Matching Items (181)
Description
Neural tissue is a delicate system comprised of neurons and their synapses, glial cells for support, and vasculature for oxygen and nutrient delivery. This complexity ultimately gives rise to the human brain, a system researchers have become increasingly interested in replicating for artificial intelligence purposes. Some have even gone so far as to use neuronal cultures as computing hardware, but utilizing an environment closer to a living brain means having to grapple with the same issues faced by clinicians and researchers trying to treat brain disorders. Most outstanding among these are the problems that arise with invasive interfaces. Optical techniques that use fluorescent dyes and proteins have emerged as a solution for noninvasive imaging with single-cell resolution in vitro and in vivo, but feeding in information in the form of neuromodulation still requires implanted electrodes. The implantation process of these electrodes damages nearby neurons and their connections, causes hemorrhaging, and leads to scarring and gliosis that diminish efficacy. Here, a new approach for noninvasive neuromodulation with high spatial precision is described. It makes use of a combination of ultrasound, high frequency acoustic energy that can be focused to submillimeter regions at significant depths, and electric fields, an effective tool for neuromodulation that lacks spatial precision when used in a noninvasive manner. The hypothesis is that, when combined in a specific manner, these will lead to nonlinear effects at neuronal membranes that cause cells only in the region of overlap to be stimulated. Computational modeling confirmed this combination to be uniquely stimulating, contingent on certain physical effects of ultrasound on cell membranes. Subsequent in vitro experiments led to inconclusive results, however, leaving the door open for future experimentation with modified configurations and approaches. The specific combination explored here is also not the only untested technique that may achieve a similar goal.
ContributorsNester, Elliot (Author) / Wang, Yalin (Thesis advisor) / Muthuswamy, Jitendran (Committee member) / Towe, Bruce (Committee member) / Arizona State University (Publisher)
Created2022
Description
Beta-Amyloid(Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer’s disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. However, current methods to detect Aβ/tau pathology are either invasive (lumbar puncture) or quite costly and not widely available (positron emission tomography (PET)). And one of the particular neurodegenerative regions is the hippocampus to which the influence of Aβ/tau on has been one of the research projects focuses in the AD pathophysiological progress.
In this dissertation, I proposed three novel machine learning and statistical models to examine subtle aspects of the hippocampal morphometry from MRI that are associated with Aβ /tau burden in the brain, measured using PET images. The first model is a novel unsupervised feature reduction model to generate a low-dimensional representation of hippocampal morphometry for each individual subject, which has superior performance in predicting Aβ/tau burden in the brain. The second one is an efficient federated group lasso model to identify the hippocampal subregions where atrophy is strongly associated with abnormal Aβ/Tau. The last one is a federated model for imaging genetics, which can identify genetic and transcriptomic influences on hippocampal morphometry. Finally, I stated the results of these three models that have been published or submitted to peer-reviewed conferences and journals.
ContributorsWu, Jianfeng (Author) / Wang, Yalin (Thesis advisor) / Li, Baoxin (Committee member) / Liang, Jianming (Committee member) / Wang, Junwen (Committee member) / Wu, Teresa (Committee member) / Arizona State University (Publisher)
Created2022
Description
Structural Magnetic Resonance Imaging analysis is a vital component in the study of Alzheimer’s Disease pathology and several techniques exist as part of the existing research conducted. In particular, volumetric approaches in this field are known to be beneficial due to the increased capability to express morphological characteristics when compared to manifold methods. To aid in the improvement of the field, this paper aims to propose an intrinsic volumetric conic system that can be applied to bounded volumetric meshes to enable a more effective study of subjects. The computation of the metric involves the use of heat kernel theory and conformal parameterization on genus-0 surfaces extended to a volumetric domain. Additionally, this paper also explores the use of the ’TetCNN’ architecture on the classification of hippocampal tetrahedral meshes to detect features that correspond to Alzheimer’s indicators. The model tested was able to achieve remarkable results with a measured classification accuracy of above 90% in the task of differentiating between subjects diagnosed with Alzheimer’s and normal control subjects.
