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- Genre: Doctoral Dissertation
- Creators: Xue, Guoliang
Description
Emission of CO2 into the atmosphere has become an increasingly concerning issue as we progress into the 21st century Flue gas from coal-burning power plants accounts for 40% of all carbon dioxide emissions. The key to successful separation and sequestration is to separate CO2 directly from flue gas (10-15% CO2, 70% N2), which can range from a few hundred to as high as 1000°C. Conventional microporous membranes (carbons/silicas/zeolites) are capable of separating CO2 from N2 at low temperatures, but cannot achieve separation above 200°C. To overcome the limitations of microporous membranes, a novel ceramic-carbonate dual-phase membrane for high temperature CO2 separation was proposed. The membrane was synthesized from porous La0.6Sr0.4Co0.8Fe0.2O3-d (LSCF) supports and infiltrated with molten carbonate (Li2CO3/Na2CO3/K2CO3). The CO2 permeation mechanism involves a reaction between CO2 (gas phase) and O= (solid phase) to form CO3=, which is then transported through the molten carbonate (liquid phase) to achieve separation. The effects of membrane thickness, temperature and CO2 partial pressure were studied. Decreasing thickness from 3.0 to 0.375 mm led to higher fluxes at 900°C, ranging from 0.186 to 0.322 mL.min-1.cm-2 respectively. CO2 flux increased with temperature from 700 to 900°C. Activation energy for permeation was similar to that for oxygen ion conduction in LSCF. For partial pressures above 0.05 atm, the membrane exhibited a nearly constant flux. From these observations, it was determined that oxygen ion conductivity limits CO2 permeation and that the equilibrium oxygen vacancy concentration in LSCF is dependent on the partial pressure of CO2 in the gas phase. Finally, the dual-phase membrane was used as a membrane reactor. Separation at high temperatures can produce warm, highly concentrated streams of CO2 that could be used as a chemical feedstock for the synthesis of syngas (H2 + CO). Towards this, three different membrane reactor configurations were examined: 1) blank system, 2) LSCF catalyst and 3) 10% Ni/y-alumina catalyst. Performance increased in the order of blank system < LSCF catalyst < Ni/y-alumina catalyst. Favorable conditions for syngas production were high temperature (850°C), low sweep gas flow rate (10 mL.min-1) and high methane concentration (50%) using the Ni/y-alumina catalyst.
ContributorsAnderson, Matthew Brandon (Author) / Lin, Jerry (Thesis advisor) / Alford, Terry (Committee member) / Rege, Kaushal (Committee member) / Anderson, James (Committee member) / Rivera, Daniel (Committee member) / Arizona State University (Publisher)
Created2011
Description
One necessary condition for the two-pass risk premium estimator to be consistent and asymptotically normal is that the rank of the beta matrix in a proposed linear asset pricing model is full column. I first investigate the asymptotic properties of the risk premium estimators and the related t-test and Wald test statistics when the full rank condition fails. I show that the beta risk of useless factors or multiple proxy factors for a true factor are priced more often than they should be at the nominal size in the asset pricing models omitting some true factors. While under the null hypothesis that the risk premiums of the true factors are equal to zero, the beta risk of the true factors are priced less often than the nominal size. The simulation results are consistent with the theoretical findings. Hence, the factor selection in a proposed factor model should not be made solely based on their estimated risk premiums. In response to this problem, I propose an alternative estimation of the underlying factor structure. Specifically, I propose to use the linear combination of factors weighted by the eigenvectors of the inner product of estimated beta matrix. I further propose a new method to estimate the rank of the beta matrix in a factor model. For this method, the idiosyncratic components of asset returns are allowed to be correlated both over different cross-sectional units and over different time periods. The estimator I propose is easy to use because it is computed with the eigenvalues of the inner product of an estimated beta matrix. Simulation results show that the proposed method works well even in small samples. The analysis of US individual stock returns suggests that there are six common risk factors in US individual stock returns among the thirteen factor candidates used. The analysis of portfolio returns reveals that the estimated number of common factors changes depending on how the portfolios are constructed. The number of risk sources found from the analysis of portfolio returns is generally smaller than the number found in individual stock returns.
