Novel Sensing Approaches towards Ultimate MEMS Sensors
Kumar, Varun Subramaniam
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Within the past few decades, several micro and nano-electromechanical (MEMS and NEMS) accelerometers, magnetometers and vibration sensors utilizing various actuation and sensing mechanisms have been developed and demonstrated. These sensors are integral to various geographical, industrial, military, environmental and biomedical applications. Although these sensors based on MEMS technology have been successfully commercialized and are widely used, this dissertation focuses on novel approaches to enhance the performance of such sensors drastically. In most cases for the MEMS accelerometer, the large power consumption of MEMS sensors is attributed to the analog front end needed for reading, processing, and analog to digital conversion of the sensor output, which is typically responsible for most to all the power consumption of the whole sensor. The proposed effort in this dissertation aims at development of a new class of digitally readable MEMS accelerometers allowing significant power reduction by eliminating the need for the analog front-end. Conventional magnetometers that offer high sensitivities for fields smaller than a few nT’s are not MEMS compatible and cannot undergo miniaturization. MEMS Magnetometers have an edge over conventional counterparts due to their unique features such as small size, low cost, lower power consumption and simplicity of operation. Such properties offer unrivalled advantages, especially when it comes to medical applications, such as magneto-encephalography, where compact arrays of ultra-sensitive sensors are desirable. This dissertation demonstrates ultra-high sensitivities (noise floor in pT/√Hz) for a Lorentz force resonant MEMS magnetometer enabled by internal-thermal piezoresistive vibration amplification. A detailed model of the magneto-thermo-electro-mechanical internal amplification is also developed and studied. Frequency modulation of a Lorentz force MEMS magnetometer for enhanced sensitivity using a leverage mechanism has also been explored. Currently, no low cost, low power, and compact vibration sensor solution exists that can provide frequency distribution data for the measured vibrations This dissertation implements and characterizes building blocks of a low-power miniaturized vibration spectrum analyzer with a resolution of 1mg over a wide frequency range (0-10kHz) using an existing Texas Instruments CMOS process, without adding any complex post processing fabrication steps.
Winner of the 2018 Best Dissertation prize in the Erik Jonsson School of Engineering and Computer Science