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The goal of the paper was to examine the fatigue mechanisms of polymers and silicone based elastomers. The mechanisms of fatigue due to crazing: the alignment of polymer chains to the stress axis, and shear banding: the localized orientation of the polymer by the shear stresses from two planes, were

The goal of the paper was to examine the fatigue mechanisms of polymers and silicone based elastomers. The mechanisms of fatigue due to crazing: the alignment of polymer chains to the stress axis, and shear banding: the localized orientation of the polymer by the shear stresses from two planes, were discussed in depth in this paper. Crazing only occurs in tensile stress, is initiated on the surface of the material, and only occurs in brittle polymers. Crazing also accounts for a 40-60% decrease in density, causing localized weakening of the material and a concentration in stress. This is due to a decrease in effective cross sectional area. The mechanism behind discontinuous growth bands was also discussed to be the cause of cyclic crazing. Shear banding only occurs in ductile polymers and can result in the failure of polymers via necking. Furthermore, the high fatigue resistance of silicone elastomers was discussed in this paper. This conclusion was made because of the lack of fatigue mechanisms (crazing, discontinuous growth bands, and shears banding) in the observed elastomer's microstructure after the samples had undergone fatigue tests. This was done through an analysis of room temperature vulcanized silicone adhesives, a heat-curing silicone elastomer, and a self-curing transparent silicone rubber. Fatigue of room temperature vulcanized silicon was observed, however this was reasoned to be the failure of the adhesion of the elastomer to the steel substrate instead of the microstructure itself. Additionally, the significance of fatigue in real world applications was discussed using SouthWest Airlines Flight 812 as an example.
ContributorsWong, Christopher Stanley (Author) / Adams, James (Thesis director) / Krause, Stephen (Committee member) / Anwar, Shahriar (Committee member) / Materials Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
Obesity and related health disparities including type 2 diabetes disproportionately impact Latino youth. These health disparities may be the result of gene-environment interactions, but limited research has examined these interactions in the pediatric age group. Lifestyle intervention is the cornerstone for preventing diabetes among high-risk populations and epigenetic and genetic

Obesity and related health disparities including type 2 diabetes disproportionately impact Latino youth. These health disparities may be the result of gene-environment interactions, but limited research has examined these interactions in the pediatric age group. Lifestyle intervention is the cornerstone for preventing diabetes among high-risk populations and epigenetic and genetic factors may help explain the biological mechanisms underlying diabetes risk reduction following lifestyle changes. MicroRNAs (miRNAs) are small, non-coding RNA’s that regulate gene expression and have emerged as potential biomarkers for predicting type 2 diabetes risk in adults but have yet to be applied to youth. Therefore, the purpose of this study was to identify changes in miRNA expression among Latino youth with prediabetes (4 female/2 male, ages 14-16, BMI percentile 99 ±.2) who participated in a 12-week lifestyle intervention focused on increasing physical activity and improving nutrition-related behaviors.
ContributorsKarch, Jamie (Co-author) / Day, Samantha (Co-author) / Shaibi, Gabriel (Thesis director) / Coletta, Dawn (Committee member) / Arizona State University. College of Nursing & Healthcare Innovation (Contributor) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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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

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
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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

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
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Description
This work presents a thorough analysis of reconstruction of global wave fields (governed by the inhomogeneous wave equation and the Maxwell vector wave equation) from sensor time series data of the wave field. Three major problems are considered. First, an analysis of circumstances under which wave fields can be fully

