxk→1的预测模型与EMD仿真进行了比较。我们的结果表明：（1）预测的自扩散对{Eth} ijxk→1的预测模型的选择不是很敏感; （2）Vignes方程仅能得出M-S扩散率的合理预测，平均误差为13％; （3）在{Eth} ijxk→1的预测模型中不能忽略溶质与溶剂之间的相互作用; （4）目前的预测模型用于根据二进制数据计算{Eth} ijxk→1，导致所研究系统的误差为8％。

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