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
Additive manufacturing (AM) describes an array of methods used to create a 3D object layer by layer. The increasing popularity of AM in the past decade has been due to its demonstrated potential to increase design flexibility, produce rapid prototypes, and decrease material waste. Temporary supports are an

Additive manufacturing (AM) describes an array of methods used to create a 3D object layer by layer. The increasing popularity of AM in the past decade has been due to its demonstrated potential to increase design flexibility, produce rapid prototypes, and decrease material waste. Temporary supports are an inconvenient necessity in many metal AM parts. These sacrificial structures are used to fabricate large overhangs, anchor the part to the build substrate, and provide a heat pathway to avoid warping. Polymers AM has addressed this issue by using support material that is soluble in an electrolyte that the base material is not. In contrast, metals AM has traditionally approached support removal using time consuming, costly methods such as electrical discharge machining or a dremel.

This work introduces dissolvable supports to single- and multi-material metals AM. The multi-material approach uses material choice to design a functionally graded material where corrosion is the functionality being varied. The single-material approach is the primary focus of this thesis, leveraging already common post-print heat treatments to locally alter the microstructure near the surface. By including a sensitizing agent in the ageing heat treatment, carbon is diffused into the part decreasing the corrosion resistance to a depth equal to at least half the support thickness. In a properly chosen electrolyte, this layer is easily chemically, or electrochemically removed. Stainless steel 316 (SS316) and Inconel 718 are both investigated to study this process using two popular alloys. The microstructure evolution and corrosion properties are investigated for both. For SS316, the effect of applied electrochemical potential is investigated to describe the varying corrosion phenomena induced, and the effect of potential choice on resultant roughness. In summary, a new approach to remove supports from metal AM parts is introduced to decrease costs and further the field of metals AM by expanding the design space.
ContributorsLefky, Christopher (Author) / Hildreth, Owen (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Azeredo, Bruno (Committee member) / Rykaczewski, Konrad (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Fatigue is a degradation process of materials that would lead to failure when materials are subjected to cyclic loadings. During past centuries, various of approaches have been proposed and utilized to help researchers understand the underlying theories of fatigue behavior of materials, as well as design engineering structures so that

Fatigue is a degradation process of materials that would lead to failure when materials are subjected to cyclic loadings. During past centuries, various of approaches have been proposed and utilized to help researchers understand the underlying theories of fatigue behavior of materials, as well as design engineering structures so that catastrophic disasters that arise from fatigue failure could be avoided. The stress-life approach is the most classical way that academia applies to analyze fatigue data, which correlates the fatigue lifetime with stress amplitudes during cyclic loadings. Fracture mechanics approach is another well-established way, by which people regard the cyclic stress intensity factor as the driving force during fatigue crack nucleation and propagation, and numerous models (such as the well-known Paris’ law) are developed by researchers.

The significant drawback of currently widely-used fatigue analysis approaches, nevertheless, is that they are all cycle-based, limiting researchers from digging into sub-cycle regime and acquiring real-time fatigue behavior data. The missing of such data further impedes academia from validating hypotheses that are related to real-time observations of fatigue crack nucleation and growth, thus the existence of various phenomena, such as crack closure, remains controversial.

In this thesis, both classical stress-life approach and fracture-mechanics-based approach are utilized to study the fatigue behavior of alloys. Distinctive material characterization instruments are harnessed to help collect and interpret key data during fatigue crack growth. Specifically, an investigation on the sub-cycle fatigue crack growth behavior is enabled by in-situ SEM mechanical testing, and a non-uniform growth mechanism within one loading cycle is confirmed by direct observation as well as image interpretation. Predictions based on proposed experimental procedure and observations show good match with cycle-based data from references, which indicates the credibility of proposed methodology and model, as well as their capability of being applied to a wide range of materials.
ContributorsLiu, Siying (Author) / Liu, Yongming (Thesis advisor) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures

