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Description
An expanse of research has demonstrated that persons with mental illness (PWMI) tend to avoid formal psychological treatment.One possible explanation for this failure to pursue formal treatment is the tendency of religious individuals to construe mental illness as spiritual in nature, leading religious communities to actively discourage emotional and psychological help-seeking through non-spiritual means. The present study examined help-seeking behaviors among religious PWMI by examining the impact of religiosity and gender on the relationship between mental illness stigma and help-seeking behaviors. Results indicate that higher levels of perceived stigma and religious salience relate to higher reported indirect support-seeking (ISS). Moreover, only religious salience appears to significantly relate to ISS among men, whereas perceived mental illness stigma significantly predicts direct and indirect support-seeking behaviors among women.
ContributorsMalouf, Laura Means (Author) / Mickelson, Kristin (Thesis advisor) / Hall, Deborah (Committee member) / Schweitzer, Nicholas (Committee member) / Arizona State University (Publisher)
Created2020
Description
Attitudes play a fundamental role when making critical judgments and the extremity of people’s attitudes can be influenced by one’s emotions, beliefs, or past experiences and behaviors. Human attitudes and preferences are susceptible to social influence and attempts to influence or change another person’s attitudes are pervasive in all societies. Given the importance of attitudes and attitude change, the current project investigated linguistic aspects of conversations that lead to attitude change by analyzing a dataset mined from Reddit’s Change My View (Priniski & Horne, 2018). Analysis of the data was done using Natural Language Processing (NLP), specifically information density, to predict attitude change. Top posts from Reddit’s (N = 510,149) were imported and processed in Python and information density measures were computed. The results indicate that comments with higher information density are more likely to be awarded a delta and are perceived to be more persuasive.
ContributorsLobo, Nicole Simone (Author) / Horne, Zachary S (Thesis advisor) / Duran, Nicholas (Committee member) / Hall, Deborah (Committee member) / Arizona State University (Publisher)
Created2020
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 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.
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
Description
Autonomous Vehicles (AVs), or self-driving cars, are poised to have an enormous impact on the automotive industry and road transportation. While advances have been made towards the development of safe, competent autonomous vehicles, there has been inadequate attention to the control of autonomous vehicles in unanticipated situations, such as imminent crashes. Even if autonomous vehicles follow all safety measures, accidents are inevitable, and humans must trust autonomous vehicles to respond appropriately in such scenarios. It is not plausible to program autonomous vehicles with a set of rules to tackle every possible crash scenario. Instead, a possible approach is to align their decision-making capabilities with the moral priorities, values, and social motivations of trustworthy human drivers.Toward this end, this thesis contributes a simulation framework for collecting, analyzing, and replicating human driving behaviors in a variety of scenarios, including imminent crashes. Four driving scenarios in an urban traffic environment were designed in the CARLA driving simulator platform, in which simulated cars can either drive autonomously or be driven by a user via a steering wheel and pedals. These included three unavoidable crash scenarios, representing classic trolley-problem ethical dilemmas, and a scenario in which a car must be driven through a school zone, in order to examine driver prioritization of reaching a destination versus ensuring safety. Sample human driving data in CARLA was logged from the simulated car’s sensors, including the LiDAR, IMU and camera. In order to reproduce human driving behaviors in a simulated vehicle, it is necessary for the AV to be able to identify objects in the environment and evaluate the volume of their bounding boxes for prediction and planning. An object detection method was used that processes LiDAR point cloud data using the PointNet neural network architecture, analyzes RGB images via transfer learning using the Xception convolutional neural network architecture, and fuses the outputs of these two networks. This method was trained and tested on both the KITTI Vision Benchmark Suite dataset and a virtual dataset exclusively generated from CARLA. When applied to the KITTI dataset, the object detection method achieved an average classification accuracy of 96.72% and an average Intersection over Union (IoU) of 0.72, where the IoU metric compares predicted bounding boxes to those used for training.