ContributorsGeorge, John Varghese (Author) / Wang, Yalin (Thesis advisor) / Hansford, Dianne (Committee member) / Gupta, Vikash (Committee member) / Arizona State University (Publisher)
Created2023
Description
In the last few decades, extensive research efforts have been focused on scaling down silicon-based complementary metal-oxide semiconductor (CMOS) technology to enable the continuation of Moore’s law. State-of-art CMOS includes fully depleted silicon-on-insulator (FDSOI) field-effect-transistors (FETs) with ultra-thin silicon channels (6 nm), as well as other three-dimensional (3D) device architectures like Fin-FETs, nanosheet FETs, etc. Significant research efforts have characterized these technologies towards various applications, and at different conditions including a wide range of temperatures from room temperature (300 K) down to cryogenic temperatures. Theoretical efforts have studied ultrascaled devices using Landauer theory to further understand their transport properties and predict their performance in the quasi-ballistic regime.Further scaling of CMOS devices requires the introduction of new semiconducting channel materials, as now established by the research community. Here, two-dimensional (2D) semiconductors have emerged as a promising candidate to replace silicon for next-generation ultrascaled CMOS devices. These emerging 2D semiconductors also have applications beyond CMOS, for example in novel memory, neuromorphic, and spintronic devices. Graphene is a promising candidate for spintronic devices due to its outstanding spin transport properties as evidenced by numerous studies in non-local lateral spin valve (LSV) geometries. The essential components of graphene-based LSV, such as graphene FETs, metal-graphene contacts, and tunneling barriers, were individually investigated as part of this doctoral dissertation.
In this work, several contributions were made to these CMOS and beyond CMOS technologies. This includes comprehensive characterization and modeling of FDSOI nanoscale FETs from room temperature down to cryogenic temperatures. Using Landauer theory for nanoscale transistors, FDSOI devices were analyzed and modeled under quasi-ballistic operation. This was extended towards a virtual-source modeling approach that accounts for temperature-dependent quasi-ballistic transport and back-gate biasing effects. Additionally, graphene devices with ultrathin high-k gate dielectrics were investigated towards FETs, non-volatile memory, and spintronic devices. New contributions were made relating to charge trapping effects and their impact on graphene device electrostatics (Dirac voltage shifts) and transport properties (impact on mobility and conductivity). This work also studied contact resistance and tunneling effects using transfer length method (TLM) graphene FET structures and magnetic tunneling junction (MTJ) towards graphene-based LSV.
ContributorsZhou, Guantong (Author) / Sanchez Esqueda, Ivan (Thesis advisor) / Vasileska, Dragica (Committee member) / Tongay, Sefaattin (Committee member) / Thornton, Trevor (Committee member) / Arizona State University (Publisher)
Created2023
Description
Dissolved inorganic carbon (DIC) and dissolved organic carbon (DOC) are crucial nutrients for autotrophic and heterotrophic microbial life, respectively, in hydrothermal systems. Biogeochemical processes that control amounts of DIC and DOC in Yellowstone hot springs can be investigated by measuring carbon abundances and respective isotopic values. A decade and a half of field work in 10 regions within Yellowstone National Park and subsequent geochemical lab analyses reveal that sulfate-dominant acidic regions have high DOC (Up to 57 ppm C) and lower DIC (up to 50 ppm C) compared to neutral-chloride regions with low DOC (< 2 ppm C) and higher DIC (up to 100 ppm C). Abundances and isotopic data suggest that sedimentary rock erosion by acidic hydrothermal fluids, fresh snow-derived meteoric water, and exogenous carbon input allowed by local topography may affect DOC levels. Evaluating the isotopic compositions of DIC and DOC in hydrothermal fluids gives insight on the geology and microbial life in the subsurface between different regions. DIC δ13C values range from -4‰ to +5‰ at pH 5-9 and from -10‰ to +3‰ at pH 2-5 with several springs lower than -10‰. DOC δ13C values parkwide range from -10‰ to -30‰. Within this range, neutral-chloride regions in the Lower Geyser Basin have lighter isotopes than sulfate-dominant acidic regions. In hot springs with elevated levels of DOC, the range only varies between -20‰ and -26‰ which may be caused by local exogenous organic matter runoff. Combining other geochemical measurements, such as differences in chloride and sulfate concentrations, demonstrates that some regions contain mixtures of multiple fluids moving through the complex hydrological system in the subsurface. The mixing of these fluids may account for increased levels of DOC in meteoric sulfate-dominant acidic regions. Ultimately, the foundational values of dissolved carbon and their isotopic composition is provided in a parkwide study, so results can be combined with future studies that apply different sequencing analyses to understand specific biogeochemical cycling and microbial communities that occur in individual hot springs.
