基于机器学习的四元共晶钎料设计
The design of quaternary eutectic solder by machine learning
摘要：
本文从机器学习模型出发，得到了Sn-Bi-In-Pb四元近共晶合金成分。共晶点和合金成分进行了评估，并通过实验输入不断改进。实际组成与机器学习给出的结果接近。我们的结论是，机器学习在焊料设计中的应用已经显示出克服寻找下一代共晶焊料的挑战的潜力，这将对行业产生广泛的影响。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