Advanced material systems refer to materials that are comprised of multiple traditional constituents but complex microstructure morphologies, which lead to their superior properties over conventional materials. This dissertation is motivated by the grand challenge in accelerating the design of advanced material systems through systematic optimization with respect to material microstructures or processing settings. While optimization techniques have mature applications to a large range of engineering systems, their application to material design meets unique challenges due to the high dimensionality of microstructures and the high costs in computing process-structure-property (PSP) mappings. The key to addressing these challenges is the learning of material representations and predictive PSP mappings while managing a small data acquisition budget. This dissertation thus focuses on developing learning mechanisms that leverage context-specific meta-data and physics-based theories. Two research tasks will be conducted: In the first, we develop a statistical generative model that learns to characterize high-dimensional microstructure samples using low-dimensional features. We improve the data efficiency of a variational autoencoder by introducing a morphology loss to the training. We demonstrate that the resultant microstructure generator is morphology-aware when trained on a small set of material samples, and can effectively constrain the microstructure space during material design. In the second task, we investigate an active learning mechanism where new samples are acquired based on their violation to a theory-driven constraint on the physics-based model. We demonstrate using a topology optimization case that while data acquisition through the physics-based model is often expensive (e.g., obtaining microstructures through simulation or optimization processes), the evaluation of the constraint can be far more affordable (e.g., checking whether a solution is optimal or equilibrium). We show that this theory-driven learning algorithm can lead to much improved learning efficiency and generalization performance when such constraints can be derived. The outcomes of this research is a better understanding of how physics knowledge about material systems can be integrated into machine learning frameworks, in order to achieve more cost-effective and reliable learning of material representations and predictive models, which are essential to accelerate computational material design.
ContributorsCang, Ruijin (Author) / Ren, Yi (Thesis advisor) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Nian, Qiong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Polymer fibers have broad applications in wearable electronics, bulletproof vests, batteries, fuel cells, filters, electrodes, conductive wires, and biomedical materials. Polymer fibers display light density and flexibility but are mostly weak and compliant. The ceramic, metallic, and carbon nanoparticles have been frequently included in polymers for fabricating continuous, durable, and

Polymer fibers have broad applications in wearable electronics, bulletproof vests, batteries, fuel cells, filters, electrodes, conductive wires, and biomedical materials. Polymer fibers display light density and flexibility but are mostly weak and compliant. The ceramic, metallic, and carbon nanoparticles have been frequently included in polymers for fabricating continuous, durable, and functional composite fibers. Nanoparticles display large specific areas, low defect density and can transfer their superior properties to polymer matrices. The main focus of this thesis is to design, fabricate and characterize the polymer
anocarbon composite fibers with unique microstructures and improved mechanical/thermal performance. The dispersions and morphologies of graphene nanoplatelets (GNPs), the interactions with polyvinyl alcohol (PVA) molecules and their influences on fiber properties are studied. The fibers were fabricated using a dry-jet wet spinning method with engineered spinneret design. Three different structured fibers were fabricated, namely, one-phase polymer fiber (1-phase), two-phase core-shell composite fiber (2-phase), and three-phase co-axial composite fiber (3-phase). These polymer or composite fibers were processed at three stages with drawing temperatures of 100˚C, 150˚C, and 200˚C. Different techniques including the mechanical tester, wide-angle X-Ray diffraction (WAXD), scanning electron microscope (SEM), thermogravimetric analysis (TGA), and differential scanning calorimeter (DSC) have been used to characterize the fiber microstructures and properties.
ContributorsVerma, Rahul (Author) / Song, Kenan (Thesis advisor) / Jiang, Hanqing (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Laser powder bed fusion (LPBF) additive manufacturing (AM) has received widespread attention due to its ability to produce parts with complicated design and better surface finish compared to other additive techniques. LPBF uses a laser heat source to melt layers of powder particles and manufactures a part based on the

