This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students. 

Displaying 41 - 50 of 66
191492-Thumbnail Image.png
Description
Phase-field (PF) models are one of the most powerful tools to simulate microstructural evolution in metallic materials, polymers, and ceramics. However, existing PF approaches rely on rigorous mathematical model development, sophisticated numerical schemes, and high-performance computing for accuracy. Although recently developed surrogate microstructure models employ deep-learning techniques and reconstruction of

Phase-field (PF) models are one of the most powerful tools to simulate microstructural evolution in metallic materials, polymers, and ceramics. However, existing PF approaches rely on rigorous mathematical model development, sophisticated numerical schemes, and high-performance computing for accuracy. Although recently developed surrogate microstructure models employ deep-learning techniques and reconstruction of microstructures from lower-dimensional data, their accuracy is fairly limited as spatio-temporal information is lost in the pursuit of dimensional reduction. Given these limitations, a novel data-driven emulator (DDE) for extrapolation prediction of microstructural evolution is presented, which combines an image-based convolutional and recurrent neural network (CRNN) with tensor decomposition, while leveraging previously obtained PF datasets for training. To assess the robustness of DDE, the emulation sequence and the scaling behavior with phase-field simulations for several noisy initial states are compared. In conclusion, the effectiveness of the microstructure emulation technique is explored in the context of accelerating runtime, along with an emphasis on its trade-off with accuracy.Meanwhile, an interpolation DDE has also been tested, which is based on obtaining a low-dimensional representation of the microstructures via tensor decomposition and subsequently predicting the microstructure evolution in the low-dimensional space using Gaussian process regression (GPR). Once the microstructure predictions are obtained in the low-dimensional space, a hybrid input-output phase retrieval algorithm will be employed to reconstruct the microstructures. As proof of concept, the results on microstructure prediction for spinodal decomposition are presented, although the method itself is agnostic of the material parameters. Results show that GPR-based DDE model are able to predict microstructure evolution sequences that closely resemble the true microstructures (average normalized mean square of 6.78 × 10−7) at time scales half of that employed in obtaining training data. This data-driven microstructure emulator opens new avenues to predict the microstructural evolution by leveraging phase-field simulations and physical experimentation where the time resolution is often quite large due to limited resources and physical constraints, such as the phase coarsening experiments previously performed in microgravity. Future work will also be discussed and demonstrate the intended utilization of these two approaches for 3D microstructure prediction through their combined application.
ContributorsWu, Peichen (Author) / Ankit, Kumar (Thesis advisor) / Iquebal, Ashif (Committee member) / Jiao, Yang (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2024
153979-Thumbnail Image.png
Description
Dissimilar metal joints such as aluminum-steel joints are extensively used in automobile, naval and aerospace applications and these are subjected to corrosive environmental and mechanical loading resulting in eventual failure of the structural joints. In the case of aluminum alloys under aggressive environment, the damage accumulation is predominantly due to

Dissimilar metal joints such as aluminum-steel joints are extensively used in automobile, naval and aerospace applications and these are subjected to corrosive environmental and mechanical loading resulting in eventual failure of the structural joints. In the case of aluminum alloys under aggressive environment, the damage accumulation is predominantly due to corrosion and is accelerated in presence of other metals. During recent years several approaches have been employed to develop models to assess the metal removal rate in the case of galvanic corrosion. Some of these models are based on empirical methods such as regression analysis while others are based on quantification of the ongoing electrochemical processes. Here, a numerical model for solving the Nernst- Planck equation, which captures the electrochemical process, is implemented to predict the galvanic current distribution and, hence, the corrosion rate of a galvanic couple. An experimentally validated numerical model for an AE44 (Magnesium alloy) and mild steel galvanic couple, available in the literature, is extended to simulate the mechano- electrochemical process in order to study the effect of mechanical loading on the galvanic current density distribution and corrosion rate in AE44-mild steel galvanic couple through a multiphysics field coupling technique in COMSOL Multiphysics®. The model is capable of tracking moving boundariesy of the corroding constituent of the couple by employing Arbitrary Langrangian Eulerian (ALE) method.Results show that, when an anode is under a purely elastic deformation, there is no apparent effect of mechanical loading on the electrochemical galvanic process. However, when the applied tensile load is sufficient to cause a plastic deformation, the local galvanic corrosion activity at the vicinity of the interface is increased remarkably. The effect of other factors, such as electrode area ratios, electrical conductivity of the electrolyte and depth of the electrolyte, are studied. It is observed that the conductivity of the electrolyte significantly influences the surface profile of the anode, especially near the junction. Although variations in electrolyte depth for a given galvanic couple noticeably affect the overall corrosion, the change in the localized corrosion rate at the interface is minimal. Finally, we use the model to predict the current density distribution, rate of corrosion and depth profile of aluminum alloy 7075-stainless steel 316 galvanic joints, which are extensively used in maritime structures.
ContributorsMuthegowda, Nitin Chandra (Author) / Solanki, Kiran N (Thesis advisor) / Rykaczewski, Konrad (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2015
157723-Thumbnail Image.png
Description
Layered chalcogenides are a diverse class of crystalline materials that consist of covalently bound building blocks held together by van der Waals forces, including the transition metal dichalcogenides (TMDCs) and the pnictogen chalcogenides (PCs) among all. These materials, in particular, MoS2 which is the most widely studied TMDC material, have

