A Computational Multiscale Modeling Method for Nanosilver-Sintered Joints with Stochastically Distributed Voids

A high power density is required in wide band gap power semiconductor packaging, which has led to the popularity of sintered nanosilver as an interconnecting material. However, affected by stochastically distributed voids in its microstructure, this material in practice exhibits instability leading to reduced reliability. In this paper, a computational multiscale modeling method is proposed to simulate the influence of micro-voids on macro-properties, providing an efficient tool to analyze the aforementioned problem. At the micro-scale, the three-parameter Weibull distribution of the equivalent Young’s modulus and the normal distribution of the equivalent Poisson’s ratio are captured by Monte Carlo-based finite element simulation on the reconstructed stochastic representative elements, where the density and distribution morphology of micro-voids are taken into consideration. At the macro-scale, the effect of the microscopic voids is transferred through a random sampling process to construct the multiscale model. The effectiveness and validity of the proposed method are verified through experimental case studies involving the modeling of nanosilver-sintered joints sintered at temperatures of 275°C and 300°C. In addition, the effects of the sintering temperature on the dispersion of the micro-voids, the distribution fluctuation of the constitutive parameters, and the mechanical properties are also discussed based on numerical and experimental results.