Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
Displaying 1 - 10 of 92
Description
There is a pervasive need in the defense industry for conformal, low-profile, efficient and broadband (HF-UHF) antennas. Broadband capabilities enable shared aperture multi-function radiators, while conformal antenna profiles minimize physical damage in army applications, reduce drag and weight penalties in airborne applications and reduce the visual and RF signatures of the communication node. This dissertation is concerned with a new class of antennas called Magneto-Dielectric wire antennas (MDWA) that provide an ideal solution to this ever-present and growing need. Magneto-dielectric structures (μr>1;εr>1) can partially guide electromagnetic waves and radiate them by leaking off the structure or by scattering from any discontinuities, much like a metal antenna of the same shape. They are attractive alternatives to conventional whip and blade antennas because they can be placed conformal to a metallic ground plane without any performance penalty. A two pronged approach is taken to analyze MDWAs. In the first, antenna circuit models are derived for the prototypical dipole and loop elements that include the effects of realistic dispersive magneto-dielectric materials of construction. A material selection law results, showing that: (a) The maximum attainable efficiency is determined by a single magnetic material parameter that we term the hesitivity: Closely related to Snoek's product, it measures the maximum magnetic conductivity of the material. (b) The maximum bandwidth is obtained by placing the highest amount of μ" loss in the frequency range of operation. As a result, high radiation efficiency antennas can be obtained not only from the conventional low loss (low μ") materials but also with highly lossy materials (tan(δm)>>1). The second approach used to analyze MDWAs is through solving the Green function problem of the infinite magneto-dielectric cylinder fed by a current loop. This solution sheds light on the leaky and guided waves supported by the magneto-dielectric structure and leads to useful design rules connecting the permeability of the material to the cross sectional area of the antenna in relation to the desired frequency of operation. The Green function problem of the permeable prolate spheroidal antenna is also solved as a good approximation to a finite cylinder.
ContributorsSebastian, Tom (Author) / Diaz, Rodolfo E (Thesis advisor) / Pan, George (Committee member) / Aberle, James T., 1961- (Committee member) / Kozicki, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
Microwave (MW), thermal, and ultraviolet (UV) annealing were used to explore the response of Ag structures on a Ge-Se chalcogenide glass (ChG) thin film as flexible radiation sensors, and Te-Ti chalcogenide thin films as a material for diffusion barriers in microelectronics devices and processing of metallized Cu. Flexible resistive radiation sensors consisting of Ag electrodes on a Ge20Se80 ChG thin film and polyethylene naphthalate substrate were exposed to UV radiation. The sensors were mounted on PVC tubes of varying radii to induce bending strains and annealed under ambient conditions up to 150 oC. Initial sensor resistance was measured to be ~1012 Ω; after exposure to UV radiation, the resistance was ~104 Ω. Bending strain and low temperature annealing had no significant effect on the resistance of the sensors. Samples of Cu on Te-Ti thin films were annealed in vacuum for up to 30 minutes and were stable up to 500 oC as revealed using Rutherford backscattering spectrometry (RBS) and four-point-probe analysis. X-ray diffractometry (XRD) indicates Cu grain growth up to 500 oC and phase instability of the Te-Ti barrier at 600 oC. MW processing was performed in a 2.45-GHz microwave cavity on Cu/Te-Ti films for up to 30 seconds to induce oxide growth. Using a calibrated pyrometer above the sample, the temperature of the MW process was measured to be below a maximum of 186 oC. Four-point-probe analysis shows an increase in resistance with an increase in MW time. XRD indicates growth of CuO on the sample surface. RBS suggests oxidation throughout the Te-Ti film. Additional samples were exposed to 907 J/cm2 UV radiation in order to ensure other possible electromagnetically induced mechanisms were not active. There were no changes observed using XRD, RBS or four point probing.
