ASU Electronic Theses and Dissertations
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.
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Description
Electromigration, the net atomic diffusion associated with the momentum transfer from electrons moving through a material, is a major cause of device and component failure in microelectronics. The deleterious effects from electromigration rise with increased current density, a parameter that will only continue to increase as our electronic devices get smaller and more compact. Understanding the dynamic diffusional pathways and mechanisms of these electromigration-induced and propagated defects can further our attempts at mitigating these failure modes. This dissertation provides insight into the relationships between these defects and parameters of electric field strength, grain boundary misorientation, grain size, void size, eigenstrain, varied atomic mobilities, and microstructure.First, an existing phase-field model was modified to investigate the various defect modes associated with electromigration in an equiaxed non-columnar microstructure. Of specific interest was the effect of grain boundary misalignment with respect to current flow and the mechanisms responsible for the changes in defect kinetics. Grain size, magnitude of externally applied electric field, and the utilization of locally distinct atomic mobilities were other parameters investigated. Networks of randomly distributed grains, a common microstructure of interconnects, were simulated in both 2- and 3-dimensions displaying the effects of 3-D capillarity on diffusional dynamics.
Also, a numerical model was developed to study the effect of electromigration on void migration and coalescence. Void migration rates were found to be slowed from compressive forces and the nature of the deformation concurrent with migration was examined through the lens of chemical potential. Void migration was also validated with previously reported theoretical explanations. Void coalescence and void budding were investigated and found to be dependent on the magnitude of interfacial energy and electric field strength.
A grasp on the mechanistic pathways of electromigration-induced defect evolution is imperative to the development of reliable electronics, especially as electronic devices continue to miniaturize. This dissertation displays a working understanding of the mechanistic pathways interconnects can fail due to electromigration, as well as provide direction for future research and understanding.
ContributorsFarmer, William McHann (Author) / Ankit, Kumar (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Jiao, Yang (Committee member) / McCue, Ian (Committee member) / Arizona State University (Publisher)
Created2022
Description
Disordered many-body systems are ubiquitous in condensed matter physics, materials science and biological systems. Examples include amorphous and glassy states of matter, granular materials, and tissues composed of packings of cells in the extra-cellular matrix (ECM). Understanding the collective emergent properties in these systems is crucial to improving the capability for controlling, engineering and optimizing their behaviors, yet it is extremely challenging due to their complexity and disordered nature. The main theme of the thesis is to address this challenge by characterizing and understanding a variety of disordered many-body systems via unique statistical geometrical and topological tools and the state-of-the-art simulation methods. Two major topics of the thesis are modeling ECM-mediated multicellular dynamics and understanding hyperuniformity in 2D material systems. Collective migration is an important mode of cell movement for several biological processes, and it has been the focus of a large number of studies over the past decades. Hyperuniform (HU) state is a critical state in a many-particle system, an exotic property of condensed matter discovered recently. The main focus of this thesis is to study the mechanisms underlying collective cell migration behaviors by developing theoretical/phenomenological models that capture the features of ECM-mediated mechanical communications in vitro and investigate general conditions that can be imposed on hyperuniformity-preserving and hyperuniformity-generating operations, as well as to understand how various novel transport physical properties arise from the unique hyperuniform long-range correlations.
ContributorsZheng, Yu (Author) / Jiao, Yang (Thesis advisor) / Zhuang, Houlong (Committee member) / Beckstein, Oliver (Committee member) / Ros, Robert (Committee member) / Arizona State University (Publisher)
Created2022
Description
The increasing availability of data and advances in computation have spurred the development of data-driven approaches for modeling complex dynamical systems. These approaches are based on the idea that the underlying structure of a complex system can be discovered from data using mathematical and computational techniques. They also show promise for addressing the challenges of modeling high-dimensional, nonlinear systems with limited data. In this research expository, the state of the art in data-driven approaches for modeling complex dynamical systems is surveyed in a systemic way. First the general formulation of data-driven modeling of dynamical systems is discussed. Then several representative methods in feature engineering and system identification/prediction are reviewed, including recent advances and key challenges.
