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Full-Text Articles in Physical Sciences and Mathematics

Photoluminescence Of Beryllium-Related Defects In Gallium Nitride, Mykhailo Vorobiov, Mykhailo Vorobiov Jan 2024

Photoluminescence Of Beryllium-Related Defects In Gallium Nitride, Mykhailo Vorobiov, Mykhailo Vorobiov

Theses and Dissertations

This study explores the potential of beryllium (Be) as an alternative dopant to magnesium (Mg) for achieving higher hole concentrations in gallium nitride (GaN). Despite Mg prominence as an acceptor in optoelectronic and high-power devices, its deep acceptor level at 0.22 eV above the valence band limits its effectiveness. By examining Be, this research aims to pave the way to overcoming these limitations and extend the findings to aluminum nitride and aluminum gallium nitride (AlGaN) alloy. Key contributions of this work include. i)Identification of three Be-related luminescence bands in GaN through photoluminescence spectroscopy, improving the understanding needed for further material …


Developing Machine Learning And Time-Series Analysis Methods With Applications In Diverse Fields, Muhammed Aljifri Jan 2024

Developing Machine Learning And Time-Series Analysis Methods With Applications In Diverse Fields, Muhammed Aljifri

Theses and Dissertations

This dissertation introduces methodologies that combine machine learning models with time-series analysis to tackle data analysis challenges in varied fields. The first study enhances the traditional cumulative sum control charts with machine learning models to leverage their predictive power for better detection of process shifts, applying this advanced control chart to monitor hospital readmission rates. The second project develops multi-layer models for predicting chemical concentrations from ultraviolet-visible spectroscopy data, specifically addressing the challenge of analyzing chemicals with a wide range of concentrations. The third study presents a new method for detecting multiple changepoints in autocorrelated ordinal time series, using the …


Adaptable And Trustworthy Machine Learning For Human Activity Recognition From Bioelectric Signals, Morgan S. Stuart Jan 2024

Adaptable And Trustworthy Machine Learning For Human Activity Recognition From Bioelectric Signals, Morgan S. Stuart

Theses and Dissertations

Enabling machines to learn measures of human activity from bioelectric signals has many applications in human-machine interaction and healthcare. However, labeled activity recognition datasets are costly to collect and highly varied, which challenges machine learning techniques that rely on large datasets. Furthermore, activity recognition in practice needs to account for user trust - models are motivated to enable interpretability, usability, and information privacy. The objective of this dissertation is to improve adaptability and trustworthiness of machine learning models for human activity recognition from bioelectric signals. We improve adaptability by developing pretraining techniques that initialize models for later specialization to unseen …


Material Extrusion-Based Additive Manufacturing: G-Code And Firmware Attacks And Defense Frameworks, Haris Rais Jan 2023

Material Extrusion-Based Additive Manufacturing: G-Code And Firmware Attacks And Defense Frameworks, Haris Rais

Theses and Dissertations

Additive Manufacturing (AM) refers to a group of manufacturing processes that create physical objects by sequentially depositing thin layers. AM enables highly customized production with minimal material wastage, rapid and inexpensive prototyping, and the production of complex assemblies as single parts in smaller production facilities. These features make AM an essential component of Industry 4.0 or Smart Manufacturing. It is now used to print functional components for aircraft, rocket engines, automobiles, medical implants, and more. However, the increased popularity of AM also raises concerns about cybersecurity. Researchers have demonstrated strength degradation attacks on printed objects by injecting cavities in the …


Synthesis And Application Of Redox-Active Covalent Organic Frameworks In Rechargeable Batteries, Mohammad K. Shehab Jan 2023

Synthesis And Application Of Redox-Active Covalent Organic Frameworks In Rechargeable Batteries, Mohammad K. Shehab

Theses and Dissertations

Synthesis and Application of Redox-Active Covalent Organic Frameworks in Rechargeable Batteries

Mohammad K. Shehab

Department of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, United States

