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- Genre: Masters Thesis
- Language: English
Description
This thesis focuses on the theoretical work done to determine thermodynamic properties of a chalcopyrite thin-film material for use as a photovoltaic material in a tandem device. The material of main focus here is ZnGeAs2, which was chosen for the relative abundance of constituents, favorable photovoltaic properties, and good lattice matching with ZnSnP2, the other component in this tandem device. This work is divided into two main chapters, which will cover: calculations and method to determine the formation energy and abundance of native point defects, and a model to calculate the vapor pressure over a ternary material from first-principles. The purpose of this work is to guide experimental work being done in tandem to synthesize ZnGeAs2 in thin-film form with high enough quality such that it can be used as a photovoltaic. Since properties of photovoltaic depend greatly on defect concentrations and film quality, a theoretical understanding of how laboratory conditions affect these properties is very valuable. The work done here is from first-principles and utilizes density functional theory using the local density approximation. Results from the native point defect study show that the zinc vacancy (VZn) and the germanium antisite (GeZn) are the more prominent defects; which most likely produce non-stoichiometric films. The vapor pressure model for a ternary system is validated using known vapor pressure for monatomic and binary test systems. With a valid ternary system vapor pressure model, results show there is a kinetic barrier to decomposition for ZnGeAs2.
ContributorsTucker, Jon R (Author) / Van Schilfgaarde, Mark (Thesis advisor) / Newman, Nathan (Committee member) / Adams, James (Committee member) / Arizona State University (Publisher)
Created2011
Description
This thesis is a qualitative research study that focuses on siblings of children with Autistic Spectrum Disorder (ASD). Even though it is expected that having a child with ASD in the family will influence the whole family including siblings of the child with ASD, the sibling population is rarely included in research related to children with ASD, and there is only limited services available for them. This exploratory study (n=6) is aimed at better understanding the siblings' lives in their family settings in order to identify the siblings' unmet needs and determine how they have been influenced by the child with ASD. This study is also aimed at identifying the most appropriate support for the siblings to help them cope better. The study followed the Resiliency Model of Family Stress, Adjustment, and Adaptation and a narrative theory approach. An in-depth interview with the parents was conducted for the study, so the findings reflect the parents' perception of the siblings. All the themes emerged into two categories: life in the family setting and supports. The findings indicate that the families are striving for balance between the siblings and the children with ASD, but still tend to focus more on the children with ASD. Also, the families tend to have autonomous personal support systems. The parents tend to perceive that these personal support systems are good enough for the siblings; therefore, the parents do not feel that formal support for the siblings was necessary. As a result of the findings, recommendations are made for the organizations that work with individuals with ASD to provide more appropriate services for the families of children with ASD, including siblings. Also, recommendations are made for future studies to clarify more factors related to the siblings due to the limitation of this study; the siblings' lives were reflected vicariously via the parents.
ContributorsJeong, Seong Hae (Author) / Marsiglia, Flavio F (Thesis advisor) / Ayers, Stephanie (Committee member) / Adams, James (Committee member) / Arizona State University (Publisher)
Created2013
Description
As world energy demands increase, research into more efficient energy production methods has become imperative. Heterogeneous catalysis and nanoscience are used to promote chemical transformations important for energy production. These concepts are important in solid oxide fuel cells (SOFCs) which have attracted attention because of their potential to provide an efficient and environmentally favorable power generation system. The SOFC is also fuel-flexible with the ability to run directly on many fuels other than hydrogen. Internal fuel reforming directly in the anode of the SOFC would greatly reduce the cost and complexity of the device. Methane is the simplest hydrocarbon and a main component in natural gas, making it useful when testing catalysts on the laboratory scale. Nickel (Ni) and gadolinium (Gd) doped ceria (CeO2) catalysts for potential use in the SOFC anode were synthesized with a spray drying method and tested for catalytic performance using partial oxidation of methane and steam reforming. The relationships between catalytic performance and structure were then investigated using X-ray diffraction, transmission electron microscopy, and environmental transmission electron microscopy. The possibility of solid solutions, segregated phases, and surface layers of Ni were explored. Results for a 10 at.% Ni in CeO2 catalyst reveal a poor catalytic behavior while a 20 at.% Ni in CeO2 catalyst is shown to have superior activity. The inclusion of both 10 at.% Gd and 10 at.% Ni in CeO2 enhances the catalytic performance. Analysis of the presence of Ni in all 3 samples reveals Ni heterogeneity and little evidence for extensive solid solution doping. Ni is found in small domains throughout CeO2 particles. In the 20 at.% Ni sample a segregated, catalytically active NiO phase is observed. Overall, it is found that significant interaction between Ni and CeO2 occurs that could affect the synthesis and functionality of the SOFC anode.
