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ABSTRACT The behavior of the fission products, as they are released from fission events during nuclear reaction, plays an important role in nuclear fuel performance. Fission product release can occur through grain boundary (GB) at low burnups; therefore, this study simulates the mass transport of fission gases in a 2-D

ABSTRACT The behavior of the fission products, as they are released from fission events during nuclear reaction, plays an important role in nuclear fuel performance. Fission product release can occur through grain boundary (GB) at low burnups; therefore, this study simulates the mass transport of fission gases in a 2-D GB network to look into the effects of GB characteristics on this phenomenon, with emphasis on conditions that can lead to percolation. A finite element model was created based on the microstructure of a depleted UO2 sample characterized by Electron Backscattering Diffraction (EBSD). The GBs were categorized into high (D2), low (D1) and bulk diffusivity (Dbulk) based on their misorientation angles and Coincident Site Lattice (CSL) types. The simulation was run using different diffusivity ratios (D2/Dbulk) ranging from 1 to 10^8. The model was set up in three ways: constant temperature case, temperature gradient effects and window methods that mimic the environments in a Light Water Reactor (LWR). In general, the formation of percolation paths was observed at a ratio higher than 10^4 in the measured GB network, which had a 68% fraction of high diffusivity GBs. The presence of temperature gradient created an uneven concentration distribution and decreased the overall mass flux. Finally, radial temperature and fission gas concentration profiles were obtained for a fuel pellet in operation using an approximate 1-D model. The 100 µm long microstructurally explicit model was used to simulate, to the scale of a real UO2 pellet, the mass transport at different radial positions, with boundary conditions obtained from the profiles. Stronger percolation effects were observed at the intermediate and periphery position of the pellet. The results also showed that highest mass flux happens at the edge of a pellet at steady state to accommodate for the sharp concentration drop.
ContributorsLim, Harn Chyi (Author) / Peralta, Pedro (Thesis advisor) / Dey, Sandwip (Committee member) / Sieradzki, Karl (Committee member) / Arizona State University (Publisher)
Created2011
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A full understanding of material behavior is important for the prediction of residual useful life of aerospace structures via computational modeling. In particular, the influence of rolling-induced anisotropy on fatigue properties has not been studied extensively and it is likely to have a meaningful effect. In this work, fatigue behavior

A full understanding of material behavior is important for the prediction of residual useful life of aerospace structures via computational modeling. In particular, the influence of rolling-induced anisotropy on fatigue properties has not been studied extensively and it is likely to have a meaningful effect. In this work, fatigue behavior of a wrought Al alloy (2024-T351) is studied using notched uniaxial samples with load axes along either the longitudinal or transverse direction, and center notched biaxial samples (cruciforms) with a uniaxial stress state of equivalent amplitude about the bore. Local composition and crystallography were quantified before testing using Energy Dispersive Spectroscopy and Electron Backscattering Diffraction. Interrupted fatigue testing at stresses close to yielding was performed on the samples to nucleate and propagate short cracks and nucleation sites were located and characterized using standard optical and Scanning Electron Microscopy. Results show that crack nucleation occurred due to fractured particles for longitudinal dogbone/cruciform samples; while transverse samples nucleated cracks by debonded and fractured particles. Change in crack nucleation mechanism is attributed to dimensional change of particles with respect to the material axes caused by global anisotropy. Crack nucleation from debonding reduced life till matrix fracture because debonded particles are sharper and generate matrix cracks sooner than their fractured counterparts. Longitudinal samples experienced multisite crack initiation because of reduced cross sectional areas of particles parallel to the loading direction. Conversely the favorable orientation of particles in transverse samples reduced instances of particle fracture eliminating multisite cracking and leading to increased fatigue life. Cyclic tests of cruciform samples showed that crack growth favors longitudinal and transverse directions with few instances of crack growth 45 degrees (diagonal) to the rolling direction. The diagonal crack growth is attributed to stronger influences of local anisotropy on crack nucleation. It was observed that majority of the time crack nucleation is governed by the mixed influences of global and local anisotropies. Measurements of crystal directions parallel to the load on main crack paths revealed directions clustered near the {110} planes and high index directions. This trend is attributed to environmental effects as a result of cyclic testing in air.
ContributorsMakaš, Admir (Author) / Peralta, Pedro D. (Thesis advisor) / Davidson, Joseph K. (Committee member) / Sieradzki, Karl (Committee member) / Arizona State University (Publisher)
Created2011
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The work presented in this thesis covers the synthesis and characterization of an ionomer that is applicable to zinc-air batteries. Polysulfone polymer is first chloromethylated and then quaternized to create an ion-conducting polymer. Nuclear magnetic resonance (NMR) spectra indicates that the degree of chloromethylation was 114%. The chemical and physical