Abstract

In recent years, lithium-ion batteries (LIBs) have been considered the dominant energy storage devices for portable electronics and electric vehicles due to their high energy density, low self-discharge rate, and long cycle life. In LIBs, the traditional positive electrodes employed are mainly derived from metal-containing inorganic compounds composed of cobalt, iron, nickel, or manganese (LiCoO2, LiMn2O4, and LiFePO4) coupled with graphite as the negative electrode. Despite …


Mechanisms Of Emulsion Destabilization: An Investigation Of Surfactant, Stabilizer, And Detergent Based Formulations Using Diffusing Wave Spectroscopy, Jordan N. Nowaczyk Jan 2023

Mechanisms Of Emulsion Destabilization: An Investigation Of Surfactant, Stabilizer, And Detergent Based Formulations Using Diffusing Wave Spectroscopy, Jordan N. Nowaczyk

Theses and Dissertations

Conventional approaches for studying emulsions, such as microscopy and macroscopic phase tracking, present challenges when it comes to establishing detailed mechanistic descriptions of the impact of emulsifier and stabilizer additives. Additionally, while a combination of sizing methods and macroscopic phase tracking can provide insights into droplet size changes and concentration, the use of multiple measurements can be cumbersome and error-prone. It is the focus of this work, to present a new method for studying water in oil (W/O) emulsions that involves using diffusing wave spectroscopy (DWS) to examine the impact of three different surface stabilizing additives at varying concentrations. By …


Learning Robot Motion From Creative Human Demonstration, Charles C. Dietzel Jan 2022

Learning Robot Motion From Creative Human Demonstration, Charles C. Dietzel

Theses and Dissertations

This thesis presents a learning from demonstration framework that enables a robot to learn and perform creative motions from human demonstrations in real-time. In order to satisfy all of the functional requirements for the framework, the developed technique is comprised of two modular components, which integrate together to provide the desired functionality. The first component, called Dancing from Demonstration (DfD), is a kinesthetic learning from demonstration technique. This technique is capable of playing back newly learned motions in real-time, as well as combining multiple learned motions together in a configurable way, either to reduce trajectory error or to generate entirely …


Universal Design In Bci: Deep Learning Approaches For Adaptive Speech Brain-Computer Interfaces, Srdjan Lesaja Jan 2022

Universal Design In Bci: Deep Learning Approaches For Adaptive Speech Brain-Computer Interfaces, Srdjan Lesaja

Theses and Dissertations

In the last two decades, there have been many breakthrough advancements in non-invasive and invasive brain-computer interface (BCI) systems. However, the majority of BCI model designs still follow a paradigm whereby neural signals are preprocessed and task-related features extracted using static, and generally customized, data-independent designs. Such BCI designs commonly optimize narrow task performance over generalizability, adaptability, and robustness, which is not well suited to meeting individual user needs. If one day BCIs are to be capable of decoding our higher-order cognitive commands and conceptual maps, their designs will need to be adaptive architectures that will evolve and grow in …


Smart City Management Using Machine Learning Techniques, Mostafa Zaman Jan 2022

Smart City Management Using Machine Learning Techniques, Mostafa Zaman

Theses and Dissertations

In response to the growing urban population, "smart cities" are designed to improve people's quality of life by implementing cutting-edge technologies. The concept of a "smart city" refers to an effort to enhance a city's residents' economic and environmental well-being via implementing a centralized management system. With the use of sensors and actuators, smart cities can collect massive amounts of data, which can improve people's quality of life and design cities' services. Although smart cities contain vast amounts of data, only a percentage is used due to the noise and variety of the data sources. Information and communication technology (ICT) …


Molten Salt Technologies For Advanced Nuclear Fuel Cycles And Molten Salt Reactors, Dimitris Killinger Jan 2022

Molten Salt Technologies For Advanced Nuclear Fuel Cycles And Molten Salt Reactors, Dimitris Killinger

