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- Genre: Academic theses
- Creators: Yang, Yezhou
Description
This thesis focuses on the theoretical work done to determine thermodynamic properties of a chalcopyrite thin-film material for use as a photovoltaic material in a tandem device. The material of main focus here is ZnGeAs2, which was chosen for the relative abundance of constituents, favorable photovoltaic properties, and good lattice matching with ZnSnP2, the other component in this tandem device. This work is divided into two main chapters, which will cover: calculations and method to determine the formation energy and abundance of native point defects, and a model to calculate the vapor pressure over a ternary material from first-principles. The purpose of this work is to guide experimental work being done in tandem to synthesize ZnGeAs2 in thin-film form with high enough quality such that it can be used as a photovoltaic. Since properties of photovoltaic depend greatly on defect concentrations and film quality, a theoretical understanding of how laboratory conditions affect these properties is very valuable. The work done here is from first-principles and utilizes density functional theory using the local density approximation. Results from the native point defect study show that the zinc vacancy (VZn) and the germanium antisite (GeZn) are the more prominent defects; which most likely produce non-stoichiometric films. The vapor pressure model for a ternary system is validated using known vapor pressure for monatomic and binary test systems. With a valid ternary system vapor pressure model, results show there is a kinetic barrier to decomposition for ZnGeAs2.
ContributorsTucker, Jon R (Author) / Van Schilfgaarde, Mark (Thesis advisor) / Newman, Nathan (Committee member) / Adams, James (Committee member) / Arizona State University (Publisher)
Created2011
Description
Electromigration in metal interconnects is the most pernicious failure mechanism in semiconductor integrated circuits (ICs). Early electromigration investigations were primarily focused on aluminum interconnects for silicon-based ICs. An alternative metallization compatible with gallium arsenide (GaAs) was required in the development of high-powered radio frequency (RF) compound semiconductor devices operating at higher current densities and elevated temperatures. Gold-based metallization was implemented on GaAs devices because it uniquely forms a very low resistance ohmic contact and gold interconnects have superior electrical and thermal conductivity properties. Gold (Au) was also believed to have improved resistance to electromigration due to its higher melting temperature, yet electromigration reliability data on passivated Au interconnects is scarce and inadequate in the literature. Therefore, the objective of this research was to characterize the electromigration lifetimes of passivated Au interconnects under precisely controlled stress conditions with statistically relevant quantities to obtain accurate model parameters essential for extrapolation to normal operational conditions. This research objective was accomplished through measurement of electromigration lifetimes of large quantities of passivated electroplated Au interconnects utilizing high-resolution in-situ resistance monitoring equipment. Application of moderate accelerated stress conditions with a current density limited to 2 MA/cm2 and oven temperatures in the range of 300°C to 375°C avoided electrical overstress and severe Joule-heated temperature gradients. Temperature coefficients of resistance (TCRs) were measured to determine accurate Joule-heated Au interconnect film temperatures. A failure criterion of 50% resistance degradation was selected to prevent thermal runaway and catastrophic metal ruptures that are problematic of open circuit failure tests. Test structure design was optimized to reduce resistance variation and facilitate failure analysis. Characterization of the Au microstructure yielded a median grain size of 0.91 ìm. All Au lifetime distributions followed log-normal distributions and Black's model was found to be applicable. An activation energy of 0.80 ± 0.05 eV was measured from constant current electromigration tests at multiple temperatures. A current density exponent of 1.91 was extracted from multiple current densities at a constant temperature. Electromigration-induced void morphology along with these model parameters indicated grain boundary diffusion is dominant and the void nucleation mechanism controlled the failure time.
