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 89
Description
A proposed visible spectrum nanoscale imaging method requires material with permittivity values much larger than those available in real world materials to shrink the visible wavelength to attain the desired resolution. It has been proposed that the extraordinarily slow propagation experienced by light guided along plasmon resonant structures is a viable approach to obtaining these short wavelengths. To assess the feasibility of such a system, an effective medium model of a chain of Noble metal plasmonic nanospheres is developed, leading to a straightforward calculation of the waveguiding properties. Evaluation of other models for such structures that have appeared in the literature, including an eigenvalue problem nearest neighbor approximation, a multi- neighbor approximation with retardation, and a method-of-moments method for a finite chain, show conflicting expectations of such a structure. In particular, recent publications suggest the possibility of regions of invalidity for eigenvalue problem solutions that are considered far below the onset of guidance, and for solutions that assume the loss is low enough to justify perturbation approximations. Even the published method-of-moments approach suffers from an unjustified assumption in the original interpretation, leading to overly optimistic estimations of the attenuation of the plasmon guided wave. In this work it is shown that the method of moments approach solution was dominated by the radiation from the source dipole, and not the waveguiding behavior claimed. If this dipolar radiation is removed the remaining fields ought to contain the desired guided wave information. Using a Prony's-method-based algorithm the dispersion properties of the chain of spheres are assessed at two frequencies, and shown to be dramatically different from the optimistic expectations in much of the literature. A reliable alternative to these models is to replace the chain of spheres with an effective medium model, thus mapping the chain problem into the well-known problem of the dielectric rod. The solution of the Green function problem for excitation of the symmetric longitudinal mode (TM01) is performed by numerical integration. Using this method the frequency ranges over which the rod guides and the associated attenuation are clearly seen. The effective medium model readily allows for variation of the sphere size and separation, and can be taken to the limit where instead of a chain of spheres we have a solid Noble metal rod. This latter case turns out to be the optimal for minimizing the attenuation of the guided wave. Future work is proposed to simulate the chain of photonic nanospheres and the nanowire using finite-difference time-domain to verify observed guided behavior in the Green's function method devised in this thesis and to simulate the proposed nanosensing devices.
ContributorsHale, Paul (Author) / Diaz, Rodolfo E (Thesis advisor) / Goodnick, Stephen (Committee member) / Aberle, James T., 1961- (Committee member) / Palais, Joseph (Committee member) / Arizona State University (Publisher)
Created2013
Description
When surgical resection becomes necessary to alleviate a patient's epileptiform activity, that patient is monitored by video synchronized with electrocorticography (ECoG) to determine the type and location of seizure focus. This provides a unique opportunity for researchers to gather neurophysiological data with high temporal and spatial resolution; these data are assessed prior to surgical resection to ensure the preservation of the patient's quality of life, e.g. avoid the removal of brain tissue required for speech processing. Currently considered the "gold standard" for the mapping of cortex, electrical cortical stimulation (ECS) involves the systematic activation of pairs of electrodes to localize functionally specific brain regions. This method has distinct limitations, which often includes pain experienced by the patient. Even in the best cases, the technique suffers from subjective assessments on the parts of both patients and physicians, and high inter- and intra-observer variability. Recent advances have been made as researchers have reported the localization of language areas through several signal processing methodologies, all necessitating patient participation in a controlled experiment. The development of a quantification tool to localize speech areas in which a patient is engaged in an unconstrained interpersonal conversation would eliminate the dependence of biased patient and reviewer input, as well as unnecessary discomfort to the patient. Post-hoc ECoG data were gathered from five patients with intractable epilepsy while each was engaged in a conversation with family members or clinicians. After the data were separated into different speech conditions, the power of each was compared to baseline to determine statistically significant activated electrodes. The results of several analytical methods are presented here. The algorithms did not yield language-specific areas exclusively, as broad activation of statistically significant electrodes was apparent across cortical areas. For one patient, 15 adjacent contacts along superior temporal gyrus (STG) and posterior part of the temporal lobe were determined language-significant through a controlled experiment. The task involved a patient lying in bed listening to repeated words, and yielded statistically significant activations that aligned with those of clinical evaluation. The results of this study do not support the hypothesis that unconstrained conversation may be used to localize areas required for receptive and productive speech, yet suggests a simple listening task may be an adequate alternative to direct cortical stimulation.
