论文标题
从量子核到热电子状态的有限温度材料建模
Finite-temperature materials modeling from the quantum nuclei to the hot electrons regime
论文作者
论文摘要
原子模拟在原子大小和长度尺度上提供了对结构特性关系的见解，这些关系与可以从实验中获得的宏观可观察到的互补。但是，定量预测通常受到在原子间电位的计算准确性与现实热力学条件的建模之间取得平衡的阻碍。机器学习技术使有效地近似准确的电子结构计算结果，因此可以与广泛的热力学采样结合使用。我们将元素镍作为一种典型材料，其合金从低温温度到接近其熔点的应用，并使用它来证明电子特性的机器学习模型和统计抽样方法的组合如何使能够以可承受的成本计算准确的有限透明特性。我们证明了在100至2500 K范围内的大量，界面和缺陷特性的计算，还需要在需要时进行建模核量子波动和电子熵的影响。我们在这里展示的框架很容易被推广到更复杂的合金和不同类别的材料。
Atomistic simulations provide insights into structure-property relations on an atomic size and length scale, that are complementary to the macroscopic observables that can be obtained from experiments. Quantitative predictions, however, are usually hindered by the need to strike a balance between the accuracy of the calculation of the interatomic potential and the modelling of realistic thermodynamic conditions. Machine-learning techniques make it possible to efficiently approximate the outcome of accurate electronic-structure calculations, that can therefore be combined with extensive thermodynamic sampling. We take elemental nickel as a prototypical material, whose alloys have applications from cryogenic temperatures up to close to their melting point, and use it to demonstrate how a combination of machine-learning models of electronic properties and statistical sampling methods makes it possible to compute accurate finite-temperature properties at an affordable cost. We demonstrate the calculation of a broad array of bulk, interfacial and defect properties over a temperature range from 100 to 2500 K, modeling also, when needed, the impact of nuclear quantum fluctuations and electronic entropy. The framework we demonstrate here can be easily generalized to more complex alloys and different classes of materials.