ContributorsKilgore, Stephen (Author) / Adams, James (Thesis advisor) / Schroder, Dieter (Thesis advisor) / Krause, Stephen (Committee member) / Gaw, Craig (Committee member) / Arizona State University (Publisher)
Created2013
Description
This thesis is a qualitative research study that focuses on siblings of children with Autistic Spectrum Disorder (ASD). Even though it is expected that having a child with ASD in the family will influence the whole family including siblings of the child with ASD, the sibling population is rarely included in research related to children with ASD, and there is only limited services available for them. This exploratory study (n=6) is aimed at better understanding the siblings' lives in their family settings in order to identify the siblings' unmet needs and determine how they have been influenced by the child with ASD. This study is also aimed at identifying the most appropriate support for the siblings to help them cope better. The study followed the Resiliency Model of Family Stress, Adjustment, and Adaptation and a narrative theory approach. An in-depth interview with the parents was conducted for the study, so the findings reflect the parents' perception of the siblings. All the themes emerged into two categories: life in the family setting and supports. The findings indicate that the families are striving for balance between the siblings and the children with ASD, but still tend to focus more on the children with ASD. Also, the families tend to have autonomous personal support systems. The parents tend to perceive that these personal support systems are good enough for the siblings; therefore, the parents do not feel that formal support for the siblings was necessary. As a result of the findings, recommendations are made for the organizations that work with individuals with ASD to provide more appropriate services for the families of children with ASD, including siblings. Also, recommendations are made for future studies to clarify more factors related to the siblings due to the limitation of this study; the siblings' lives were reflected vicariously via the parents.
ContributorsJeong, Seong Hae (Author) / Marsiglia, Flavio F (Thesis advisor) / Ayers, Stephanie (Committee member) / Adams, James (Committee member) / Arizona State University (Publisher)
Created2013
Description
This report will review the mechanical and microstructural properties of the refractory element rhenium (Re) deposited using Laser Additive Manufacturing (LAM). With useable structural strength over 2200 °C, existing applications up to 2760 °C, very high strength, ductility and chemical resistance, interest in Re is understandable. This study includes data about tensile properties including tensile data up to 1925 °C, fracture modes, fatigue and microstructure including deformation systems and potential applications of that information. The bulk mechanical test data will be correlated with nanoindentation and crystallographic examination. LAM properties are compared to the existing properties found in the literature for other manufacturing processes. The literature indicates that Re has three significant slip systems but also twins as part of its deformation mechanisms. While it follows the hcp metal characteristics for deformation, it has interesting and valuable extremes such as high work hardening, potentially high strength, excellent wear resistance and superior elevated temperature strength. These characteristics are discussed in detail.
ContributorsAdams, Robbie (Author) / Chawla, Nikhilesh (Thesis advisor) / Adams, James (Committee member) / Krause, Stephen (Committee member) / Arizona State University (Publisher)
Created2012
Description
In 2022, integrated circuit interconnects will approach 10 nm and the diffusion barrier layers needed to ensure long lasting devices will be at 1 nm. This dimension means the interconnect will be dominated by the interface and it has been shown the interface is currently eroding device performance. The standard interconnect system has three layers - a Copper metal core, a Tantalum Adhesion layer and a Tantalum Nitride Diffusion Barrier Layer. An alternate interconnect schema is a Tantalum Nitride barrier layer and Silver as a metal. The adhesion layer is removed from the system along with changing to an alternate, low resistivity metal. First principles are used to assess the interface of the Silver and Tantalum Nitride. Several stoichiometric 1:1 Tantalum Nitride polymorphs are assessed and it is found that the Fe2P crystal structure is actually the most stable crystal structure which is at odds with the published phase diagram for ambient crystal structure. The surface stability of Fe2P-TaN is assessed and the absorption enthalpy of Silver adatoms is calculated. Finally, the thermodynamic stability of the TaN-Ag interconnect system is assessed.