ContributorsRoos, Benjamin, 1990- (Author) / Alford, Terry L. (Thesis advisor) / Theodore, David (Committee member) / Kozicki, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
Creative design lies at the intersection of novelty and technical feasibility. These objectives can be achieved through cycles of divergence (idea generation) and convergence (idea evaluation) in conceptual design. The focus of this thesis is on the latter aspect. The evaluation may involve any aspect of technical feasibility and may be desired at component, sub-system or full system level. Two issues that are considered in this work are: 1. Information about design ideas is incomplete, informal and sketchy 2. Designers often work at multiple levels; different aspects or subsystems may be at different levels of abstraction Thus, high fidelity analysis and simulation tools are not appropriate for this purpose. This thesis looks at the requirements for a simulation tool and how it could facilitate concept evaluation. The specific tasks reported in this thesis are: 1. The typical types of information available after an ideation session 2. The typical types of technical evaluations done in early stages 3. How to conduct low fidelity design evaluation given a well-defined feasibility question A computational tool for supporting idea evaluation was designed and implemented. It was assumed that the results of the ideation session are represented as a morphological chart and each entry is expressed as some combination of a sketch, text and references to physical effects and machine components. Approximately 110 physical effects were identified and represented in terms of algebraic equations, physical variables and a textual description. A common ontology of physical variables was created so that physical effects could be networked together when variables are shared. This allows users to synthesize complex behaviors from simple ones, without assuming any solution sequence. A library of 16 machine elements was also created and users were given instructions about incorporating them. To support quick analysis, differential equations are transformed to algebraic equations by replacing differential terms with steady state differences), only steady state behavior is considered and interval arithmetic was used for modeling. The tool implementation is done by MATLAB; and a number of case studies are also done to show how the tool works. textual description. A common ontology of physical variables was created so that physical effects could be networked together when variables are shared. This allows users to synthesize complex behaviors from simple ones, without assuming any solution sequence. A library of 15 machine elements was also created and users were given instructions about incorporating them. To support quick analysis, differential equations are transformed to algebraic equations by replacing differential terms with steady state differences), only steady state behavior is considered and interval arithmetic was used for modeling. The tool implementation is done by MATLAB; and a number of case studies are also done to show how the tool works.
ContributorsKhorshidi, Maryam (Author) / Shah, Jami J. (Thesis advisor) / Wu, Teresa (Committee member) / Gel, Esma (Committee member) / Arizona State University (Publisher)
Created2014
Description
Vehicles powered by electricity and alternative-fuels are becoming a more popular form of transportation since they have less of an environmental impact than standard gasoline vehicles. Unfortunately, their success is currently inhibited by the sparseness of locations where the vehicles can refuel as well as the fact that many of the vehicles have a range that is less than those powered by gasoline. These factors together create a "range anxiety" in drivers, which causes the drivers to worry about the utility of alternative-fuel and electric vehicles and makes them less likely to purchase these vehicles. For the new vehicle technologies to thrive it is critical that range anxiety is minimized and performance is increased as much as possible through proper routing and scheduling. In the case of long distance trips taken by individual vehicles, the routes must be chosen such that the vehicles take the shortest routes while not running out of fuel on the trip. When many vehicles are to be routed during the day, if the refueling stations have limited capacity then care must be taken to avoid having too many vehicles arrive at the stations at any time. If the vehicles that will need to be routed in the future are unknown then this problem is stochastic. For fleets of vehicles serving scheduled operations, switching to alternative-fuels requires ensuring the schedules do not cause the vehicles to run out of fuel. This is especially problematic since the locations where the vehicles may refuel are limited due to the technology being new. This dissertation covers three related optimization problems: routing a single electric or alternative-fuel vehicle on a long distance trip, routing many electric vehicles in a network where the stations have limited capacity and the arrivals into the system are stochastic, and scheduling fleets of electric or alternative-fuel vehicles with limited locations to refuel. Different algorithms are proposed to solve each of the three problems, of which some are exact and some are heuristic. The algorithms are tested on both random data and data relating to the State of Arizona.
ContributorsAdler, Jonathan D (Author) / Mirchandani, Pitu B. (Thesis advisor) / Askin, Ronald (Committee member) / Gel, Esma (Committee member) / Xue, Guoliang (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2014
Description
The design and development of analog/mixed-signal (AMS) integrated circuits (ICs) is becoming increasingly expensive, complex, and lengthy. Rapid prototyping and emulation of analog ICs will be significant in the design and testing of complex analog systems. A new approach, Programmable ANalog Device Array (PANDA) that maps any AMS design problem to a transistor-level programmable hardware, is proposed. This approach enables fast system level validation and a reduction in post-Silicon bugs, minimizing design risk and cost. The unique features of the approach include 1) transistor-level programmability that emulates each transistor behavior in an analog design, achieving very fine granularity of reconfiguration; 2) programmable switches that are treated as a design component during analog transistor emulating, and optimized with the reconfiguration matrix; 3) compensation of AC performance degradation through boosting the bias current. Based on these principles, a digitally controlled PANDA platform is designed at 45nm node that can map AMS modules across 22nm to 90nm technology nodes. A systematic emulation approach to map any analog transistor to 45nm PANDA cell is proposed, which achieves transistor level matching accuracy of less than 5% for ID and less than 10% for Rout and Gm. Circuit level analog metrics of a voltage-controlled oscillator (VCO) emulated by PANDA, match to those of the original designs in 22nm and 90nm nodes with less than a 5% error. Several other 90nm and 22nm analog blocks are successfully emulated by the 45nm PANDA platform, including a folded-cascode operational amplifier and a sample-and-hold module (S/H). Further capabilities of PANDA are demonstrated by the first full-chip silicon of PANDA which is implemented on 65nm process This system consists of a 24×25 cell array, reconfigurable interconnect and configuration memory. The voltage and current reference circuits, op amps and a VCO with a phase interpolation circuit are emulated by PANDA.
