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.

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.

In recent years, the scientific community around the synthesis and processing of nanoporous metals is striving to integrate them into powder metallurgy processes such as additive manufacturing since it has a potential to fabricate 3D hierarchical high surface area electrodes for energy applications. Recent research in dealloying – a versatile method for synthesizing nanoporous metals – emphasized the need in understanding its process-structure relationships to independently control the relative density, ligament and pore sizes with good process reproducibly. In this dissertation, a new understanding of the dealloying process is presented for synthesizing (i) nanoporous gold thin-films and (ii) nanoporous Cu spherical powders with an emphasis on understanding variability in their process-structure relationships and process scalability. First, this work sheds the light on the nature of the dealloying front and its percolation along the grain boundaries in nanocrystalline gold-silver thin films by studying the early stages of ligament nucleation. Additionally, this work analyses its variability by investigating new process variables such as (i) equilibration time and (ii) precursor aging and their impacts in achieving process reproducibility. The correlation of relative density with ligament size is contextualized with state-of-the-art data mining research. Second, this work provides a new methodology for large scale production of nanoporous Cu powder and demonstrates its integration with powder casting to fabricate porous conductive electrode. By understanding the influence of etching solution concentration and titration methodology on the structure and composition of nanoporous Cu, it was possible to fabricate precipitate-free powders at high throughputs. Further, the nature of oxygen incorporation into porous Cu powder was studied as a function of surface-to-volume ratio of powder in atmospheric conditions. To consolidate powders into parts via open-die casting, this work harvests Ostwald Ripening phenomena associated with thermal coarsening in nanoporous metals to weld them at low temperatures (approximately one-third of its melting temperature). This work represents a major step towards the integration of nanoporous Cu feedstocks into additive manufacturing.

Glasses have many applications such as containers, substrates of displays, high strength fibers and portable electronic display panels. Their excellent mechanical properties such as high hardness, good forming ability and scratch resistance make glasses ideal for these applications. Many factors affect the selection of one glass over another for a given purpose such as cost, ingredients, scalability of manufacturing, etc. Typically, silicate based glasses are often selected because they satisfy most of the selection criteria. However, with the recent abundant use of these glasses in touch-based applications, understanding their abilities to dissipate energy due to surface contact loads has become increasingly desirable. The most common silicate glasses worldwide are glassy silica and soda lime. Calcium aluminosilicates are also gaining popularity due to their importance as substrates for display screens in electronic devices. The surface energy dissipation and strength of these glasses are based on several factors, but predominantly rely on ingredient composition and the so-called Indentation Size Effect (ISE), where the strength depends on the maximum surface force. Both the composition and ISE alter the strength and favored energy dissipation mechanisms of the glass. Unlocking the contribution of these mechanisms and elucidating their dependence on composition and force is the underlining goal of this thesis.Prior to cracking, silicate glasses can inelastically deform by shear and densification. However, the link between the mechanical properties, strength, glass structure and maximum force and the propensity by which either of these mechanisms are favored still remains unclear. In this study, the first aim is to elucidate the causes of the ISE and i explore the relationships between the ISE and the dissipation mechanisms, and identify what feature(s) of the glass can be used to infer their behavior. All glasses have shown a strong link between the ISE and shear flow and densification. Second, the link between composition and the dissipation mechanisms will be elucidated. This is accomplished by performing indentation tests coupled with an annealing method to independently quantify the amount of volume associated with each dissipation mechanism and elucidate relationships with ingredients and structure of the glasses. Some conclusions will then be presented that link all these behaviors together.

