This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.

Displaying 1 - 10 of 61
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Description
Doppler radar can be used to measure respiration and heart rate without contact and through obstacles. In this work, a Doppler radar architecture at 2.4 GHz and a new signal processing algorithm to estimate the respiration and heart rate are presented. The received signal is dominated by the transceiver noise,

Doppler radar can be used to measure respiration and heart rate without contact and through obstacles. In this work, a Doppler radar architecture at 2.4 GHz and a new signal processing algorithm to estimate the respiration and heart rate are presented. The received signal is dominated by the transceiver noise, LO phase noise and clutter which reduces the signal-to-noise ratio of the desired signal. The proposed architecture and algorithm are used to mitigate these issues and obtain an accurate estimate of the heart and respiration rate. Quadrature low-IF transceiver architecture is adopted to resolve null point problem as well as avoid 1/f noise and DC offset due to mixer-LO coupling. Adaptive clutter cancellation algorithm is used to enhance receiver sensitivity coupled with a novel Pattern Search in Noise Subspace (PSNS) algorithm is used to estimate respiration and heart rate. PSNS is a modified MUSIC algorithm which uses the phase noise to enhance Doppler shift detection. A prototype system was implemented using off-the-shelf TI and RFMD transceiver and tests were conduct with eight individuals. The measured results shows accurate estimate of the cardio pulmonary signals in low-SNR conditions and have been tested up to a distance of 6 meters.
ContributorsKhunti, Hitesh Devshi (Author) / Kiaei, Sayfe (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Bliss, Daniel (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Integrated photonics requires high gain optical materials in the telecom wavelength range for optical amplifiers and coherent light sources. Erbium (Er) containing materials are ideal candidates due to the 1.5 μm emission from Er3+ ions. However, the Er density in typical Er-doped materials is less than 1 x 1020 cm-3,

Integrated photonics requires high gain optical materials in the telecom wavelength range for optical amplifiers and coherent light sources. Erbium (Er) containing materials are ideal candidates due to the 1.5 μm emission from Er3+ ions. However, the Er density in typical Er-doped materials is less than 1 x 1020 cm-3, thus limiting the maximum optical gain to a few dB/cm, too small to be useful for integrated photonics applications. Er compounds could potentially solve this problem since they contain much higher Er density. So far the existing Er compounds suffer from short lifetime and strong upconversion effects, mainly due to poor quality of crystals produced by various methods of thin film growth and deposition. This dissertation explores a new Er compound: erbium chloride silicate (ECS, Er3(SiO4)2Cl ) in the nanowire form, which facilitates the growth of high quality single crystals. Growth methods for such single crystal ECS nanowires have been established. Various structural and optical characterizations have been carried out. The high crystal quality of ECS material leads to a long lifetime of the first excited state of Er3+ ions up to 1 ms at Er density higher than 1022 cm-3. This Er lifetime-density product was found to be the largest among all Er containing materials. A unique integrating sphere method was developed to measure the absorption cross section of ECS nanowires from 440 to 1580 nm. Pump-probe experiments demonstrated a 644 dB/cm signal enhancement from a single ECS wire. It was estimated that such large signal enhancement can overcome the absorption to result in a net material gain, but not sufficient to compensate waveguide propagation loss. In order to suppress the upconversion process in ECS, Ytterbium (Yb) and Yttrium (Y) ions are introduced as substituent ions of Er in the ECS crystal structure to reduce Er density. While the addition of Yb ions only partially succeeded, erbium yttrium chloride silicate (EYCS) with controllable Er density was synthesized successfully. EYCS with 30 at. % Er was found to be the best. It shows the strongest PL emission at 1.5 μm, and thus can be potentially used as a high gain material.
ContributorsYin, Leijun (Author) / Ning, Cun-Zheng (Thesis advisor) / Chamberlin, Ralph (Committee member) / Yu, Hongbin (Committee member) / Menéndez, Jose (Committee member) / Ponce, Fernando (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Electrical neural activity detection and tracking have many applications in medical research and brain computer interface technologies. In this thesis, we focus on the development of advanced signal processing algorithms to track neural activity and on the mapping of these algorithms onto hardware to enable real-time tracking. At the heart

