论文标题
计算来自密度波动的流体的热电导率
Computing the heat conductivity of fluids from density fluctuations
论文作者
论文摘要
平衡分子动力学模拟，结合绿色 - 库博（GK）方法，已广泛用于计算液体的导热率。但是，GK方法依赖于微观热通量的模棱两可的定义，这取决于人们选择如何在原子上分配能量。这种歧义使使用GK方法对具有非对互动的系统进行了问题。在这项工作中，我们证明了热驱动密度波动的流体动力描述可用于明确地获得散装流体的热导率，从而绕开了定义热通量的需求。我们验证，对于仅成对相互作用的模型流体，我们的方法得出与GK方法一致的导热性估计值。我们采用我们的方法来计算超临界条件下非双向添加剂模型的导热率，然后在33 GPA和2000 K处用机器学习的原子间电位描述的液体氢系统。
Equilibrium molecular dynamics simulations, in combination with the Green-Kubo (GK) method, have been extensively used to compute the thermal conductivity of liquids. However, the GK method relies on an ambiguous definition of the microscopic heat flux, which depends on how one chooses to distribute energies over atoms. This ambiguity makes it problematic to employ the GK method for systems with non-pairwise interactions. In this work, we show that the hydrodynamic description of thermally driven density fluctuations can be used to obtain the thermal conductivity of a bulk fluid unambiguously, thereby bypassing the need to define the heat flux. We verify that, for a model fluid with only pairwise interactions, our method yields estimates of thermal conductivity consistent with the GK approach. We apply our approach to compute the thermal conductivity of a non-pairwise additive water model at supercritical conditions, and then of a liquid hydrogen system described by a machine-learning interatomic potential, at 33 GPa and 2000 K.