ContributorsCavendish, Rio (Author) / Crozier, Peter (Thesis advisor) / Adams, James (Committee member) / Smith, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
It is possible in a properly controlled environment, such as industrial metrology, to make significant headway into the non-industrial constraints on image-based position measurement using the techniques of image registration and achieve repeatable feature measurements on the order of 0.3% of a pixel, or about an order of magnitude improvement on conventional real-world performance. These measurements are then used as inputs for a model optimal, model agnostic, smoothing for calibration of a laser scribe and online tracking of velocimeter using video input. Using appropriate smooth interpolation to increase effective sample density can reduce uncertainty and improve estimates. Use of the proper negative offset of the template function has the result of creating a convolution with higher local curvature than either template of target function which allows improved center-finding. Using the Akaike Information Criterion with a smoothing spline function it is possible to perform a model-optimal smooth on scalar measurements without knowing the underlying model and to determine the function describing the uncertainty in that optimal smooth. An example of empiric derivation of the parameters for a rudimentary Kalman Filter from this is then provided, and tested. Using the techniques of Exploratory Data Analysis and the "Formulize" genetic algorithm tool to convert the spline models into more accessible analytic forms resulted in stable, properly generalized, KF with performance and simplicity that exceeds "textbook" implementations thereof. Validation of the measurement includes that, in analytic case, it led to arbitrary precision in measurement of feature; in reasonable test case using the methods proposed, a reasonable and consistent maximum error of around 0.3% the length of a pixel was achieved and in practice using pixels that were 700nm in size feature position was located to within ± 2 nm. Robust applicability is demonstrated by the measurement of indicator position for a King model 2-32-G-042 rotameter.
ContributorsMunroe, Michael R (Author) / Phelan, Patrick (Thesis advisor) / Kostelich, Eric (Committee member) / Mahalov, Alex (Committee member) / Arizona State University (Publisher)
Created2012
Description
White organic light emitting diodes (WOLEDs) are currently being developed as the next generation of solid state lighting sources. Although, there has been considerable improvements in device efficiency from the early days up until now, there are still major drawbacks for the implementation of WOLEDs to commercial markets. These drawbacks include short lifetimes associated with highly efficient and easier to fabricate device structures. Platinum (II) complexes are been explored as emitters for single emissive layer WOLEDs, due to their higher efficiencies and stability in device configurations. These properties have been attributed to their square planar nature. Tetradentate platinum (II) complexes in particular have been shown to be more rigid and thus more stable than their other multidentate counterparts. This thesis aims to explore the different pathways via molecular design of tetradentate platinum II complexes and in particular the percipient engineering of a highly efficient and stable device structure. Previous works have been able to obtain either highly efficient devices or stable devices in different device configurations. In this work, we demonstrate a device structure employing Pt2O2 as the emitter using mCBP as a host with EQE of above 20% and lifetime values (LT80) exceeding 6000hours at practical luminance of 100cd/m2. These results open up the pathway towards the commercialization of white organic light emitting diodes as a solid state lighting source.
ContributorsOloye, Temidayo Abiola (Author) / Li, Jian (Thesis advisor) / Alford, Terry (Committee member) / Adams, James (Committee member) / Arizona State University (Publisher)
Created2016
Description
Efforts to treat prostate cancer have seen an uptick, as the world’s most commoncancer in men continues to have increasing global incidence. Clinically, metastatic
prostate cancer is most commonly treated with hormonal therapy. The idea behind
hormonal therapy is to reduce androgen production, which prostate cancer cells
require for growth. Recently, the exploration of the synergistic effects of the drugs
used in hormonal therapy has begun. The aim was to build off of these recent
advancements and further refine the synergistic drug model. The advancements I
implement come by addressing biological shortcomings and improving the model’s
internal mechanistic structure. The drug families being modeled, anti-androgens,
and gonadotropin-releasing hormone analogs, interact with androgen production in a
way that is not completely understood in the scientific community. Thus the models
representing the drugs show progress through their ability to capture their effect
on serum androgen. Prostate-specific antigen is the primary biomarker for prostate
cancer and is generally how population models on the subject are validated. Fitting
the model to clinical data and comparing it to other clinical models through the
ability to fit and forecast prostate-specific antigen and serum androgen is how this
improved model achieves validation. The improved model results further suggest that
the drugs’ dynamics should be considered in adaptive therapy for prostate cancer.
prostate cancer is most commonly treated with hormonal therapy. The idea behind
hormonal therapy is to reduce androgen production, which prostate cancer cells
require for growth. Recently, the exploration of the synergistic effects of the drugs
used in hormonal therapy has begun. The aim was to build off of these recent
advancements and further refine the synergistic drug model. The advancements I
implement come by addressing biological shortcomings and improving the model’s
internal mechanistic structure. The drug families being modeled, anti-androgens,
and gonadotropin-releasing hormone analogs, interact with androgen production in a
way that is not completely understood in the scientific community. Thus the models
representing the drugs show progress through their ability to capture their effect
on serum androgen. Prostate-specific antigen is the primary biomarker for prostate
cancer and is generally how population models on the subject are validated. Fitting
the model to clinical data and comparing it to other clinical models through the
ability to fit and forecast prostate-specific antigen and serum androgen is how this
improved model achieves validation. The improved model results further suggest that
the drugs’ dynamics should be considered in adaptive therapy for prostate cancer.
ContributorsReckell, Trevor (Author) / Kostelich, Eric (Thesis advisor) / Kuang, Yang (Committee member) / Mahalov, Alex (Committee member) / Arizona State University (Publisher)
Created2020