The work presented in this thesis covers the synthesis and characterization of an ionomer that is applicable to zinc-air batteries. Polysulfone polymer is first chloromethylated and then quaternized to create an ion-conducting polymer. Nuclear magnetic resonance (NMR) spectra indicates that the degree of chloromethylation was 114%. The chemical and physical properties that were investigated include: the ionic conductivity, ion exchange capacity, water retention capacity, diameter and thickness swelling ratios, porosity, glass transition temperature, ionic conductivity enhanced by free salt addition, and the concentration and diffusivity of oxygen within the ionomer. It was found that the fully hydrated hydroxide form of the ionomer had a room temperature ionic conductivity of 39.92mS/cm while the chloride form had a room temperature ionic conductivity of 11.80mS/cm. The ion exchange capacity of the ionomer was found to be 1.022mmol/g. The water retention capacity (WRC) of the hydroxide form was found to be 172.6% while the chloride form had a WRC of 67.9%. The hydroxide form of the ionomer had a diameter swelling ratio of 34% and a thickness swelling ratio of 55%. The chloride form had a diameter swelling ratio of 32% and a thickness swelling ratio of 28%. The largest pore size in the ionomer was found to be 32.6nm in diameter. The glass transition temperature of the ionomer is speculated to be 344°C. A definite measurement could not be made. The room temperature ionic conductivity at 50% relative humidity was improved to 12.90mS/cm with the addition of 80% free salt. The concentration and diffusivity of oxygen in the ionomer was found to be 1.3 ±0.2mMol and (0.49 ±0.15)x10-5 cm2/s respectively. The ionomer synthesized in this research had material properties and performance that is comparable to other ionomers reported in the literature. This is an indication that this ionomer is suitable for further study and integration into a zinc-air battery. This thesis is concluded with suggestions for future research that is focused on improving the performance of the ionomer as well as improving the methodology.
ContributorsPadilla, Manuel (Author) / Friesen, Cody A (Thesis advisor) / Buttry, Daniel (Committee member) / Sieradzki, Karl (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Lithium-ion batteries can fail and catch fire when overcharged, exposed to high temperatures or short-circuited due to the highly flammable organic liquid used in the electrolyte. Using inorganic solid electrolyte materials can potentially improve the safety factor. Additionally, nanostructured electrolyte materials may further enhanced performance by taking advantage of their

Lithium-ion batteries can fail and catch fire when overcharged, exposed to high temperatures or short-circuited due to the highly flammable organic liquid used in the electrolyte. Using inorganic solid electrolyte materials can potentially improve the safety factor. Additionally, nanostructured electrolyte materials may further enhanced performance by taking advantage of their large aspect ratio. In this work, the synthesis of two promising nanostructured solid electrolyte materials was explored. Amorphous lithium niobate nanowires were synthesized through the decomposition of a niobium-containing complex in a structure-directing solvent using a reflux method. Lithium lanthanum titanate was obtained via solid state reaction with titanium oxide nanowires as the titanium precursor, but the nanowire morphology could not be preserved due to high temperature sintering. Hyperbranched potassium lanthanum titanate was synthesized through hydrothermal route. This was the first time that hyperbranched nanowires with perovskite structure were made without any catalyst or substrate. This result has the potential to be applied to other perovskite materials.
ContributorsYang, Ting (Author) / Chan, Candace K. (Thesis advisor) / Crozier, Peter A. (Committee member) / Sieradzki, Karl (Committee member) / Arizona State University (Publisher)
Created2012
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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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This thesis presents a study of Boron Nitride (BN) and Copper (Cu)/BN multilayer thin films in terms of synthesis, chemical, structural, morphological, and mechanical properties characterization. In this study, the influence of Ar/N₂ flow rate in synthesizing stoichiometric BN thin films via magnetron sputtering was investigated initially. Post magnetron

This thesis presents a study of Boron Nitride (BN) and Copper (Cu)/BN multilayer thin films in terms of synthesis, chemical, structural, morphological, and mechanical properties characterization. In this study, the influence of Ar/N₂ flow rate in synthesizing stoichiometric BN thin films via magnetron sputtering was investigated initially. Post magnetron sputtering, the crystalline nature and B:N stoichiometric ratio of deposited thin films were investigated by X-ray diffraction (XRD) and X-ray Photoelectron Spectroscopy (XPS) respectively. Thicknesses revealed by ellipsometry analysis for nearly stoichiometric B:N thin films and their corresponding deposition times were used for estimating BN interlayer deposition times during the deposition of Cu/BN multilayer thin films. To characterize the microstructure of the synthesized Cu/BN multilayer thin films, XRD and scanning electron microscopy (SEM) have been used. Finally, a comparison of nanoindentation measurements on pure Cu and Cu/BN multilayer thin films having different number of BN interlayers were used for studying the influence of BN interlayers on improving mechanical properties such as hardness and elastic modulus. The results show that the stoichiometry of BN thin films is dependent on the Ar/N₂ flow rate during magnetron sputtering. An optimal Ar/N₂ flow rate of 13:5 during deposition was required to achieve an approximately 1:1 B:N stoichiometry. Grazing incidence and powder XRD analysis on these stoichiometric BN thin films deposited at room temperature did not reveal a phase match when compared to hexagonal boron nitride (h-BN) and cubic boron nitride (c-BN) reference XRD patterns. For a BN thin film deposition time of 5 hours, a thickness of approximately 40 nm was achieved, as revealed by ellipsometry. XRD and microstructure analysis using scanning electron microscopy (SEM) on pure Cu and Cu/BN thin films showed that the Cu grain size in Cu/BN thin films is much finer than pure Cu thin films. Interestingly, nanoindentation measurements on pure Cu and Cu/BN thin films having a similar overall thickness demonstrated that hardness and Young’s modulus of the films were improved significantly when BN interlayers are present.
ContributorsCaner, Sumeyye (Author) / Rajagopalan, Jagannathan (Thesis advisor) / Oswald, Jay (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2023
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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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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
In the age of 5th and upcoming 6th generation fighter aircraft one key proponent of these impressive machines is the inclusion of stealth. This inclusion is demonstrated by thoughtful design pertaining to the shape of the aircraft and rigorous material selection. Both criteria aim to minimize the radar cross section