ContributorsBarnes, Tanner (Author) / Shock, Everett (Thesis advisor) / Meyer-Dombard, D'Arcy (Committee member) / Hartnett, Hilairy (Committee member) / Arizona State University (Publisher)
Created2023
Description
The research of alternative materials and new device architectures to exceed the limits of conventional silicon-based devices has been sparked by the persistent pursuit of semiconductor technology scaling. The development of tungsten diselenide (WSe2) and molybdenum disulfide (MoS2), well-known member of the transition metal dichalcogenide (TMD) family, has made great strides towards ultrascaled two-dimensional (2D) field-effect-transistors (FETs). The scaling issues facing silicon-based complementary metal-oxide-semiconductor (CMOS) technologies can be solved by 2D FETs, which show extraordinary potential.This dissertation provides a comprehensive experimental analysis relating to improvements in p-type metal-oxide-semiconductor (PMOS) FETs with few-layer WSe2 and high-κ metal gate (HKMG) stacks. Compared to this works improved methods, standard metallization (more damaging to underlying channel) results in significant Fermi-level pinning, although Schottky barrier heights remain small (< 100 meV) when using high work function metals. Temperature-dependent analysis reveals a dominant contribution to contact resistance from the damaged channel access region. Thus, through less damaging metallization methods combined with strongly scaled HKMG stacks significant improvements were achieved in contact resistance and PMOS FET overall performance. A clean contact/channel interface was achieved through high-vacuum evaporation and temperature-controlled stepped deposition. Theoretical analysis using a Landauer transport adapted to WSe2 Schottky barrier FETs (SB-FETs) elucidates the prospects of nanoscale 2D PMOS FETs indicating high-performance towards the ultimate CMOS scaling limit.
Next, this dissertation discusses how device electrical characteristics are affected by scaling of equivalent oxide thickness (EOT) and by adopting double-gate FET architectures, as well as how this might support CMOS scaling. An improved gate control over the channel is made possible by scaling EOT, improving on-off current ratios, carrier mobility, and subthreshold swing. This study also elucidates the impact of EOT scaling on FET gate hysteresis attributed to charge-trapping effects in high-κ-dielectrics prepared by atomic layer deposition (ALD). These developments in 2D FETs offer a compelling alternative to conventional silicon-based devices and a path for continued transistor scaling. This research contributes to ongoing efforts in 2D materials for future semiconductor technologies. Finally, this work introduces devices based on emerging Janus TMDs and bismuth oxyselenide (Bi2O2Se) layered semiconductors.