ContributorsSuh, Jounghyuk (Author) / Bakkaloglu, Bertan (Thesis advisor) / Cao, Yu (Committee member) / Ozev, Sule (Committee member) / Kozicki, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
Accelerated life testing (ALT) is the process of subjecting a product to stress conditions (temperatures, voltage, pressure etc.) in excess of its normal operating levels to accelerate failures. Product failure typically results from multiple stresses acting on it simultaneously. Multi-stress factor ALTs are challenging as they increase the number of experiments due to the stress factor-level combinations resulting from the increased number of factors. Chapter 2 provides an approach for designing ALT plans with multiple stresses utilizing Latin hypercube designs that reduces the simulation cost without loss of statistical efficiency. A comparison to full grid and large-sample approximation methods illustrates the approach computational cost gain and flexibility in determining optimal stress settings with less assumptions and more intuitive unit allocations.
Implicit in the design criteria of current ALT designs is the assumption that the form of the acceleration model is correct. This is unrealistic assumption in many real-world problems. Chapter 3 provides an approach for ALT optimum design for model discrimination. We utilize the Hellinger distance measure between predictive distributions. The optimal ALT plan at three stress levels was determined and its performance was compared to good compromise plan, best traditional plan and well-known 4:2:1 compromise test plans. In the case of linear versus quadratic ALT models, the proposed method increased the test plan's ability to distinguish among competing models and provided better guidance as to which model is appropriate for the experiment.
Chapter 4 extends the approach of Chapter 3 to ALT sequential model discrimination. An initial experiment is conducted to provide maximum possible information with respect to model discrimination. The follow-on experiment is planned by leveraging the most current information to allow for Bayesian model comparison through posterior model probability ratios. Results showed that performance of plan is adversely impacted by the amount of censoring in the data, in the case of linear vs. quadratic model form at three levels of constant stress, sequential testing can improve model recovery rate by approximately 8% when data is complete, but no apparent advantage in adopting sequential testing was found in the case of right-censored data when censoring is in excess of a certain amount.
Implicit in the design criteria of current ALT designs is the assumption that the form of the acceleration model is correct. This is unrealistic assumption in many real-world problems. Chapter 3 provides an approach for ALT optimum design for model discrimination. We utilize the Hellinger distance measure between predictive distributions. The optimal ALT plan at three stress levels was determined and its performance was compared to good compromise plan, best traditional plan and well-known 4:2:1 compromise test plans. In the case of linear versus quadratic ALT models, the proposed method increased the test plan's ability to distinguish among competing models and provided better guidance as to which model is appropriate for the experiment.
Chapter 4 extends the approach of Chapter 3 to ALT sequential model discrimination. An initial experiment is conducted to provide maximum possible information with respect to model discrimination. The follow-on experiment is planned by leveraging the most current information to allow for Bayesian model comparison through posterior model probability ratios. Results showed that performance of plan is adversely impacted by the amount of censoring in the data, in the case of linear vs. quadratic model form at three levels of constant stress, sequential testing can improve model recovery rate by approximately 8% when data is complete, but no apparent advantage in adopting sequential testing was found in the case of right-censored data when censoring is in excess of a certain amount.
ContributorsNasir, Ehab (Author) / Pan, Rong (Thesis advisor) / Runger, George C. (Committee member) / Gel, Esma (Committee member) / Kao, Ming-Hung (Committee member) / Montgomery, Douglas C. (Committee member) / Arizona State University (Publisher)
Created2014
Description
There is an ever growing need for larger memories which are reliable and fast. New technologies to implement non-volatile memories which are large, fast, compact and cost-efficient are being studied extensively. One of the most promising technologies being developed is the resistive RAM (ReRAM). In ReRAM the resistance of the device varies with the voltage applied across it. Programmable metallization cells (PMC) is one of the devices belonging to this category of non-volatile memories.
