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A novel technique for measuring heavy trace elements in geologic materials with secondary ion mass spectrometry (SIMS) is presented. This technique combines moderate levels of mass resolving power (MRP) with energy filtering in order to remove molecular ion interferences while maintaining enough sensitivity to measure trace elements. The technique was

A novel technique for measuring heavy trace elements in geologic materials with secondary ion mass spectrometry (SIMS) is presented. This technique combines moderate levels of mass resolving power (MRP) with energy filtering in order to remove molecular ion interferences while maintaining enough sensitivity to measure trace elements. The technique was evaluated by measuring a set of heavy chalcophilic elements in two sets of doped glasses similar in composition to rhyolites and basalts, respectively. The normalized count rates of Cu, As, Se, Br, and Te were plotted against concentrations to test that the signal increased linearly with concentration. The signal from any residual molecular ion interferences (e.g. ²⁹Si³⁰Si¹⁶O on ⁷⁵As) represented apparent concentrations ≤ 1 μg/g for most of the chalcophiles in rhyolitic matrices and between 1 and 10 μg/g in basaltic compositions. This technique was then applied to two suites of melt inclusions from the Bandelier Tuff: Ti-rich, primitive and Ti-poor, evolved rhyolitic compositions. The results showed that Ti-rich inclusions contained ~30 μg/g Cu and ~3 μg/g As while the Ti-poor inclusions contained near background Cu and ~6 μg/g As. Additionally, two of the Ti-rich inclusions contained > 5 μg/g of Sb and Te, well above background. Other elements were at or near background. This suggests certain chalcophilic elements may be helpful in unraveling processes relating to diversity of magma sources in large eruptions. Additionally, an unrelated experiment is presented demonstrating changes in the matrix effect on SIMS counts when normalizing against ³⁰Si⁺ versus ²⁸Si²⁺. If one uses doubly charged silicon as a reference, (common when using large-geometry SIMS instruments to study the light elements Li - C) it is important that the standards closely match the major element chemistry of the unknown.
ContributorsCarlson, Eric Norton (Author) / Hervig, Richard L (Thesis advisor) / Roggensack, Kurt (Committee member) / Burt, Donald M (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Desorption processes are an important part of all processes which involve utilization of solid adsorbents such as adsorption cooling, sorption thermal energy storage, and drying and dehumidification processes and are inherently energy-intensive. Here, how those energy requirements can be reduced through the application of ultrasound for three widely used

Desorption processes are an important part of all processes which involve utilization of solid adsorbents such as adsorption cooling, sorption thermal energy storage, and drying and dehumidification processes and are inherently energy-intensive. Here, how those energy requirements can be reduced through the application of ultrasound for three widely used adsorbents namely zeolite 13X, activated alumina and silica gel is investigated. To determine and justify the effectiveness of incorporating ultrasound from an energy-savings point of view, an approach of constant overall input power of 20 and 25 W was adopted. To measure the extent of the effectiveness of using ultrasound, the ultrasonic-power-to-total power ratios of 0.2, 0.25, 0.4 and 0.5 were investigated and the results compared with those of no-ultrasound (heat only) at the same total power. Duplicate experiments were performed at three nominal frequencies of 28, 40 and 80 kHz to observe the influence of frequency on regeneration dynamics. Regarding moisture removal, application of ultrasound results in higher desorption rate compared to a non-ultrasound process. A nonlinear inverse proportionality was observed between the effectiveness of ultrasound and the frequency at which it is applied. Based on the variation of desorption dynamics with ultrasonic power and frequency, three mechanisms of reduced adsorbate adsorption potential, increased adsorbate surface energy and enhanced mass diffusion are proposed. Two analytical models that describe the desorption process were developed based on the experimental data from which novel efficiency metrics were proposed, which can be employed to justify incorporating ultrasound in regeneration and drying processes.
ContributorsDaghooghi Mobarakeh, Hooman (Author) / Phelan, Patrick (Thesis advisor) / Wang, Liping (Committee member) / Wang, Robert (Committee member) / Calhoun, Ronald (Committee member) / Deng, Shuguang (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Wide bandgap semiconductors, also known as WBG semiconductors are materials which have larger bandgaps than conventional semiconductors such as Si or GaAs. They permit devices to operate at much higher voltages, frequencies and temperatures. They are the key material used to make LEDs, lasers, radio frequency applications, military applications, and

