Accelerated discovery of lead-free solder alloys with enhanced creep resistance via complementary machine learning strategy

• DOI: 10.1016/j.jmrt.2024.07.229
• Publication Date: 2024-07-31T07:14:35Z
• Authors: Zhengheng Lian; Youyang Chen; Chao Zhou; Minjie Li; Ziqiang Dong; Wencong Lu
• Keywords: Lead (geology)

Minor alloying is an effective method to improve the performance of lead-free solder alloys. In this study, we propose a complementary Machine Learning (ML) strategy for minor design alloys with enhanced creep resistance. Two ML models, leveraging compositional and knowledge-aware features, respectively, were constructed predict stress exponent Sn–Ag–Cu (SAC)-based Five new designed experimentally evaluated by screening virtual sample space consisting critical elements, including Bi, In, Ni, affecting resistance SAC model. The was characterized using nanoindentation tests. Notably, SAC387-3 wt % Bi-0.4 wt% Ni determined be 12.82 at room temperature, indicating significant 33.9% decrease in strain rate compared SAC387 alloy. This study demonstrates potential approach