Prediction model of elastic constants of BCC high-entropy alloys based on first-principles calculations and machine learning techniques
Prediction model of elastic constants of BCC high-entropy alloys based on first-principles calculations and machine learning techniques
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基于第一性原理计算和机器学习技术的BCC高熵合金弹性常数预测模型
DOI：
10.1080/27660400.2022.2125853
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
K. Sato
中科院分区：
文献类型：
--
作者：
G. Hayashi;K. Suzuki;T. Terai;H. Fujii;M. Ogura;K. Sato
结合第一性原理电子结构计算和机器学习技术，从3d、4d和5d过渡金属中选取5种不同元素，以相同的浓度，建立了体心立方高熵合金（HEA）弹性常数的预测模型.在相干势近似（CPA）下，采用全势Korringa-Kohn-Rostoker（FPKKR）方法计算了随机选取的2555个HEAs的三个独立弹性常数.从所获得的弹性常数的数据库中，使用由线性独立描述符生成（LIDG）方法生成的描述符，通过线性回归构建预测模型。通过优化选择的描述符的基础上的遗传算法（GA），预测误差为10.2 GPa，4.5 GPa，2.4 GPa和7.7 GPa的体积模量，剪切模量，杨氏模量，分别实现。通过使用生成的模型，我们提出了一些HEAs低。众所周知，的大小是密切相关的形状的计算态密度（DOS）。这一说法在BCC HEA中得到了再次确认，即，在费米能级具有较大DOS的HEAs显示较小的杨氏模量，反之亦然。
By combining first-principles electronic structure calculations and machine learning techniques, prediction models of elastic constants are constructed for BCC high-entropy alloys (HEA) containing 5 different elements chosen from 3d, 4d and 5d transition metals with equal concentration. Three independent elastic constants of randomly selected 2555 HEAs are calculated by using the full potential Korringa–Kohn–Rostoker (FPKKR) method with taking configurational disorder into account within the coherent potential approximation (CPA). From the obtained database of the elastic constants, prediction models are constructed by the linear regression using the descriptors generated by the linearly independent descriptor generation (LIDG) method. By optimizing the selection of descriptors based on the genetic algorithm (GA), prediction errors of 10.2 GPa, 4.5 GPa, 2.4 GPa and 7.7 GPa are achieved for bulk modulus, shear moduli,and Young’s modulus, respectively. By using the generated model we propose some HEAs with low. It is well known that the magnitude ofis closely related to the shape of the calculated density of states (DOS). This statement is reconfirmed within the BCC HEAs,i.e., HEAs with larger DOS at the Fermi level shows smaller Young’s modulus and vice versa.
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