Design of two layer clamped-clamped microsensor based on classical and non-classical theories

Abstract

In this paper, the two-layer micro sensor is modeled as a two-layer clamped-clamped microbeam and it is optimized using the genetic algorithm. Using the results of this research, clamped- clamped microbeams can be designed in such a way that the performance of microsensors whose structure includes these microbeams will be improved. The quality factor, the sensitivity, and the maximum stress are selected as objective functions. The thickness of each layer, the width of the microbeam, and the length of the microbeam are selected as design variables. The optimization is done based on classical and non-classical theory by the genetic algorithm. The results based on both theories are approximately equal. The length of the microbeam is the most important variable and very changes (approximately 190%). The thickness of the silicon layer has the least effect on the results and changes just lower than 2μm (approximately 20%). The results show that when the maximum stress decreases and the sensitivity increases, the quality factor decreases which is undesirable. Maximum sensitivity obtains when the microbeam is very small.