Layered chalcogenides are a diverse class of crystalline materials that consist of covalently bound building blocks held together by van der Waals forces, including the transition metal dichalcogenides (TMDCs) and the pnictogen chalcogenides (PCs) among all. These materials, in particular, MoS2 which is the most widely studied TMDC material, have attracted significant attention in recent years due to their unique physical, electronic, optical, and chemical properties that depend on the number of layers. Due to their high aspect ratios and extreme thinness, 2D materials are sensitive to modifications via chemistry on their surfaces. For instance, covalent functionalization can be used to robustly modify the electronic properties of 2D materials, and can also be used to attach other materials or structures. Metal adsorption on the surfaces of 2D materials can also tune their electronic structures, and can be used as a strategy for removing metal contaminants from water. Thus, there are many opportunities for studying the fundamental surface interactions of 2D materials and in particular the TMDCs and PCs.

The work reported in this dissertation represents detailed fundamental studies of the covalent functionalization and metal adsorption behavior of layered chalcogenides, which are two significant aspects of the surface interactions of 2D materials. First, we demonstrate that both the Freundlich and Temkin isotherm models, and the pseudo-second-order reaction kinetics model are good descriptors of the reaction due to the energetically inhomogeneous surface MoS2 and the indirect adsorbate-adsorbate interactions from previously attached nitrophenyl (NP) groups. Second, the covalent functionalization using aryl diazonium salts is extended to nanosheets of other representative TMDC materials MoSe2, WS2, and WSe2, and of the representative PC materials Bi2S3 and Sb2S3, demonstrated using atomic force microscopy (AFM) imaging and Fourier transform infrared spectroscopy (FTIR). Finally, using AFM and X-ray photoelectron spectroscopy (XPS), it is shown that Pb, Cd Zn and Co form nanoclusters on the MoS2 surface without affecting the structure of the MoS2 itself. The metals can also be thermally desorbed from MoS2, thus suggesting a potential application as a reusable water purification technology.
ContributorsLi, Duo, Ph.D (Author) / Wang, Qing Hua (Thesis advisor) / Green, Alexander A. (Committee member) / Chan, Candace K. (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2019
157787-Thumbnail Image.png
Description
Niobium is the primary material for fabricating superconducting radio-frequency (SRF) cavities. However, presence of impurities and defects degrade the superconducting behavior of niobium twofold, first by nucleating non-superconducting phases and second by increasing the residual surface resistance of cavities. In particular, niobium absorbs hydrogen during cavity fabrication and promotes precipitation

Niobium is the primary material for fabricating superconducting radio-frequency (SRF) cavities. However, presence of impurities and defects degrade the superconducting behavior of niobium twofold, first by nucleating non-superconducting phases and second by increasing the residual surface resistance of cavities. In particular, niobium absorbs hydrogen during cavity fabrication and promotes precipitation of non-superconducting niobium hydride phases. Additionally, magnetic flux trapping at defects leads to a normal conducting (non-superconducting) core which increases surface resistance and negatively affects niobium performance for superconducting applications. However, undelaying mechanisms related to hydride formation and dissolution along with defect interaction with magnetic fields is still unclear. Therefore, this dissertation aims to investigate the role of defects and impurities on functional properties of niobium for SRF cavities using first-principles methods.

Here, density functional theory calculations revealed that nitrogen addition suppressed hydrogen absorption interstitially and at grain boundaries, and it also decreased the energetic stability of niobium hydride precipitates present in niobium. Further, hydrogen segregation at the screw dislocation was observed to transform the dislocation core structure and increase the barrier for screw dislocation motion. Valence charge transfer calculations displayed a strong tendency of nitrogen to accumulate charge around itself, thereby decreasing the strength of covalent bonds between niobium and hydrogen leading to a very unstable state for interstitial hydrogen and hydrides. Thus, presence of nitrogen during processing plays a critical role in controlling hydride precipitation and subsequent SRF properties.