ContributorsLingo VanGilder, Jennapher (Author) / Helms Tillery, Stephen I (Thesis advisor) / Wahnoun, Remy (Thesis advisor) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2013
Description
Intracortical microstimulation (ICMS) within somatosensory cortex can produce artificial sensations including touch, pressure, and vibration. There is significant interest in using ICMS to provide sensory feedback for a prosthetic limb. In such a system, information recorded from sensors on the prosthetic would be translated into electrical stimulation and delivered directly to the brain, providing feedback about features of objects in contact with the prosthetic. To achieve this goal, multiple simultaneous streams of information will need to be encoded by ICMS in a manner that produces robust, reliable, and discriminable sensations. The first segment of this work focuses on the discriminability of sensations elicited by ICMS within somatosensory cortex. Stimulation on multiple single electrodes and near-simultaneous stimulation across multiple electrodes, driven by a multimodal tactile sensor, were both used in these experiments. A SynTouch BioTac sensor was moved across a flat surface in several directions, and a subset of the sensor's electrode impedance channels were used to drive multichannel ICMS in the somatosensory cortex of a non-human primate. The animal performed a behavioral task during this stimulation to indicate the discriminability of sensations evoked by the electrical stimulation. The animal's responses to ICMS were somewhat inconsistent across experimental sessions but indicated that discriminable sensations were evoked by both single and multichannel ICMS. The factors that affect the discriminability of stimulation-induced sensations are not well understood, in part because the relationship between ICMS and the neural activity it induces is poorly defined. The second component of this work was to develop computational models that describe the populations of neurons likely to be activated by ICMS. Models of several neurons were constructed, and their responses to ICMS were calculated. A three-dimensional cortical model was constructed using these cell models and used to identify the populations of neurons likely to be recruited by ICMS. Stimulation activated neurons in a sparse and discontinuous fashion; additionally, the type, number, and location of neurons likely to be activated by stimulation varied with electrode depth.
ContributorsOverstreet, Cynthia K (Author) / Helms Tillery, Stephen I (Thesis advisor) / Santos, Veronica (Committee member) / Buneo, Christopher (Committee member) / Otto, Kevin (Committee member) / Santello, Marco (Committee member) / Arizona State University (Publisher)
Created2013
Description
GaN high electron mobility transistors (HEMTs) based on the III-V nitride material system have been under extensive investigation because of their superb performance as high power RF devices. Two dimensional electron gas(2-DEG) with charge density ten times higher than that of GaAs-based HEMT and mobility much higher than Si enables a low on-resistance required for RF devices. Self-heating issues with GaN HEMT and lack of understanding of various phenomena are hindering their widespread commercial development. There is a need to understand device operation by developing a model which could be used to optimize electrical and thermal characteristics of GaN HEMT design for high power and high frequency operation. In this thesis work a physical simulation model of AlGaN/GaN HEMT is developed using commercially available software ATLAS from SILVACO Int. based on the energy balance/hydrodynamic carrier transport equations. The model is calibrated against experimental data. Transfer and output characteristics are the key focus in the analysis along with saturation drain current. The resultant IV curves showed a close correspondence with experimental results. Various combinations of electron mobility, velocity saturation, momentum and energy relaxation times and gate work functions were attempted to improve IV curve correlation. Thermal effects were also investigated to get a better understanding on the role of self-heating effects on the electrical characteristics of GaN HEMTs. The temperature profiles across the device were observed. Hot spots were found along the channel in the gate-drain spacing. These preliminary results indicate that the thermal effects do have an impact on the electrical device characteristics at large biases even though the amount of self-heating is underestimated with respect to thermal particle-based simulations that solve the energy balance equations for acoustic and optical phonons as well (thus take proper account of the formation of the hot-spot). The decrease in drain current is due to decrease in saturation carrier velocity. The necessity of including hydrodynamic/energy balance transport models for accurate simulations is demonstrated. Possible ways for improving model accuracy are discussed in conjunction with future research.