In the age of 5th and upcoming 6th generation fighter aircraft one key proponent of these impressive machines is the inclusion of stealth. This inclusion is demonstrated by thoughtful design pertaining to the shape of the aircraft and rigorous material selection. Both criteria aim to minimize the radar cross section of these aircraft over a wide bandwidth of frequencies corresponding to an ever-evolving field of radar technology. Stealth is both an offensive and defensive capability meaning that service men and women depend on this feature to carry out their missions, and to return home safely. The goal of this paper is to introduce a novel method to designing disordered two-phase composites with desired electromagnetic properties. This task is accomplished by employing the spatial point correlation function, specifically at the two-point level. Effective at describing the dispersion of phases within a two-phase system, the two-point correlation function serves as a statistical function that becomes a realizable target for heterogeneous composites. Simulated annealing is exercised to reconstruct two-phase composite microstructures that initially do not match their target function, followed by two separate experiments aimed at studying the impact of the provided inputs on its outcome. Once conditions for reconstructing highly accurate microstructures are identified, modifications are made to the target function to extract and compare dielectric constants associated with each microstructure. Both the real and imaginary components, which respectively affect wave propagation and attenuation, of the dielectric constants are plotted to illustrate their behavior with increasing wavenumber. Conclusions suggest that favorable values of the complex dielectric constant can be reverse-engineered via careful consideration of the two-point correlation function. Subsequently, corresponding microstructures of the composite can be simulated and then produced through 3-D printing for testing and practical applications.
ContributorsPlantz, Alex Chadewick (Author) / Jiao, Yang (Thesis advisor) / Zhuang, Houlong (Committee member) / Yang, Sui (Committee member) / Arizona State University (Publisher)
Created2024
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High-entropy alloys (HEAs) is a new class of materials which have been studied heavily due to their special mechanical properties. HEAs refers to alloys with multiple equimolar or nearly equimolar elements. HEAs show exceptional and attractive properties currently absent from conventional alloys, which make them the center of intense investigation.

High-entropy alloys (HEAs) is a new class of materials which have been studied heavily due to their special mechanical properties. HEAs refers to alloys with multiple equimolar or nearly equimolar elements. HEAs show exceptional and attractive properties currently absent from conventional alloys, which make them the center of intense investigation. HEAs obtain their properties from four core effects that they exhibit and most of the work on them have been dedicated to study their mechanical properties. In contrast, little or no research have gone into studying the functional or even thermal properties of HEAs. Some HEAs have also shown exceptional or very high melting points. According to the definition of HEAs, Si-Ge-Sn alloys with equal or comparable concentrations of the three group IV elements belong to the category of HEAs. Thus, the equimolar components of Si-Ge-Sn alloys probably allow their atomic structures to display the same fundamental effects of metallic HEAs. The experimental fabrication of such alloys has been proven to be very difficult, which is mainly due to differences between the properties of their constituent elements, as indicated from their binary phase diagrams. However, previous computational studies have shown that SiGeSn HEAs have some very interesting properties, such as high electrical conductivity, low thermal conductivity and semiconducting properties. In this work, going for a complete characterization of the SiGeSn HEA properties, the melting point of this alloy is studied using classical molecular dynamics (MD) simulations and density functional theory (DFT) calculations. The aim is to investigate the effects of high Sn content in this alloy on the melting point compared with the traditional SiGe alloys. Classical MD simulations results strongly indicates that none of the available empirical potentials is able to predict accurate or reasonable melting points for SiGeSn HEAs and most of its subsystems. DFT calculations results show that SiGeSn HEA have a melting point which represent the mean value of its constituent elements and that no special deviations are found. This work contributes to the study of SiGeSn HEA properties, which can serve as guidance before the successful experimental fabrication of this alloy.
ContributorsAlqaisi, Ahmad Madhat Odeh (Author) / Hong, Qi-Jun (Thesis advisor) / Zhuang, Houlong (Thesis advisor) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2023