First-principles methods were further implemented to gain a theoretical perspective about the experimental observations that lattice defects are effective at trapping magnetic flux in high-purity superconducting niobium. Full-potential linear augmented plane-wave methods were used to analyze the effects of magnetic field on the superconducting state surrounding these defects. A considerable amount of trapped flux was obtained at the dislocation core and grain boundaries which can be attributed to significantly different electronic structure of defects as compared to bulk niobium. Electron redistribution at defects enhances non-paramagnetic effects that perturb superconductivity, resulting in local conditions suitable for flux trapping. Therefore, controlling accumulation or depletion of charge at the defects could mitigate these tendencies and aid in improving superconductive behavior of niobium.
ContributorsGarg, Pulkit (Author) / Solanki, Kiran N (Thesis advisor) / Jiao, Yang (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2019
157979-Thumbnail Image.png
Description
Nanomaterials that exhibit enzyme-like catalytic activity or nanozymes have many advantages compared to biological enzymes such as low cost of production and high stability. There is a substantial interest in studying two-dimensional materials due to their exceptional properties. Hafnium diboride is a type of two-dimensional material and belongs to the

Nanomaterials that exhibit enzyme-like catalytic activity or nanozymes have many advantages compared to biological enzymes such as low cost of production and high stability. There is a substantial interest in studying two-dimensional materials due to their exceptional properties. Hafnium diboride is a type of two-dimensional material and belongs to the metal diborides family made of hexagonal layers of boron atoms separated by metal layers. In this work, the peroxidase-like activity of hafnium diboride nanoflakes dispersed in the block copolymer F77 was discovered for the first time. The kinetics, mechanisms and catalytic performance towards the oxidation of the chromogenic substrate 3,3,5,5-tetramethylbenzidine (TMB) in the presence of hydrogen peroxide are presented in this work. Kinetic parameters were determined by steady-state kinetics and a comparison with other nanozymes is given. Results show that the HfB2/F77 nanozyme possesses a unique combination of unusual high affinity towards hydrogen peroxide and high activity per cost. These findings are important for applications that involve reactions with hydrogen peroxide.
ContributorsMatar Abed, Mahmoud (Author) / Wang, Qing Hua (Thesis advisor) / Green, Alexander (Thesis advisor) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2019
158656-Thumbnail Image.png
Description
Transition metal di- and tri-halides (TMH) have recently gathered research attention owing to their intrinsic magnetism all the way down to their two-dimensional limit. 2D magnets, despite being a crucial component for realizing van der Waals heterostructures and devices with various functionalities, were not experimentally proven until very recently in

Transition metal di- and tri-halides (TMH) have recently gathered research attention owing to their intrinsic magnetism all the way down to their two-dimensional limit. 2D magnets, despite being a crucial component for realizing van der Waals heterostructures and devices with various functionalities, were not experimentally proven until very recently in 2017. The findings opened up enormous possibilities for studying new quantum states of matter that can enable potential to design spintronic, magnetic memory, data storage, sensing, and topological devices. However, practical applications in modern technologies demand materials with various physical and chemical properties such as electronic, optical, structural, catalytic, magnetic etc., which cannot be found within single material systems. Considering that compositional modifications in 2D systems lead to significant changes in properties due to the high anisotropy inherent to their crystallographic structure, this work focuses on alloying of TMH compounds to explore the potentials for tuning their properties. In this thesis, the ternary cation alloys of Co(1-x)Ni(x)Cl(2) and Mo(1-x)Cr(x)Cl(3) were synthesized via chemical vapor transport at a various stoichiometry. Their compositional, structural, and magnetic properties were studied using Energy Dispersive Spectroscopy, Raman Spectroscopy, X-Ray Diffraction, and Vibrating Sample Magnetometry. It was found that completely miscible ternary alloys of Co(1-x)Ni(x)Cl(2) show an increasing Néel temperature with nickel concentration. The Mo(1-x)Cr(x)Cl(3) alloy shows potential magnetic phase changes induced by the incorporation of molybdenum species within the host CrCl3 lattice. Magnetic measurements give insight into potential antiferromagnetic to ferromagnetic transition with molybdenum incorporation, accompanied by a shift in the magnetic easy-axis from parallel to perpendicular. Phase separation was found in the Fe(1-x)Cr(x)Cl(3) ternary alloy indicating that crystallographic structure compatibility plays an essential role in determining the miscibility of two parent compounds. Alloying across two similar (TMH) compounds appears to yield predictable results in properties as in the case of Co(1-x)Ni(x)Cl(2), while more exotic transitions, as in the case of Mo(1-x)Cr(x)Cl(3), can emerge by alloying dissimilar compounds. When dissimilarity reaches a certain limit, as with Fe(1-x)Cr(x)Cl(3), phase separation becomes more favorable. Future studies focusing on magnetic and structural phase transitions will reveal more insight into the effect of alloying in these TMH systems.
ContributorsKolari, Pranvera (Author) / Tongay, Sefaattin (Thesis advisor) / Jiao, Yang (Committee member) / Muhich, Christopher (Committee member) / Arizona State University (Publisher)
Created2020
158750-Thumbnail Image.png
Description
Polyurea is a highly versatile material used in coatings and armor systems to protect against extreme conditions such as ballistic impact, cavitation erosion, and blast loading. However, the relationships between microstructurally-dependent deformation mechanisms and the mechanical properties of polyurea are not yet fully understood, especially under extreme conditions. In this