ContributorsWang, Na (Author) / Ahn, Seung C. (Thesis advisor) / Kallberg, Jarl G. (Committee member) / Liu, Crocker H. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Thin films of ever reducing thickness are used in a plethora of applications and their performance is highly dependent on their microstructure. Computer simulations could then play a vital role in predicting the microstructure of thin films as a function of processing conditions. FACET is one such software tool designed by our research group to model polycrystalline thin film growth, including texture evolution and grain growth of polycrystalline films in 2D. Several modifications to the original FACET code were done to enhance its usability and accuracy. Simulations of sputtered silver thin films are presented here with FACET 2.0 with qualitative and semi-quantitative comparisons with previously published experimental results. Comparisons of grain size, texture and film thickness between simulations and experiments are presented which describe growth modes due to various deposition factors like flux angle and substrate temperature. These simulations provide reasonable agreement with the experimental data over a diverse range of process parameters. Preliminary experiments in depositions of Silver films are also attempted with varying substrates and thickness in order to generate complementary experimental and simulation studies of microstructure evolution. Overall, based on the comparisons, FACET provides interesting insights into thin film growth processes, and the effects of various deposition conditions on thin film structure and microstructure. Lastly, simple molecular dynamics simulations of deposition on bi-crystals are attempted for gaining insight into texture based grain competition during film growth. These simulations predict texture based grain coarsening mechanisms like twinning and grain boundary migration that have been commonly reported in FCC films.
ContributorsRairkar, Asit (Author) / Adams, James B (Thesis advisor) / Krause, Stephen (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2011
Description
Programmable metallization cell (PMC) technology is based on an electrochemical phenomenon in which a metallic electrodeposit can be grown or dissolved between two electrodes depending on the voltage applied between them. Devices based on this phenomenon exhibit a unique, self-healing property, as a broken metallic structure can be healed by applying an appropriate voltage between the two broken ends. This work explores methods of fabricating interconnects and switches based on PMC technology on flexible substrates. The objective was the evaluation of the feasibility of using this technology in flexible electronics applications in which reliability is a primary concern. The re-healable property of the interconnect is characterized for the silver doped germanium selenide (Ag-Ge-Se) solid electrolyte system. This property was evaluated by measuring the resistances of the healed interconnect structures and comparing these to the resistances of the unbroken structures. The reliability of the interconnects in both unbroken and healed states is studied by investigating the resistances of the structures to DC voltages, AC voltages and different temperatures as a function of time. This work also explores replacing silver with copper for these interconnects to enhance their reliability. A model for PMC-based switches on flexible substrates is proposed and compared to the observed device behavior with the objective of developing a formal design methodology for these devices. The switches were subjected to voltage sweeps and their resistance was investigated as a function of sweep voltage. The resistance of the switches as a function of voltage pulse magnitude when placed in series with a resistance was also investigated. A model was then developed to explain the behavior of these devices. All observations were based on statistical measurements to account for random errors. The results of this work demonstrate that solid electrolyte based interconnects display self-healing capability, which depends on the applied healing voltage and the current limit. However, they fail at lower current densities than metal interconnects due to an ion-drift induced failure mechanism. The results on the PMC based switches demonstrate that a model comprising a Schottky diode in parallel with a variable resistor predicts the behavior of the device.
ContributorsBaliga, Sunil Ravindranath (Author) / Kozicki, Michael N (Thesis advisor) / Schroder, Dieter K. (Committee member) / Chae, Junseok (Committee member) / Alford, Terry L. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Multi-task learning (MTL) aims to improve the generalization performance (of the resulting classifiers) by learning multiple related tasks simultaneously. Specifically, MTL exploits the intrinsic task relatedness, based on which the informative domain knowledge from each task can be shared across multiple tasks and thus facilitate the individual task learning. It is particularly desirable to share the domain knowledge (among the tasks) when there are a number of related tasks but only limited training data is available for each task. Modeling the relationship of multiple tasks is critical to the generalization performance of the MTL algorithms. In this dissertation, I propose a series of MTL approaches which assume that multiple tasks are intrinsically related via a shared low-dimensional feature space. The proposed MTL approaches are developed to deal with different scenarios and settings; they are respectively formulated as mathematical optimization problems of minimizing the empirical loss regularized by different structures. For all proposed MTL formulations, I develop the associated optimization algorithms to find their globally optimal solution efficiently. I also conduct theoretical analysis for certain MTL approaches by deriving the globally optimal solution recovery condition and the performance bound. To demonstrate the practical performance, I apply the proposed MTL approaches on different real-world applications: (1) Automated annotation of the Drosophila gene expression pattern images; (2) Categorization of the Yahoo web pages. Our experimental results demonstrate the efficiency and effectiveness of the proposed algorithms.
