A superconducting Transition Edge Sensor (TES) can be used to make the most sensitive thermometer which operates in a very narrow temperature range. The thin film bi-layer fabrication details are discussed as well as application in condensed matter physics. These include: measurement of quasi-adiabatic latent heat of superconducting transition, cobalt thermometry and photon detection.

Free Spectral Range Matched Interrogation (FSRMI) technique for wavelength demodulation of fiber Bragg grating sensors. We designed and tested a new wavelength demodulation system based on free-spectral-range-matched interrogation which employs a tunable fiber Fabry-Perot interferometer (FPI) and a multi-channel bandpass filter. This technique was deployed to test fiber Bragg gratings (FBG), long period gratings (LPG) and tilted fiber Bragg gratings (TFBG). In the experimental setup, a broadband source launches light into a fiber Bragg grating under test and the reflection/transmission spectrum is fed into a tunable FPI. By tuning an external bias applied to the FPI, the transmission spectrum of FPI scans over a wavelength range. The input optical signal is therefore selectively passed through the FPI and then fed into a four-channel bandpass filter followed by four photodetectors. The optical signal is converted to electrical signal by the photodiodes and is acquired by a data acquisition system. Since a bandpass filter with four channels are used in this interrogation system it can scan four distinguished wavelength ranges simultaneously and thus the scan rate is four time faster. We used this setup for doing some temperature and strain sensitivity measurements on some fiber gratings. Strain sensitivity measurements were done on FBG, TFBG and LPG and temperature sensitivity measurements were performed on TFBG. The strain and temperature sensitivity coefficients of these fiber Bragg grating sensors were obtained from experimental data. Our results show the potential of the integration of the FSRMI system with fiber Bragg gratings for temperature and strain multiple-sensor arrays with high sampling speed and high accuracy.

Rapid progress over the last decade on large area thin film transistor (TFT) arrays led to the emergence of high-performance, low-power, low-cost active matrix flat panel imagers. Despite the shortcomings associated with the instability and low mobility of TFTs, the amorphous silicon TFT technology still remains the primary solution for the backplane of flat panel imagers. The use of a-Si:H TFTs as the building block of the large area integrated circuit becomes challenging particularly when the role of the TFT is extended from traditional switching applications to on-pixel signal amplifier for large area digital imaging. This is the idea behind active pixel sensor (APS) architectures in which under each pixel an amplifier circuit consisting of one or two switching TFTs integrated with one amplifying TFT is fabricated. To take advantage of the full potential of these amplifiers, it is crucial to develop APS architectures to compensate for the limitations of the TFTs. In this thesis several APS architectures are designed, simulated, fabricated, and tested addressing these challenges using the mask sets presented in Appendix A. The proposed APS architectures can compensate for inherent stabilities of the comprising TFTs. Therefore, the sensitivity of their output data to the transistor variations is significantly suppressed. This is achieved by using a well defined external current source instead of the traditional voltage source to reset the APS architectures during the reset cycle of their periodic operation. The performance of these circuits is analyzed in terms of their stability, settling time, noise, and temperature-dependence. For appropriate readout of the current mode APS architectures, high gain transresistance amplifiers with correlated double sampling capability is designed, simulated and fabricated in CMOS technology. Measurement and measurement based calculation results reveal that the proposed APS architectures can meet even the stringent requirements of low noise, real-time digital fluoroscopy.

Current municipal solid waste (MSW) practices have encouraged rapid waste degradation (stabilization) as an alternative to past methods of isolating the waste from the surrounding environment. There are challenges to rapid-stabilization technology, in particular, the management of the in-situ MSW moisture content.<p> The primary objective of this study was to evaluate the use of capacitance moisture probes for the purpose of measuring the moisture content within MSW. Capacitance moisture probes have not previously been used in MSW, however their use in agriculture is extensive and knowledge of their potential for monitoring MSW is limited.<p> The specific objectives of this research were to: i) establish a laboratory based correlation between sensor data and volumetric moisture content in MSW, ii) establish a correlation between field-installed capacitance sensors and moisture content derived from continuous-depth in-situ sampling of MSW, and iii) demonstrate the ability of capturing advancing/receding moisture fronts with the field-installed capacitance sensors.<p> Laboratory trials were conducted using hand-compacted MSW at volumetric moisture contents ranging from 15%-55% and a manual type of capacitance sensor. This series of laboratory trials successfully produced a correlation between sensor output and volumetric moisture content.<p> To evaluate the sensors in a real-world application, two configurations of capacitance moisture probes were installed in the field: i) an in-place, continuous-time capacitance probe, and ii) a portable, continuous-depth at discrete time, capacitance probe.<p> Field results indicated that capacitance moisture probes were able to capture the passing of both an artificially and naturally induced moisture front, though quantitative correlation between the in-situ moisture content of the sampled MSW and the readings of the sensors could not be achieved.<p> The reasons for this were a combination of three factors:<p> 1. The introduction of void-space during sensor installation significantly reduced sensor output;<p> 2. Poor MSW sampling technique resulted in 57% recovery (causing the exact origin of samples to be unknown); and<p> 3. The sampling technique disturbed the MSW samples, resulting in incorrect volumetric moisture contents in the samples.

