Miura Akira, Hokimoto Tsukasa, Nagao Masanori, Yanase Takashi, Shimada Toshihiro, Tadanaga Kiyoharu
Faculty of Engineering, Hokkaido University, Kita 13 Nishi 8, Kita-ku, Sapporo 060-8628, Japan.
Hokkaido Information University, 59-2 Nishinopporo, Ebetsu 069-0832, Japan.
ACS Omega. 2017 Aug 31;2(8):5271-5282. doi: 10.1021/acsomega.7b00784.
The relationship of liquidus temperatures among six binary and four ternary phases in a Ag-Al-Sn-Zn system was analyzed by means of statistical modeling. Four statistical models to predict changes in the liquidus temperatures in Ag-Al-Sn-Zn were proposed on the basis of different hypotheses derived from macroscopic and microscopic standpoints. The results of interpolation tests to evaluate the prediction accuracies of the ternary liquidus temperatures suggested that the multivariate regression model based on binary liquidus temperatures, interactive binary liquidus temperatures, and products of atomic ratios was found to be the most effective among the four models. It was numerically shown that the prediction accuracies of the liquidus temperatures in local ternary systems of Ag-Al-Sn-Zn can be improved further by using the models identified in their neighboring systems. Finally, the possibility to extract the general trend and the abnormal combination of elements for the prediction of liquidus temperatures was discussed on the basis of the statistical framework we considered.
通过统计建模分析了Ag-Al-Sn-Zn体系中六个二元相和四个三元相之间的液相线温度关系。基于从宏观和微观角度得出的不同假设，提出了四个预测Ag-Al-Sn-Zn体系中液相线温度变化的统计模型。评估三元液相线温度预测精度的插值测试结果表明，基于二元液相线温度、交互式二元液相线温度和原子比乘积的多元回归模型在这四个模型中最为有效。数值结果表明，通过使用在其相邻体系中确定的模型，可以进一步提高Ag-Al-Sn-Zn局部三元体系中液相线温度的预测精度。最后，基于我们所考虑的统计框架，讨论了提取液相线温度预测的元素总体趋势和异常组合的可能性。