This work presents a thorough analysis of reconstruction of global wave fields (governed by the inhomogeneous wave equation and the Maxwell vector wave equation) from sensor time series data of the wave field. Three major problems are considered. First, an analysis of circumstances under which wave fields can be fully reconstructed from a network of fixed-location sensors is presented. It is proven that, in many cases, wave fields can be fully reconstructed from a single sensor, but that such reconstructions can be sensitive to small perturbations in sensor placement. Generally, multiple sensors are necessary. The next problem considered is how to obtain a global approximation of an electromagnetic wave field in the presence of an amplifying noisy current density from sensor time series data. This type of noise, described in terms of a cylindrical Wiener process, creates a nonequilibrium system, derived from Maxwell’s equations, where variance increases with time. In this noisy system, longer observation times do not generally provide more accurate estimates of the field coefficients. The mean squared error of the estimates can be decomposed into a sum of the squared bias and the variance. As the observation time $\tau$ increases, the bias decreases as $\mathcal{O}(1/\tau)$ but the variance increases as $\mathcal{O}(\tau)$. The contrasting time scales imply the existence of an ``optimal'' observing time (the bias-variance tradeoff). An iterative algorithm is developed to construct global approximations of the electric field using the optimal observing times. Lastly, the effect of sensor acceleration is considered. When the sensor location is fixed, measurements of wave fields composed of plane waves are almost periodic and so can be written in terms of a standard Fourier basis. When the sensor is accelerating, the resulting time series is no longer almost periodic. This phenomenon is related to the Doppler effect, where a time transformation must be performed to obtain the frequency and amplitude information from the time series data. To obtain frequency and amplitude information from accelerating sensor time series data in a general inhomogeneous medium, a randomized algorithm is presented. The algorithm is analyzed and example wave fields are reconstructed.
ContributorsBarclay, Bryce Matthew (Author) / Mahalov, Alex (Thesis advisor) / Kostelich, Eric J (Thesis advisor) / Moustaoui, Mohamed (Committee member) / Motsch, Sebastien (Committee member) / Platte, Rodrigo (Committee member) / Arizona State University (Publisher)
Created2023
Description

Sulfate deficiency is seen in children with autism through increased urinary excretion of sulfate and low plasma sulfate levels. Potential factors impacting reduced sulfation include phenosulfotransferase activity, sulfate availability, and the presence of the gut toxin p-cresol. Epsom salt baths, vitamin supplementation, and fecal microbiota transplant therapy are all potential

Sulfate deficiency is seen in children with autism through increased urinary excretion of sulfate and low plasma sulfate levels. Potential factors impacting reduced sulfation include phenosulfotransferase activity, sulfate availability, and the presence of the gut toxin p-cresol. Epsom salt baths, vitamin supplementation, and fecal microbiota transplant therapy are all potential treatments with promising results. Sulfate levels have potential for use as a diagnostic biomarker, allowing for earlier diagnosis and intervention.

ContributorsErickson, Payton (Author) / Adams, James (Thesis director) / Krajmalnik-Brown, Rosa (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Historical, Philosophical & Religious Studies, Sch (Contributor) / School of Human Evolution & Social Change (Contributor)
Created2023-05
Description

Climate is a critical determinant of agricultural productivity, and the ability to accurately predict this productivity is necessary to provide guidance regarding food security and agricultural management. Previous predictions vary in approach due to the myriad of factors influencing agricultural productivity but generally suggest long-term declines in productivity and agricultural

Climate is a critical determinant of agricultural productivity, and the ability to accurately predict this productivity is necessary to provide guidance regarding food security and agricultural management. Previous predictions vary in approach due to the myriad of factors influencing agricultural productivity but generally suggest long-term declines in productivity and agricultural land suitability under climate change. In this paper, I relate predicted climate changes to yield for three major United States crops, namely corn, soybeans, and wheat, using a moderate emissions scenario. By adopting data-driven machine learning approaches, I used the following machine learning methods: random forest (RF), extreme gradient boosting (XGB), and artificial neural networks (ANN) to perform comparative analysis and ensemble methodology. I omitted the western US due to the region's susceptibility to water stress and the prevalence of artificial irrigation as a means to compensate for dry conditions. By considering only climate, the model's results suggest an ensemble mean decline in crop yield of 23.4\% for corn, 19.1\% for soybeans, and 7.8\% for wheat between the years of 2017 and 2100. These results emphasize potential negative impacts of climate change on the current agricultural industry as a result of shifting bio-climactic conditions.

ContributorsSwarup, Shray (Author) / Eikenberry, Steffen (Thesis director) / Mahalov, Alex (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2023-05
Description

The Healthy Pregnancy Summit is a collection of videos from a variety of specialists detailing how to have a healthy pregnancy and healthy child, based on the latest scientific and medical information. This project summarizes each presentation, and compares to the Healthy Child Guide, a document supplementary to the summit.