ContributorsPatoary, Md Naim Hossain (Author) / Sanchez Esqueda, Ivan (Thesis advisor) / Tongay, Sefaattin (Committee member) / Vasileska, Dragica (Committee member) / Goodnick, Stephen (Committee member) / Arizona State University (Publisher)
Created2023
Description
As air quality standards become more stringent to combat poor air quality, there is a greater need for more effective pollutant control measures and increased air monitoring network coverage. Polluted air, in the form of aerosols and gases, can impact respiratory and cardiovascular health, visibility, the climate, and material weathering. This work demonstrates how traditional networks can be used to study generational events, how these networks can be supplemented with low-cost sensors, and the effectiveness of several control measures. First, an existing network was used to study the effect of COVID-19 travel restrictions on air quality in Maricopa County, Arizona, which would not have been possible without the historical record that a traditional network provides. Although this study determined that decreases in CO and NO2 were not unique to the travel restrictions, it was limited to only three locations due to network sparseness. The second part of this work expanded the traditional NO2 monitoring network using low-cost sensors, that were first collocated with a reference monitor to evaluate their performance and establish a robust calibration. The sensors were then deployed to the field to varying results; their calibration was further improved by cycling the sensors between deployment and reference locations throughout the summer. This calibrated NO2 data, along with volatile organic compound data, were combined to enhance the understanding of ozone formation in Maricopa County, especially during wildfire season. In addition to being in non-attainment for ozone standards, Maricopa County fails to meet particulate matter under 10 μm (PM10) standards. A large portion of PM10 emissions is attributed to fugitive dust that is either windblown or kicked up by vehicles. The third part of this work demonstrated that Enzyme Induced Carbonate Precipitation (EICP) treatments aggregate soil particles and prevent fugitive dust emissions. The final part of the work examined tire wear PM10 emissions, as vehicles are another significant contributor to PM10. Observations showed a decrease in tire wear PM10 during winter with little change when varying the highway surface type.
ContributorsMiech, Jason Andrew (Author) / Herckes, Pierre (Thesis advisor) / Fraser, Matthew P (Committee member) / Shock, Everett (Committee member) / Arizona State University (Publisher)
Created2023
Description
Doping is the cornerstone of Semiconductor technology, enabling the functionalities of modern digital electronics. Two-dimensional (2D) transition metal dichalcogenides (TMDCs) have tunable direct bandgaps, strong many-body interactions, and promising applications in future quantum information sciences, optoelectronic, spintronic, and valleytronic devices. However, their wafer-scale synthesis and precisely controllable doping are challenging. Moreover, there is no fixed framework to identify the doping concentration, which impedes their process integration for future commercialization. This work utilizes the Neutron Transmutation Doping technique to control the doping uniformly and precisely in TMDCs. Rhenium and Tin dopants are introduced in Tungsten- and Indium-based Chalcogenides, respectively. Fine-tuning over 0.001% doping level is achieved. Precise analytical techniques such as Gamma spectroscopy and Secondary Ion Mass Spectrometry are used to quantify ultra-low doping levels ranging from 0.005-0.01% with minimal error. Dopants in 2D TMDCs often exhibit a broad stokes-shifted emission, with high linewidths, due to extrinsic effects such as substrate disorder and surface adsorbates. A well-defined bound exciton emission induced by Rhenium dopants in monolayer WSe2 and WS2 at liquid nitrogen temperatures is reported along with specific annealing regimes to minimize the defects induced in the Neutron Transmutation process. This work demonstrates a framework for Neutron Doping in 2D materials, which can be a scalable process for controlling doping and doping-induced effects in 2D materials.