ContributorsShi, Wenlong (Author) / Ren, Yi (Thesis advisor) / Hong, Qijun (Committee member) / Jiao, Yang (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Created2022
Description
Applications such as heat exchangers, surface-based cellular structures, rotating blades, and waveguides rely on thin metal walls as crucial constituent elements of the structure. The design freedom enabled by laser powder bed fusion has led to an interest in exploiting this technology to further the performance of these components, many of which retain their as-built surface morphologies on account of their design complexity. However, there is limited understanding of how and why mechanical properties vary by wall thickness for specimens that are additively manufactured and maintain an as-printed surface finish. Critically, the contributions of microstructure and morphology to the mechanical behavior of thin wall laser powder bed fusion structures have yet to be systematically identified and decoupled. This work focuses on elucidating the room temperature quasi-static tensile and high cycle fatigue properties of as-printed, thin-wall Inconel 718 fabricated using laser powder bed fusion, with the aim of addressing this critical gap in the literature. Wall thicknesses studied range from 0.3 - 2.0 mm, and the effects of Hot Isostatic Pressing are also examined, with sheet metal specimens used as a baseline for comparison. Statistical analyses are conducted to identify the significance of the dependence of properties on wall thickness and Hot Isostatic Pressing, as well as to examine correlations of these properties to section area, porosity, and surface roughness. A thorough microstructural study is complemented with a first-of-its-kind study of surface morphology to decouple their contributions and identify underlying causes for observed changes in mechanical properties. This thesis finds that mechanical properties in the quasi-static and fatigue framework do not see appreciable declines until specimen thickness is under 0.75 mm in thickness. The added Hot Isostatic Pressing heat treatment effectively closed pores, recrystallized the grain structure, and provided a more homogenous microstructure that benefits the modulus, tensile strength, elongation, and fatigue performance at higher stresses. Stress heterogeneities, primarily caused by surface defects, negatively affected the thinner specimens disproportionately. Without the use of the Hot Isostatic Pressing, the grain structure remained much more refined and benefitted the yield strength and fatigue endurance limit.
ContributorsParadise, Paul David (Author) / Bhate, Dhruv (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Azeredo, Bruno (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2022
Description
Fatigue fracture is one of the most common types of mechanical failures seen in structures. Considering that fatigue failures usually initiate on surfaces, it is accepted that surface roughness has a detrimental effect on the fatigue life of components. Irregularities on the surface cause stress concentrations and form nucleation sites for cracks. As surface conditions are not always satisfactory, particularly for additively manufactured components, it is necessary to develop a reliable model for fatigue life estimation considering surface roughness effects and assure structural integrity. This research study focuses on extending a previously developed subcycle fatigue crack growth model to include the effects of surface roughness. Unlike other models that consider surface irregularities as series of cracks, the proposed model is unique in the way that it treats the peaks and valleys of surface texture as a single equivalent notch. First, an equivalent stress concentration factor for the roughness was estimated and introduced into an asymptotic interpolation method for notches. Later, a concept called equivalent initial flaw size was incorporated along with linear elastic fracture mechanics to predict the fatigue life of Ti-6Al-4V alloy with different levels of roughness under uniaxial and multiaxial loading conditions. The predicted results were validated using the available literature data. The developed model can also handle variable amplitude loading conditions, which is suggested for future work.
ContributorsKethamukkala, Kaushik (Author) / Liu, Yongming (Thesis advisor) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2022
Description
Microstructure refinement and alloy additions are considered potential routes to increase high temperature performance of existing metallic superalloys used under extreme conditions. Nanocrystalline (NC) Cu-10at%Ta exhibits such improvements over microstructurally unstable NC metals, leading to enhanced creep behavior compared to its coarse-grained (CG) counterparts. However, the low melting point of Cu compared to other FCC metals, e.g., Ni, might lead to an early onset of diffusional creep mechanisms. Thus, this research seeks to study the thermo-mechanical behavior and stability of hierarchical (prepared using arc-melting) and NC (prepared by collaborators through powder pressing and annealing) Ni-Y-Zr alloys where Zr is expected to provide solid solution and grain boundary strengthening in hierarchical and NC alloys, respectively, while Ni-Y and Ni-Zr intermetallic precipitates (IMCs) would provide kinetic stability. Hierarchical alloys had microstructures stable up to 1100 °C with ultrafine eutectic of ~300 nm, dendritic arm spacing of ~10 μm, and grain size ~1-2 mm. Room temperature hardness tests along with uniaxial compression performed at 25 and 600 °C revealed that microhardness and yield strength of hierarchical alloys with small amounts of Y (0.5-1wt%) and Zr (1.5-3 wt%) were comparable to Ni-superalloys, due to the hierarchical microstructure and potential presence of nanoscale IMCs. In contrast, NC alloys of the same composition were found to be twice as hard as the hierarchical alloys. Creep tests at 0.5 homologous temperature showed active Coble creep mechanisms in hierarchical alloys at low stresses with creep rates slower than Fe-based superalloys and dislocation creep mechanisms at higher stresses. Creep in NC alloys at lower stresses was only 20 times faster than hierarchical alloys, with the difference in grain size ranging from 10^3 to 10^6 times at the same temperature. These NC alloys showed enhanced creep properties over other NC metals and are expected to have rates equal to or improved over the CG hierarchical alloys with ECAP processing techniques. Lastly, the in-situ wide-angle x-ray scattering (WAXS) measurements during quasi-static and creep tests implied stresses being carried mostly by the matrix before yielding and in the primary creep stage, respectively, while relaxation was observed in Ni5Zr for both hierarchical and NC alloys. Beyond yielding and in the secondary creep stage, lattice strains reached a steady state, thereby, an equilibrium between plastic strain rates was achieved across different phases, so that deformation reaches a saturation state where strain hardening effects are compensated by recovery mechanisms.