Wide bandgap semiconductors, also known as WBG semiconductors are materials which have larger bandgaps than conventional semiconductors such as Si or GaAs. They permit devices to operate at much higher voltages, frequencies and temperatures. They are the key material used to make LEDs, lasers, radio frequency applications, military applications, and power electronics. Their intrinsic qualities make them promising for next-generation devices for general semiconductor use. Their ability to handle higher power density is particularly attractive for attempts to sustain Moore's law, as conventional technologies appear to be reaching a bottleneck. Apart from WBG materials, ultra-wide bandgap (UWBG) materials, such as Ga2O3, AlN, diamond, or BN, are also attractive since they have even more extreme properties. Although this field is relatively new, which still remains a lot of effort to study and investigate, people can still expect that these materials could be the main characters for more advanced applications in the near future. In the dissertation, three topics with power devices made by WBG or UWBG semiconductors were introduced. In chapter 1, a generally background knowledge introduction is given. This helps the reader to learn current research focuses. In chapter 2, a comprehensive study of temperature-dependent characteristics of Ga2O3 SBDs with highly-doped substrate is demonstrated. A modified thermionic emission model over an inhomogeneous barrier with a voltage-dependent barrier height is investigated. Besides, the mechanism of surface leakage current is also discussed. These results are beneficial for future developments of low-loss β-Ga2O3 electronics and optoelectronics. In chapter 3, vertical GaN Schottky barrier diodes (SBDs) with floating metal rings (FMRs) as edge termination structures on bulk GaN substrates was introduced. This work represents a useful reference for the FMR termination design for GaN power devices. In chapter 4, AlGaN/GaN metal-insulator-semiconductor high electron mobility transistors (MISHEMTs) fabricated on Si substrates with a 10 nm boron nitride (BN) layer as gate dielectric was demonstrated. The material characterization was investigated by X-ray photoelectric spectroscopy (XPS) and UV photoelectron spectroscopy (UPS). And the gate leakage current mechanisms were also investigated by temperature-dependent current-voltage measurements. Although still in its infancy, past and projected future progress of electronic designs will ultimately achieve this very goal that WBG and UWBG semiconductors will be indispensable for today and future’s science, technologies and society.
ContributorsYang, Tsung-Han (Author) / Zhao, Yuji (Thesis advisor) / Vasileska, Dragica (Committee member) / Yu, Hongbin (Committee member) / Nemanich, Robert (Committee member) / Arizona State University (Publisher)
Created2021
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Description
As India expanded its grid infrastructure, decentralized renewable energy technologies, such as off-grid solar, also emerged in parallel as an electrification solution. This dissertation critically examines the role of off-grid solar in facilitating rural electrification efforts in India. Specifically, it applies the frameworks of the multi-level perspective, capabilities approach, and

As India expanded its grid infrastructure, decentralized renewable energy technologies, such as off-grid solar, also emerged in parallel as an electrification solution. This dissertation critically examines the role of off-grid solar in facilitating rural electrification efforts in India. Specifically, it applies the frameworks of the multi-level perspective, capabilities approach, and energy justice to achieve three objectives: (1) trace the evolution of off-grid solar in India; (2) understand the role of solar micro-grids in improving household capabilities and well-being; (1) examine whether and how community-scale solar micro-grids can operate as just means of electrification. This research relies on qualitative case-study methods. The historical research in Paper 1 is based on published policy documents and interviews with energy experts in India. It finds that landscape-regime-niche actor relations and politics were crucial in shaping off-grid solar transition outcomes. There is also a narrative component, as the key narratives of energy security, environmental degradation, climate change and energy for development converged to create spaces for state and non-state interactions that could nurture the development of off-grid solar. The community-level research in Papers 2 and 3 analyze a local energy initiative of community operated solar micro-grid using semi-structured interviews and participant observations from three villages in Maharashtra. Solar micro-grids play an important part in expanding people’s choices and opportunities. The benefits are not uniform across all people, however. Increases in energy-related capabilities vary by economic class and gender, and to some extent this means certain biases can get reinforced. In addition, the inability of solar micro-grids to keep up with the changing electrification landscape and daily practices means that the challenges of affordability, reliability and community engagement emerged as important concerns over-time. Empirically, this dissertation finds that off-grid energy initiatives must be carefully designed to be in alignment with local values and realities. Theoretically, it adds to debates on justice in energy transitions by showcasing the regime-led innovations, and temporality elements of energy justice local energy initiatives.
ContributorsRajagopalan, Sushil (Author) / Breetz, Hanna (Thesis advisor) / Klinsky, Sonja (Thesis advisor) / Singh, Kartikeya (Committee member) / Arizona State University (Publisher)
Created2021
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Description
The need of effective forecasting models for multi-variate time series has been underlined by the integration of sensory technologies into essential applications such as building energy optimizations, flight monitoring, and health monitoring. To meet this requirement, time series prediction techniques have been expanded from uni-variate to multi-variate. However, due to

