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 134
Description
There is a lack of music therapy services for college students who have problems with depression and/or anxiety. Even among universities and colleges that offer music therapy degrees, there are no known programs offering music therapy to the institution's students. Female college students are particularly vulnerable to depression and anxiety symptoms compared to their male counterparts. Many students who experience mental health problems do not receive treatment, because of lack of knowledge, lack of services, or refusal of treatment. Music therapy is proposed as a reliable and valid complement or even an alternative to traditional counseling and pharmacotherapy because of the appeal of music to young women and the potential for a music therapy group to help isolated students form supportive networks. The present study recruited 14 female university students to participate in a randomized controlled trial of short-term group music therapy to address symptoms of depression and anxiety. The students were randomly divided into either the treatment group or the control group. Over 4 weeks, each group completed surveys related to depression and anxiety. Results indicate that the treatment group's depression and anxiety scores gradually decreased over the span of the treatment protocol. The control group showed either maintenance or slight worsening of depression and anxiety scores. Although none of the results were statistically significant, the general trend indicates that group music therapy was beneficial for the students. A qualitative analysis was also conducted for the treatment group. Common themes were financial concerns, relationship problems, loneliness, and time management/academic stress. All participants indicated that they benefited from the sessions. The group progressed in its cohesion and the participants bonded to the extent that they formed a supportive network which lasted beyond the end of the protocol. The results of this study are by no means conclusive, but do indicate that colleges with music therapy degree programs should consider adding music therapy services for their general student bodies.
ContributorsAshton, Barbara (Author) / Crowe, Barbara J. (Thesis advisor) / Rio, Robin (Committee member) / Davis, Mary (Committee member) / Arizona State University (Publisher)
Created2013
Description
ABSTRACT This work seeks to develop a practical solution for short range ultrasonic communications and produce an integrated array of acoustic transmitters on a flexible substrate. This is done using flexible thin film transistor (TFT) and micro electromechanical systems (MEMS). The goal is to develop a flexible system capable of communicating in the ultrasonic frequency range at a distance of 10 - 100 meters. This requires a great deal of innovation on the part of the FDC team developing the TFT driving circuitry and the MEMS team adapting the technology for fabrication on a flexible substrate. The technologies required for this research are independently developed. The TFT development is driven primarily by research into flexible displays. The MEMS development is driving by research in biosensors and micro actuators. This project involves the integration of TFT flexible circuit capabilities with MEMS micro actuators in the novel area of flexible acoustic transmitter arrays. This thesis focuses on the design, testing and analysis of the circuit components required for this project.
ContributorsDaugherty, Robin (Author) / Allee, David R. (Thesis advisor) / Chae, Junseok (Thesis advisor) / Aberle, James T (Committee member) / Vasileska, Dragica (Committee member) / Arizona State University (Publisher)
Created2012
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
New technologies enable the exploration of space, high-fidelity defense systems, lighting fast intercontinental communication systems as well as medical technologies that extend and improve patient lives. The basis for these technologies is high reliability electronics devised to meet stringent design goals and to operate consistently for many years deployed in the field. An on-going concern for engineers is the consequences of ionizing radiation exposure, specifically total dose effects. For many of the different applications, there is a likelihood of exposure to radiation, which can result in device degradation and potentially failure. While the total dose effects and the resulting degradation are a well-studied field and methodologies to help mitigate degradation have been developed, there is still a need for simulation techniques to help designers understand total dose effects within their design. To that end, the work presented here details simulation techniques to analyze as well as predict the total dose response of a circuit. In this dissertation the total dose effects are broken into two sub-categories, intra-device and inter-device effects in CMOS technology. Intra-device effects degrade the performance of both n-channel and p-channel transistors, while inter-device effects result in loss of device isolation. In this work, multiple case studies are presented for which total dose degradation is of concern. Through the simulation techniques, the individual device and circuit responses are modeled post-irradiation. The use of these simulation techniques by circuit designers allow predictive simulation of total dose effects, allowing focused design changes to be implemented to increase radiation tolerance of high reliability electronics.