Electrical neural activity detection and tracking have many applications in medical research and brain computer interface technologies. In this thesis, we focus on the development of advanced signal processing algorithms to track neural activity and on the mapping of these algorithms onto hardware to enable real-time tracking. At the heart of these algorithms is particle filtering (PF), a sequential Monte Carlo technique used to estimate the unknown parameters of dynamic systems. First, we analyze the bottlenecks in existing PF algorithms, and we propose a new parallel PF (PPF) algorithm based on the independent Metropolis-Hastings (IMH) algorithm. We show that the proposed PPF-IMH algorithm improves the root mean-squared error (RMSE) estimation performance, and we demonstrate that a parallel implementation of the algorithm results in significant reduction in inter-processor communication. We apply our implementation on a Xilinx Virtex-5 field programmable gate array (FPGA) platform to demonstrate that, for a one-dimensional problem, the PPF-IMH architecture with four processing elements and 1,000 particles can process input samples at 170 kHz by using less than 5% FPGA resources. We also apply the proposed PPF-IMH to waveform-agile sensing to achieve real-time tracking of dynamic targets with high RMSE tracking performance. We next integrate the PPF-IMH algorithm to track the dynamic parameters in neural sensing when the number of neural dipole sources is known. We analyze the computational complexity of a PF based method and propose the use of multiple particle filtering (MPF) to reduce the complexity. We demonstrate the improved performance of MPF using numerical simulations with both synthetic and real data. We also propose an FPGA implementation of the MPF algorithm and show that the implementation supports real-time tracking. For the more realistic scenario of automatically estimating an unknown number of time-varying neural dipole sources, we propose a new approach based on the probability hypothesis density filtering (PHDF) algorithm. The PHDF is implemented using particle filtering (PF-PHDF), and it is applied in a closed-loop to first estimate the number of dipole sources and then their corresponding amplitude, location and orientation parameters. We demonstrate the improved tracking performance of the proposed PF-PHDF algorithm and map it onto a Xilinx Virtex-5 FPGA platform to show its real-time implementation potential. Finally, we propose the use of sensor scheduling and compressive sensing techniques to reduce the number of active sensors, and thus overall power consumption, of electroencephalography (EEG) systems. We propose an efficient sensor scheduling algorithm which adaptively configures EEG sensors at each measurement time interval to reduce the number of sensors needed for accurate tracking. We combine the sensor scheduling method with PF-PHDF and implement the system on an FPGA platform to achieve real-time tracking. We also investigate the sparsity of EEG signals and integrate compressive sensing with PF to estimate neural activity. Simulation results show that both sensor scheduling and compressive sensing based methods achieve comparable tracking performance with significantly reduced number of sensors.
ContributorsMiao, Lifeng (Author) / Chakrabarti, Chaitali (Thesis advisor) / Papandreou-Suppappola, Antonia (Thesis advisor) / Zhang, Junshan (Committee member) / Bliss, Daniel (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2013
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Description
In this dissertation, remote plasma interactions with the surfaces of low-k interlayer dielectric (ILD), Cu and Cu adhesion layers are investigated. The first part of the study focuses on the simultaneous plasma treatment of ILD and chemical mechanical polishing (CMP) Cu surfaces using N2/H2 plasma processes. H atoms and radicals

