The design of quaternary eutectic solder by machine learning

Zhenhua Guo; Xintong Ren; Jiahua Jiang; Haoyang Liu; Yongjun Huo; Xiuchen Zhao; K. N. Tu; Yingxia Liu

The design of quaternary eutectic solder by machine learning

Applied Physics 2021-10-12 v1 Materials Science

Authors: Zhenhua Guo , Xintong Ren , Jiahua Jiang , Haoyang Liu , Yongjun Huo , Xiuchen Zhao , K. N. Tu , Yingxia Liu

Abstract

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.

Cite

@article{arxiv.2110.04529,
  title  = {The design of quaternary eutectic solder by machine learning},
  author = {Zhenhua Guo and Xintong Ren and Jiahua Jiang and Haoyang Liu and Yongjun Huo and Xiuchen Zhao and K. N. Tu and Yingxia Liu},
  journal= {arXiv preprint arXiv:2110.04529},
  year   = {2021}
}

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