ContributorsSchlenvogt, Garrett (Author) / Barnaby, Hugh (Thesis advisor) / Goodnick, Stephen (Committee member) / Vasileska, Dragica (Committee member) / Holbert, Keith E. (Committee member) / Arizona State University (Publisher)
Created2014
Description
Silicon solar cells with heterojunction carrier collectors based on a-Si/c-Si heterojunction (SHJ) have a potential to overcome the limitations of the conventional diffused junction solar cells and become the next industry standard manufacturing technology of solar cells. A brand feature of SHJ technology is ultrapassivated surfaces with already demonstrated 750 mV open circuit voltages (Voc) and 24.7% efficiency on large area solar cell. Despite very good results achieved in research and development, large volume manufacturing of high efficiency SHJ cells remains a fundamental challenge. The main objectives of this work were to develop a SHJ solar cell fabrication flow using industry compatible tools and processes in a pilot production environment, study the interactions between the used fabrication steps, identify the minimum set of optimization parameters and characterization techniques needed to achieve 20% baseline efficiency, and analyze the losses of power in fabricated SHJ cells by numerical and analytical modeling. This manuscript presents a detailed description of a SHJ solar cell fabrication flow developed at ASU Solar Power Laboratory (SPL) which allows large area solar cells with >750 mV Voc. SHJ cells on 135 um thick 153 cm2 area wafers with 19.5% efficiency were fabricated. Passivation quality of (i)a-Si:H film, bulk conductivity of doped a-Si films, bulk conductivity of ITO, transmission of ITO and the thickness of all films were identified as the minimum set of optimization parameters necessary to set up a baseline high efficiency SHJ fabrication flow. The preparation of randomly textured wafers to minimize the concentration of surface impurities and to avoid epitaxial growth of a-Si films was found to be a key challenge in achieving a repeatable and uniform passivation. This work resolved this issue by using a multi-step cleaning process based on sequential oxidation in nitric/acetic acids, Piranha and RCA-b solutions. The developed process allowed state of the art surface passivation with perfect repeatability and negligible reflectance losses. Two additional studies demonstrated 750 mV local Voc on 50 micron thick SHJ solar cell and < 1 cm/s effective surface recombination velocity on n-type wafers passivated by a-Si/SiO2/SiNx stack.
ContributorsHerasimenka, Stanislau Yur'yevich (Author) / Honsberg, C. (Christiana B.) (Thesis advisor) / Bowden, Stuart G (Thesis advisor) / Tracy, Clarence (Committee member) / Vasileska, Dragica (Committee member) / Holman, Zachary (Committee member) / Sinton, Ron (Committee member) / Arizona State University (Publisher)
Created2013
Description
Zinc oxide (ZnO), a naturally n-type semiconductor has been identified as a promising candidate to replace indium tin oxide (ITO) as the transparent electrode in solar cells, because of its wide bandgap (3.37 eV), abundant source materials and suitable refractive index (2.0 at 600 nm). Spray deposition is a convenient and low cost technique for large area and uniform deposition of semiconductor thin films. In particular, it provides an easier way to dope the film by simply adding the dopant precursor into the starting solution. In order to reduce the resistivity of undoped ZnO, many works have been done by doping in the ZnO with either group IIIA elements or VIIA elements using spray pyrolysis. However, the resistivity is still too high to meet TCO's resistivity requirement. In the present work, a novel co-spray deposition technique is developed to bypass a fundamental limitation in the conventional spray deposition technique, i.e. the deposition of metal oxides from incompatible precursors in the starting solution. With this technique, ZnO films codoped with one cationic dopant, Al, Cr, or Fe, and an anionic dopant, F, have been successfully synthesized, in which F is incompatible with all these three cationic dopants. Two starting solutions were prepared and co-sprayed through two separate spray heads. One solution contained only the F precursor, NH 4F. The second solution contained the Zn and one cationic dopant precursors, Zn(O 2CCH 3) 2 and AlCl 3, CrCl 3, or FeCl 3. The deposition was carried out at 500 °C; on soda-lime glass in air. Compared to singly-doped ZnO thin films, codoped ZnO samples showed better electrical properties. Besides, a minimum sheet resistance, 55.4 Ω/sq, was obtained for Al and F codoped ZnO films after vacuum annealing at 400 °C;, which was lower than singly-doped ZnO with either Al or F. The transmittance for the Al and F codoped ZnO samples was above 90% in the visible range. This co-spray deposition technique provides a simple and cost-effective way to synthesize metal oxides from incompatible precursors with improved properties.
ContributorsZhou, Bin (Author) / Tao, Meng (Thesis advisor) / Goryll, Michael (Committee member) / Vasileska, Dragica (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2013
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
Sometimes difficult life events challenge our existing resources in such a way that routinized responses are inadequate to handle the challenge. Some individuals will persist in habitual, automatic behavior, regardless of environmental cues that indicate a mismatch between coping strategy and the demands of the stressor. Other individuals will marshal adaptive resources to construct new courses of action and reconceptualize the problem, associated goals and/or values. A mixed methods approach was used to describe and operationalize cognitive shift, a relatively unexplored construct in existing literature. The study was conducted using secondary data from a parent multi-year cross-sectional study of resilience with eight hundred mid-aged adults from the Phoenix metro area. Semi-structured telephone interviews were analyzed using a purposive sample (n=136) chosen by type of life event. Participants' beliefs, assumptions, and experiences were examined to understand how they shaped adaptation to adversity. An adaptive mechanism, "cognitive shift," was theorized as the transition from automatic coping to effortful cognitive processes aimed at novel resolution of issues. Aims included understanding when and how cognitive shift emerges and manifests. Cognitive shift was scored as a binary variable and triangulated through correlational and logistic regression analyses. Interaction effects revealed that positive personality attributes influence cognitive shift most when people suffered early adversity. This finding indicates that a certain complexity, self-awareness and flexibility of mind may lead to a greater capacity to find meaning in adversity. This work bridges an acknowledged gap in literature and provides new insights into resilience.
ContributorsRivers, Crystal T (Author) / Zautra, Alex (Thesis advisor) / Davis, Mary (Committee member) / Kurpius, Sharon (Committee member) / Arizona State University (Publisher)
Created2014
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
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