Author: Guo, Zhenhua; Ren, Xintong; Jiang, Jiahua; Liu, Haoyang; Huo, Yongjun; Zhao, Xiuchen; Tu, K. N.; Liu, Yingxia
Title: The design of quaternary eutectic solder by machine learning Cord-id: yle49u42 Document date: 2021_10_9
ID: yle49u42
Snippet: In this paper, we obtain a Sn-Bi-In-Pb quaternary near eutectic alloy composition from machine learning model. The eutectic points and the alloy composition were evaluated and continuously improved by experimental input. The actual composition is near the result given by machine learning. We conclude that the application of machine learning in solder design has shown the potential to overcome the challenge in searching for the next generation eutectic solders, which will have a broad impact on t
Document: In this paper, we obtain a Sn-Bi-In-Pb quaternary near eutectic alloy composition from machine learning model. The eutectic points and the alloy composition were evaluated and continuously improved by experimental input. The actual composition is near the result given by machine learning. We conclude that the application of machine learning in solder design has shown the potential to overcome the challenge in searching for the next generation eutectic solders, which will have a broad impact on the industry.
Search related documents:
Co phrase search for related documents, hyperlinks ordered by date