Microstructure Modeling, Prediction, and Verification of Cu-Ag Sintered Paste for Die-attach Based on the Quartet Structure Generation Set (QSGS) Algorithm

Cu-Ag composite sintered pastes are promising die-attach materials for wide bandgap power modules, yet their electrothermal performance is governed by 3D phase connectivity and interfacial morphology. In this work, a workflow for better predicting the thermal and electrical conductivity was presented, using 2D SEM processing, 3D reconstruction with a self-learning optimized QSGS algorithm, and electrothermal finite element simulations in COMSOL Multiphysics. A Hashin Shtrikman composition baseline, together with closed-form structure-corrected equations, was further introduced for better prediction accuracy, which enables rapid screening and microstructure-informed design of composite sintering materials for die-attach.