In this dissertation, remote plasma interactions with the surfaces of low-k interlayer dielectric (ILD), Cu and Cu adhesion layers are investigated. The first part of the study focuses on the simultaneous plasma treatment of ILD and chemical mechanical polishing (CMP) Cu surfaces using N2/H2 plasma processes. H atoms and radicals in the plasma react with the carbon groups leading to carbon removal for the ILD films. Results indicate that an N2 plasma forms an amide-like layer on the surface which apparently leads to reduced carbon abstraction from an H2 plasma process. In addition, FTIR spectra indicate the formation of hydroxyl (Si-OH) groups following the plasma exposure. Increased temperature (380 °C) processing leads to a reduction of the hydroxyl group formation compared to ambient temperature processes, resulting in reduced changes of the dielectric constant. For CMP Cu surfaces, the carbonate contamination was removed by an H2 plasma process at elevated temperature while the C-C and C-H contamination was removed by an N2 plasma process at elevated temperature. The second part of this study examined oxide stability and cleaning of Ru surfaces as well as consequent Cu film thermal stability with the Ru layers. The ~2 monolayer native Ru oxide was reduced after H-plasma processing. The thermal stability or islanding of the Cu film on the Ru substrate was characterized by in-situ XPS. After plasma cleaning of the Ru adhesion layer, the deposited Cu exhibited full coverage. In contrast, for Cu deposition on the Ru native oxide substrate, Cu islanding was detected and was described in terms of grain boundary grooving and surface and interface energies. The thermal stability of 7 nm Ti, Pt and Ru ii interfacial adhesion layers between a Cu film (10 nm) and a Ta barrier layer (4 nm) have been investigated in the third part. The barrier properties and interfacial stability have been evaluated by Rutherford backscattering spectrometry (RBS). Atomic force microscopy (AFM) was used to measure the surfaces before and after annealing, and all the surfaces are relatively smooth excluding islanding or de-wetting phenomena as a cause of the instability. The RBS showed no discernible diffusion across the adhesion layer/Ta and Ta/Si interfaces which provides a stable underlying layer. For a Ti interfacial layer RBS indicates that during 400 °C annealing Ti interdiffuses through the Cu film and accumulates at the surface. For the Pt/Cu system Pt interdiffuion is detected which is less evident than Ti. Among the three adhesion layer candidates, Ru shows negligible diffusion into the Cu film indicating thermal stability at 400 °C.
ContributorsLiu, Xin (Author) / Nemanich, Robert (Thesis advisor) / Chamberlin, Ralph (Committee member) / Chen, Tingyong (Committee member) / Smith, David (Committee member) / Ponce, Fernando (Committee member) / Arizona State University (Publisher)
Created2012
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Description
In this dissertation, the interface chemistry and electronic structure of plasma-enhanced atomic layer deposited (PEALD) dielectrics on GaN are investigated with x-ray and ultraviolet photoemission spectroscopy (XPS and UPS). Three interrelated issues are discussed in this study: (1) PEALD dielectric growth process optimization, (2) interface electronic structure of comparative PEALD

In this dissertation, the interface chemistry and electronic structure of plasma-enhanced atomic layer deposited (PEALD) dielectrics on GaN are investigated with x-ray and ultraviolet photoemission spectroscopy (XPS and UPS). Three interrelated issues are discussed in this study: (1) PEALD dielectric growth process optimization, (2) interface electronic structure of comparative PEALD dielectrics on GaN, and (3) interface electronic structure of PEALD dielectrics on Ga- and N-face GaN. The first study involved an in-depth case study of PEALD Al2O3 growth using dimethylaluminum isopropoxide, with a special focus on oxygen plasma effects. Saturated and self-limiting growth of Al2O3 films were obtained with an enhanced growth rate within the PEALD temperature window (25-220 ºC). The properties of Al2O3 deposited at various temperatures were characterized to better understand the relation between the growth parameters and film properties. In the second study, the interface electronic structures of PEALD dielectrics on Ga-face GaN films were measured. Five promising dielectrics (Al2O3, HfO2, SiO2, La2O3, and ZnO) with a range of band gap energies were chosen. Prior to dielectric growth, a combined wet chemical and in-situ H2/N2 plasma clean process was employed to remove the carbon contamination and prepare the surface for dielectric deposition. The surface band bending and band offsets were measured by XPS and UPS for dielectrics on GaN. The trends of the experimental band offsets on GaN were related to the dielectric band gap energies. In addition, the experimental band offsets were near the calculated values based on the charge neutrality level model. The third study focused on the effect of the polarization bound charge of the Ga- and N-face GaN on interface electronic structures. A surface pretreatment process consisting of a NH4OH wet chemical and an in-situ NH3 plasma treatment was applied to remove carbon contamination, retain monolayer oxygen coverage, and potentially passivate N-vacancy related defects. The surface band bending and polarization charge compensation of Ga- and N-face GaN were investigated. The surface band bending and band offsets were determined for Al2O3, HfO2, and SiO2 on Ga- and N-face GaN. Different dielectric thicknesses and post deposition processing were investigated to understand process related defect formation and/or reduction.
ContributorsYang, Jialing (Author) / Nemanich, Robert J (Thesis advisor) / Chen, Tingyong (Committee member) / Peng, Xihong (Committee member) / Ponce, Fernando (Committee member) / Smith, David (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Immunosignaturing is a medical test for assessing the health status of a patient by applying microarrays of random sequence peptides to determine the patient's immune fingerprint by associating antibodies from a biological sample to immune responses. The immunosignature measurements can potentially provide pre-symptomatic diagnosis for infectious diseases or detection of

