从第一性原理模拟宽压温范围内的液体内能和heat capacity
Modelling of liquid internal energy and heat capacity over a wide pressure-temperature range from first principles
摘要：
最近有显着的理论进展，我们了解的液体和致密的超临界流体的基础上，他们的能力，以支持高频横向（剪切）波。在这里，我们已经建立了一个新的计算机模型，使用这些最新的理论研究结果（液体热力学的声子理论），在很宽的压力-温度范围内模拟液体内能。我们已经将其应用到一些真正的液体在亚临界状态和超临界状态，其中液体状态划分的弗伦克尔线。我们在很宽的压力-温度范围内拟合实验数据，使我们能够以前所未有的严格性测试新的理论模型。我们已经量化了内能和热容的预测受到不同输入参数约束的程度：液体弛豫时间（最初从粘度获得），德拜波数和无限频率剪切模量。该模型被成功地应用于输出的内能和热容的数据，为几种不同的流体（Ar，Ne，$N_2$，Kr）的密度和温度范围内。我们发现，预测的热容是非常敏感的液体弛豫时间的值。如果这些是直接从粘度数据计算的，那么在某些情况下，粘度数据中实验误差范围内的变化可能导致热容作为温度的函数呈现出完全不同的趋势。我们的代码在计算上是廉价的，它可供其他研究人员使用。
英文摘要：
Recently there have been significant theoretical advances in our understanding of liquids and dense supercritical fluids based on their ability to support high frequency transverse (shear) waves. Here, we have constructed a new computer model using these recent theoretical findings (the phonon theory of liquid thermodynamics), to model liquid internal energy across a wide pressure-temperature range. We have applied it to a number of real liquids in both the subcritical regime and the supercritical regime, in which the liquid state is demarcated by the Frenkel line. Our fitting to experimental data in a wide pressure-temperature range has allowed us to test the new theoretical model with hitherto unprecedented rigour. We have quantified the degree to which the prediction of internal energy and heat capacity is constrained by the different input parameters: The liquid relaxation time (initially obtained from the viscosity), the Debye wavenumber and the infinite-frequency shear modulus. The model is successfully applied to output the internal energy and heat capacity data for several different fluids (Ar, Ne, $N_2$, Kr) over a range of densities and temperatures. We find that the predicted heat capacities are extremely sensitive to the values used for the liquid relaxation time. If these are calculated directly from the viscosity data then, in some cases, changes within the margins of experimental error in the viscosity data can cause the heat capacity to exhibit a completely different trend as a function of temperature. Our code is computationally inexpensive, and it is available for other researchers to use.
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