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Description
Widespread knowledge of fracture mechanics is mostly based on previous models that generalize crack growth in materials over several loading cycles. The objective of this project is to characterize crack growth that occurs in titanium alloys, specifically Grade 5 Ti-6Al-4V, at the sub-cycle scale, or within a single loading cycle.

Widespread knowledge of fracture mechanics is mostly based on previous models that generalize crack growth in materials over several loading cycles. The objective of this project is to characterize crack growth that occurs in titanium alloys, specifically Grade 5 Ti-6Al-4V, at the sub-cycle scale, or within a single loading cycle. Using scanning electron microscopy (SEM), imaging analysis is performed to observe crack behavior at ten loading steps throughout the loading and unloading paths. Analysis involves measuring the incremental crack growth and crack tip opening displacement (CTOD) of specimens at loading ratios of 0.1, 0.3, and 0.5. This report defines the relationship between crack growth and the stress intensity factor, K, of the specimens, as well as the relationship between the R-ratio and stress opening level. The crack closure phenomena and effect of microcracks are discussed as they influence the crack growth behavior. This method has previously been used to characterize crack growth in Al 7075-T6. The results for Ti-6Al-4V are compared to these previous findings in order to strengthen conclusions about crack growth behavior.
ContributorsNazareno, Alyssa Noelle (Author) / Liu, Yongming (Thesis director) / Jiao, Yang (Committee member) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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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

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
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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

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
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Description
For the past two centuries, coal has played a vital role as the primary carbon source, fueling industries and enabling the production of essential carbon-rich materials, including carbon nanotubes, graphite, and diamond. However, the global transition towards sustainable energy production has resulted in a decline in coal usage for energy

For the past two centuries, coal has played a vital role as the primary carbon source, fueling industries and enabling the production of essential carbon-rich materials, including carbon nanotubes, graphite, and diamond. However, the global transition towards sustainable energy production has resulted in a decline in coal usage for energy purposes, with the United States alone witnessing a substantial 50% reduction over the past decade. This shift aligns with the UN’s 2030 sustainability goals, which emphasize the reduction of greenhouse gas emissions and the promotion of cleaner energy sources. Despite the decreased use in energy production, the abundance of coal has sparked interest in exploring its potential for other sustainable and valuable applications.In this context, Direct Ink Writing (DIW) has emerged as a promising additive manufacturing technique that employs liquid or gel-like resins to construct three-dimensional structures. DIW offers a unique advantage by allowing the incorporation of particulate reinforcements, which enhance the properties and functionalities of the materials. This study focuses on evaluating the viability of coal as a sustainable and cost-effective substitute for other carbon-based reinforcements, such as graphite or carbon nanotubes. The research utilizes a thermosetting resin based on phenol-formaldehyde (commercially known as Bakelite) as the matrix, while pulverized coal (250 µm) and carbon black (CB) function as the reinforcements. The DIW ink is meticulously formulated to exhibit shear-thinning behavior, facilitating uniform and continuous printing of structures. Mechanical property testing of the printed structures was conducted following ASTM standards. Interestingly, the study reveals that incorporating a 2 wt% concentration of coal in the resin yields the most significant improvements in tensile modulus and flexural strength, with enhancements of 35% and 12.5% respectively. These findings underscore the promising potential of coal as a sustainable and environmentally friendly reinforcement material in additive manufacturing applications. By harnessing the unique properties of coal, this research opens new avenues for its utilization in the pursuit of greener and more efficient manufacturing processes.
ContributorsSundaravadivelan, Barath (Author) / Song, Kenan (Thesis advisor) / Marvi, Hamidreza (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2023
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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

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
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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

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
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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

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
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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

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
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Description
This research seeks to answer the question if there is a singular relationship between stishovite nucleation and the atomistic structure of the preshocked amorphous SiO$_2$. To do this a stishovite manufacturing method is developed in which 1,152 samples were produced. The majority of these samples did crystallize. The method was

