Integration of machine learning with phase field method to model the electromigration induced Cu6Sn5 IMC growth at anode side Cu/Sn interface
Currently, in the era of big data and 5G communication technology, electromigration has become a serious reliability issue for the miniaturized solder joints used in microelectronic devices. Since the effective charge number (Z*) is considered as the driving force for electromigration, the lack of accurate experimental values for Z* poses severe challenges for the simulation-aided design of electr
