Evolved Finite Difference Model to Investigate Humidity-Related Failure Modes for Microelectronic and Power Electronic Devices

The precise determination of material-dependent parameters with regard to moisture diffusion processes has a fundamental impact on the reliability of electronic devices and systems in microelectronics and power electronics. Moisture related failure modes (e.g. corrosion effects or the formation of dendrites) are often responsible for component failures. Deter-mining parameters related to moisture diffusion processes for each individual material class is a fundamental requirement for more complex multi-physical simulation approaches in order to investigate moisture induced failure modes. Often, numerical simulation approaches to determine the material characteristics are limited to the general partial differential equation of second order, postulated by Fick's second law of diffusion. In this paper, we present a numerical approach based on the finite difference method (FDM) implemented into Python3 which can be used for advanced material parameter identification taking complex diffusion approaches into account. The simulation approach can be used for a variety of different packaging material classes like silicone-based insulations, foils, thermos-settings or epoxy-based materials taking additional microstructural effects into account (e.g. temperature and concentration dependency, cluster formation, local material defects like void and gap formation on filler particles). The presented method allows to model more complex material phenomena that occur during the moisture diffusion process. For example, desorption and absorption processes inside the material, related to cluster formation, are described by a concentration dependency for certain parameters. Furthermore, the model benefits from a large flexibility to model transient boundary conditions (like transient flux conditions) adjusted to real experimental test setups.