This study investigated the behavior of porous silicon gas sensors under exposure to CO, NO, and NH3 gas at the part per million level. Parameters of interest in this study included the electrical, environmental, and chemi-resistive performance associated with various porous silicon morphologies. Based upon the variability of preliminary results, a gas pulsing method was combined with signal processing in order to analyze small impedance changes in an environment of substantial noise. With this technique, sensors could be effectively screened and characterized. Finally this method was combined with various post-treatments in order to improve the sensitivity and selectivity of individual sensors.

While nonlinear behavior in mechanical systems typically degrades the behavior and performance the devices, the presence of system nonlinearities can sometimes improve the quality of the system. A reason for avoiding nonlinearities within a device is the difficulty in controlling the device due to the effects of the nonlinearities on system behavior. However, careful analysis of nonlinear systems can allow for one to take advantage of the nonlinear behavior to improve system performance. The objective of this thesis is to exploit the use of nonlinearities to enhance system performance, specifically the sensitivity of a micromachined magnetic sensor. A device design will be presented that is similar to a prototype that has been fabricated by a student within the Electrical and Computer Engineering Department at Georgia Tech. The operating principle of the device is that changes in the orientation and the strength of an external magnetic field will result in changes in the dynamic behavior of the sensor. While previous device provided a proof of the design concept, it was unable to achieve a sensitivity that would allow for its use as a compass. Improvements in the sensitivity of the sensor are achieved through the modeling and optimization of the magnetic sensor. The optimization and redesign of the magnetic sensor will improve the quality of the device and provide another step towards sensor commercialization. A new design that incorporates the use of variable force comb drives will be proposed that will further improve the sensitivity of the device by modifying the dynamic behavior of the sensor. Another approach that is presented to exploit the nonlinear behavior of the magnetic sensor involves a frequency detection scheme that uses nonlinear vibrations to characterize sensor behavior. Some benefits of this detection technique are that it is insensitive to noise in the vibration of the sensor and is also independent of the damping present within the system. In addition, the implementation of this sensing technique can be readily applied to variety of sensors types without the redesign of a system or the addition of complex components such as vacuum packaging or signal processing electronics.

In-process turbine monitoring has been a subject of research since the advent of gas turbines; however, it is difficult because it requires precision measurements to be made at high speeds and temperatures. The measurement of turbine blade tips is especially intriguing because of the potential it holds to greatly increase the efficiency of engine operation and maintenance. Tip-to-casing clearance is one of the major sources of inefficiency in a turbine and monitoring of this clearance would allow active tip-clearance control systems to be implemented. Also, analysis of engine wear through vibration monitoring may increase the effectiveness of engine maintenance and repair. A sensor recently developed at Georgia Tech could answer this challenge. The sensor operates by measuring the phase change of reflected microwaves to measure blade tip displacement. It is robust even in the harsh turbine environment. However, in sensor measurements, the microwave beam pattern causes a phenomenon called spatial filtering to occur, which may compromise the precision of measurements. Since the beam is not a thin line reflecting off a single point on the turbine blade, measurements are a weighted average of measurements along the entire surface within the field-of-view of the sensor. The net effect is a blurred measurement. In measuring turbine blades, only the tip is vital, so the blurring in between blades is not extremely detrimental. However, changing measurement geometry affects the amount of spatial filtering and hence the accuracy of the measurement. This thesis presents a detailed analysis of this phenomenon and especially its effect on turbine blade tip clearance measurements. A design of experiments is presented to qualitatively understand the effect of geometric factors on tip measurements. Along with experimentation, a robust, three-dimensional, ray-tracing, electromagnetic model is presented which was developed to further understand spatial filtering and to analyze specific geometric factors in the measurement of turbine blades. The research shows that microwave measurements may still be made to sufficient accuracy even considering the effect of spatial filtering, and by quantifying spatial filtering in measurements, it may be possible in to glean additional useful data from measurements.