ContributorsGovada, Yashaswy (Author) / Berman, Spring (Thesis advisor) / Johnson, Kathryn (Committee member) / Marvi, Hamidreza (Committee member) / Arizona State University (Publisher)
Created2020
Description
Temporal-order judgments can require integration of self-generated action-events and external sensory information. In a previous study, it was found that participants are biased to perceive one’s own action-events to occur prior to simultaneous external events. This phenomenon, named the “Egocentric Temporal Order Bias”, or ETO bias, was demonstrated as a 67% probability for participants to report self-generated events as occurring prior to simultaneous externally-determined events. These results were interpreted as supporting a feed-forward, constructive model of perception. However, the empirical data could support many potential mechanisms. The present study tests whether the ETO bias is driven by attentional differences, feed-forward predictability, or action. These findings support that participants exhibit a bias due to both feed-forward predictability and action, and a Bayesian analysis supports that these effects are quantitatively unique. Therefore, the results indicate that the ETO bias is largely driven by one’s own action, over and above feed-forward predictability.
ContributorsTang, Tim (Author) / Mcbeath, Michael K (Thesis advisor) / Brewer, Gene A. (Committee member) / Sanabria, Federico (Committee member) / Arizona State University (Publisher)
Created2020
Description
Deformable heat exchangers could provide a multitude of previously untapped advantages ranging from adaptable performance via macroscale, dynamic shape change (akin to dilation/constriction seen in blood vessels) to enhanced heat transfer at thermal interfaces through microscale, surface deformations. So far, making deformable, ‘soft heat exchangers’ (SHXs) has been limited by the low thermal conductivity of materials with suitable mechanical properties. The recent introduction of liquid-metal embedded elastomers by Bartlett et al1 has addressed this need. Specifically, by remaining soft and stretchable despite the addition of filler, these thermally conductive composites provide an ideal material for the new class of “soft thermal systems”, which is introduced in this work. Understanding such thermal systems will be a key element in enabling technology that require high levels of stretchability, such as thermoregulatory garments, soft electronics, wearable electronics, and high-powered robotics. Shape change inherent to SHX operation has the potential to violate many conventional assumptions used in HX design and thus requires the development of new theoretical approaches to predict performance. To create a basis for understanding these devices, this work highlights two sequential studies. First, the effects of transitioning to a surface deformable, SHX under steady state static conditions in the setting of a liquid cooling device for thermoregulation, electronics and robotics applications was explored. In this study, a thermomechanical model was built and validated to predict the thermal performance and a system wide analysis to optimize such devices was carried out. Second, from a more fundamental perspective, the effects of SHXs undergoing transient shape deformation during operation was explored. A phase shift phenomenon in cooling performance dependent on stretch rate, stretch extent and thermal diffusivity was discovered and explained. With the use of a time scale analysis, the extent of quasi-static assumption viability in modeling such systems was quantified and multiple shape modulation regime limits were defined. Finally, nuance considerations and future work of using liquid metal-silicone composites in SHXs were discussed.
ContributorsKotagama, Praveen (Author) / Rykaczewski, Konrad (Thesis advisor) / Wang, Robert (Committee member) / Phelan, Patrick (Committee member) / Herrmann, Marcus (Committee member) / Green, Matthew (Committee member) / Arizona State University (Publisher)
Created2020
Description
The maximum theoretical efficiency of a terrestrial non-concentrated silicon solar cell is 29.4%, as obtained from detailed balance analysis. Over 90% of the current silicon photovoltaics market is based on solar cells with diffused junctions (Al-BSF, PERC, PERL, etc.), which are limited in performance by increased non-radiative recombination in the doped regions. This limitation can be overcome through the use of passivating contacts, which prevent recombination at the absorber interfaces while providing the selectivity to efficiently separate the charge carriers generated in the absorber. This thesis aims at developing an understanding of how the material properties of the contact affect device performance through simulations.The partial specific contact resistance framework developed by Onno et al. aims to link material behavior to device performance specifically at open circuit. In this thesis, the framework is expanded to other operating points of a device, leading to a model for calculating the partial contact resistances at any current flow. The error in calculating these resistances is irrelevant to device performance resulting in an error in calculating fill factor from resistances below 0.1% when the fill factors of the cell are above 70%, i.e., for cells with good passivation and selectivity.