The need of effective forecasting models for multi-variate time series has been underlined by the integration of sensory technologies into essential applications such as building energy optimizations, flight monitoring, and health monitoring. To meet this requirement, time series prediction techniques have been expanded from uni-variate to multi-variate. However, due to the extended models’ poor ability to capture the intrinsic relationships among variates, naïve extensions of prediction approaches result in an unwanted rise in the cost of model learning and, more critically, a significant loss in model performance. While recurrent models like Long Short-Term Memory (LSTM) and Recurrent Neural Network Network (RNN) are designed to capture the temporal intricacies in data, their performance can soon deteriorate. First, I claim in this thesis that (a) by exploiting temporal alignments of variates to quantify the importance of the recorded variates in relation to a target variate, one can build a more accurate forecasting model. I also argue that (b) traditional time series similarity/distance functions, such as Dynamic Time Warping (DTW), which require that variates have similar absolute patterns are fundamentally ill-suited for this purpose, and that should instead quantify temporal correlation in terms of temporal alignments of key “events” impacting these series, rather than series similarity. Further, I propose that (c) while learning a temporal model with recurrence-based techniques (such as RNN and LSTM – even when leveraging attention strategies) is challenging and expensive, the better results can be obtained by coupling simpler CNNs with an adaptive variate selection strategy. Putting these together, I introduce a novel Selego framework for variate selection based on these arguments, and I experimentally evaluate the performance of the proposed approach on various forecasting models, such as LSTM, RNN, and CNN, for different top-X% percent variates and different forecasting time in the future (lead), on multiple real-world data sets. Experiments demonstrate that the proposed framework can reduce the number of recorded variates required to train predictive models by 90 - 98% while also increasing accuracy. Finally, I present a fault onset detection technique that leverages the precise baseline forecasting models trained using the Selego framework. The proposed, Selego-enabled Fault Detection Framework (FDF-Selego) has been experimentally evaluated within the context of detecting the onset of faults in the building Heating, Ventilation, and Air Conditioning (HVAC) system.
ContributorsTiwaskar, Manoj (Author) / Candan, K. Selcuk (Thesis advisor) / Sapino, Maria Luisa (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2021
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Description
The GlueX experiment housed in Hall D of the Thomas Jefferson National Laboratory was created to map the light meson spectrum in order to contribute to the Standard Model of particle physics by strengthening our understanding of the strong interaction. GlueX is a medium-energy photoproduction experiment that utilizes a linearly

The GlueX experiment housed in Hall D of the Thomas Jefferson National Laboratory was created to map the light meson spectrum in order to contribute to the Standard Model of particle physics by strengthening our understanding of the strong interaction. GlueX is a medium-energy photoproduction experiment that utilizes a linearly polarized photon beam to create hadronic forms of matter. By mapping the light meson spectrum, the GlueX collaboration hopes to identify meson states forbidden by the Constituent Quark Model. As a main research objective, the GlueX collaboration is searching for hybrid $q\bar{q}g$ meson states that exhibit exotic quantum numbers. One hybrid meson candidate is the $\eta'_1$, which is predicted to decay to $K^\ast\bar{K}$ and have a mass near $2.3~\mathrm{GeV}$ (\citeauthor{qn_exotic_status}, \citeyear{qn_exotic_status}; \citeauthor{hybrid_mesons}, \citeyear{hybrid_mesons}). At this time, very few meson states have been identified in the $2.0~\mathrm{GeV}$ mass region. This dearth of evidence for existing states requires any tool developed to search for meson states above $2.0~\mathrm{GeV}$ must be verified by looking at known meson states. In order to search for the $\eta'_1$ hybrid meson candidate in $\gamma p \rightarrow pK^+K^-\gamma\gamma$ events, meson states decaying $K^\ast\bar{K}$ that contribute to the low mass region must be identified, defined in this document as particles having masses between $1400$ and $1600~\mathrm{MeV}$. Identifying what meson states exist in the low mass region is also critical to mapping the light meson spectrum and determining the quark-gluonic content of those meson states. The results of a partial wave analysis (PWA) of $\gamma p \rightarrow pX$ where $X\rightarrow K^\ast\bar{K}$ from $\gamma p \rightarrow pK^+K^-\gamma\gamma$ events in GlueX are presented. In the $J=0$ invariant mass distribution, the $\eta(1405)$ and $\eta(1475)$ are identified, adding to the debate as to whether two pseudoscalar mesons exist in the low mass region. For the $J=1$ distribution, the $f_1(1420)$ and $f_1(1510)$ axial vector mesons are seen, where the former helps further elaborate on the $E\iota$ puzzle of the twentieth century \citep{E_iota_puzzle}. With respect to the controversy of meson states in the low mass region, evidence for the existence of the $f_2(1430)$ meson is strengthened in the $J=2$ distribution, and the $f'_2(1525)$ state is seen. This work lays a foundation for the ASU Meson Physics Group to continue a wider search for hybrid mesons in the $\gamma p \rightarrow pK^+K^-\gamma\gamma$ reaction topology.
ContributorsCole, Sebastian Miles (Author) / Dugger, Michael (Thesis advisor) / Ritchie, Barry (Committee member) / Alarcon, Ricardo (Committee member) / Shovkovy, Igor (Committee member) / Arizona State University (Publisher)
Created2021
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Description
This thesis argues that physical landscapes, from intentional sites of memory to average public spaces, play a foundational role in the formation and continuation of the official politics of memory that underpins Serbian cultural memory and collective identity. Thus, in order to understand the complexities of the Serbian collective identity,

