Design of Integrated Microwave Frequency Synthesizer-Based Dielectric Sensor Systems
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Dielectric sensors have several biomedical and industrial applications where they are used to characterize the permittivity of materials versus frequency. Characterization at RF/microwave frequencies is particularly useful since many chemicals/bio-materials show significant changes in this band. The potential system cost and size reduction possible motivates the development of fully integrated dielectric sensor systems on CMOS with high sensitivity for point-of-care medical diagnosis platforms and for lab-on-chip industrial sensors. Voltage-controlled oscillator (VCO)-based dielectric sensors embed the sensing capacitor within the excitation VCO to allow for self-sustained measurement of the material under test (MUT)-induced frequency shift with simple and precise readout circuits. Despite their advantages, VCO-based sensors have several design challenges. First, low frequency noise and environmental variations limit their sensitivity. Also, these systems usually place the VCO in a frequency synthesizer to control the sample excitation frequency which reduces the resolution of the read-out circuitry. Finally, conventional VCO-based systems utilizing LC oscillators have limited tuning range, and can only characterize the real part of the permittivity of the MUT. This dissertation proposes several ideas to: 1) improve the sensitivity of the system by filtering the low frequency noise and enhance the resolution of the read-out circuitry, 2) improve the tuning range, and 3) enable complex dielectric characterization in VCO/synthesizer-based dielectric spectroscopy systems. The first prototype proposes a highly-sensitive CMOS-based sensing system for permittivity detection and mixture characterization of organic chemicals at microwave frequencies. The system determines permittivity by measuring the frequency difference between two VCOs; a sensor oscillator with an operating frequency that shifts with the change in tank capacitance due to exposure to the MUT and a reference oscillator insensitive to the MUT. This relative measurement approach improves sensor accuracy by tracking frequency drifts due to environmental variations. Embedding the sensor and reference VCOs in a fractional-N phase-locked loop (PLL) frequency synthesizer enables material characterization at a precise frequency and provides an efficient material-induced frequency shift read-out mechanism with a low-complexity bang-bang control loop that adjusts a fractional frequency divider. The majority of the PLL-based sensor system, except for an external fractional frequency divider, is implemented with a 90 nm CMOS prototype that consumes 22 mW when characterizing material near 10 GHz. Material-induced frequency shifts are detected at an accuracy level of 15 ppmrms and binary mixture characterization of organic chemicals yield maximum errors in permittivity of <1.5%. The second prototype proposes a fully-integrated sensing system for wideband complex dielectric detection of MUT. The system utilizes a ring oscillator-based PLL for wide tuning range and precise control of the sensor's excitation frequency. Characterization of both real and imaginary MUT permittivity is achieved by measuring the frequency difference between two VCOs: a sensing oscillator, with a frequency that varies with MUT-induced changes in capacitance and conductance of a delay-cells' sensing capacitor loads, and a MUT-insensitive reference oscillator that is controlled by an amplitude-locked loop (ALL). The fully integrated system is fabricated in 0.18 μm CMOS, and occupies 6.25 mm2 area. When tested with common organic chemicals (ε`r < 30), the system operates between 0.7-6 GHz and achieves 3.7% maximum permittivity error. Characterization is also performed with higher ε`r water-methanol mixtures and phosphate buffered saline (PBS) solutions, with 5.4% maximum permittivity error achieved over a 0.7-4.77 GHz range.
El-Hadidy, Osama (2015). Design of Integrated Microwave Frequency Synthesizer-Based Dielectric Sensor Systems. Doctoral dissertation, Texas A & M University. Available electronically from