Modeling high signal-to-noise ratio in a novel silicon MEMS microphone with comb readout

Johannes Manz; Alfons Dehe; Gabriele Schrag

doi:10.1117/12.2266014

30 May 2017 Modeling high signal-to-noise ratio in a novel silicon MEMS microphone with comb readout

Johannes Manz, Alfons Dehe, Gabriele Schrag

Proceedings Volume 10246, Smart Sensors, Actuators, and MEMS VIII; 1024608 (2017) https://doi.org/10.1117/12.2266014
Event: SPIE Microtechnologies, 2017, Barcelona, Spain

Abstract

Strong competition within the consumer market urges the companies to constantly improve the quality of their devices. For silicon microphones excellent sound quality is the key feature in this respect which means that improving the signal-to-noise ratio (SNR), being strongly correlated with the sound quality is a major task to fulfill the growing demands of the market. MEMS microphones with conventional capacitive readout suffer from noise caused by viscous damping losses arising from perforations in the backplate [1]. Therefore, we conceived a novel microphone design based on capacitive read-out via comb structures, which is supposed to show a reduction in fluidic damping compared to conventional MEMS microphones. In order to evaluate the potential of the proposed design, we developed a fully energy-coupled, modular system-level model taking into account the mechanical motion, the slide film damping between the comb fingers, the acoustic impact of the package and the capacitive read-out. All submodels are physically based scaling with all relevant design parameters. We carried out noise analyses and due to the modular and physics-based character of the model, were able to discriminate the noise contributions of different parts of the microphone. This enables us to identify design variants of this concept which exhibit a SNR of up to 73 dB (A). This is superior to conventional and at least comparable to high-performance variants of the current state-of-the art MEMS microphones [2].

Conference Presentation

Citation Download Citation

Johannes Manz, Alfons Dehe, and Gabriele Schrag "Modeling high signal-to-noise ratio in a novel silicon MEMS microphone with comb readout", Proc. SPIE 10246, Smart Sensors, Actuators, and MEMS VIII, 1024608 (30 May 2017); https://doi.org/10.1117/12.2266014

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