Effect of Imperfections Due to Material Heterogeneity on the Offset of Polysilicon MEMS Structures

Monte Carlo analyses on statistical volume elements allow quantifying the effect of polycrystalline morphology, in terms of grain topology and orientation, on the scattering of the elastic properties of polysilicon springs. The results are synthesized through statistical (lognormal) distributions depending on grain size and morphology: such statistical distributions are an accurate and manageable alternative to numerically-burdensome analyses. Together with this quantification of material property uncertainties, the effect of the scattering of the over-etch on the stiffness of the supporting springs can also be accounted for, by subdividing them into domains wherein statistical fluctuations are assumed not to exist. The effectiveness of the proposed stochastic approach is checked with the problem of the quantification of the offset from the designed configuration, due to the residual stresses, for a statically-indeterminate MEMS structure made of heterogeneous (polycrystalline) material.

Tribological characteristics of few-layer graphene over Ni grain and interface boundaries

The tribological properties of metal-supported few-layered graphene depend strongly on the grain topology of the metal substrate.

Study on Grain Topology with Potts Model Monte Carlo Simulation

Three-dimensional normal grain growth has been simulated in scale 300×300×300 using the generally accepted Potts model Monte Carlo method. The studies of the topology of grains indicate that the mean number of faces in the grain network <f>=13.91 is similar to other simulation results, but higher than most of the experimental data which containing a wide range of values, i.e., <f>=11.16~13.93. The three-dimensional AboavWeaire law and Liu-Yu law are observed to hold, but the fit coefficient is different from the theory models.