This thesis argues that physical landscapes, from intentional sites of memory to average public spaces, play a foundational role in the formation and continuation of the official politics of memory that underpins Serbian cultural memory and collective identity. Thus, in order to understand the complexities of the Serbian collective identity, the landscapes that underpin such an identity must first be understood. Building off prior findings, the three landscapes to be considered relate to three pivotal moments in Serbian nation-building and identity formation: the end of the Ottoman presence, World War II and Yugoslavia, and the wars of the 1990s. This thesis put surveys of Serbian landscapes, which map both sites of remembrance and sites left to be forgotten in Belgrade, as well as oral histories with local young-adult Serbians in conversation in order to elucidate the extent to which individual conceptions of the past and of the Serbian identity correlate to the official politics of memory in Serbia. Young-adult Serbians have been selected, as their only personal experience with each moment of history under consideration is generational memory and state narratives of the past. Ultimately, this study seeks to expand and verify the themes of remembrance found in Serbia as well as understand how the reconstruction of the past, starting from the end of the Ottoman presence to the 1990s war, has figured into the various nation-building projects in Serbia. Building on Halbwachs and Nora, this study understands culture memory as dependent on objectivized culture, like buildings, which naturally challenges the traditional separation of memory and history. Though it does not represent the full Serbian public, this study demonstrates the limited role the physical landscape has in shaping the understanding of the past held by the Serbians interviewees.
ContributorsStull, Madeline (Author) / Manchester, Laurie (Thesis advisor) / Cichopek-Gajraj, Anna (Committee member) / Thompson, Victoria (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Stressors to marine environments are predicted to increase and affect the well-being of marine ecosystems and coastal communities. Marine protected areas (MPAs) are one most widely implemented interventions for marine stressors. Despite the implementation of thousands of protected areas worldwide, people are still striving to understand their dynamics as they

Stressors to marine environments are predicted to increase and affect the well-being of marine ecosystems and coastal communities. Marine protected areas (MPAs) are one most widely implemented interventions for marine stressors. Despite the implementation of thousands of protected areas worldwide, people are still striving to understand their dynamics as they vary in their efficacy and many MPAs have not met their objectives. Additionally, those that have often fail to protect the ecosystem services and cultural values necessary for human community health. Thus, research has expanded to include analyses of the human and social dimensions that may limit their effectiveness. This dissertation explores the role of community engagement in marine protected areas and perceptions of environmental changes in coastal communities. Currently, existing research on the roles of community engagement in marine conservation interventions is limited, particularly in the island-states of the Caribbean region. This dissertation contains a review of the literature to understand the nuances of community engagement in relation to MPAs. Through the review, it was determined that primary forms of engagement are interviews and surveys, and respondents primarily included businesses, community members, fishers, and resource users. To better understand the perceptions and practices on-the-ground, key informants were interviewed across the Caribbean. There are strong desires to conduct community engagement for innumerable benefits, but there are barriers that some participants have overcome. Sharing information between MPA sites offers an opportunity to effectively engage community members. For the local case study, Charlotteville, Trinidad and Tobago, a small, coastal fishing town in the northeast region of Tobago was selected to understand the role of perceptions of environmental changes. There were strong ties of environmental and social changes, with an emphasis on the impacts of environmental stressors to human health. The heterogeneity and diversity of responses in this chapter highlight the need to consider who is engaged in community engagement activities.
ContributorsBernard, Miranda Lynn (Author) / Gerber, Leah (Thesis advisor) / Buzinde, Christine (Committee member) / Schoon, Michael (Committee member) / Kittinger, Jack (Committee member) / Cheng, Samantha (Committee member) / Arizona State University (Publisher)
Created2021
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Description
The current study explores the extent to which different processing strategies affect comprehension accuracy and integration of information across multiple texts. Reading comprehension of single texts is a difficult task, in which the challenges are compounded by the need to integrate information across texts. Processing strategies, such as self-explanation and