ContributorsChowdhury, Towhid (Author) / Vasileska, Dragica (Thesis advisor) / Goodnick, Stephen (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
Humans' ability to perform fine object and tool manipulation is a defining feature of their sensorimotor repertoire. How the central nervous system builds and maintains internal representations of such skilled hand-object interactions has attracted significant attention over the past three decades. Nevertheless, two major gaps exist: a) how digit positions and forces are coordinated during natural manipulation tasks, and b) what mechanisms underlie the formation and retention of internal representations of dexterous manipulation. This dissertation addresses these two questions through five experiments that are based on novel grip devices and experimental protocols. It was found that high-level representation of manipulation tasks can be learned in an effector-independent fashion. Specifically, when challenged by trial-to-trial variability in finger positions or using digits that were not previously engaged in learning the task, subjects could adjust finger forces to compensate for this variability, thus leading to consistent task performance. The results from a follow-up experiment conducted in a virtual reality environment indicate that haptic feedback is sufficient to implement the above coordination between digit position and forces. However, it was also found that the generalizability of a learned manipulation is limited across tasks. Specifically, when subjects learned to manipulate the same object across different contexts that require different motor output, interference was found at the time of switching contexts. Data from additional studies provide evidence for parallel learning processes, which are characterized by different rates of decay and learning. These experiments have provided important insight into the neural mechanisms underlying learning and control of object manipulation. The present findings have potential biomedical applications including brain-machine interfaces, rehabilitation of hand function, and prosthetics.
ContributorsFu, Qiushi (Author) / Santello, Marco (Thesis advisor) / Helms Tillery, Stephen (Committee member) / Buneo, Christopher (Committee member) / Santos, Veronica (Committee member) / Artemiadis, Panagiotis (Committee member) / Arizona State University (Publisher)
Created2013
Description
High electron mobility transistors (HEMTs) based on Group III-nitride heterostructures have been characterized by advanced electron microscopy methods including off-axis electron holography, nanoscale chemical analysis, and electrical measurements, as well as other techniques. The dissertation was organized primarily into three topical areas: (1) characterization of near-gate defects in electrically stressed AlGaN/GaN HEMTs, (2) microstructural and chemical analysis of the gate/buffer interface of AlN/GaN HEMTs, and (3) studies of the impact of laser-liftoff processing on AlGaN/GaN HEMTs. The electrical performance of stressed AlGaN/GaN HEMTs was measured and the devices binned accordingly. Source- and drain-side degraded, undegraded, and unstressed devices were then prepared via focused-ion-beam milling for examination. Defects in the near-gate region were identified and their correlation to electrical measurements analyzed. Increased gate leakage after electrical stressing is typically attributed to "V"-shaped defects at the gate edge. However, strong evidence was found for gate metal diffusion into the barrier layer as another contributing factor. AlN/GaN HEMTs grown on sapphire substrates were found to have high electrical performance which is attributed to the AlN barrier layer, and robust ohmic and gate contact processes. TEM analysis identified oxidation at the gate metal/AlN buffer layer interface. This thin a-oxide gate insulator was further characterized by energy-dispersive x-ray spectroscopy and energy-filtered TEM. Attributed to this previously unidentified layer, high reverse gate bias up to −30 V was demonstrated and drain-induced gate leakage was suppressed to values of less than 10−6 A/mm. In addition, extrinsic gm and ft * LG were improved to the highest reported values for AlN/GaN HEMTs fabricated on sapphire substrates. Laser-liftoff (LLO) processing was used to separate the active layers from sapphire substrates for several GaN-based HEMT devices, including AlGaN/GaN and InAlN/GaN heterostructures. Warpage of the LLO samples resulted from relaxation of the as-grown strain and strain arising from dielectric and metal depositions, and this strain was quantified by both Newton's rings and Raman spectroscopy methods. TEM analysis demonstrated that the LLO processing produced no detrimental effects on the quality of the epitaxial layers. TEM micrographs showed no evidence of either damage to the ~2 μm GaN epilayer generated threading defects.
