UC Davis

Permittivity sensing has wide applications in a variety of industries such as petroleum, agriculture,food production, etc.. The complex permittivity serves as an effective indicator of the valuable information of the sample material such as their constitute, moisture or quality, which are critical in the process of product development, production, and treatment. The nondestructive nature of the permittivity sensing makes it highly cost-effective and enables it for real time material characterization. This calls for the adoption of CMOS technologies to achieve a high level of integration of signal processing capabilities for cost-effective and ubiquitous applications without sacrificing precision and accuracy. Therefore, numerous works featuring CMOS permittivity sensor have been developed. Among all aspects of CMOS permittivity sensing systems, high resolution sensing is of particular importance, which enables CMOS sensing in applications such as high precision biosensing, precision medicine, etc. High resolution sensing enables high throughput measurement, capturing fast process in real time, etc. To achieve high resolution, the prior art focuses on two key aspects: permittivity sensor’s sensitivity boost and system noise reduction. In the optical community, ultra-high sensitivity is achieved by utilizing resonator based sensors, whose resonant frequency is shifted by the permittivity of different MUT’s. Sharp curvature and steep slope of the transmission coefficient of the high Q resonator sensors result in high sensitivity. Whispering gallery mode (WGM) resonators show particularly high sensitivity due to its high Q and the strong field interaction with the MUT’s. However, the expensive and bulky tunable optical sources and the limited signal processing and readout capabilities severely constrain the applications of the high sensitivity optical sensors. To advance the state of the arts of the high resolution permittivity sensors, this dissertation dedicates to the theory, design and implementation of sub-THz WGM resonator based CMOS permittivity sensor. Thanks to its short wavelength, the WGM resonator sensor at sub-THz possesses a compact form-factor, achieving a high level of integration with the CMOS transceivers (TRX). Like its optical counterparts, the compactness of the sub-THz sensor also enables high sensitivity detection while requiring a smaller amount of MUT samples than sensors working at GHz frequency range. The CMOS TRX generates the sub-THz signal to excite the WGM sensor and readout the signal to obtain the permittivity information. The dissertation analyzes the EM mechanisms of the WGM resonator sensor, including the loss analysis and coupling condition analysis, lays theoretical foundations for the sensitivity optimization for high resolution sensing. A novel mechanism to detect complex permittivity using the WGM resonator sensor is proposed for the first time in the permittivity sensing and resonator sensor community. A low power permittivity sensing system at 160 GHz is prototyped to verify the permittivity sensing capability of the WGM resonator sensor integrated with the CMOS TRX IC, which demonstrates a permittivity sensing resolution of 0.098 for a integration time of 10 us with a power consumption of only 9 mW. A high resolution complex permittivity sensing system at 160 GHz is implemented that adopts a band-stop WGM disk resonator based sensor structure and multi-fold noise suppression techniques, which demonstrates a record of 0.05% complex sensing resolution within 14-us integration time and consumes 54 mW of DC power. In the process of designing the high resolution permittivity sensing system, mathematical derivations are developed to predict the noise suppression effect of the three noise reduction techniques: the phase noise suppression by the coherent phase noise cancellation, the flicker noise suppression by the chopping scheme and the thermal noise suppression by the integrator. Since these three noise reduction techniques are commonly used in sensing / imaging systems, the developed derivation in this dissertation can be readily applied to predict the noise suppression effect numerically and to guide the design of the noise reduction circuitry.