Polyurea is a highly versatile material used in coatings and armor systems to protect against extreme conditions such as ballistic impact, cavitation erosion, and blast loading. However, the relationships between microstructurally-dependent deformation mechanisms and the mechanical properties of polyurea are not yet fully understood, especially under extreme conditions. In this work, multi-scale coarse-grained models are developed to probe molecular dynamics across the wide range of time and length scales that these fundamental deformation mechanisms operate. In the first of these models, a high-resolution coarse-grained model of polyurea is developed, where similar to united-atom models, hydrogen atoms are modeled implicitly. This model was trained using a modified iterative Boltzmann inversion method that dramatically reduces the number of iterations required. Coarse-grained simulations using this model demonstrate that multiblock systems evolve to form a more interconnected hard phase, compared to the more interrupted hard phase composed of distinct ribbon-shaped domains found in diblock systems. Next, a reactive coarse-grained model is developed to simulate the influence of the difference in time scales for step-growth polymerization and phase segregation in polyurea. Analysis of the simulated cured polyurea systems reveals that more rapid reaction rates produce a smaller diameter ligaments in the gyroidal hard phase as well as increased covalent bonding connecting the hard domain ligaments as evidenced by a larger fraction of bridging segments and larger mean radius of gyration of the copolymer chains. The effect that these processing-induced structural variations have on the mechanical properties of the polymer was tested by simulating uniaxial compression, which revealed that the higher degree of hard domain connectivity leads to a 20% increase in the flow stress. A hierarchical multiresolution framework is proposed to fully link coarse-grained molecular simulations across a broader range of time scales, in which a family of coarse-grained models are developed. The models are connected using an incremental reverse–mapping scheme allowing for long time scale dynamics simulated at a highly coarsened resolution to be passed all the way to an atomistic representation.
ContributorsLiu, Minghao (Author) / Oswald, Jay (Thesis advisor) / Muhich, Christopher (Committee member) / Jiang, Hanqing (Committee member) / Peralta, Pedro (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2020
158739-Thumbnail Image.png
Description
The structural and electronic properties of compositionally complex semiconductors have long been of both theoretical interest and engineering importance. As a new class of materials with an intrinsic compositional complexity, medium entropy alloys (MEAs) are immensely studied mainly for their excellent mechanical properties. The electronic properties of MEAs, however, are