ContributorsChen, Jianhui (Author) / Ye, Jieping (Thesis advisor) / Kumar, Sudhir (Committee member) / Liu, Huan (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2011
Description
Chalcogenide glass (ChG) materials have gained wide attention because of their applications in conductive bridge random access memory (CBRAM), phase change memories (PC-RAM), optical rewritable disks (CD-RW and DVD-RW), microelectromechanical systems (MEMS), microfluidics, and optical communications. One of the significant properties of ChG materials is the change in the resistivity of the material when a metal such as Ag or Cu is added to it by diffusion. This study demonstrates the potential radiation-sensing capabilities of two metal/chalcogenide glass device configurations. Lateral and vertical device configurations sense the radiation-induced migration of Ag+ ions in germanium selenide glasses via changes in electrical resistance between electrodes on the ChG. Before irradiation, these devices exhibit a high-resistance `OFF-state' (in the order of 10E12) but following irradiation, with either 60-Co gamma-rays or UV light, their resistance drops to a low-resistance `ON-state' (around 10E3). Lateral devices have exhibited cyclical recovery with room temperature annealing of the Ag doped ChG, which suggests potential uses in reusable radiation sensor applications. The feasibility of producing inexpensive flexible radiation sensors has been demonstrated by studying the effects of mechanical strain and temperature stress on sensors formed on flexible polymer substrate. The mechanisms of radiation-induced Ag/Ag+ transport and reactions in ChG have been modeled using a finite element device simulator, ATLAS. The essential reactions captured by the simulator are radiation-induced carrier generation, combined with reduction/oxidation for Ag species in the chalcogenide film. Metal-doped ChGs are solid electrolytes that have both ionic and electronic conductivity. The ChG based Programmable Metallization Cell (PMC) is a technology platform that offers electric field dependent resistance switching mechanisms by formation and dissolution of nano sized conductive filaments in a ChG solid electrolyte between oxidizable and inert electrodes. This study identifies silver anode agglomeration in PMC devices following large radiation dose exposure and considers device failure mechanisms via electrical and material characterization. The results demonstrate that by changing device structural parameters, silver agglomeration in PMC devices can be suppressed and reliable resistance switching may be maintained for extremely high doses ranging from 4 Mrad(GeSe) to more than 10 Mrad (ChG).
ContributorsDandamudi, Pradeep (Author) / Kozicki, Michael N (Thesis advisor) / Barnaby, Hugh J (Committee member) / Holbert, Keith E. (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2013
Description
Sparsity has become an important modeling tool in areas such as genetics, signal and audio processing, medical image processing, etc. Via the penalization of l-1 norm based regularization, the structured sparse learning algorithms can produce highly accurate models while imposing various predefined structures on the data, such as feature groups or graphs. In this thesis, I first propose to solve a sparse learning model with a general group structure, where the predefined groups may overlap with each other. Then, I present three real world applications which can benefit from the group structured sparse learning technique. In the first application, I study the Alzheimer's Disease diagnosis problem using multi-modality neuroimaging data. In this dataset, not every subject has all data sources available, exhibiting an unique and challenging block-wise missing pattern. In the second application, I study the automatic annotation and retrieval of fruit-fly gene expression pattern images. Combined with the spatial information, sparse learning techniques can be used to construct effective representation of the expression images. In the third application, I present a new computational approach to annotate developmental stage for Drosophila embryos in the gene expression images. In addition, it provides a stage score that enables one to more finely annotate each embryo so that they are divided into early and late periods of development within standard stage demarcations. Stage scores help us to illuminate global gene activities and changes much better, and more refined stage annotations improve our ability to better interpret results when expression pattern matches are discovered between genes.
