Physical Parameter Extraction and Modeling of Metallized Deeply-Etched Vertical Mirrors

In this work, vertical micromirrors that are fabricated using deep etching of silicon followed by metal sputtering are studied. Physical parameter extraction methodology, image processing, machine learning and discrete element analysis are used to extend the easy-to-take scanning electron microscope images into 3-D topographical information, that are usually obtained using atomic force microscope and transmission electron microscope. The experimental results show that vertical micromirrors surface quality has a granular nature showing degraded performance and a different optical response with respect to the bulk metal. A physical model is developed and validated by comparing the measured reflectivity of the fabricated micromirrors with a multi-layer reflectivity optical model based on the effective medium theory fed by the extracted physical parameters. In agreement with the experimental results, the model predicts a reflectivity of about 60 % for a sputtered aluminum thickness of 50 nm, compared to 97.5% reflectivity predicted by the bulk metal model. [2021-0154]