TY - GEN
T1 - A machine learning approach to explore tensile properties of low-temperature solders
AU - Liu, Yu Chen
AU - Kholik, Ahmad
AU - Lin, Shih Kang
N1 - Funding Information:
Y.-c. Liu gratefully acknowledge the financial support from National Science and Technology Council (NSTC) (110-2222-E-006-008, 111-2222-E-006-011-MY3, and 111-2622-8-006-029), the Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) and NSTC (111-2634-F-006-008) in Taiwan.
Publisher Copyright:
© 2023 Japan Institute of Electronics Packaging.
PY - 2023
Y1 - 2023
N2 - Low-temperature solder material has been proposed as a solution in reducing the reflow temperature in order to solve the warpage issue in the advanced electronic packaging. Currently, Sn-Bi solder system is considered as a promising material system for low-temperature solder. Nevertheless, (Bi) phase coarsening after thermal aging causes the brittleness of the solder and thus decreases the reliability in real application. Element doping to Sn-Bi solder is typically used in tailoring its properties. However, tailoring properties in the multi-component system with experimental trial-and-error method is not economically feasible. This study employed machine learning approach to explore tensile properties of low-temperature solders.
AB - Low-temperature solder material has been proposed as a solution in reducing the reflow temperature in order to solve the warpage issue in the advanced electronic packaging. Currently, Sn-Bi solder system is considered as a promising material system for low-temperature solder. Nevertheless, (Bi) phase coarsening after thermal aging causes the brittleness of the solder and thus decreases the reliability in real application. Element doping to Sn-Bi solder is typically used in tailoring its properties. However, tailoring properties in the multi-component system with experimental trial-and-error method is not economically feasible. This study employed machine learning approach to explore tensile properties of low-temperature solders.
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U2 - 10.23919/ICEP58572.2023.10129657
DO - 10.23919/ICEP58572.2023.10129657
M3 - Conference contribution
AN - SCOPUS:85161841771
T3 - 2023 International Conference on Electronics Packaging, ICEP 2023
SP - 71
EP - 72
BT - 2023 International Conference on Electronics Packaging, ICEP 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 22nd International Conference on Electronics Packaging, ICEP 2023
Y2 - 19 April 2023 through 22 April 2023
ER -