Further, silicon heterojunction (SHJ) and tunnel-oxide based solar cells are simulated in 1D finite-difference modeling package AFORS-HET. The effects of material property changes on device performance are investigated using novel contact materials like Al0.8Ga0.2As (hole contact for SHJ) and ITO (electron contact for tunnel-oxide cells). While changing the bandgap and electron affinity of the contact affect the height of the Schottky barrier and hence contact resistivity, increasing the doping of the contact will increase its selectivity. In the case of ITO, the contact needs to have a work function below 4.2 eV to be electron selective, which suggests that other low work function TCOs (like AZO) will be more applicable as alternative dopant-free electron contacts. The AFORS-HET model also shows that buried doped regions arising from boron diffusion in the absorber can damage passivation and decrease the open circuit voltage of the device.
Further, silicon heterojunction (SHJ) and tunnel-oxide based solar cells are simulated in 1D finite-difference modeling package AFORS-HET. The effects of material property changes on device performance are investigated using novel contact materials like Al0.8Ga0.2As (hole contact for SHJ) and ITO (electron contact for tunnel-oxide cells). While changing the bandgap and electron affinity of the contact affect the height of the Schottky barrier and hence contact resistivity, increasing the doping of the contact will increase its selectivity. In the case of ITO, the contact needs to have a work function below 4.2 eV to be electron selective, which suggests that other low work function TCOs (like AZO) will be more applicable as alternative dopant-free electron contacts. The AFORS-HET model also shows that buried doped regions arising from boron diffusion in the absorber can damage passivation and decrease the open circuit voltage of the device.
ContributorsDasgupta, Sagnik (Author) / Holman, Zachary (Thesis advisor) / Onno, Arthur (Committee member) / Wang, Qing Hua (Committee member) / Arizona State University (Publisher)
Created2020
Description
Lateral programmable metallization cells (PMC) utilize the properties of electrodeposits grown over a solid electrolyte channel. Such devices have an active anode and an inert cathode separated by a long electrodeposit channel in a coplanar arrangement. The ability to transport large amount of metallic mass across the channel makes these devices attractive for various More-Than-Moore applications. Existing literature lacks a comprehensive study of electrodeposit growth kinetics in lateral PMCs. Moreover, the morphology of electrodeposit growth in larger, planar devices is also not understood. Despite the variety of applications, lateral PMCs are not embraced by the semiconductor industry due to incompatible materials and high operating voltages needed for such devices. In this work, a numerical model based on the basic processes in PMCs – cation drift and redox reactions – is proposed, and the effect of various materials parameters on the electrodeposit growth kinetics is reported. The morphology of the electrodeposit growth and kinetics of the electrodeposition process are also studied in devices based on Ag-Ge30Se70 materials system. It was observed that the electrodeposition process mainly consists of two regimes of growth – cation drift limited regime and mixed regime. The electrodeposition starts in cation drift limited regime at low electric fields and transitions into mixed regime as the field increases. The onset of mixed regime can be controlled by applied voltage which also affects the morphology of electrodeposit growth. The numerical model was then used to successfully predict the device kinetics and onset of mixed regime. The problem of materials incompatibility with semiconductor manufacturing was solved by proposing a novel device structure. A bilayer structure using semiconductor foundry friendly materials was suggested as a candidate for solid electrolyte. The bilayer structure consists of a low resistivity oxide shunt layer on top of a high resistivity ion carrying oxide layer. Devices using Cu2O as the low resistivity shunt on top of Cu doped WO3 oxide were fabricated. The bilayer devices provided orders of magnitude improvement in device performance in the context of operating voltage and switching time. Electrical and materials characterization revealed the structure of bilayers and the mechanism of electrodeposition in these devices.