Layer-wise extrusion of soft-solid like cement pastes and mortars is commonly used in 3D printing of concrete. Rheological and mechanical characterization of the printable binder for on-demand flow and subsequent structuration is a critical challenge. This research is an effort to understand the mechanics of cementitious binders as soft solids in the fresh state, towards establishing material-process relationships to enhance print quality. This study introduces 3D printable binders developed based on rotational and capillary rheology test parameters, and establish the direct influence of packing coefficients, geometric ratio, slip velocities, and critical print velocities on the extrudate quality. The ratio of packing fraction to the square of average particle diameter (0.01-0.02), and equivalent microstructural index (5-20) were suitable for printing, and were directly related to the cohesion and extrusional yield stress of the material. In fact, steady state pressure for printing (30-40 kPa) is proportional to the extrusional yield stress, and increases with the geometric ratio (0-60) and print velocity (5-50 mm/s). Higher print velocities results in higher wall shear stresses and was exponentially related to the slip layer thickness (estimated between 1-5μ), while the addition of superplasticizers improve the slip layer thickness and the extrudate flow. However, the steady state pressure and printer capacity limits the maximum print velocity while the deadzone length limits the minimum velocity allowable (critical velocity regime) for printing. The evolution of buildability with time for the fresh state mortars was characterized with digital image correlation using compressive strain and strain rate in printed layers. The fresh state characteristics (interlayer and interfilamentous) and process parameters (layer height and fiber dimensions) influence the hardened mechanical properties. A lower layer height generally improves the mechanical properties and slight addition of fiber (up to 0.3% by volume) results in a 15-30% increase in the mechanical properties. 3D scanning and point-cloud analysis was also used to assess the geometric tolerance of a print based on mean error distances, print accuracy index, and layer-wise percent overlap. The research output will contribute to a synergistic material-process design and development of test methods for printability in the context of 3D printing of concrete.

Special thermal interface materials are required for connecting devices that operate at high temperatures up to 300°C. Because devices used in power electronics, such as GaN, SiC, and other wide bandgap semiconductors, can reach very high temperatures (beyond 250°C), a high melting point, and high thermal & electrical conductivity are required for the thermal interface material. Traditional solder materials for packaging cannot be used for these applications as they do not meet these requirements. Sintered nano-silver is a good candidate on account of its high thermal and electrical conductivity and very high melting point. The high temperature operating conditions of these devices lead to very high thermomechanical stresses that can adversely affect performance and also lead to failure. A number of these devices are mission critical and, therefore, there is a need for very high reliability. Thus, computational and nondestructive techniques and design methodology are needed to determine, characterize, and design the packages. Actual thermal cycling tests can be very expensive and time consuming. It is difficult to build test vehicles in the lab that are very close to the production level quality and therefore making comparisons or making predictions becomes a very difficult exercise. Virtual testing using a Finite Element Analysis (FEA) technique can serve as a good alternative. In this project, finite element analysis is carried out to help achieve this objective. A baseline linear FEA is performed to determine the nature and magnitude of stresses and strains that occur during the sintering step. A nonlinear coupled thermal and mechanical analysis is conducted for the sintering step to study the behavior more accurately and in greater detail. Damage and fatigue analysis are carried out for multiple thermal cycling conditions. The results are compared with the actual results from a prior study. A process flow chart outlining the FEA modeling process is developed as a template for the future work. A Coffin-Manson type relationship is developed to help determine the accelerated aging conditions and predict life for different service conditions.

Ultra High Performance (UHP) cementitious binders are a class of cement-based materials with high strength and ductility, designed for use in precast bridge connections, bridge superstructures, high load-bearing structural members like columns, and in structural repair and strengthening. This dissertation aims to elucidate the chemo-mechanical relationships in complex UHP binders to facilitate better microstructure-based design of these materials and develop machine learning (ML) models to predict their scale-relevant properties from microstructural information.To establish the connection between micromechanical properties and constitutive materials, nanoindentation and scanning electron microscopy experiments are performed on several cementitious pastes. Following Bayesian statistical clustering, mixed reaction products with scattered nanomechanical properties are observed, attributable to the low degree of reaction of the constituent particles, enhanced particle packing, and very low water-to-binder ratio of UHP binders. Relating the phase chemistry to the micromechanical properties, the chemical intensity ratios of Ca/Si and Al/Si are found to be important parameters influencing the incorporation of Al into the C-S-H gel.
ML algorithms for classification of cementitious phases are found to require only the intensities of Ca, Si, and Al as inputs to generate accurate predictions for more homogeneous cement pastes. When applied to more complex UHP systems, the overlapping chemical intensities in the three dominant phases – Ultra High Stiffness (UHS), unreacted cementitious replacements, and clinker – led to ML models misidentifying these three phases. Similarly, a reduced amount of data available on the hard and stiff UHS phases prevents accurate ML regression predictions of the microstructural phase stiffness using only chemical information. The use of generic virtual two-phase microstructures coupled with finite element analysis is also adopted to train MLs to predict composite mechanical properties. This approach applied to three different representations of composite materials produces accurate predictions, thus providing an avenue for image-based microstructural characterization of multi-phase composites such UHP binders. This thesis provides insights into the microstructure of the complex, heterogeneous UHP binders and the utilization of big-data methods such as ML to predict their properties. These results are expected to provide means for rational, first-principles design of UHP mixtures.

