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Jia Zhao, Taixi Feng, and Guimin Lu, Understanding the local structure and thermophysical behavior of Mg–La liquid alloys via machine learning potential, Int. J. Miner. Metall. Mater., 32(2025), No. 2, pp.439-449. https://dx.doi.org/10.1007/s12613-024-2928-2
Jia Zhao, Taixi Feng, and Guimin Lu, Understanding the local structure and thermophysical behavior of Mg–La liquid alloys via machine learning potential, Int. J. Miner. Metall. Mater., 32(2025), No. 2, pp.439-449. https://dx.doi.org/10.1007/s12613-024-2928-2
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利用机器学习势函数揭示液态Mg–La合金的局部结构和热物理行为

摘要: 利用机器学习驱动的深度势能分子动力学(DPMD)模拟深入研究了液态Mg–La合金的局部结构和热物理行为,以促进Mg–La合金的发展。通过均方根误差(RMSE),能量和力数据以及结构信息的对比结果考察了训练的深度势函数(DP)模型的可靠性。分析了液态Mg–La合金局部结构的组成和温度依赖性。Mg–La合金体系中镁含量对体系中原子对的第一配位层影响与温度对其作用规律一致。结构因子中的预峰信号表明液态Mg–La合金中存在中程有序性,且当Mg含量为80at%时最明显。体系的中程有序性会随温度升高而消失。利用DPMD模拟预测了液态Mg–La合金的密度、自扩散系数和剪切粘度,并讨论了这些性质随体系中Mg含量和温度变化的规律,建立了相应的性质数据库。最后,计算了1200 K时液态Mg–La合金的混合焓和元素活度。

 

Understanding the local structure and thermophysical behavior of Mg–La liquid alloys via machine learning potential

Abstract: The local structure and thermophysical behavior of Mg–La liquid alloys were in-depth understood using deep potential molecular dynamic (DPMD) simulation driven via machine learning to promote the development of Mg–La alloys. The robustness of the trained deep potential (DP) model was thoroughly evaluated through several aspects, including root-mean-square errors (RMSEs), energy and force data, and structural information comparison results; the results indicate the carefully trained DP model is reliable. The component and temperature dependence of the local structure in the Mg–La liquid alloy was analyzed. The effect of Mg content in the system on the first coordination shell of the atomic pairs is the same as that of temperature. The pre-peak demonstrated in the structure factor indicates the presence of a medium-range ordered structure in the Mg–La liquid alloy, which is particularly pronounced in the 80at% Mg system and disappears at elevated temperatures. The density, self-diffusion coefficient, and shear viscosity for the Mg–La liquid alloy were predicted via DPMD simulation, the evolution patterns with Mg content and temperature were subsequently discussed, and a database was established accordingly. Finally, the mixing enthalpy and elemental activity of the Mg–La liquid alloy at 1200 K were reliably evaluated, which provides new guidance for related studies.

 

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