Theses and Dissertations
This collection includes both ASU Theses and Dissertations, submitted by graduate students, and the Barrett, Honors College theses submitted by undergraduate students.
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- Creators: Rajagopalan, Jagannathan
- Creators: Turaga, Pavan
Description
Electromigration (EM) has been a serious reliability concern in microelectronics packaging for close to half a century now. Whenever the challenges of EM are overcome newer complications arise such as the demand for better performance due to increased miniaturization of semiconductor devices or the problems faced due to undesirable properties of lead-free solders. The motivation for the work is that there exists no fully computational modeling study on EM damage in lead-free solders (and also in lead-based solders). Modeling techniques such as one developed here can give new insights on effects of different grain features and offer high flexibility in varying parameters and study the corresponding effects. In this work, a new computational approach has been developed to study void nucleation and initial void growth in solders due to metal atom diffusion. It involves the creation of a 3D stochastic mesoscale model of the microstructure of a polycrystalline Tin structure. The next step was to identify regions of current crowding or ‘hot-spots’. This was done through solving a finite difference scheme on top of the 3D structure. The nucleation of voids due to atomic diffusion from the regions of current crowding was modeled by diffusion from the identified hot-spot through a rejection free kinetic Monte-Carlo scheme. This resulted in the net movement of atoms from the cathode to the anode. The above steps of identifying the hotspot and diffusing the atoms at the hot-spot were repeated and this lead to the initial growth of the void. This procedure was studied varying different grain parameters. In the future, the goal is to explore the effect of more grain parameters and consider other mechanisms of failure such as the formation of intermetallic compounds due to interstitial diffusion and dissolution of underbump metallurgy.
ContributorsKarunakaran, Deepak (Thesis advisor) / Jiao, Yang (Committee member) / Chawla, Nikhilesh (Committee member) / Rajagopalan, Jagannathan (Committee member) / Arizona State University (Publisher)
Created2016
Description
Nanocrystalline (NC) and Ultrafine-grained (UFG) metal films exhibit a wide range of enhanced mechanical properties compared to their coarse-grained counterparts. These properties, such as very high strength, primarily arise from the change in the underlying deformation mechanisms. Experimental and simulation studies have shown that because of the small grain size, conventional dislocation plasticity is curtailed in these materials and grain boundary mediated mechanisms become more important. Although the deformation behavior and the underlying mechanisms in these materials have been investigated in depth, relatively little attention has been focused on the inhomogeneous nature of their microstructure (particularly originating from the texture of the film) and its influence on their macroscopic response. Furthermore, the rate dependency of mechanical response in NC/UFG metal films with different textures has not been systematically investigated. The objectives of this dissertation are two-fold.
The first objective is to carry out a systematic investigation of the mechanical behavior of NC/UFG thin films with different textures under different loading rates. This includes a novel approach to study the effect of texture-induced plastic anisotropy on mechanical behavior of the films. Efforts are made to correlate the behavior of UFG metal films and the underlying deformation mechanisms. The second objective is to understand the deformation mechanisms of UFG aluminum films using in-situ transmission electron microscopy (TEM) experiments with Automated Crystal Orientation Mapping. This technique enables us to investigate grain rotations in UFG Al films and to monitor the microstructural changes in these films during deformation, thereby revealing detailed information about the deformation mechanisms prevalent in UFG metal films.
The first objective is to carry out a systematic investigation of the mechanical behavior of NC/UFG thin films with different textures under different loading rates. This includes a novel approach to study the effect of texture-induced plastic anisotropy on mechanical behavior of the films. Efforts are made to correlate the behavior of UFG metal films and the underlying deformation mechanisms. The second objective is to understand the deformation mechanisms of UFG aluminum films using in-situ transmission electron microscopy (TEM) experiments with Automated Crystal Orientation Mapping. This technique enables us to investigate grain rotations in UFG Al films and to monitor the microstructural changes in these films during deformation, thereby revealing detailed information about the deformation mechanisms prevalent in UFG metal films.
ContributorsIzadi, Ehsan (Author) / Rajagopalan, Jagannathan (Thesis advisor) / Peralta, Pedro (Committee member) / Chawla, Nikhilesh (Committee member) / Solanki, Kiran (Committee member) / Oswald, Jay (Committee member) / Arizona State University (Publisher)
Created2017
Description
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.
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.
ContributorsKarasz, Erin (Author) / Sieradzki, Karl (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Peralta, Pedro (Committee member) / Rajagopalan, Jagannathan (Committee member) / Arizona State University (Publisher)
Created2020
Description
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.
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.
ContributorsBarboza, Daniel (Author) / Turaga, Pavan (Thesis advisor) / Chawla, Nikhilesh (Committee member) / Jayasuriya, Suren (Committee member) / Arizona State University (Publisher)
Created2020