  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.