ContributorsJohnson, Michael R. (Author) / Mccartney, Martha R (Thesis advisor) / Smith, David J. (Committee member) / Goodnick, Stephen (Committee member) / Shumway, John (Committee member) / Chen, Tingyong (Committee member) / Arizona State University (Publisher)
Created2012
Description
Advances in implantable MEMS technology has made possible adaptive micro-robotic implants that can track and record from single neurons in the brain. Development of autonomous neural interfaces opens up exciting possibilities of micro-robots performing standard electrophysiological techniques that would previously take researchers several hundred hours to train and achieve the desired skill level. It would result in more reliable and adaptive neural interfaces that could record optimal neural activity 24/7 with high fidelity signals, high yield and increased throughput. The main contribution here is validating adaptive strategies to overcome challenges in autonomous navigation of microelectrodes inside the brain. The following issues pose significant challenges as brain tissue is both functionally and structurally dynamic: a) time varying mechanical properties of the brain tissue-microelectrode interface due to the hyperelastic, viscoelastic nature of brain tissue b) non-stationarities in the neural signal caused by mechanical and physiological events in the interface and c) the lack of visual feedback of microelectrode position in brain tissue. A closed loop control algorithm is proposed here for autonomous navigation of microelectrodes in brain tissue while optimizing the signal-to-noise ratio of multi-unit neural recordings. The algorithm incorporates a quantitative understanding of constitutive mechanical properties of soft viscoelastic tissue like the brain and is guided by models that predict stresses developed in brain tissue during movement of the microelectrode. An optimal movement strategy is developed that achieves precise positioning of microelectrodes in the brain by minimizing the stresses developed in the surrounding tissue during navigation and maximizing the speed of movement. Results of testing the closed-loop control paradigm in short-term rodent experiments validated that it was possible to achieve a consistently high quality SNR throughout the duration of the experiment. At the systems level, new generation of MEMS actuators for movable microelectrode array are characterized and the MEMS device operation parameters are optimized for improved performance and reliability. Further, recommendations for packaging to minimize the form factor of the implant; design of device mounting and implantation techniques of MEMS microelectrode array to enhance the longevity of the implant are also included in a top-down approach to achieve a reliable brain interface.
ContributorsAnand, Sindhu (Author) / Muthuswamy, Jitendran (Thesis advisor) / Tillery, Stephen H (Committee member) / Buneo, Christopher (Committee member) / Abbas, James (Committee member) / Tsakalis, Konstantinos (Committee member) / Arizona State University (Publisher)
Created2013
Description
The goal of this research work is to develop a particle-based device simulator for modeling strained silicon devices. Two separate modules had to be developed for that purpose: A generic bulk Monte Carlo simulation code which in the long-time limit solves the Boltzmann transport equation for electrons; and an extension to this code that solves for the bulk properties of strained silicon. One scattering table is needed for conventional silicon, whereas, because of the strain breaking the symmetry of the system, three scattering tables are needed for modeling strained silicon material. Simulation results for the average drift velocity and the average electron energy are in close agreement with published data. A Monte Carlo device simulation tool has also been employed to integrate the effects of self-heating into device simulation for Silicon on Insulator devices. The effects of different types of materials for buried oxide layers have been studied. Sapphire, Aluminum Nitride (AlN), Silicon dioxide (SiO2) and Diamond have been used as target materials of interest in the analysis and the effects of varying insulator layer thickness have also been investigated. It was observed that although AlN exhibits the best isothermal behavior, diamond is the best choice when thermal effects are accounted for.
