The characteristics of atomic-scale mixing are determined by diffusive processes driven by gradients. One such process is interdiffusion, a process driven by density gradients. We consider the various options for formulating interdiffusion in terms of Green–Kubo autocorrelation functions and the thermodynamic factor. Through models for the direct correlation function, we generalize expressions for the thermodynamic factor to include different electron and ion temperatures, electron degeneracy, finite-temperature exchange, and strong coupling. Additionally, a Gaussian autocorrelation function (GAF) is employed for a binary ionic mixture, yielding a simple analytic transport model for interdiffusion. The GAF model is shown to be accurate for moderately and strongly coupled plasmas.

中文翻译：

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密集等离子体混合物中相互扩散的分析模型

原子级混合的特性是由梯度驱动的扩散过程决定的。一个这样的过程是相互扩散，这是一种由密度梯度驱动的过程。我们考虑根据 Green-Kubo 自相关函数和热力学因子来制定相互扩散的各种选项。通过直接相关函数的模型，我们将热力学因子的表达式概括为包括不同的电子和离子温度、电子简并、有限温度交换和强耦合。此外，高斯自相关函数 (GAF) 用于二元离子混合物，产生一个简单的互扩散分析传输模型。GAF 模型被证明对于中等和强耦合等离子体是准确的。