ContributorsLakhavade, Sushant Sambhaji (Author) / Tongay, Sefaattin (Thesis advisor) / Alford, Terry (Committee member) / Yang, Sui (Committee member) / Arizona State University (Publisher)
Created2023
Description
The prevalence and unique properties of airborne nanoparticles have raised concerns regarding their potential adverse health effects. Despite their significance, the understanding of nanoparticle generation, transport, and exposure remains incomplete. This study first aimed to assess nanoparticle exposure in indoor workplace environments, in the semiconductor manufacturing industry. On-site observations during tool preventive maintenance revealed a significant release of particles smaller than 30 nm, which subsequent instrumental analysis confirmed as predominantly composed of transition metals. Although the measured mass concentration levels did not exceed current federal limits, it prompted concerns regarding how well filter-based air sampling methods would capture the particles for exposure assessment and how well common personal protective equipment would protect from exposure. To address these concerns, this study evaluated the capture efficiency of filters and masks. When challenged by aerosolized engineered nanomaterials, common filters used in industrial hygiene sampling exhibited capture efficiencies of over 60%. Filtering Facepiece Respirators, such as the N95 mask, exhibited a capture efficiency of over 98%. In contrast, simple surgical masks showed a capture efficiency of approximately 70%. The experiments showed that face velocity and ambient humidity influence capture performance and mostly identified the critical role of mask and particle surface charge in capturing nanoparticles. Masks with higher surface potential exhibited higher capture efficiency towards nanoparticles. Eliminating their surface charge resulted in a significantly diminished capture efficiency, up to 43%. Finally, this study characterized outdoor nanoparticle concentrations in the Phoenix metropolitan area, revealing typical concentrations on the order of 10^4 #/cm3 consistent with other urban environments. During the North American monsoon season, in dust storms, with elevated number concentrations of large particles, particularly in the size range of 1-10 μm, the number concentration of nanoparticles in the size range of 30-100 nm was substantially lower by approximately 55%. These findings provide valuable insights for future assessments of nanoparticle exposure risks and filter capture mechanisms associated with airborne nanoparticles.
ContributorsZhang, Zhaobo (Author) / Herckes, Pierre (Thesis advisor) / Westerhoff, Paul (Committee member) / Shock, Everett (Committee member) / Fraser, Matthew (Committee member) / Arizona State University (Publisher)
Created2023
Description
In the past decade, 2D materials especially transition metal dichalcogenides (TMDc), have been studied extensively for their remarkable optical and electrical properties arising from their reduced dimensionality. A new class of materials developed based on 2D TMDc that has gained great interest in recent years is Janus crystals. In contrast to TMDc, Janus monolayer consists of two different chalcogen atomic layers between which the transition metal layer is sandwiched. This structural asymmetry causes strain buildup or a vertically oriented electric field to form within the monolayer. The presence of strain brings questions about the materials' synthesis approach, particularly when strain begins to accumulate and whether it causes defects within monolayers.The initial research demonstrated that Janus materials could be synthesized at high temperatures inside a chemical vapor deposition (CVD) furnace. Recently, a new method (selective epitaxy atomic replacement - SEAR) for plasma-based room temperature Janus crystal synthesis was proposed. In this method etching and replacing top layer chalcogen atoms of the TMDc monolayer happens with reactive hydrogen and sulfur radicals. Based on Raman and photoluminescence studies, the SEAR method produces high-quality Janus materials. Another method used to create Janus materials was the pulsed laser deposition (PLD) technique, which utilizes the interaction of sulfur/selenium plume with monolayer to replace the top chalcogen atomic layer in a single step.
The goal of this analysis is to characterize microscale defects that appear in 2D Janus materials after they are synthesized using SEAR and PLD techniques. Various microscopic techniques were used for this purpose, as well as to understand the
mechanism of defect formation. The main mechanism of defect formation was proposed to be strain release phenomena. Furthermore, different chalcogen atom positions within the monolayer result in different types of defects, such as the appearance of cracks or wrinkles across monolayers. In addition to investigating sample topography, Kelvin probe force microscopy (KPFM) was used to examine its electrical properties to see if the formation of defects impacts work function. Further study directions have been suggested for identifying and characterizing defects and their formation mechanism in the Janus crystals to understand their fundamental properties.
ContributorsSinha, Shantanu (Author) / Tongay, Sefaattin (Thesis advisor) / Alford, Terry (Committee member) / Yang, Sui (Committee member) / Arizona State University (Publisher)
Created2022