ContributorsChamele, Ninad (Author) / Kozicki, Michael (Thesis advisor) / Barnaby, Hugh (Committee member) / Newman, Nathan (Committee member) / Gonzalez-Velo, Yago (Committee member) / Arizona State University (Publisher)
Created2020
Description
The passivity of metals is a phenomenon of vast importance as it prevents many materials in important applications from rapid deterioration by corrosion. Alloying with a sufficient quantity of passivating elements (Cr, Al, Si), typically in the range of 10% - 20%, is commonly employed to improve the corrosion resistance of elemental metals. However, the compositional criteria for enhanced corrosion resistance have been a long-standing unanswered question for alloys design. With the emerging interest in multi-principal element alloy design, a percolation model is developed herein for the initial stage of passive film formation, termed primary passivation. The successful validation of the assumptions and predictions of the model in three corrosion-resistant binary alloys, Fe-Cr, Ni-Cr, and Cu-Rh supports that the model which can be used to provide a quantitative design strategy for designing corrosion-resistant alloys. To date, this is the only model that can provide such criteria for alloy design.The model relates alloy passivation to site percolation of the passivating elements in the alloy matrix. In the initial passivation stage, Fe (Ni in Ni-Cr or Cu in Cu-Rh) is selectively dissolved, destroying the passive network built up by Cr (or Rh) oxides and undercutting isolated incipient Cr (Rh) oxide nuclei. The only way to prevent undercutting and form a stable protective passive film is if the concentration of Cr (Rh) is high enough to realize site percolation within the thickness of the passive film or the dissolution depth. This 2D-3D percolation cross-over transition explains the compositional dependent passivation of these alloys. The theoretical description of the transition and its assumptions is examined via experiments and kinetic Monte Carlo simulations. The initial passivation scenario of the dissolution selectivity is validated by the inductively coupled plasma mass spectrum (ICP-MS). The electronic effect not considered in the kinetic Monte Carlo simulations is addressed by density functional theory (DFT). Additionally, the impact of the atomic configuration parameter on alloy passivation is experimentally measured, which turns out to agree well with the model predictions developed using Monte Carlo renormalization group (MC-RNG) methods.
ContributorsXie, Yusi (Author) / Sieradzki, Karl KS (Thesis advisor) / Chan, Candace CC (Committee member) / Wang, Qing QHW (Committee member) / Buttry, Daniel DB (Committee member) / Arizona State University (Publisher)
Created2020
Description
With the rise of Posttraumatic Stress Disorder (PTSD) among adults in the United States, understanding the processes of trauma, trauma related disorders, and the long-term impact of living with them is an area of continued focus for researchers. This is especially a concern in the case of current and former military service members (veterans), whose work activities and deployment cycles place them at an increased risk of exposure to trauma-inducing experiences but who have a low rate of self-referral to healthcare professionals. There is thus an urgent need for developing procedures for early diagnosis and treatment. The present study examines how the tools and findings of the field of linguistics may contribute to the field of trauma research. Previous research has shown that cognition and language production are closely linked. This study focuses on the role of prosody in PTSD and pilots a procedure for the data collection and analysis. Data consist of monologic talk from a sample of student-veterans and analyzed with speech software (Praat) for pauses greater than 250 milliseconds per 100 words. The pause frequency was compared to a PCL-5 score, an assessment used to check for PTSD symptoms and evaluate need for further assessment and possible diagnosis of PTSD. This pilot study found the methods successfully elicited data that could be used to measure and test the research questions. Although the findings of the study were inconclusive due to limitations of the participant pool, it found that the research model proved effect as a model for future linguistic research on trauma.
ContributorsSouthee, Richard Aaron (Author) / Prior, Matthew T. (Thesis advisor) / Pruitt, Kathryn (Committee member) / Pereira, Jennifer (Committee member) / Arizona State University (Publisher)
Created2020