Immunosignaturing is a medical test for assessing the health status of a patient by applying microarrays of random sequence peptides to determine the patient's immune fingerprint by associating antibodies from a biological sample to immune responses. The immunosignature measurements can potentially provide pre-symptomatic diagnosis for infectious diseases or detection of biological threats. Currently, traditional bioinformatics tools, such as data mining classification algorithms, are used to process the large amount of peptide microarray data. However, these methods generally require training data and do not adapt to changing immune conditions or additional patient information. This work proposes advanced processing techniques to improve the classification and identification of single and multiple underlying immune response states embedded in immunosignatures, making it possible to detect both known and previously unknown diseases or biothreat agents. Novel adaptive learning methodologies for un- supervised and semi-supervised clustering integrated with immunosignature feature extraction approaches are proposed. The techniques are based on extracting novel stochastic features from microarray binding intensities and use Dirichlet process Gaussian mixture models to adaptively cluster the immunosignatures in the feature space. This learning-while-clustering approach allows continuous discovery of antibody activity by adaptively detecting new disease states, with limited a priori disease or patient information. A beta process factor analysis model to determine underlying patient immune responses is also proposed to further improve the adaptive clustering performance by formatting new relationships between patients and antibody activity. In order to extend the clustering methods for diagnosing multiple states in a patient, the adaptive hierarchical Dirichlet process is integrated with modified beta process factor analysis latent feature modeling to identify relationships between patients and infectious agents. The use of Bayesian nonparametric adaptive learning techniques allows for further clustering if additional patient data is received. Significant improvements in feature identification and immune response clustering are demonstrated using samples from patients with different diseases.
ContributorsMalin, Anna (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Bliss, Daniel (Committee member) / Chakrabarti, Chaitali (Committee member) / Kovvali, Narayan (Committee member) / Lacroix, Zoé (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This dissertation introduces stochastic ordering of instantaneous channel powers of fading channels as a general method to compare the performance of a communication system over two different channels, even when a closed-form expression for the metric may not be available. Such a comparison is with respect to a variety of

This dissertation introduces stochastic ordering of instantaneous channel powers of fading channels as a general method to compare the performance of a communication system over two different channels, even when a closed-form expression for the metric may not be available. Such a comparison is with respect to a variety of performance metrics such as error rates, outage probability and ergodic capacity, which share common mathematical properties such as monotonicity, convexity or complete monotonicity. Complete monotonicity of a metric, such as the symbol error rate, in conjunction with the stochastic Laplace transform order between two fading channels implies the ordering of the two channels with respect to the metric. While it has been established previously that certain modulation schemes have convex symbol error rates, there is no study of the complete monotonicity of the same, which helps in establishing stronger channel ordering results. Toward this goal, the current research proves for the first time, that all 1-dimensional and 2-dimensional modulations have completely monotone symbol error rates. Furthermore, it is shown that the frequently used parametric fading distributions for modeling line of sight exhibit a monotonicity in the line of sight parameter with respect to the Laplace transform order. While the Laplace transform order can also be used to order fading distributions based on the ergodic capacity, there exist several distributions which are not Laplace transform ordered, although they have ordered ergodic capacities. To address this gap, a new stochastic order called the ergodic capacity order has been proposed herein, which can be used to compare channels based on the ergodic capacity. Using stochastic orders, average performance of systems involving multiple random variables are compared over two different channels. These systems include diversity combining schemes, relay networks, and signal detection over fading channels with non-Gaussian additive noise. This research also addresses the problem of unifying fading distributions. This unification is based on infinite divisibility, which subsumes almost all known fading distributions, and provides simplified expressions for performance metrics, in addition to enabling stochastic ordering.
ContributorsRajan, Adithya (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Bliss, Daniel (Committee member) / Kosut, Oliver (Committee member) / Arizona State University (Publisher)
Created2014
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Description
In this dissertation, combined photo-induced and thermionic electron emission from low work function diamond films is studied through low energy electron spectroscopy analysis and other associated techniques. Nitrogen-doped, hydrogen-terminated diamond films prepared by the microwave plasma chemical vapor deposition method have been the most focused material. The theme of this

