Sn-based solder design using machine learning approach

Yu Chen Liu, Chih Han Yang, Shih Kang Lin

研究成果: Conference contribution

摘要

Sn-based solder is a typical material for electronic interconnections. Low-Ag-content Sn-based solder exhibits a low hardness and is promising for avoiding the drop-induced failure. However, Sn-based solder has a wide range of composition and thus modulating its hardness via experimental trial-and-error method is not economically feasible. In this study, we employed the machine learning approach to design low-hardness Sn-based solders. We successfully designed an alloy that showed a hardness value lower than pure Sn, which has the potential of having a high-resistance to drop-induced failure.

原文English
主出版物標題2022 International Conference on Electronics Packaging, ICEP 2022
發行者Institute of Electrical and Electronics Engineers Inc.
頁面43-44
頁數2
ISBN(電子)9784991191138
DOIs
出版狀態Published - 2022
事件21st International Conference on Electronics Packaging, ICEP 2022 - Sapporo, Japan
持續時間: 2022 5月 112022 5月 14

出版系列

名字2022 International Conference on Electronics Packaging, ICEP 2022

Conference

Conference21st International Conference on Electronics Packaging, ICEP 2022
國家/地區Japan
城市Sapporo
期間22-05-1122-05-14

All Science Journal Classification (ASJC) codes

  • 製程化學與技術
  • 電氣與電子工程
  • 工業與製造工程
  • 電子、光磁材料

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