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- Creators: Barrett, The Honors College
Description
Recent satellite and remote sensing innovations have led to an eruption in the amount and variety of geospatial ice data available to the public, permitting in-depth study of high-definition ice imagery and digital elevation models (DEMs) for the goal of safe maritime navigation and climate monitoring. Few researchers have investigated texture in optical imagery as a predictive measure of Arctic sea ice thickness due to its cloud pollution, uniformity, and lack of distinct features that make it incompatible with standard feature descriptors. Thus, this paper implements three suitable ice texture metrics on 1640 Arctic sea ice image patches, namely (1) variance pooling, (2) gray-level co-occurrence matrices (GLCMs), and (3) textons, to assess the feasibly of a texture-based ice thickness regression model. Results indicate that of all texture metrics studied, only one GLCM statistic, namely homogeneity, bore any correlation (0.15) to ice freeboard.
ContributorsWarner, Hailey (Author) / Cochran, Douglas (Thesis director) / Jayasuria, Suren (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Electrical Engineering Program (Contributor)
Created2024-05
Description
Discovering more about social hierarchies within groups of mice and the underlying brain mechanisms supporting differences in dominance is essential to understanding social roles and individuality. In this study, we aimed to discover if a novel dominance assay is able to determine social hierarchies in groups of three, as well as how this novel assay compares to a classic dominance tube test. SLEAP software, a machine learning tool, was used to analyze the behaviors of the mice in the novel dominance apparatus. In addition, cytokine levels were collected from the mice to assess possible correlations between hierarchical standing and presence of inflammatory agents.
ContributorsFarrington, Jaime (Author) / Verpeut, Jessica (Thesis director) / Bimonte-Nelson, Heather (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor)
Created2024-05
ContributorsMones, M (Author) / Karimi, Robert Farid (Thesis director) / Sprowls, Jared (Committee member) / Wasserman, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Music, Dance and Theatre (Contributor) / Dean, Herberger Institute for Design and the Arts (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor)
Created2024-05
DescriptionThis project reflects on the historical constructions of queer Jewish diasporic deviance, presents a theology of misfit mysticism, and offers an in-process play surrounding these topics. Musings include anti-nationalism, sacred-profanity, degeneracy, divinity, paradox, and infinity.
ContributorsMones, M (Author) / Karimi, Robert Farid (Thesis director) / Sprowls, Jared (Committee member) / Wasserman, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Music, Dance and Theatre (Contributor) / Dean, Herberger Institute for Design and the Arts (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor)
Created2024-05
ContributorsMones, M (Author) / Karimi, Robert Farid (Thesis director) / Sprowls, Jared (Committee member) / Wasserman, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Music, Dance and Theatre (Contributor) / Dean, Herberger Institute for Design and the Arts (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor)
Created2024-05
ContributorsMones, M (Author) / Karimi, Robert Farid (Thesis director) / Sprowls, Jared (Committee member) / Wasserman, Michael (Committee member) / Barrett, The Honors College (Contributor) / School of Music, Dance and Theatre (Contributor) / Dean, Herberger Institute for Design and the Arts (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor)
Created2024-05
Description
As the microelectronics industry continues to decrease the size of solder joints, each joint will have to carry a greater current density, making atom diffusion due to current flow, electromigration (EM), a problem of ever-increasing severity. The rate of EM damage depends on current density, operating temperature, and the original microstructure of the solder joint, including void volume, grain orientation, and grain size. While numerous studies have investigated the post-mortem effects of EM and have tested a range of current densities and temperatures, none have been able to analyze how the same joint evolves from its initial to final microstructure. This thesis focuses on the study of EM, thermal aging, and thermal cycling in Sn-rich solder joints. Solder joints were either of controlled microstructure and orientation or had trace alloying element additions. Sn grain orientation has been linked to a solder joints’ susceptibility to EM damage, but the precise relationship between orientation and intermetallic (IMC) and void growth has not been deduced. In this research x-ray microtomography was used to nondestructively scan samples and generate 3D reconstructions of both surface and internal features such as interfaces, IMC particles, and voids within a solder joint. Combined with controlled fabrication techniques to create comparable samples and electron backscatter diffraction (EBSD) and energy-dispersive spectroscopy (EDS) analysis for grain orientation and composition analysis, this work shows how grain structure plays a critical role in EM damage and how it differs from damage accrued from thermal effects that occur simultaneously. Unique IMC growth and voiding behaviors are characterized and explained in relation to the solder microstructures that cause their formation and the possible IMC-suppression effects of trace alloying element addition are discussed.