In this dissertation, combined photo-induced and thermionic electron emission from low work function diamond films is studied through low energy electron spectroscopy analysis and other associated techniques. Nitrogen-doped, hydrogen-terminated diamond films prepared by the microwave plasma chemical vapor deposition method have been the most focused material. The theme of this research is represented by four interrelated issues. (1) An in-depth study describes combined photo-induced and thermionic emission from nitrogen-doped diamond films on molybdenum substrates, which were illuminated with visible light photons, and the electron emission spectra were recorded as a function of temperature. The diamond films displayed significant emissivity with a low work function of ~ 1.5 eV. The results indicate that these diamond emitters can be applied in combined solar and thermal energy conversion. (2) The nitrogen-doped diamond was further investigated to understand the physical mechanism and material-related properties that enable the combined electron emission. Through analysis of the spectroscopy, optical absorbance and photoelectron microscopy results from sample sets prepared with different configurations, it was deduced that the photo-induced electron generation involves both the ultra-nanocrystalline diamond and the interface between the diamond film and metal substrate. (3) Based on results from the first two studies, possible photon-enhanced thermionic emission was examined from nitrogen-doped diamond films deposited on silicon substrates, which could provide the basis for a novel approach for concentrated solar energy conversion. A significant increase of emission intensity was observed at elevated temperatures, which was analyzed using computer-based modeling and a combination of different emission mechanisms. (4) In addition, the electronic structure of vanadium-oxide-terminated diamond surfaces was studied through in-situ photoemission spectroscopy. Thin layers of vanadium were deposited on oxygen-terminated diamond surfaces which led to oxide formation. After thermal annealing, a negative electron affinity was found on boron-doped diamond, while a positive electron affinity was found on nitrogen-doped diamond. A model based on the barrier at the diamond-oxide interface was employed to analyze the results. Based on results of this dissertation, applications of diamond-based energy conversion devices for combined solar- and thermal energy conversion are proposed.
ContributorsSun, Tianyin (Author) / Nemanich, Robert (Thesis advisor) / Ponce, Fernando (Committee member) / Peng, Xihong (Committee member) / Spence, John (Committee member) / Treacy, Michael (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This thesis describes the fabrication of several new classes of Ge1-x-ySixSny materials with the required compositions and crystal quality to engineer the band gaps above and below that of elemental Ge (0.8 eV) in the near IR. The work initially focused on Ge1-x-ySixSny (1-5% Sn, 4-20% Si) materials grown on

