Abstract
Miniaturized capacitive microphones often show sensitivity degradation in the low-frequency region due to electrical and acoustical time constants. For low-frequency sound detection, conventional systems use a microphone with a large diaphragm and a large back chamber to increase the time constant. In order to overcome this limitation, an electret gate on a field-effect transistor (ElGoFET) structure was proposed, which is the field-effect transistor (FET) mounted diaphragm faced on electret. The use of the sensing mechanism consisting of the integrated FET and electret enables the direct detection of diaphragm displacement, which leads its acoustic senor application (ElGoFET microphone) and has a strong ability to detect low-frequency sound. We studied a theoretical model and design for low-frequency operation of the ElGoFET microphone prototype. Experimental investigations pertaining to the design, fabrication, and acoustic measurement of the microphone were performed and the results were compared to our analytical predictions. The feasibility of the microphone as a low-frequency micro-electromechanical system (MEMS) microphone, without the need for a direct current bias voltage (which is of particular interest for applications requiring miniaturized components), was demonstrated by the flat-band frequency response in the low-frequency region.
Highlights
The advent of the Internet of Things has created high demand for small, high-performance micro-electromechanical system (MEMS) microphones
This paper describes a novel electromechanical transduction mechanism that depends on the displacement of the diaphragm, which differs from the existing velocity-based capacitive transduction
Transduction for a microphone application was developed, its validity was electret gate on a field-effect transistor (ElGoFET) transduction is fundamentally based on displacement electromechanical transduction, transduction for a microphone application was developed, and its validity was experimentally investigated
Summary
The advent of the Internet of Things has created high demand for small, high-performance micro-electromechanical system (MEMS) microphones. Demand for sensors that detect low-frequency sound with high quality has increased for applications including mobile information technologies, private and military security systems, and healthcare monitoring platforms [1,2,3,4]. Detecting low-frequency sound using commercial MEMS microphones is difficult due to the low cut-off frequency associated with the energy transduction mechanism in these microphones, namely capacitive-type energy transduction. Commercial MEMS microphones have a fundamental limitation in detecting frequencies below 100 Hz, with the reduction in capacitance and back chamber volume due to the miniaturization of the microphone. Capacitive-type transduction measures the sensor capacitance change caused by acoustic pressure arising from the bias voltage and a load resistor, and turns the acoustic signal into an output voltage signal. As a velocity measurement of the diaphragm, the frequency response in the low-frequency
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