ContributorsQazi, Suleman (Author) / Vasileska, Dragica (Thesis advisor) / Goodnick, Stephen (Committee member) / Tao, Meng (Committee member) / Arizona State University (Publisher)
Created2013
Description
GaAs-based solar cells have attracted much interest because of their high conversion efficiencies of ~28% under one sun illumination. The main carrier recombination mechanisms in the GaAs-based solar cells are surface recombination, radiative recombination and non-radiative recombination. Photon recycling reduces the effect of radiative recombination and is an approach to obtain the device performance described by detailed balance theory. The photon recycling model has been developed and was applied to investigate the loss mechanisms in the state-of-the-art GaAs-based solar cell structures using PC1D software. A standard fabrication process of the GaAs-based solar cells is as follows: wafer preparation, individual cell isolation by mesa, n- and p-type metallization, rapid thermal annealing (RTA), cap layer etching, and anti-reflection coating (ARC). The growth rate for GaAs-based materials is one of critical factors to determine the cost for the growth of GaAs-based solar cells. The cost for fabricating GaAs-based solar cells can be reduced if the growth rate is increased without degrading the crystalline quality. The solar cell wafers grown at different growth rates of 14 μm/hour and 55 μm/hour were discussed in this work. The structural properties of the wafers were characterized by X-ray diffraction (XRD) to identify the crystalline quality, and then the as-grown wafers were fabricated into solar cell devices under the same process conditions. The optical and electrical properties such as surface reflection, external quantum efficiency (EQE), dark I-V, Suns-Voc, and illuminated I-V under one sun using a solar simulator were measured to compare the performances of the solar cells with different growth rates. Some simulations in PC1D have been demonstrated to investigate the reasons of the different device performances between fast growth and slow growth structures. A further analysis of the minority carrier lifetime is needed to investigate into the difference in device performances.
ContributorsZhang, Chaomin (Author) / Honsberg, Christiana (Thesis advisor) / Goodnick, Stephen (Committee member) / Faleev, Nikolai (Committee member) / Arizona State University (Publisher)
Created2014
Description
Increasing the conversion efficiencies of photovoltaic (PV) cells beyond the single junction theoretical limit is the driving force behind much of third generation solar cell research. Over the last half century, the experimental conversion efficiency of both single junction and tandem solar cells has plateaued as manufacturers and researchers have optimized various materials and structures. While existing materials and technologies have remarkably good conversion efficiencies, they are approaching their own limits. For example, tandem solar cells are currently well developed commercially but further improvements through increasing the number of junctions struggle with various issues related to material interfacial defects. Thus, there is a need for novel theoretical and experimental approaches leading to new third generation cell structures. Multiple exciton generation (MEG) and intermediate band (IB) solar cells have been proposed as third generation alternatives and theoretical modeling suggests they can surpass the detailed balance efficiency limits of single junction and tandem solar cells. MEG or IB solar cell has a variety of advantages enabling the use of low bandgap materials. Integrating MEG and IB with other cell types to make novel solar cells (such as MEG with tandem, IB with tandem or MEG with IB) potentially offers improvements by employing multi-physics effects in one device. This hybrid solar cell should improve the properties of conventional solar cells with a reduced number of junction, increased light-generated current and extended material selections. These multi-physics effects in hybrid solar cells can be achieved through the use of nanostructures taking advantage of the carrier confinement while using existing solar cell materials with excellent characteristics. This reduces the additional cost to develop novel materials and structures. In this dissertation, the author develops thermodynamic models for several novel types of solar cells and uses these models to optimize and compare their properties to those of existing PV cells. The results demonstrate multiple advantages from combining MEG and IB technology with existing solar cell structures.
ContributorsLee, Jongwon (Author) / Honsberg, C. (Christiana B.) (Thesis advisor) / Bowden, Stuart (Committee member) / Roedel, Ronald (Committee member) / Goodnick, Stephen (Committee member) / Schroder, Dieter (Committee member) / Arizona State University (Publisher)
Created2014