Laser powder bed fusion (LPBF) additive manufacturing (AM) has received widespread attention due to its ability to produce parts with complicated design and better surface finish compared to other additive techniques. LPBF uses a laser heat source to melt layers of powder particles and manufactures a part based on the CAD design. This process can benefit significantly through computational modeling. The objective of this thesis was to understand the thermal transport, and fluid flow phenomena of the process, and to optimize the main process parameters such as laser power and scan speed through a combination of computational, experimental, and statistical analysis. A multi-physics model was built using to model temperature profile, bead geometry and elemental evaporation in powder bed process using a non-gaussian interaction between laser heat source and metallic powder. Owing to the scarcity of thermo-physical properties of metallic powders in literature, thermal conductivity, diffusivity, and heat capacity was experimentally tested up to a temperature of 1400 degrees C. The values were used in the computational model, which improved the results significantly. The computational work was also used to assess the impact of fluid flow around melt pool. Dimensional analysis was conducted to determine heat transport mode at various laser power/scan speed combinations. Convective heat flow proved to be the dominant form of heat transfer at higher energy input due to violent flow of the fluid around the molten region, which can also create keyhole effect. The last part of the thesis focused on gaining useful information about several features of the bead area such as contact angle, porosity, voids and melt pool that were obtained using several combinations of laser power and scan speed. These features were quantified using process learning, which was then used to conduct a full factorial design that allows to estimate the effect of the process parameters on the output features. Both single and multi-response analysis are applied to analyze the output response. It was observed that laser power has more influential effect on all the features. Multi response analysis showed 150 W laser power and 200 mm/s produced bead with best possible features.
ContributorsAhsan, Faiyaz (Author) / Ladani, Leila (Thesis advisor) / Razmi, Jafar (Committee member) / Kwon, Beomjin (Committee member) / Nian, Qiong (Committee member) / Zhuang, Houlong (Committee member) / Arizona State University (Publisher)
Created2021
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Description
High-temperature mechanical behaviors of metal alloys and underlying microstructural variations responsible for such behaviors are essential areas of interest for many industries, particularly for applications such as jet engines. Anisotropic grain structures, change of preferred grain orientation, and other transformations of grains occur both during metal powder bed fusion additive

High-temperature mechanical behaviors of metal alloys and underlying microstructural variations responsible for such behaviors are essential areas of interest for many industries, particularly for applications such as jet engines. Anisotropic grain structures, change of preferred grain orientation, and other transformations of grains occur both during metal powder bed fusion additive manufacturing processes, due to variation of thermal gradient and cooling rates, and afterward during different thermomechanical loads, which parts experience in their specific applications, could also impact its mechanical properties both at room and high temperatures. In this study, an in-depth analysis of how different microstructural features, such as crystallographic texture, grain size, grain boundary misorientation angles, and inherent defects, as byproducts of electron beam powder bed fusion (EB-PBF) AM process, impact its anisotropic mechanical behaviors and softening behaviors due to interacting mechanisms. Mechanical testing is conducted for EB-PBF Ti6Al4V parts made at different build orientations up to 600°C temperature. Microstructural analysis using electron backscattered diffraction (EBSD) is conducted on samples before and after mechanical testing to understand the interacting impact that temperature and mechanical load have on the activation of certain mechanisms. The vertical samples showed larger grain sizes, with an average of 6.6 µm, a lower average misorientation angle, and subsequently lower strength values than the other two horizontal samples. Among the three strong preferred grain orientations of the α phases, <1 1 2 ̅ 1> and <1 1 2 ̅ 0> were dominant in horizontally built samples, whereas the <0 0 0 1> was dominant in vertically built samples. Thus, strong microstructural variation, as observed among different EB-PBF Ti6Al4V samples, mainly resulted in anisotropic behaviors. Furthermore, alpha grain showed a significant increase in average grain size for all samples with the increasing test temperature, especially from 400°C to 600°C, indicating grain growth and coarsening as potential softening mechanisms along with temperature-induced possible dislocation motion. The severity of internal and external defects on fatigue strength has been evaluated non-destructively using quantitative methods, i.e., Murakami’s square root of area parameter model and Basquin’s model, and the external surface defects were rendered to be more critical as potential crack initiation sites.
ContributorsMian, Md Jamal (Author) / Ladani, Leila (Thesis advisor) / Razmi, Jafar (Committee member) / Shuaib, Abdelrahman (Committee member) / Mobasher, Barzin (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2022
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Description
The purpose of this study was to comprehend the global warming potential (GWP), cost variability, and competitiveness of steel with rising carbon taxes. Aluminum, glass fiber composite, and carbon fiber composite were chosen as competing materials. In order to compare the aforementioned factors, the GWP of several processes to produce

