机器学习在材料研发中的应用

谢建新, 宿彦京, 薛德祯, 姜雪, 付华栋, 黄海友

Machine Learning for Materials Research and Development

XIE Jianxin, SU Yanjing, XUE Dezhen, JIANG Xue, FU Huadong, HUANG Haiyou

图5 高熵合金固溶强化模型精度(MRE)的对比[80] (a) the new model (b) S-model (c) T-model (d) V-model (e) comparison of predicted and experimental solid solution strength (ΔσSSS) (f) the revised model

Fig.5 The Solid solution strengthening prediction via different physical models (MRE—the mean relative error, R—correlation coefficient, DFT—density functional theory)[80]