Testing is an integral part of modern semiconductor industry. The necessity of test is evident, especially for low-yielding processes, to ensure Quality of Service (QoS) to the customers. Testing is a major contributing factor to the total manufacturing cost of analog/RF systems, with test cost estimated to be up to 40% of the overall cost. Due to the lack of low-cost, high-speed testers and other test instrumentation that can be used in a production line, low-cost testing of high-frequency devices/systems is a tremendous challenge to semiconductor test community. Also, simulation times being very high for such systems, the only possible way to generate reliable tests for RF systems is by performing direct measurements on hardware. At the same time, inserting test points for such circuits while maintaining signal integrity is a difficult task to achieve. The proposed research develops a test strategy to reduce overall test cost for RF circuits. A built-in-test (BIT) approach using sensors is proposed for this purpose, which are designed into high-frequency circuits. The work develops algorithms for selecting optimal test access points, and the stimulus for testing the DUT. The test stimulus can be generated on-chip, through efficient design reuse or using custom built circuits. The test responses are captured and analyzed by on-chip sensors, which are custom designed to extract test response features. The sensors, which have low silicon area overhead, output either DC or low frequency test response signals and are compatible to low-speed testers; hence are low-cost. The specifications of the system are computed using a set of nonlinear models developed using the alternate test methodology. The whole approach has been applied to a RF receiver at 1 GHz, used as a test vehicle to prove the feasibility of the proposed approach. Finally, the method is verified through measurements made on a large number of devices, similar to an industrial production test situation. The proposed method using sensors estimated system-level as well as device-level specifications very accurately in the emulated production test environment with a significantly smaller test cost than existing production tests.

The research is divided into two main parts: the sensing part and the gas delivery part. The reliable chemical information from the chemical sensor requires that the sensitive layer of the sensor exhibits long-term stability. To improve the stability of the sensing layer, camphorsulfonic acid was added to the formic acid. The introduction of photo-irradiation at 254 nm as an additional treatment to the sensing layer was proved to be effective. For gas selectivity of PANI matrix, metal or metal oxide clusters have been incorporated into the matrix. The composite materials of PANI with silver, copper, iron, nickel, palladium and mercury were also prepared and exposed to different gases. The second part of the thesis discusses the gas delivery system to the sensors using the synthetic jet technology. The sniffing functionality was demonstrated using the designed jet cell for operation in the open system. The gas sniffing experiments showed that in the presence of the jet, the response time of the sensor is faster by about two orders of magnitude (20 compared to 1800 seconds). The jet sampling system was applied to continuous monitoring of ammonia gas filter performance using the chemFET array. The jet system collected the gas before and after filtering, and the difference between the two responses was compared to observe the break-through of the filter. It was concluded that the gas sensing system integrated with the gas sampling functionality can be applied to monitor a gas filter performance. The cell was designed so that the impinging jet covers the sensing active area of the array of eight chemFETs. The two-dimensional distribution of the ammonia gas concentrations showed that the jet covers the active sensing area in an effective way so that the sampling volume for sensing is significantly reduced compared with the conventional gas flow cell system. Based on these initial studies shown in this thesis, the proposed gas sniffing system was shown to be effective in realizing fast detections of gases for critical applications of a gas sensor system.

The goal of this thesis is to provide an adaptable protocol stack architecture for data fusion applications. Towards the goal, this thesis presents the design of SensorStack, that addresses three key issues. First, towards network-level adaptability, how to dynamically adapt the placement of a fusion application task graph on the network? We have designed a distributed role assignment algorithm and implemented in the context of DFuse, a framework for distributed data fusion. Second, towards node-level adaptability, how to facilitate cross-layering on a node to foster agile adaptation of a node's behavior commensurate with the network-level changes? SensorStack provides information exchange service (IES) as a framework for cross-module information exchange. Finally, towards tying the network and node level adaptability together, control data published in IES needs to be shared across the network. SensorStack uses a probabilistic broadcast based dissemination service (IDS) for control data. We implement SensorStack in TinyOS and Linux to validate the SensorStack design, and use simulation experiments to investigate its network performance. Experiments demonstrate the utility of adaptability in SensorStack to increase application longevity.