ContributorsSharma, Shruti (Author) / Peralta, Pedro (Thesis advisor) / Alford, Terry (Committee member) / Jiao, Yang (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2022
Description
Intelligent engineering designs require an accurate understanding of material behavior, since any uncertainties or gaps in knowledge must be counterbalanced with heightened factors of safety, leading to overdesign. Therefore, building better structures and pushing the performance of new components requires an improved understanding of the thermomechanical response of advanced materials under service conditions. This dissertation provides fundamental investigations of several advanced materials: thermoset polymers, a common matrix material for fiber-reinforced composites and nanocomposites; aluminum alloy 7075-T6 (AA7075-T6), a high-performance aerospace material; and ceramic matrix composites (CMCs), an advanced composite for extreme-temperature applications. To understand matrix interactions with various interfaces and nanoinclusions at their fundamental scale, the properties of thermoset polymers are studied at the atomistic scale. An improved proximity-based molecular dynamics (MD) technique for modeling the crosslinking of thermoset polymers is carefully established, enabling realistic curing simulations through its ability to dynamically and probabilistically perform complex topology transformations. The proximity-based MD curing methodology is then used to explore damage initiation and the local anisotropic evolution of mechanical properties in thermoset polymers under uniaxial tension with an emphasis on changes in stiffness through a series of tensile loading, unloading, and reloading experiments. Aluminum alloys in aerospace applications often require a fatigue life of over 109 cycles, which is well over the number of cycles that can be practically tested using conventional fatigue testing equipment. In order to study these high-life regimes, a detailed ultrasonic cycle fatigue study is presented for AA7075-T6 under fully reversed tension-compression loading. The geometric sensitivity, frequency effects, size effects, surface roughness effects, and the corresponding failure mechanisms for ultrasonic fatigue across different fatigue regimes are investigated. Finally, because CMCs are utilized in extreme environments, oxidation plays an important role in their degradation. A multiphysics modeling methodology is thus developed to address the complex coupling between oxidation, mechanical stress, and oxygen diffusion in heterogeneous carbon fiber-reinforced CMC microstructures.
ContributorsSchichtel, Jacob (Author) / Chattopadhyay, Aditi (Thesis advisor) / Dai, Lenore (Committee member) / Ghoshal, Anindya (Committee member) / Huang, Huei-Ping (Committee member) / Jiao, Yang (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2022
Description
With the abundance of increasingly large datasets, the ability to predict the phase of high-entropy alloys (HEAs) based solely on elemental composition could become a reliable tool for the discovery of new HEAs. However, as the amount of data expands so does the computational time and resources required to train predictive classical machine learning models. Quantum computers, which use quantum bits (qubits), could be the solution to overcoming these demands. Their ability to use quantum superposition and interference to perform calculations could be the key to handling large amounts of data. In this work, a hybrid quantum-classical machine learning algorithm is implemented on both quantum simulators and quantum processors to perform the supervised machine learning task. Their feasibility as a future tool for HEA discovery is evaluated based on the algorithm’s performance. An artificial neural network (ANN), run by classical computers, is also trained on the same data for performance comparison. The accuracy of the quantum-classical model was found to be comparable to the accuracy achieved by the classical ANN with a slight decrease in accuracy when ran on quantum hardware due to qubit susceptibility to decoherence. Future developments in the applied quantum machine learning method are discussed.