The purpose of this study was to comprehend the global warming potential (GWP), cost variability, and competitiveness of steel with rising carbon taxes. Aluminum, glass fiber composite, and carbon fiber composite were chosen as competing materials. In order to compare the aforementioned factors, the GWP of several processes to produce steel, aluminum, and fiber composites was examined. Cost analyses of various methods were also carried out to determine their viability. Energy consumption data for each of the paths under consideration were taken from the literature for the study. To get the consistent GWP for traditional and decarbonized scenarios, the required energy is multiplied with corresponding energy source (natural gas or electricity). Even after accounting for the carbon tax and the weight-reduction factor, the results show that steel still has the lowest production costs, followed by aluminum, while fiber composites remain the most costly. EAF- steel and secondary aluminum has least GWP followed by H2-DRI (Hydrogen- Direct Reduced Iron)steel and NG-DRI (Natural Gas- Direct Reduced Iron) steel with carbon capture and storage (CCS). The state of art technology for glass fiber reinforced composite also emits less carbon dioxide but the cost of production is still high. Carbon fiber reinforced composite emits most carbon dioxide and is least economical.
ContributorsRajulwar, Vaishnavi Vijay (Author) / Seetharaman, Sridhar (Thesis advisor) / Emady, Heather (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Stereolithography (SLA) is an innovative additive manufacturing technique that has gained immense popularity in recent times due to its ability to produce complex and precise three-dimensional objects. However, the quality of the final product depends on the stability and homogeneity of the photocurable metallic ink used, which is crucial for

Stereolithography (SLA) is an innovative additive manufacturing technique that has gained immense popularity in recent times due to its ability to produce complex and precise three-dimensional objects. However, the quality of the final product depends on the stability and homogeneity of the photocurable metallic ink used, which is crucial for manufacturing high-quality parts with good surface finish and higher density. To achieve homogeneity in the photocurable metallic resin, the study conducted on optimizing the printing ink for ultrafast layer less fabrication of 3D metal objects investigated the effectiveness of different dispersants such as KH 560, Triton X-100, BYK 2013, BYK 2030, and BYK 111. The use of dispersants plays a vital role in optimizing the ink and enhancing the surface finish and density of the final product. The rheology results showed that the appropriate dispersant has the potential to improve the properties of the printing ink and benefit the integrity of the printed green bodies and their surface finish. By using the optimized suspension, the study was able to fabricate parts with high metallic loading at an ultrafast speed using the Continuous Liquid Interface Production technique. FTIR analysis, sedimentation testing, and rheology study has been carried out which demonstrates the effects of the utilization of various dispersants optimally to improve the homogeneity and manufactured part’s integrity. Power law has been used to understand the viscosity behavior of dispersants in a photocurable ink with copper sulfate keeping the parameters such as shearing rate, stress, and torque intact. The microscopic images of the sintered parts showed high precision and an extremely smooth surface finish, which underscores the technique's potential to produce high-quality 3D metal objects. The solubility of dispersants significantly influenced the structural quality after washing and debinding processes. This study provides valuable information to design photocurable metallic suspensions for metal salts like copper sulfate pentahydrate.
ContributorsVerma, Harsh Pyarelal (Author) / Li, Xiangjia (Thesis advisor) / Nian, Qiong (Committee member) / Xie, Renxuan (Committee member) / Arizona State University (Publisher)
Created2023
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Description
Nanomaterials redefine the lens through which the world is viewed today. The miniaturization of devices and systems to the nanoscale explodes the realm of what is possible as the interactions with neighboring atoms and molecules increase. This interactivity creates ripple effects that lead to superior mechanical, thermal, electrical, and optical

