Design Optimization of a Corrugated Piezoelectric MEMS Microphone applying Genetic Algorithms

In this work we present an automated design optimization framework based on genetic algorithms to explore and assess the full potential of high-performance piezoelectric MEMS microphones. The novel device concept is based on fully clamped, corrugated aluminum nitride (AlN) membranes with a high number of geometrical degrees of freedom. The key performance parameters are extracted with the help of finite element simulations, while the whole optimization flow is controlled with MATLAB. We show that this method enables a wide search within the parameter space and helps in finding optimal microphone designs with improved performance compared to device variants conceived purely by engineering intuition.