In order to advance the development of these devices, there is a need to develop simulation models which replicate the behavior of these devices in circuits. In this thesis, a verilogA model for the PMC has been developed. The behavior of the model has been tested using DC and transient simulations. Experimental data obtained from testing PMC devices fabricated at Arizona State University have been compared to results obtained from simulation.
A basic memory cell known as the 1T 1R cell built using the PMC has also been simulated and verified. These memory cells have the potential to be building blocks of large scale memories. I believe that the verilogA model developed in this thesis will prove to be a powerful tool for researchers and circuit developers looking to develop non-volatile memories using alternative technologies.
In order to advance the development of these devices, there is a need to develop simulation models which replicate the behavior of these devices in circuits. In this thesis, a verilogA model for the PMC has been developed. The behavior of the model has been tested using DC and transient simulations. Experimental data obtained from testing PMC devices fabricated at Arizona State University have been compared to results obtained from simulation.
A basic memory cell known as the 1T 1R cell built using the PMC has also been simulated and verified. These memory cells have the potential to be building blocks of large scale memories. I believe that the verilogA model developed in this thesis will prove to be a powerful tool for researchers and circuit developers looking to develop non-volatile memories using alternative technologies.
ContributorsBharadwaj, Vineeth (Author) / Barnaby, Hugh (Thesis advisor) / Kozicki, Michael (Committee member) / Mikkola, Esko (Committee member) / Arizona State University (Publisher)
Created2014
Description
Nonvolatile memory (NVM) technologies have been an integral part of electronic systems for the past 30 years. The ideal non-volatile memory have minimal physical size, energy usage, and cost while having maximal speed, capacity, retention time, and radiation hardness. A promising candidate for next-generation memory is ion-conducting bridging RAM which is referred to as programmable metallization cell (PMC), conductive bridge RAM (CBRAM), or electrochemical metallization memory (ECM), which is likely to surpass flash memory in all the ideal memory characteristics. A comprehensive physics-based model is needed to completely understand PMC operation and assist in design optimization.
To advance the PMC modeling effort, this thesis presents a precise physical model parameterizing materials associated with both ion-rich and ion-poor layers of the PMC's solid electrolyte, so that captures the static electrical behavior of the PMC in both its low-resistance on-state (LRS) and high resistance off-state (HRS). The experimental data is measured from a chalcogenide glass PMC designed and manufactured at ASU. The static on- and off-state resistance of a PMC device composed of a layered (Ag-rich/Ag-poor) Ge30Se70 ChG film is characterized and modeled using three dimensional simulation code written in Silvaco Atlas finite element analysis software. Calibrating the model to experimental data enables the extraction of device parameters such as material bandgaps, workfunctions, density of states, carrier mobilities, dielectric constants, and affinities.
The sensitivity of our modeled PMC to the variation of its prominent achieved material parameters is examined on the HRS and LRS impedance behavior.
The obtained accurate set of material parameters for both Ag-rich and Ag-poor ChG systems and process variation verification on electrical characteristics enables greater fidelity in PMC device simulation, which significantly enhances our ability to understand the underlying physics of ChG-based resistive switching memory.
To advance the PMC modeling effort, this thesis presents a precise physical model parameterizing materials associated with both ion-rich and ion-poor layers of the PMC's solid electrolyte, so that captures the static electrical behavior of the PMC in both its low-resistance on-state (LRS) and high resistance off-state (HRS). The experimental data is measured from a chalcogenide glass PMC designed and manufactured at ASU. The static on- and off-state resistance of a PMC device composed of a layered (Ag-rich/Ag-poor) Ge30Se70 ChG film is characterized and modeled using three dimensional simulation code written in Silvaco Atlas finite element analysis software. Calibrating the model to experimental data enables the extraction of device parameters such as material bandgaps, workfunctions, density of states, carrier mobilities, dielectric constants, and affinities.
The sensitivity of our modeled PMC to the variation of its prominent achieved material parameters is examined on the HRS and LRS impedance behavior.
The obtained accurate set of material parameters for both Ag-rich and Ag-poor ChG systems and process variation verification on electrical characteristics enables greater fidelity in PMC device simulation, which significantly enhances our ability to understand the underlying physics of ChG-based resistive switching memory.