ContributorsBranch Kelly, Marion (Author) / Chawla, Nikhilesh (Thesis advisor) / Ankit, Kumar (Committee member) / Antoniswamy, Aravindha (Committee member) / Arizona State University (Publisher)
Created2019
Description
Traditionally nanoporous gold is created by selective dissolution of silver or copper from a binary silver-gold or copper-gold alloy. These alloys serve as prototypical model systems for a phenomenon referred to as stress-corrosion cracking. Stress-corrosion cracking is the brittle failure of a normally ductile material occurring in a corrosive environment under a tensile stress. Silver-gold can experience this type of brittle fracture for a range of compositions. The corrosion process in this alloy results in a bicontinuous nanoscale morphology composed of gold-rich ligaments and voids often referred to as nanoporous gold. Experiments have shown that monolithic nanoporous gold can sustain high speed cracks which can then be injected into parent-phase alloy. This work compares nanoporous gold created from ordered and disordered copper-gold using digital image analysis and electron backscatter diffraction. Nanoporous gold from both disordered copper-gold and silver-gold, and ordered copper-gold show that grain orientation and shape remain largely unchanged by the dealloying process. Comparing the morphology of the nanoporous gold from ordered and disordered copper-gold with digital image analysis, minimal differences are found between the two and it is concluded that they are not statistically significant. This reveals the robust nature of nanoporous gold morphology against small variations in surface diffusion and parent-phase crystal structure.
Then the corrosion penetration down the grain boundary is compared to the depth of crack injections in polycrystal silver-gold. Based on statistical comparison, the crack-injections penetrate into the parent-phase grain boundary beyond the corrosion-induced porosity. To compare crack injections to stress-corrosion cracking, single crystal silver-gold samples are employed. Due to the cleavage-like nature of the fracture surfaces, electron backscatter diffraction is possible and employed to compare the crystallography of stress-corrosion crack surfaces and crack-injection surfaces. From the crystallographic similarities of these fracture surfaces, it is concluded that stress-corrosion can occur via a series of crack-injection events. This relationship between crack injections and stress corrosion cracking is further examined using electrochemical data from polycrystal silver-gold samples during stress-corrosion cracking. The results support the idea that crack injection is a mechanism for stress-corrosion cracking.
Then the corrosion penetration down the grain boundary is compared to the depth of crack injections in polycrystal silver-gold. Based on statistical comparison, the crack-injections penetrate into the parent-phase grain boundary beyond the corrosion-induced porosity. To compare crack injections to stress-corrosion cracking, single crystal silver-gold samples are employed. Due to the cleavage-like nature of the fracture surfaces, electron backscatter diffraction is possible and employed to compare the crystallography of stress-corrosion crack surfaces and crack-injection surfaces. From the crystallographic similarities of these fracture surfaces, it is concluded that stress-corrosion can occur via a series of crack-injection events. This relationship between crack injections and stress corrosion cracking is further examined using electrochemical data from polycrystal silver-gold samples during stress-corrosion cracking. The results support the idea that crack injection is a mechanism for stress-corrosion cracking.
ContributorsKarasz, Erin (Author) / Sieradzki, Karl (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Peralta, Pedro (Committee member) / Rajagopalan, Jagannathan (Committee member) / Arizona State University (Publisher)
Created2020
Description
Semantic image segmentation has been a key topic in applications involving image processing and computer vision. Owing to the success and continuous research in the field of deep learning, there have been plenty of deep learning-based segmentation architectures that have been designed for various tasks. In this thesis, deep-learning architectures for a specific application in material science; namely the segmentation process for the non-destructive study of the microstructure of Aluminum Alloy AA 7075 have been developed. This process requires the use of various imaging tools and methodologies to obtain the ground-truth information. The image dataset obtained using Transmission X-ray microscopy (TXM) consists of raw 2D image specimens captured from the projections at every beam scan. The segmented 2D ground-truth images are obtained by applying reconstruction and filtering algorithms before using a scientific visualization tool for segmentation. These images represent the corrosive behavior caused by the precipitates and inclusions particles on the Aluminum AA 7075 alloy. The study of the tools that work best for X-ray microscopy-based imaging is still in its early stages.
