Integration of machine learning with phase field method to model the electromigration induced Cu6Sn5 IMC growth at anode side Cu/Sn interface
Anil Kunwara,*(
), Yuri Amorim Coutinhoa, Johan Hektorb,c, Haitao Mad, Nele Moelansa
), Yuri Amorim Coutinhoa, Johan Hektorb,c, Haitao Mad, Nele Moelansa
.
Fig. 5.. Graphs of the IMC thickness as a function of time for a current density: (a) j = 1.0 × 106 A/m2, and (b) j = 10.0 × 106 A/m2 for the 5 sets of effective charge numbers, ${{\bar{Z}}_{1}}$, ${{\bar{Z}}_{2}}$, ${{\bar{Z}}_{3}}$, ${{\bar{Z}}_{4}}$ and ${{\bar{Z}}_{5}}$ (see Eq. (26)). The graphs show the effect on Cu6Sn5 IMC thickness due to variations in the effective charge numbers of the phases and components. For the higher current density (graph (b)), the effect of variations in the effective charge numbers on the growth is more pronounced.