This research seeks to answer the question if there is a singular relationship between stishovite nucleation and the atomistic structure of the preshocked amorphous SiO$_2$. To do this a stishovite manufacturing method is developed in which 1,152 samples were produced. The majority of these samples did crystallize. The method was produced through two rounds of experiments and fine-tuning with the pressure damp, temperature damp, shock pressure using an NPHug fix, and sample origin. A new random atomic insertion method was used to generate a new and different SiO$_2$ amorphous structure not before seen within the research literature. The optimal values for shock were found to be 60~GPa for randomly atom insertion samples and 55~GPa for quartz origin samples. Temperature damp appeared to have a slight effect optimizing at 0.05~ps and the pressure damp had no visible effect, testing was done with temperature damp from 0.05 to 0.5~ps and pressure damp from 0.1 to 10.0~ps. There appeared to be significant randomness in crystallization behavior. The preshocked and postnucleated samples were transformed into Gaussian fields of crystal, mass, and charge. These fields were divided and classified using a cut-off method taking the number of crystals produced in portions of each simulation and classifying each potion as nucleated or non-nucleated. Data in which some nucleation but not a critical amount was present was removed constituting 2.6\% to 20.3\% of data in all tests. A max method was also used which takes only the maximum portions of each simulation to classify as nucleating. There are three other variables tested within this work, a sample size of 18,000 or 72,728~atoms, Gaussian variance of 1 or 4~\AA, and Convolutional neural network (CNN) architecture of a garden verity or all convolution along with the portioning classification method, sample origination, and Gaussian field type. In total 64 tests were performed to try every combination of variable. No significant classifications were made by the CNNs to nucleation or non-nucleation portions. The results clearly confirmed that the data was not abstracting to atomistic structure and was random by all classifications of the CNNs. The all convolution CNN testing did show smoother outcomes in training with less fluctuations. 59\% of all validation accuracy was held at 0.5 for a random state and 84\% was within $\pm0.02$ of 0.5. It is conclusive that prenucleation structure is not the sole predictor of nucleation behavior. It is not conclusive if prenucleation structure is a partial or non-factor within nucleation of stishovite from amorphous SiO$_2$.
ContributorsChristen, Jonathan Scorr (Author) / Oswald, Jay (Thesis advisor) / Muhich, Christopher (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Atmospheric water extraction (AWE) is an emerging technology to tackle water resource shortage challenges. One such approach to provide fresh water utilizes stimuli-responsive hydrogel-based desiccants to capture the moisture from the air and release it into the liquid form. Typical gel desiccants are composed of a hygroscopic agent for capturing

Atmospheric water extraction (AWE) is an emerging technology to tackle water resource shortage challenges. One such approach to provide fresh water utilizes stimuli-responsive hydrogel-based desiccants to capture the moisture from the air and release it into the liquid form. Typical gel desiccants are composed of a hygroscopic agent for capturing and a hydrophilic gel matrix for storage. The desorption process can be completed by elevating the temperature above the upper or lower critical solution temperature point to initiate the volume phase transition of either thermo-responsive or photothermal types. This thesis focuses on investigating the structural effect of hydrogels on moisture uptake. Firstly, the main matrix of gel desiccant, poly(N-isopropylacrylamide) hydrogel, was optimized via tuning synthesis temperature and initial monomer concentration. Secondly, a series of hydrogel-based desiccants consisting of a hygroscopic material, vinyl imidazole, and optimized poly(N-isopropylacrylamide) gel matrix were synthesized with different network structures. The moisture uptake result showed that the gel desiccant with an interpenetrating polymeric network (IPN) resulted in the best-performing moisture capturing. The gel desiccant with the best performance will be used as a primary structural unit to evaluate the feasibility of developing a light-responsive gel desiccant to materialize light-trigger moisture desorption for AWE technology in the future.
ContributorsZhao, Xingbang (Author) / Dai, Lenore (Thesis advisor) / Westerhoff, Paul (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2021