ContributorsRajabi, Saba (Author) / Barnaby, Hugh (Thesis advisor) / Kozicki, Michael (Committee member) / Vasileska, Dragica (Committee member) / Arizona State University (Publisher)
Created2014
Description
A new loop configuration capable of reducing power radiation magnitudes lower than conventional loops has been developed. This configuration is demonstrated for the case of two coaxial loops of 0.1 meter radius coupled via the magnetic reactive field. Utilizing electromagnetism theory, techniques from antenna design and a new near field design initiative, the ability to design a magnetic field has been investigated by using a full wave simulation tool. The method for realization is initiated from first order physics model, ADS and onto a full wave situation tool for the case of a non-radiating helical loop. The exploration into the design of a magnetic near field while mitigating radiation power is demonstrated using an real number of twists to form a helical wire loop while biasing the integer twisted loop in a non-conventional moebius termination. The helix loop setup as a moebius loop convention can also be expressed as a shorted antenna scheme. The 0.1 meter radius helix antenna is biased with a 1MHz frequency that categorized the antenna loop as electrically small. It is then demonstrated that helical configuration reduces the electric field and mitigates power radiation into the far field. In order to compare the radiated power reduction performance of the helical loop a shielded loop is used as a baseline for comparison. The shielded loop system of the same geometric size and frequency is shown to have power radiation expressed as -46.1 dBm. The power radiated mitigation method of the helix loop reduces the power radiated from the two loop system down to -98.72 dBm.
ContributorsMoreno, Fernando (Author) / Diaz, Rodolfo (Thesis advisor) / Aberle, James T., 1961- (Committee member) / Kozicki, Michael (Committee member) / Arizona State University (Publisher)
Created2015
Description
This work explores how flexible electronics and display technology can be applied to develop new biomedical devices for medical, biological, and life science applications. It demonstrates how new biomedical devices can be manufactured by only modifying or personalizing the upper layers of a conventional thin film transistor (TFT) display process. This personalization was applied first to develop and demonstrate the world's largest flexible digital x-ray detector for medical and industrial imaging, and the world's first flexible ISFET pH biosensor using TFT technology. These new, flexible, digital x-ray detectors are more durable than conventional glass substrate x-ray detectors, and also can conform to the surface of the object being imaged. The new flexible ISFET pH biosensors are >10X less expensive to manufacture than comparable CMOS-based ISFETs and provide a sensing area that is orders of magnitude larger than CMOS-based ISFETs. This allows for easier integration with area intensive chemical and biological recognition material as well as allow for a larger number of unique recognition sites for low cost multiple disease and pathogen detection.
The flexible x-ray detector technology was then extended to demonstrate the viability of a new technique to seamlessly combine multiple smaller flexible x-ray detectors into a single very large, ultimately human sized, composite x-ray detector for new medical imaging applications such as single-exposure, low-dose, full-body digital radiography. Also explored, is a new approach to increase the sensitivity of digital x-ray detectors by selectively disabling rows in the active matrix array that are not part of the imaged region. It was then shown how high-resolution, flexible, organic light-emitting diode display (OLED) technology can be used to selectively stimulate and/or silence small groups of neurons on the cortical surface or within the deep brain as a potential new tool to diagnose and treat, as well as understand, neurological diseases and conditions. This work also explored the viability of a new miniaturized high sensitivity fluorescence measurement-based lab-on-a-chip optical biosensor using OLED display and a-Si:H PiN photodiode active matrix array technology for point-of-care diagnosis of multiple disease or pathogen biomarkers in a low cost disposable configuration.
The flexible x-ray detector technology was then extended to demonstrate the viability of a new technique to seamlessly combine multiple smaller flexible x-ray detectors into a single very large, ultimately human sized, composite x-ray detector for new medical imaging applications such as single-exposure, low-dose, full-body digital radiography. Also explored, is a new approach to increase the sensitivity of digital x-ray detectors by selectively disabling rows in the active matrix array that are not part of the imaged region. It was then shown how high-resolution, flexible, organic light-emitting diode display (OLED) technology can be used to selectively stimulate and/or silence small groups of neurons on the cortical surface or within the deep brain as a potential new tool to diagnose and treat, as well as understand, neurological diseases and conditions. This work also explored the viability of a new miniaturized high sensitivity fluorescence measurement-based lab-on-a-chip optical biosensor using OLED display and a-Si:H PiN photodiode active matrix array technology for point-of-care diagnosis of multiple disease or pathogen biomarkers in a low cost disposable configuration.
ContributorsSmith, Joseph T. (Author) / Allee, David (Thesis advisor) / Goryll, Michael (Committee member) / Kozicki, Michael (Committee member) / Blain Christen, Jennifer (Committee member) / Couture, Aaron (Committee member) / Arizona State University (Publisher)
Created2014