Ghisi Aldo, Mariani Stefano
Department of Civil and Environmental Engineering, Politecnico di Milano, Piazza Leonardo Da Vinci 32, 20133 Milano, Italy.
Sensors (Basel). 2019 Jul 24;19(15):3256. doi: 10.3390/s19153256.
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.
对统计体积单元进行蒙特卡罗分析，可以从晶粒拓扑结构和取向的角度量化多晶形态对多晶硅弹簧弹性性能散射的影响。结果通过取决于晶粒尺寸和形态的统计（对数正态）分布进行综合：这种统计分布是数值计算负担较重的分析的一种准确且易于管理的替代方法。除了对材料性能不确定性进行这种量化之外，通过将支撑弹簧细分为假定不存在统计波动的区域，还可以考虑过蚀刻散射对支撑弹簧刚度的影响。对于由异质（多晶）材料制成的超静定MEMS结构，由于残余应力导致的与设计配置的偏差量化问题，检验了所提出的随机方法的有效性。
