Size effect in molecular dynamics simulation of nucleation process during solidification of pure metals: investigating modified embedded atom method interatomic potentials
Size effect in molecular dynamics simulation of nucleation process during solidification of pure metals: investigating modified embedded atom method interatomic potentials
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DOI：
10.1088/1361-651x/ab4b36
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发表时间：
2019-10
影响因子：
1.8
通讯作者：
A. Mahata;M. Asle Zaeem
中科院分区：
文献类型：
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作者：
A. Mahata;M. Asle Zaeem
由于近年来计算能力的显著提高，用于研究凝固形核过程的原子学方法的模拟规模逐渐扩大，甚至达到数十亿个原子模拟(亚微米尺度)。但问题是，需要多大的模型才能独立于尺寸和准确地模拟凝固过程中的形核过程？在这项工作中，模型尺寸从∼2000到∼800万个原子的分子动力学模拟被用来研究凝固过程中的形核。为了得到与晶体结构无关的一般性结论，采用最先进的次近邻修正嵌入原子方法对Al(面心立方)、Fe(体心立方)和Mg(六方密排)的原子间相互作用势进行了分子动力学模拟。分析了形核时间、形核密度、形核率、自扩散系数以及凝固过程中自由能的变化等几个定量特征。结果表明，通过将模型尺寸增加到约200万个原子，模拟和可测量的量完全与模拟单元的大小无关。预测与尺寸无关的计算数据所需的单元大小，可以大大降低原子模拟的计算成本，同时提高计算数据的准确性和可靠性。
Due to the significant increase in computing power in recent years, the simulation size of atomistic methods for studying the nucleation process during solidification has been gradually increased, even to billion atom simulations (sub-micron length scale). But the question is how big of a model is required for size-independent and accurate simulations of the nucleation process during solidification? In this work, molecular dynamics simulations with model sizes ranging from ∼2000 to ∼8 million atoms were used to study nucleation during solidification. To draw general conclusions independent of crystal structures, the most advanced second nearest-neighbor modified embedded atom method interatomic potentials for Al (face-centered cubic), Fe (body-centered cubic), and Mg (hexagonal-close packed) were utilized for molecular dynamics simulations. We have analyzed several quantitative characteristics such as nucleation time, density of nuclei, nucleation rate, self-diffusion coefficient, and change in free energy during solidification. The results showed that by increasing the model size to about two million atoms, the simulations and measurable quantities become entirely independent of simulation cell size. The prediction of cell size required for size-independent computed data can considerably reduce the computational costs of atomistic simulations and at the same time increase the accuracy and reliability of the computational data.