Traditionally nanoporous gold is created by selective dissolution of silver or copper from a binary silver-gold or copper-gold alloy. These alloys serve as prototypical model systems for a phenomenon referred to as stress-corrosion cracking. Stress-corrosion cracking is the brittle failure of a normally ductile material occurring in a corrosive environment under a tensile stress. Silver-gold can experience this type of brittle fracture for a range of compositions. The corrosion process in this alloy results in a bicontinuous nanoscale morphology composed of gold-rich ligaments and voids often referred to as nanoporous gold. Experiments have shown that monolithic nanoporous gold can sustain high speed cracks which can then be injected into parent-phase alloy. This work compares nanoporous gold created from ordered and disordered copper-gold using digital image analysis and electron backscatter diffraction. Nanoporous gold from both disordered copper-gold and silver-gold, and ordered copper-gold show that grain orientation and shape remain largely unchanged by the dealloying process. Comparing the morphology of the nanoporous gold from ordered and disordered copper-gold with digital image analysis, minimal differences are found between the two and it is concluded that they are not statistically significant. This reveals the robust nature of nanoporous gold morphology against small variations in surface diffusion and parent-phase crystal structure.
Then the corrosion penetration down the grain boundary is compared to the depth of crack injections in polycrystal silver-gold. Based on statistical comparison, the crack-injections penetrate into the parent-phase grain boundary beyond the corrosion-induced porosity. To compare crack injections to stress-corrosion cracking, single crystal silver-gold samples are employed. Due to the cleavage-like nature of the fracture surfaces, electron backscatter diffraction is possible and employed to compare the crystallography of stress-corrosion crack surfaces and crack-injection surfaces. From the crystallographic similarities of these fracture surfaces, it is concluded that stress-corrosion can occur via a series of crack-injection events. This relationship between crack injections and stress corrosion cracking is further examined using electrochemical data from polycrystal silver-gold samples during stress-corrosion cracking. The results support the idea that crack injection is a mechanism for stress-corrosion cracking.

Semantic image segmentation has been a key topic in applications involving image processing and computer vision. Owing to the success and continuous research in the field of deep learning, there have been plenty of deep learning-based segmentation architectures that have been designed for various tasks. In this thesis, deep-learning architectures for a specific application in material science; namely the segmentation process for the non-destructive study of the microstructure of Aluminum Alloy AA 7075 have been developed. This process requires the use of various imaging tools and methodologies to obtain the ground-truth information. The image dataset obtained using Transmission X-ray microscopy (TXM) consists of raw 2D image specimens captured from the projections at every beam scan. The segmented 2D ground-truth images are obtained by applying reconstruction and filtering algorithms before using a scientific visualization tool for segmentation. These images represent the corrosive behavior caused by the precipitates and inclusions particles on the Aluminum AA 7075 alloy. The study of the tools that work best for X-ray microscopy-based imaging is still in its early stages.

In this thesis, the underlying concepts behind Convolutional Neural Networks (CNNs) and state-of-the-art Semantic Segmentation architectures have been discussed in detail. The data generation and pre-processing process applied to the AA 7075 Data have also been described, along with the experimentation methodologies performed on the baseline and four other state-of-the-art Segmentation architectures that predict the segmented boundaries from the raw 2D images. A performance analysis based on various factors to decide the best techniques and tools to apply Semantic image segmentation for X-ray microscopy-based imaging was also conducted.

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.