fig15

Integrating computational materials science and materials informatics for the modeling of phase stability

Figure 15. Machine learning results of phase stability of doped SmCo7 alloys. (A) Average area under curve (AUC) value as a function of the number of composition features, where the highest AUC corresponding to each number of features is marked with red. (B) Data distribution and classification of phase constitutions of SmCo7-xMx alloys in the dataset based on the two selected features of doping elements. (C) Prediction of 1:7 single phase probability with various doping elements for SmCo7-xMx ribbons. (D) Prediction of 1:7 single phase probability with various doping elements for SmCo7-xMx sintered bulks. In (C) and (D), different grain sizes and doping contents are considered for various doping elements.

Journal of Materials Informatics
ISSN 2770-372X (Online)
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