Design High Shear Strength Sn-Bi-X Low-Temperature Solders on Cu Substrate using a Machine Learning Approach

Low-temperature solder has been proposed as a solution to reduce reflow temperature and mitigate warpage issues in advanced electronic packaging. Among various candidates, the Sn-Bi solder system stands out as a promising option. However, after aging, the coarsening of the (Bi) phase increases brittleness and weakens joint strength. While element doping is a common strategy to enhance its properties, traditional trial-and-error methods are costly and inefficient. To address this, this study utilizes a machine learning approach to explore the shear strength of low-temperature solder, offering a more efficient and systematic method for material design.