ContributorsGrumski, Michael (Author) / Adams, James (Thesis advisor) / Krause, Stephen (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2012
Description
As world energy demands increase, research into more efficient energy production methods has become imperative. Heterogeneous catalysis and nanoscience are used to promote chemical transformations important for energy production. These concepts are important in solid oxide fuel cells (SOFCs) which have attracted attention because of their potential to provide an efficient and environmentally favorable power generation system. The SOFC is also fuel-flexible with the ability to run directly on many fuels other than hydrogen. Internal fuel reforming directly in the anode of the SOFC would greatly reduce the cost and complexity of the device. Methane is the simplest hydrocarbon and a main component in natural gas, making it useful when testing catalysts on the laboratory scale. Nickel (Ni) and gadolinium (Gd) doped ceria (CeO2) catalysts for potential use in the SOFC anode were synthesized with a spray drying method and tested for catalytic performance using partial oxidation of methane and steam reforming. The relationships between catalytic performance and structure were then investigated using X-ray diffraction, transmission electron microscopy, and environmental transmission electron microscopy. The possibility of solid solutions, segregated phases, and surface layers of Ni were explored. Results for a 10 at.% Ni in CeO2 catalyst reveal a poor catalytic behavior while a 20 at.% Ni in CeO2 catalyst is shown to have superior activity. The inclusion of both 10 at.% Gd and 10 at.% Ni in CeO2 enhances the catalytic performance. Analysis of the presence of Ni in all 3 samples reveals Ni heterogeneity and little evidence for extensive solid solution doping. Ni is found in small domains throughout CeO2 particles. In the 20 at.% Ni sample a segregated, catalytically active NiO phase is observed. Overall, it is found that significant interaction between Ni and CeO2 occurs that could affect the synthesis and functionality of the SOFC anode.
ContributorsCavendish, Rio (Author) / Crozier, Peter (Thesis advisor) / Adams, James (Committee member) / Smith, David (Committee member) / Arizona State University (Publisher)
Created2012
Description
Feature embeddings differ from raw features in the sense that the former obey certain properties like notion of similarity/dissimilarity in it's embedding space. word2vec is a preeminent example in this direction, where the similarity in the embedding space is measured in terms of the cosine similarity. Such language embedding models have seen numerous applications in both language and vision community as they capture the information in the modality (English language) efficiently. Inspired by these language models, this work focuses on learning embedding spaces for two visual computing tasks, 1. Image Hashing 2. Zero Shot Learning. The training set was used to learn embedding spaces over which similarity/dissimilarity is measured using several distance metrics like hamming / euclidean / cosine distances. While the above-mentioned language models learn generic word embeddings, in this work task specific embeddings were learnt which can be used for Image Retrieval and Classification separately.
Image Hashing is the task of mapping images to binary codes such that some notion of user-defined similarity is preserved. The first part of this work focuses on designing a new framework that uses the hash-tags associated with web images to learn the binary codes. Such codes can be used in several applications like Image Retrieval and Image Classification. Further, this framework requires no labelled data, leaving it very inexpensive. Results show that the proposed approach surpasses the state-of-art approaches by a significant margin.
Zero-shot classification is the task of classifying the test sample into a new class which was not seen during training. This is possible by establishing a relationship between the training and the testing classes using auxiliary information. In the second part of this thesis, a framework is designed that trains using the handcrafted attribute vectors and word vectors but doesn’t require the expensive attribute vectors during test time. More specifically, an intermediate space is learnt between the word vector space and the image feature space using the hand-crafted attribute vectors. Preliminary results on two zero-shot classification datasets show that this is a promising direction to explore.
Image Hashing is the task of mapping images to binary codes such that some notion of user-defined similarity is preserved. The first part of this work focuses on designing a new framework that uses the hash-tags associated with web images to learn the binary codes. Such codes can be used in several applications like Image Retrieval and Image Classification. Further, this framework requires no labelled data, leaving it very inexpensive. Results show that the proposed approach surpasses the state-of-art approaches by a significant margin.
Zero-shot classification is the task of classifying the test sample into a new class which was not seen during training. This is possible by establishing a relationship between the training and the testing classes using auxiliary information. In the second part of this thesis, a framework is designed that trains using the handcrafted attribute vectors and word vectors but doesn’t require the expensive attribute vectors during test time. More specifically, an intermediate space is learnt between the word vector space and the image feature space using the hand-crafted attribute vectors. Preliminary results on two zero-shot classification datasets show that this is a promising direction to explore.
