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Prediction of Ternary Liquidus Temperatures by StatisticalModeling of Binary and Ternary Ag–Al–Sn–Zn Systems

机译:通过统计预测三元液相线温度二元和三元Ag-Al-Sn-Zn系统的建模

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摘要

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 frameworkwe considered.
机译:通过统计模型分析了Ag-Al-Sn-Zn系统中六个二元相和四个三元相之间的液相线温度之间的关系。根据从宏观和微观角度得出的不同假设,提出了四种统计模型来预测Ag-Al-Sn-Zn液相线温度的变化。用来评估三元液相线温度预测准确性的插值测试结果表明,在四个模型中,基于二元液相线温度,交互式二元液相线温度和原子比的乘积的多元回归模型被认为是最有效的。数值显示,通过使用在其相邻系统中识别出的模型,可以进一步提高Ag-Al-Sn-Zn本地三元系统中液相线温度的预测精度。最后,在统计框架的基础上讨论了提取总趋势和元素异常组合以预测液相线温度的可能性。我们考虑过。

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