Fan Zheyong, Wang Yanzhou, Gu Xiaokun, Qian Ping, Su Yanjing, Ala-Nissila Tapio
School of Mathematics and Physics, Bohai University, Jinzhou, People's Republic of China. QTF Centre of Excellence, Department of Applied Physics, Aalto University, FI-00076 Aalto, Finland.
J Phys Condens Matter. 2020 Mar 27;32(13):135901. doi: 10.1088/1361-648X/ab5c5f.
Silicon is an important material and many empirical interatomic potentials have been developed for atomistic simulations of it. Among them, the Tersoff potential and its variants are the most popular ones. However, all the existing Tersoff-like potentials fail to reproduce the experimentally measured thermal conductivity of diamond silicon. Here we propose a modified Tersoff potential and develop an efficient open source code called GPUGA (graphics processing units genetic algorithm) based on the genetic algorithm and use it to fit the potential parameters against energy, virial and force data from quantum density functional theory calculations. This potential, which is implemented in the efficient open source GPUMD (graphics processing units molecular dynamics) code, gives significantly improved descriptions of the thermal conductivity and phonon dispersion of diamond silicon as compared to previous Tersoff potentials and at the same time well reproduces the elastic constants. Furthermore, we find that quantum effects on the thermal conductivity of diamond silicon at room temperature are non-negligible but small: using classical statistics underestimates the thermal conductivity by about 10% as compared to using quantum statistics.
硅是一种重要的材料,已经开发了许多经验性原子间势用于对其进行原子模拟。其中,Tersoff势及其变体是最受欢迎的。然而,所有现有的类Tersoff势都无法重现实验测量的金刚石硅的热导率。在此,我们提出一种修正的Tersoff势,并基于遗传算法开发了一个名为GPUGA(图形处理单元遗传算法)的高效开源代码,并用它根据量子密度泛函理论计算得到的能量、维里系数和力数据来拟合势参数。这种势在高效开源的GPUMD(图形处理单元分子动力学)代码中实现,与之前的Tersoff势相比,它能显著改进对金刚石硅热导率和声子色散的描述,同时能很好地重现弹性常数。此外,我们发现室温下量子效应在金刚石硅热导率上的影响不可忽略但较小:与使用量子统计相比,使用经典统计会使热导率低估约10%。