ContributorsGattupalli, Jaya Vijetha (Author) / Li, Baoxin (Thesis advisor) / Yang, Yezhou (Committee member) / Venkateswara, Hemanth (Committee member) / Arizona State University (Publisher)
Created2019
Description
With the substantial development of intelligent robots, human-robot interaction (HRI) has become ubiquitous in applications such as collaborative manufacturing, surgical robotic operations, and autonomous driving. In all these applications, a human behavior model, which can provide predictions of human actions, is a helpful reference that helps robots to achieve intelligent interaction with humans. The requirement elicits an essential problem of how to properly model human behavior, especially when individuals are interacting or cooperating with each other. The major objective of this thesis is to utilize the human intention decoding method to help robots enhance their performance while interacting with humans. Preliminary work on integrating human intention estimation with an HRI scenario is shown to demonstrate the benefit. In order to achieve this goal, the research topic is divided into three phases. First, a novel method of an online measure of the human's reliance on the robot, which can be estimated through the intention decoding process from human actions，is described. An experiment that requires human participants to complete an object-moving task with a robot manipulator was conducted under different conditions of distractions. A relationship is discovered between human intention and trust while participants performed a familiar task with no distraction. This finding suggests a relationship between the psychological construct of trust and joint physical coordination, which bridges the human's action to its mental states. Then, a novel human collaborative dynamic model is introduced based on game theory and bounded rationality, which is a novel method to describe human dyadic behavior with the aforementioned theories. The mutual intention decoding process was also considered to inform this model. Through this model, the connection between the mental states of the individuals to their cooperative actions is indicated. A haptic interface is developed with a virtual environment and the experiments are conducted with 30 human subjects. The result suggests the existence of mutual intention decoding during the human dyadic cooperative behaviors. Last, the empirical results show that allowing agents to have empathy in inference, which lets the agents understand that others might have a false understanding of their intentions, can help to achieve correct intention inference. It has been verified that knowledge about vehicle dynamics was also important to correctly infer intentions. A new courteous policy is proposed that bounded the courteous motion using its inferred set of equilibrium motions. A simulation, which is set to reproduce an intersection passing case between an autonomous car and a human driving car, is conducted to demonstrate the benefit of the novel courteous control policy.
ContributorsWang, Yiwei (Author) / Zhang, Wenlong (Thesis advisor) / Berman, Spring (Committee member) / Lee, Hyunglae (Committee member) / Ren, Yi (Committee member) / Yang, Yezhou (Committee member) / Arizona State University (Publisher)
Created2021
Description
Organic light-emitting diodes (OLEDs) have been successfully implemented in various display applications owing to rapid advancements in material design and device architecture. Their success in the display industry has ignited a rising interest in applying OLEDs for solid-state lighting applications through the development of white OLEDs (WOLEDs). However, to enter the market as a serious competitor, WOLEDs must achieve excellent color quality, high external quantum efficiency (EQE) as well as a long operational lifetime. In this research, novel materials and device architectures were explored to improve the performance of single-stack WOLEDs. A new Pt-based phosphorescent emitter, Pt2O2-p2m, was examined as a single emissive emitter for the development of a stable and efficient single-doped WOLED. A bilayer structure was employed to balance the charges carriers within the emissive layer resulting in low efficiency roll-off at high brightness, realizing a peak EQE of 21.5% and EQEs of 20% at 1000 cd m-2 and 15.3% at 7592 cd m-2. A novel phosphorescent/fluorescent, or hybrid, WOLED device architecture was also proposed. To gather a thorough understanding of blue fluorescent OLEDs prior to its use in a WOLED, a study was conducted to investigate the impact of the material selection on the device performance. The use of an anthracene type host demonstrated an improvement to the operational stability of the blue OLED by reducing the occurrence of degradation events. Additionally, various dopant concentrations and blocking materials revealed vastly different efficiency and lifetime results. Finally, a Pd (II) complex, Pd3O8-Py5, with efficient amber-colored aggregate emission was employed to produce a WOLED. Various host materials were investigated to achieve balanced white emission and the addition of an interlayer composed of a high triplet energy material was used to reduce quenching effects. Through this strategy, a color stable WOLED device with a peak EQE of 45% and an estimated LT95 over 50,000 hours at 1000 cd m-2 was realized. The comprehensive performance of the proposed device architecture competes with WOLED devices that are commercially available and reported within the literature domain, providing a strong foundation to further advance the development of highly efficient and stable single-stack WOLEDs.
ContributorsAmeri, Lydia (Author) / Li, Jian (Thesis advisor) / Adams, James (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2022
Description
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021