ContributorsYuan, Lei (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Xue, Guoliang (Committee member) / Kumar, Sudhir (Committee member) / Arizona State University (Publisher)
Created2013
Description
ABSTRACT Along with the fast development of science and technology, the studied materials are becoming more complicated and smaller. All these achievements have advanced with the fast development of powerful tools currently, such as Scanning electron microscopy (SEM), Focused Ion Beam (FIB), Transmission electron microscopy (TEM), Energy dispersive X-ray spectroscopy (EDX), Electron energy loss spectroscopy (EELS) and so on. SiTiO3 thin film, which is grown on Si (100) single crystals, attracts a lot of interest in its structural and electronic properties close to its interface. Valence EELS is used to investigate the Plasmon excitations of the ultrathin SrTiO3 thin film which is sandwiched between amorphous Si and crystalline Si layers. On the other hand, theoretical simulations based on dielectric functions have been done to interpret the experimental results. Our findings demonstrate the value of valence electron energy-loss spectroscopy in detecting a local change in the effective electron mass. Recently it is reported that ZnO-LiYbO2 hybrid phosphor is an efficient UV-infrared convertor for silicon solar cell but the mechanism is still not very clear. The microstructure of Li and Yb co-doped ZnO has been studied by SEM and EDX, and our results suggest that a reaction (or diffusion) zone is very likely to exist between LiYbO2 and ZnO. Such diffusion regions may be responsible for the enhanced infrared emission in the Yb and Li co-doped ZnO. Furthermore, to help us study the diffusion zone under TEM in future, the radiation damage on synthesized LiYbO2 has been studied at first, and then the electronic structure of the synthesized LiYbO2 is compared with Yb2O3 experimentally and theoretically, by EELS and FEFF8 respectively.
ContributorsYang, Bo (Author) / Alford, Terry (Thesis advisor) / Jiang, Nan (Committee member) / Theodore, N. David (Committee member) / Arizona State University (Publisher)
Created2013
Description
As crystalline silicon solar cells continue to get thinner, the recombination of carriers at the surfaces of the cell plays an ever-important role in controlling the cell efficiency. One tool to minimize surface recombination is field effect passivation from the charges present in the thin films applied on the cell surfaces. The focus of this work is to understand the properties of charges present in the SiNx films and then to develop a mechanism to manipulate the polarity of charges to either negative or positive based on the end-application. Specific silicon-nitrogen dangling bonds (·Si-N), known as K center defects, are the primary charge trapping defects present in the SiNx films. A custom built corona charging tool was used to externally inject positive or negative charges in the SiNx film. Detailed Capacitance-Voltage (C-V) measurements taken on corona charged SiNx samples confirmed the presence of a net positive or negative charge density, as high as +/- 8 x 1012 cm-2, present in the SiNx film. High-energy (~ 4.9 eV) UV radiation was used to control and neutralize the charges in the SiNx films. Electron-Spin-Resonance (ESR) technique was used to detect and quantify the density of neutral K0 defects that are paramagnetically active. The density of the neutral K0 defects increased after UV treatment and decreased after high temperature annealing and charging treatments. Etch-back C-V measurements on SiNx films showed that the K centers are spread throughout the bulk of the SiNx film and not just near the SiNx-Si interface. It was also shown that the negative injected charges in the SiNx film were stable and present even after 1 year under indoor room-temperature conditions. Lastly, a stack of SiO2/SiNx dielectric layers applicable to standard commercial solar cells was developed using a low temperature (< 400 °C) PECVD process. Excellent surface passivation on FZ and CZ Si substrates for both n- and p-type samples was achieved by manipulating and controlling the charge in SiNx films.
ContributorsSharma, Vivek (Author) / Bowden, Stuart (Thesis advisor) / Schroder, Dieter (Committee member) / Honsberg, Christiana (Committee member) / Roedel, Ronald (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2013
Description
Ball Grid Array (BGA) using lead-free or lead-rich solder materials are widely used as Second Level Interconnects (SLI) in mounting packaged components to the printed circuit board (PCB). The reliability of these solder joints is of significant importance to the performance of microelectronics components and systems. Product design/form-factor, solder material, manufacturing process, use condition, as well as, the inherent variabilities present in the system, greatly influence product reliability. Accurate reliability analysis requires an integrated approach to concurrently account for all these factors and their synergistic effects. Such an integrated and robust methodology can be used in design and development of new and advanced microelectronics systems and can provide significant improvement in cycle-time, cost, and reliability. IMPRPK approach is based on a probabilistic methodology, focusing on three major tasks of (1) Characterization of BGA solder joints to identify failure mechanisms and obtain statistical data, (2) Finite Element analysis (FEM) to predict system response needed for life prediction, and (3) development of a probabilistic methodology to predict the reliability, as well as, the sensitivity of the system to various parameters and the variabilities. These tasks and the predictive capabilities of IMPRPK in microelectronic reliability analysis are discussed.
ContributorsFallah-Adl, Ali (Author) / Tasooji, Amaneh (Thesis advisor) / Krause, Stephen (Committee member) / Alford, Terry (Committee member) / Jiang, Hanqing (Committee member) / Mahajan, Ravi (Committee member) / Arizona State University (Publisher)
Created2013