Polysilicon MEMS Sensors: Sensitivity to Sub-Micron Imperfections

In this work, through Monte Carlo analyses on statistical volume elements, we show the effect of the grain morphology and orientation on the effective elastic properties of polysilicon beams constituting critical MEMS components. The outcomes of the numerical investigation are summarized through statistical (lognormal) distributions for the elastic properties as functions of grain size and morphology, quantifying therefore not only the relevant expected mean values, but also the scattering around them. Such statistical distributions represent a simple, yet rigorous alternative to cumbersome numerical analyses. Their utility is testified through the analysis of a statically indeterminate MEMS structure, quantifying the possible initial offset away from the designed configuration due to the residual stresses arising from the micro-fabrication process.