The current study explores the extent to which different processing strategies affect comprehension accuracy and integration of information across multiple texts. Reading comprehension of single texts is a difficult task, in which the challenges are compounded by the need to integrate information across texts. Processing strategies, such as self-explanation and source-evaluation, help reduce the challenges that readers face when attempting to comprehend texts. Self-explanation has been a successful strategy for coherence-building processes in single text comprehension, but the benefits for supporting inter-textual comprehension have not yet been explored. Source-evaluation supports identification of different sources, which helps resolve inconsistencies between texts; yet it remains unclear whether sourcing alone supports comprehension within as well as between texts. Think-aloud is a strategy intended to encourage further processing of the text without providing any explicit comprehension strategy. The differences between these two strategies prompts questions regarding the adequacy of either strategy for supporting inferencing and integration within and across texts. In this study, participants (n=80) were randomly assigned to one of three strategy conditions: self-explanation, source-evaluation, or think-aloud. Students read four texts after which they completed three types of open-ended comprehension questions (i.e., textbase, intra-textual inference, and inter-textual inference), a source memory task, and individual difference measures. Prior knowledge and reading skill were strongly correlated (r = .65) and showed moderate correlations (r = .31 to .60) with participants’ comprehension accuracy, total number of integrations within their responses, and their memory for sources. Participants were more likely to respond accurately and demonstrate integrations across texts for the text-based questions in comparison to the more challenging inference questions. There was a marginal effect of condition on comprehension question accuracy, wherein participants who self-explained responded more accurately than those who engaged in the think-aloud task. In addition, those in the self-explanation or source-evaluation conditions recalled more sources than those in the think-aloud condition. There were no significant differences in performance between the self-explanation and the source-evaluation conditions. Overall, the results of this study indicate that encouraging students to self-explain and/or evaluate sources while they read multiple documents enhances comprehension and memory for sources.
ContributorsPerret, Cecile Aline (Author) / McNamara, Danielle S (Thesis advisor) / Brewer, Gene (Committee member) / Glenberg, Arthur (Committee member) / Arizona State University (Publisher)
Created2021
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Description
In many real-world machine learning classification applications, well labeled training data can be difficult, expensive, or even impossible to obtain. In such situations, it is sometimes possible to label a small subset of data as belonging to the class of interest though it is impractical to manually label all data

In many real-world machine learning classification applications, well labeled training data can be difficult, expensive, or even impossible to obtain. In such situations, it is sometimes possible to label a small subset of data as belonging to the class of interest though it is impractical to manually label all data not of interest. The result is a small set of positive labeled data and a large set of unknown and unlabeled data. This is known as the Positive and Unlabeled learning (PU learning) problem, a type of semi-supervised learning. In this dissertation, the PU learning problem is rigorously defined, several common assumptions described, and a literature review of the field provided. A new family of effective PU learning algorithms, the MLR (Modified Logistic Regression) family of algorithms, is described. Theoretical and experimental justification for these algorithms is provided demonstrating their success and flexibility. Extensive experimentation and empirical evidence are provided comparing several new and existing PU learning evaluation estimation metrics in a wide variety of scenarios. The surprisingly clear advantage of a simple recall estimate as the best estimate for overall PU classifier performance is described. Finally, an application of PU learning to the field of solar fault detection, an area not previously explored in the field, demonstrates the advantage and potential of PU learning in new application domains.
ContributorsJaskie, Kristen P (Author) / Spanias, Andreas (Thesis advisor) / Blain-Christen, Jennifer (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Thiagarajan, Jayaraman (Committee member) / Arizona State University (Publisher)
Created2021