Nanomaterials redefine the lens through which the world is viewed today. The miniaturization of devices and systems to the nanoscale explodes the realm of what is possible as the interactions with neighboring atoms and molecules increase. This interactivity creates ripple effects that lead to superior mechanical, thermal, electrical, and optical properties that are highly desired across several industries. Two-dimensional (2D) materials are a branch of this family, and the focus of this paper revolves around a recent addition to this category called MXenes. The versatile properties of these 2D nanomaterials have made them unique, as they have the desired performance that can be utilized in several industries, especially energy management, wastewater treatment, and microelectronic devices. Followed by the MAX phase synthesis, hydrofluoric (HF) acid has been the primary etchant utilized to derive these 2D nanoparticles. However, alternative etchants via reactions are desirable to achieve similar selective etching without involving highly toxic HF. Therefore, this study investigated MXene synthesis and applications in 3D printing, followed by the formation of the precursor MAX, an optimized in-situ etching method, and streamlined post-etching processes to maximize 2D MXene yield. The etched powders were then analyzed using scanning electron microscopy (SEM), x-ray diffraction (XRD), atomic force microscopy (AFM), and energy-dispersive x-ray spectroscopy (EDS) characterization methods to verify and validate the MXene dimensions, chemistry, and crystal structures. Simple applications, such as the dispersion feasibility for customizing micropatterns via 3D printing, were also demonstrated as examples. Finally, this research showed the simple processing of 2D MXenes and their potential in structural support, heat dissipation, microelectronics, optical meta-surfaces, and other areas.
ContributorsFagade, Mofetoluwa (Author) / Song, Kenan (Thesis advisor) / Kwon, Beomjin (Committee member) / Nian, Qiong (Committee member) / Arizona State University (Publisher)
Created2023
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Description
This dissertation is focused on the rheology scaling of metal particle reinforced polymermatrix composite made of solid and nanoporous metal powders to enable their continuous 3D printing at high (>60vol%) metal content. There remained a specific knowledge gap on how to predict successful extrusion with densely packed metals by utilizing their suspension melt

This dissertation is focused on the rheology scaling of metal particle reinforced polymermatrix composite made of solid and nanoporous metal powders to enable their continuous 3D printing at high (>60vol%) metal content. There remained a specific knowledge gap on how to predict successful extrusion with densely packed metals by utilizing their suspension melt rheological properties. In the first project, the scaling of the dynamic viscosity of melt-extrudate filaments made of Polylactic acid (PLA) and gas-atomized solid NiCu powders was studied as a function of the metal’s volumetric packing and feedstock pre-mixing strategies and correlated to its extrudability performance, which fitted well with the Krieger-Dougherty analytical model. 63.4 vol% Filaments were produced by employing solution-mixing strategy to reduce sintered part porosity and shrinkage. After sintering, the linear shrinkage dropped by 76% compared to the physical mixing. By characterizing metal particle reinforced polymer matrix composite feedstock via flow-sweep rheology, a distinct extension of shear-thinning towards high shear rates (i.e. 100 s-1) was observed at high metal content – a result that was attributed to the improved wall adhesion. In comparison, physically mixed filament failed to sustain more than 10s-1 shear rate proving that they were prone to wall slippage at a higher shear rate, giving an insight into the onset of extrusion jamming. In the second project, nanoporous copper made out of electroless chemical dealloying was utilized as fillers, because of their unique physiochemical properties. The role of capillary imbibition of polymers into metal nanopores was investigated to understand their effect on density, zero-shear viscosity, and shear thinning. It was observed that, although the polymeric fluid’s transient concentration regulates its wettability, the polymer chain length ultimately dictates its melt rheology, which consequentially facilitates densification of pores during vacuum annealing. Finally, it was demonstrated that higher imbibition into nanopores leads to extrusion failure due to a combined effect of volumetric packing increase and nanoconfinement, providing a deterministic materials design tool to enable continuous 3D printing. The outcome of this study might be beneficial to integrate nanoporous metals into binder-based 3D printing technology to fabricate interdigitated battery electrodes and multifunctional 3D printed electronics.
ContributorsHasib, Amm (Author) / Azeredo, Bruno (Thesis advisor) / Song, Kenan (Thesis advisor) / Nian, Qiong (Committee member) / Kwon, Beomjin (Committee member) / Li, Xiangjia (Committee member) / Arizona State University (Publisher)
Created2022