ContributorsBrown, Payden Lance (Author) / Zhuang, Houlong (Thesis advisor) / Ankit, Kumar (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2022
Description
Cellular metamaterials arouse broad scientific interests due to the combination of host material and structure together to achieve a wide range of physical properties rarely found in nature. Stochastic foam as one subset has been considered as a competitive candidate for versatile applications including heat exchangers, battery electrodes, automotive, catalyst devices, magnetic shielding, etc. For the engineering of the cellular foam architectures, closed-form models that can be used to predict the mechanical and thermal properties of foams are highly desired especially for the recently developed ultralight weight shellular architectures. Herein, for the first time, a novel packing three-dimensional (3D) hollow pentagonal dodecahedron (HPD) model is proposed to simulate the cellular architecture with hollow struts. An electrochemical deposition process is utilized to manufacture the metallic hollow foam architecture. Mechanical and thermal testing of the as-manufactured foams are carried out to compare with the HPD model. Timoshenko beam theory is utilized to verify and explain the derived power coefficient relation. Our HPD model is proved to accurately capture both the topology and the physical properties of hollow stochastic foam. Understanding how the novel HPD model packing helps break the conventional impression that 3D pentagonal topology cannot fulfill the space as a representative volume element. Moreover, the developed HPD model can predict the mechanical and thermal properties of the manufactured hollow metallic foams and elucidating of how the inevitable manufacturing defects affect the physical properties of the hollow metallic foams. Despite of the macro-scale stochastic foam architecture, nano gradient gyroid lattices are studied using Molecular Dynamics (MD) simulation. The simulation result reveals that, unlike homogeneous architecture, gradient gyroid not only shows novel layer-by-layer deformation behavior, but also processes significantly better energy absorption ability. The deformation behavior and energy absorption are predictable and designable, which demonstrate its highly programmable potential.
ContributorsDai, Rui (Author) / Nian, Qiong (Thesis advisor) / Jiao, Yang (Committee member) / Kwon, Beomjin (Committee member) / Liu, Yongming (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2021
Description
Ultra-fast 2D/3D material microstructure reconstruction and quantitative structure-property mapping are crucial components of integrated computational material engineering (ICME). It is particularly challenging for modeling random heterogeneous materials such as alloys, composites, polymers, porous media, and granular matters, which exhibit strong randomness and variations of their material properties due to the hierarchical uncertainties associated with their complex microstructure at different length scales. Such uncertainties also exist in disordered hyperuniform systems that are statistically isotropic and possess no Bragg peaks like liquids and glasses, yet they suppress large-scale density fluctuations in a similar manner as in perfect crystals. The unique hyperuniform long-range order in these systems endow them with nearly optimal transport, electronic and mechanical properties. The concept of hyperuniformity was originally introduced for many-particle systems and has subsequently been generalized to heterogeneous materials such as porous media, composites, polymers, and biological tissues for unconventional property discovery. An explicit mixture random field (MRF) model is proposed to characterize and reconstruct multi-phase stochastic material property and microstructure simultaneously, where no additional tuning step nor iteration is needed compared with other stochastic optimization approaches such as the simulated annealing. The proposed method is shown to have ultra-high computational efficiency and only requires minimal imaging and property input data. Considering microscale uncertainties, the material reliability will face the challenge of high dimensionality. To deal with the so-called “curse of dimensionality”, efficient material reliability analysis methods are developed. Then, the explicit hierarchical uncertainty quantification model and efficient material reliability solvers are applied to reliability-based topology optimization to pursue the lightweight under reliability constraint defined based on structural mechanical responses. Efficient and accurate methods for high-resolution microstructure and hyperuniform microstructure reconstruction, high-dimensional material reliability analysis, and reliability-based topology optimization are developed. The proposed framework can be readily incorporated into ICME for probabilistic analysis, discovery of novel disordered hyperuniform materials, material design and optimization.
ContributorsGao, Yi (Author) / Liu, Yongming (Thesis advisor) / Jiao, Yang (Committee member) / Ren, Yi (Committee member) / Pan, Rong (Committee member) / Mignolet, Marc (Committee member) / Arizona State University (Publisher)
Created2021