This thesis describes the fabrication of several new classes of Ge1-x-ySixSny materials with the required compositions and crystal quality to engineer the band gaps above and below that of elemental Ge (0.8 eV) in the near IR. The work initially focused on Ge1-x-ySixSny (1-5% Sn, 4-20% Si) materials grown on Ge(100) via gas-source epitaxy of Ge4H10, Si4H10 and SnD4. Both intrinsic and doped layers were produced with defect-free microstructure and viable thickness, allowing the fabrication of high-performance photodetectors. These exhibited low ideality factors, state-of-the-art dark current densities and adjustable absorption edges between 0.87 and 1.03 eV, indicating that the band gaps span a significant range above that of Ge. Next Sn-rich Ge1-x-ySixSny alloys (2-4% Si and 4-10% Sn) were fabricated directly on Si and were found to show significant optical emission using photoluminescence measurements, indicating that the alloys have direct band gaps below that of pure Ge in the range of 0.7-0.55 eV. A series of Sn-rich Ge1-x-ySixSny analogues (y>x) with fixed 3-4% Si content and progressively increasing Sn content in the 4-10% range were then grown on Ge buffered Si platforms for the purpose of improving the material's crystal quality. The films in this case exhibited lower defect densities than those grown on Si, allowing a meaningful study of both the direct and indirect gaps. The results show that the separation of the direct and indirect edges can be made smaller than in Ge even for non-negligible 3-4% Si content, confirming that with a suitable choice of Sn compositions the ternary Ge1-x-ySixSny reproduces all features of the electronic structure of binary Ge1-ySny, including the sought-after indirect-to-direct gap cross over. The above synthesis of optical quality Ge1-x-ySixSny on virtual Ge was made possible by the development of high quality Ge-on-Si buffers via chemical vapor deposition of Ge4H10. The resultant films exhibited structural and electrical properties significantly improved relative to state-of-the-art results obtained using conventional approaches. It was found that pure Ge4H10 facilitates the control of residual doping and enables p-i-n devices whose dark currents are not entirely determined by defects and whose zero-bias collection efficiencies are higher than those obtained from samples fabricated using alternative Ge-on-Si approaches.
ContributorsXu, Chi (Author) / Kouvetakis, John (Thesis advisor) / Menéndez, Jose (Thesis advisor) / Chizmeshya, Andrew (Committee member) / Drucker, Jeffrey (Committee member) / Ponce, Fernando (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The initial microstructure of oxide fuel pellets can play a key role in their performance. At low burnups, the transport of fission products has a strong dependence on oxygen content, grain size distribution, porosity and grain boundary (GB) characteristics (crystallography, geometry and topology), all of which, in turn depend on

The initial microstructure of oxide fuel pellets can play a key role in their performance. At low burnups, the transport of fission products has a strong dependence on oxygen content, grain size distribution, porosity and grain boundary (GB) characteristics (crystallography, geometry and topology), all of which, in turn depend on processing conditions. These microstructural features can also affect the fuel densification, thermal conductivity and microstructure evolution inside the reactor. Understanding these effects can provide insight into microstructure evolution of fuels in-pile. In this work, mechanical and ion beam serial sectioning techniques were developed to obtain Electron Backscatter Diffraction (EBSD) data, both in 2-D and 3-D, for depleted UO2+X pellets manufactured under different conditions. The EBSD maps were used to relate processing conditions to microstructural features, with emphasis on special GBs according to the Coincident Site Lattice (CSL) model, as well as correlations between pore size and location in the microstructure. Furthermore, larger grains (at least 2.5 times the average grain size) were observed in all the samples and studied. Results indicate that larger grains, in samples manufactured under different conditions, dominate the overall crystallographic texture and have a fairly strong GB texture. Moreover, it seems that the preferential misorientation axis for these GBs, regardless of the O/M, is {001}. These results might be related to GB energy and structure and, suggest that the mechanism that controls grain growth seems to be independent of both processing conditions and stoichiometry. Additionally, a sample was heat treated to relate grain growth and crystallography. The results indicate that at least two mechanisms were involved. Lengthening of GBs was observed for larger grains. Another mechanism of grain growth was observed, in this case, grains rotate to match a neighboring grain forming a larger grain. In the new grain, the misorientation between the two neighboring grains decreases to less than 5 degrees, forming a new larger grain. The results presented in this work indicate that detailed studies of the initial microstructure of the fuel, with emphasis on the crystallography of grains and GBs could help to give insights on the in-pile microstructural evolution of the fuel.
ContributorsRudman Prieto, Karin (Author) / Peralta, Pedro (Thesis advisor) / Ponce, Fernando (Committee member) / Sieradski, Karl (Committee member) / Arizona State University (Publisher)
Created2014