In this thesis, the underlying concepts behind Convolutional Neural Networks (CNNs) and state-of-the-art Semantic Segmentation architectures have been discussed in detail. The data generation and pre-processing process applied to the AA 7075 Data have also been described, along with the experimentation methodologies performed on the baseline and four other state-of-the-art Segmentation architectures that predict the segmented boundaries from the raw 2D images. A performance analysis based on various factors to decide the best techniques and tools to apply Semantic image segmentation for X-ray microscopy-based imaging was also conducted.
In this thesis, the underlying concepts behind Convolutional Neural Networks (CNNs) and state-of-the-art Semantic Segmentation architectures have been discussed in detail. The data generation and pre-processing process applied to the AA 7075 Data have also been described, along with the experimentation methodologies performed on the baseline and four other state-of-the-art Segmentation architectures that predict the segmented boundaries from the raw 2D images. A performance analysis based on various factors to decide the best techniques and tools to apply Semantic image segmentation for X-ray microscopy-based imaging was also conducted.
ContributorsBarboza, Daniel (Author) / Turaga, Pavan (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Jayasuriya, Suren (Committee member) / Arizona State University (Publisher)
Created2020
Description
Energy return in footwear is associated with the damping behavior of midsole foams, which stems from the combination of cellular structure and polymeric material behavior. Recently, traditional ethyl vinyl acetate (EVA) foams have been replaced by BOOST(TM) foams, thereby reducing the energetic cost of running. These are bead foams made from expanded thermoplastic polyurethane (eTPU), which have a multi-scale structure consisting of fused porous beads, at the meso-scale, and thousands of small closed cells within the beads at the micro-scale. Existing predictive models coarsely describe the macroscopic behavior but do not take into account strain localizations and microstructural heterogeneities. Thus, enhancement in material performance and optimization requires a comprehensive understanding of the foam’s cellular structure at all length scales and its influence on mechanical response.
This dissertation focused on characterization and deformation behavior of eTPU bead foams with a unique graded cell structure at the micro and meso-scale. The evolution of the foam structure during compression was studied using a combination of in situ lab scale and synchrotron x-ray tomography using a four-dimensional (4D, deformation + time) approach. A digital volume correlation (DVC) method was developed to elucidate the role of cell structure on local deformation mechanisms. The overall mechanical response was also studied ex situ to probe the effect of cell size distribution on the force-deflection behavior. The radial variation in porosity and ligament thickness profoundly influenced the global mechanical behavior. The correlation of changes in void size and shape helped in identifying potentially weak regions in the microstructure. Strain maps showed the initiation of failure in cell structure and it was found to be influenced by the heterogeneities around the immediate neighbors in a cluster of voids. Poisson’s ratio evaluated from DVC was related to the microstructure of the bead foams. The 4D approach taken here provided an in depth and mechanistic understanding of the material behavior, both at the bead and plate levels, that will be invaluable in designing the next generation of high-performance footwear.
This dissertation focused on characterization and deformation behavior of eTPU bead foams with a unique graded cell structure at the micro and meso-scale. The evolution of the foam structure during compression was studied using a combination of in situ lab scale and synchrotron x-ray tomography using a four-dimensional (4D, deformation + time) approach. A digital volume correlation (DVC) method was developed to elucidate the role of cell structure on local deformation mechanisms. The overall mechanical response was also studied ex situ to probe the effect of cell size distribution on the force-deflection behavior. The radial variation in porosity and ligament thickness profoundly influenced the global mechanical behavior. The correlation of changes in void size and shape helped in identifying potentially weak regions in the microstructure. Strain maps showed the initiation of failure in cell structure and it was found to be influenced by the heterogeneities around the immediate neighbors in a cluster of voids. Poisson’s ratio evaluated from DVC was related to the microstructure of the bead foams. The 4D approach taken here provided an in depth and mechanistic understanding of the material behavior, both at the bead and plate levels, that will be invaluable in designing the next generation of high-performance footwear.
ContributorsSundaram Singaravelu, Arun Sundar (Author) / Chawla, Nikhilesh (Thesis advisor) / Emady, Heather (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2020