The structural and electronic properties of compositionally complex semiconductors have long been of both theoretical interest and engineering importance. As a new class of materials with an intrinsic compositional complexity, medium entropy alloys (MEAs) are immensely studied mainly for their excellent mechanical properties. The electronic properties of MEAs, however, are less well investigated. In this thesis, various properties such as electronic, spin, and thermal properties of two three-dimensional (3D) and two two-dimensional (2D) compositionally complex semiconductors are demonstrated to have promising various applications in photovoltaic, thermoelectric, and spin quantum bits (qubits).3D semiconducting Si-Ge-Sn and C3BN alloys is firstly introduced. Density functional theory (DFT) calculations and Monte Carlo simulations show that the Si1/3Ge1/3Sn1/3 MEA exhibits a large local distortion effect yet no chemical short-range order. Single vacancies in this MEA can be stabilized by bond reformations while the alloy retains semiconducting. DFT and molecular dynamics calculations predict that increasing the compositional disorder in SiyGeySnx MEAs enhances their electrical conductivity while weakens the thermal conductivity at room temperature, making the SiyGeySnx MEAs promising functional materials for thermoelectric devices. Furthermore, the nitrogen-vacancy (NV) center analog in C3BN (NV-C3BN) is studied to explore its applications in quantum computers. This analog possesses similar properties to the NV center in diamond such as a highly localized spin density and strong hyperfine interactions, making C3BN suitable for hosting spin qubits. The analog also displays two zero-phonon-line energies corresponding to wavelengths close to the ideal telecommunication band width, useful for quantum communications.
2D semiconducting transition metal chalcogenides (TMCs) and PtPN are also investigated. The quaternary compositionally complex TMCs show tunable properties such as in-plane lattice constants, band gaps, and band alignment, using a high through-put workflow from DFT calculations in conjunction with the virtual crystal approximation. A novel 2D semiconductor PtPN of direct bandgap is also predicted, based on pentagonal tessellation.
The work in the thesis offers guidance to the experimental realization of these novel semiconductors, which serve as valuable prototypes of other compositionally complex systems from other elements.
ContributorsWang, Duo (Author) / Zhuang, Houlong (Thesis advisor) / Singh, Arunima (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2020
158742-Thumbnail Image.png
Description
Single-layer pentagonal materials have received limited attention compared with their counterparts with hexagonal structures. They are two-dimensional (2D) materials with pentagonal structures, that exhibit novel electronic, optical, or magnetic properties. There are 15 types of pentagonal tessellations which allow plenty of options for constructing 2D pentagonal lattices. Few of them

Single-layer pentagonal materials have received limited attention compared with their counterparts with hexagonal structures. They are two-dimensional (2D) materials with pentagonal structures, that exhibit novel electronic, optical, or magnetic properties. There are 15 types of pentagonal tessellations which allow plenty of options for constructing 2D pentagonal lattices. Few of them have been explored theoretically or experimentally. Studying this new type of 2D materials with density functional theory (DFT) will inspire the discovery of new 2D materials and open up applications of these materials in electronic and magnetic devices.In this dissertation, DFT is applied to discover novel 2D materials with pentagonal structures. Firstly, I examine the possibility of forming a 2D nanosheet with the vertices of type 15 pentagons occupied by boron, silicon, phosphorous, sulfur, gallium, germanium or tin atoms. I obtain different rearranged structures such as a single-layer gallium sheet with triangular patterns. Then the exploration expands to other 14 types of pentagons, leading to the discoveries of carbon nanosheets with Cairo tessellation (type 2/4 pentagons) and other patterns. The resulting 2D structures exhibit diverse electrical properties. Then I reveal the hidden Cairo tessellations in the pyrite structures and discover a family of planar 2D materials (such as PtP2), with a chemical formula of AB2 and space group pa ̄3. The combination of DFT and geometries opens up a novel route for the discovery of new 2D materials. Following this path, a series of 2D pentagonal materials such as 2D CoS2 are revealed with promising electronic and magnetic applications. Specifically, the DFT calculations show that CoS2 is an antiferromagnetic semiconductor with a band gap of 2.24 eV, and a N ́eel temperature of about 20 K. In order to enhance the superexchange interactions between the ions in this binary compound, I explore the ternary 2D pentagonal material CoAsS, that lacks the inversion symmetry. I find out CoAsS exhibits a higher Curie temperature of 95 K and a sizable piezoelectricity (d11=-3.52 pm/V). In addition to CoAsS, 34 ternary 2D pentagonal materials are discovered, among which I focus on FeAsS, that is a semiconductor showing strong magnetocrystalline anisotropy and sizable Berry curvature. Its magnetocrystalline anisotropy energy is 440 μeV/Fe ion, higher than many other 2D magnets that have been found.
Overall, this work not only provides insights into the structure-property relationship of 2D pentagonal materials and opens up a new route of studying 2D materials by combining geometry and computational materials science, but also shows the potential applications of 2D pentagonal materials in electronic and magnetic devices.
ContributorsLiu, Lei (Author) / Zhuang, Houlong (Thesis advisor) / Singh, Arunima (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2020
158652-Thumbnail Image.png
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

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.
ContributorsSundaram Singaravelu, Arun Sundar (Author) / Chawla, Nikhilesh (Thesis advisor) / Emady, Heather (Committee member) / Jiao, Yang (Committee member) / Arizona State University (Publisher)
Created2020