The Healthy Pregnancy Summit is a collection of videos from a variety of specialists detailing how to have a healthy pregnancy and healthy child, based on the latest scientific and medical information. This project summarizes each presentation, and compares to the Healthy Child Guide, a document supplementary to the summit. Finally, this project analyzes the overall usefulness of the summit and each presentation, and suggests areas for improvement.

ContributorsKragenbring, Kylee (Author) / Adams, James (Thesis director) / Matthews, Julie (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / School of Human Evolution & Social Change (Contributor)
Created2023-05
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Description
Organic materials have emerged as an attractive component of electronics over the past few decades, particularly in the development of efficient and stable organic light-emitting diodes (OLEDs) and organic neuromorphic devices. The electrical, chemical, physical, and optical studies of organic materials and their corresponding devices have been conducted for efficient

Organic materials have emerged as an attractive component of electronics over the past few decades, particularly in the development of efficient and stable organic light-emitting diodes (OLEDs) and organic neuromorphic devices. The electrical, chemical, physical, and optical studies of organic materials and their corresponding devices have been conducted for efficient and stable electronics. The development of efficient and stable deep blue OLED devices remains a challenge that has obstructed the progress of large-scale OLED commercialization. One approach was taken to achieve a deep blue emitter through a color tuning strategy. A new complex, PtNONS56-dtb, was designed and synthesized by controlling the energy gap between T1 and T2 energy states to achieve narrowed and blueshifted emission spectra. This emitter material showed an emission spectrum at 460 nm with a FWHM of 59 nm at room temperature in PMMA, and the PtNONS56-dtb-based device exhibited a peak EQE of 8.5% with CIE coordinates of (0.14, 0.27). A newly developed host and electron blocking materials were demonstrated to achieve efficient and stable OLED devices. The indolocarbazole-based materials were designed to have good hole mobility and high triplet energy. BCN34 as an electron blocking material achieved the estimated LT80 of 12509 h at 1000 cd m-2 with a peak EQE of 30.3% in devices employing Pd3O3 emitter. Additionally, a device with bi-layer emissive layer structure, using BCN34 and CBP as host materials doped with PtN3N emitter, achieved a peak EQE of 16.5% with the LT97 of 351 h at 1000 cd m-2. A new neuromorphic device using Ru(bpy)3(PF6)2 as an active layer was designed to emulate the short-term characteristics of a biological synapse. This memristive device showed a similar operational mechanism with biological synapse through the movement of ions and electronic charges. Furthermore, the performance of the device showed tunability by adding salt. Ultimately, the device with 2% LiClO4 salt shows similar timescales to short-term plasticity characteristics of biological synapses.
ContributorsShin, Samuel (Author) / Li, Jian (Thesis advisor) / Adams, James (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2021
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Description

Cities in the Global South face rapid urbanization challenges and often suffer an acute lack of infrastructure and governance capacities. Smart Cities Mission, in India, launched in 2015, aims to offer a novel approach for urban renewal of 100 cities following an area‐based development approach, where the use of ICT

Cities in the Global South face rapid urbanization challenges and often suffer an acute lack of infrastructure and governance capacities. Smart Cities Mission, in India, launched in 2015, aims to offer a novel approach for urban renewal of 100 cities following an area‐based development approach, where the use of ICT and digital technologies is particularly emphasized. This article presents a critical review of the design and implementation framework of this new urban renewal program across selected case‐study cities. The article examines the claims of the so‐called “smart cities” against actual urban transformation on‐ground and evaluates how “inclusive” and “sustainable” these developments are. We quantify the scale and coverage of the smart city urban renewal projects in the cities to highlight who the program includes and excludes. The article also presents a statistical analysis of the sectoral focus and budgetary allocations of the projects under the Smart Cities Mission to find an inherent bias in these smart city initiatives in terms of which types of development they promote and the ones it ignores. The findings indicate that a predominant emphasis on digital urban renewal of selected precincts and enclaves, branded as “smart cities,” leads to deepening social polarization and gentrification. The article offers crucial urban planning lessons for designing ICT‐driven urban renewal projects, while addressing critical questions around inclusion and sustainability in smart city ventures.`

ContributorsPraharaj, Sarbeswar (Author)
Created2021-05-07