Theses and Dissertations

This dissertation provides five topics—an assessment of different monitoring and analytical techniques often cited in the literature for molten salt systems and designs for nuclear engineering applications. First, we explored commonly used materials for quasi-reference electrodes in molten chloride salts. Second, the limitations of the electrochemical analysis known as cyclic voltammetry due to the concentration of uranium(III) present were being investigated. Third, we provided an experimental assessment on the development of a spectroelectrochemical cell for interrogating various spectroelectrochemical techniques, namely chronoabsorptometry and chronofluorometry, and their limitations due to the presence of uranium(III) ions. Fourth, a study on the corrosion resistance …


Detection Of 2,4,6-Trinitrotoluene Using A Colorimetric Gold Nanoparticle Air Cassette Filter, Andrea I. Ferrer Vega Jan 2021

Detection Of 2,4,6-Trinitrotoluene Using A Colorimetric Gold Nanoparticle Air Cassette Filter, Andrea I. Ferrer Vega

Theses and Dissertations

Trinitrotoluene (TNT) is an explosive commonly used during military and terrorist activities. Current methods to identify this compound require sampling, transport and analysis at a forensic lab using analytical instrumentation. However, on-site detection is needed to assist efforts to prevent detonation. Gold nanoparticles have been used as sensors throughout the years due to their versatility and surface enhanced Raman scattering properties in the presence of an analyte and low limits of detection. By taking advantage of the Meisenheimer complex that TNT forms in the presence of amines, it is possible to determine its presence at picogram levels. Subsequently, adhering amine …


Equations Of State For Warm Dense Carbon From Quantum Espresso, Derek J. Schauss Jan 2021

Equations Of State For Warm Dense Carbon From Quantum Espresso, Derek J. Schauss

Theses and Dissertations

Warm dense plasma is the matter that exists, roughly, in the range of 10,000 to 10,000,000 Kelvin and has solid-like densities, typically between 0.1 and 10 grams per centimeter. Warm dense fluids like hydrogen, helium, and carbon are believed to make up the interiors of many planets, white dwarfs, and other stars in our universe. The existence of warm dense matter (WDM) on Earth, however, is very rare, as it can only be created with high-energy sources like a nuclear explosion. In such an event, theoretical and computational models that accurately predict the response of certain materials are thus very …


Applied Machine Learning In Extrusion-Based Bioprinting, Shuyu Tian Jan 2021

Applied Machine Learning In Extrusion-Based Bioprinting, Shuyu Tian

Theses and Dissertations

Optimization of extrusion-based bioprinting (EBB) parameters have been systematically conducted through experimentation. However, the process is time and resource-intensive and not easily translatable across different laboratories. A machine learning (ML) approach to EBB parameter optimization can accelerate this process for laboratories across the field through training using data collected from published literature. In this work, regression-based and classification-based ML models were investigated for their abilities to predict printing outcomes of cell viability and filament diameter for cell-containing alginate and gelatin composite hydrogels. Regression-based models were investigated for their ability to predict suitable extrusion pressure given desired cell viability when keeping …


Nebulizer-Based Systems To Improve Pharmaceutical Aerosol Delivery To The Lungs, Benjamin M. Spence Jan 2021

Nebulizer-Based Systems To Improve Pharmaceutical Aerosol Delivery To The Lungs, Benjamin M. Spence

Theses and Dissertations

Combining vibrating mesh nebulizers with additional new technologies leads to substantial improvements in pharmaceutical aerosol delivery to the lungs across therapeutic administration methods. In this dissertation, streamlined components, aerosol administration synchronization, and/or Excipient Enhanced Growth (EEG) technologies were utilized to develop and test several novel devices and aerosol delivery systems. The first focus of this work was to improve the poor delivery efficiency, e.g., 3.6% of nominal dose (Dugernier et al. 2017), of aerosolized medication administration to adult human subjects concurrent with high flow nasal cannula (HFNC) therapy, a form of continuous-flow non-invasive ventilation (NIV). The developed Low-Volume Mixer-Heater (LVMH) …


Information Architecture For A Chemical Modeling Knowledge Graph, Adam R. Luxon Jan 2021

Information Architecture For A Chemical Modeling Knowledge Graph, Adam R. Luxon

Theses and Dissertations

Machine learning models for chemical property predictions are high dimension design challenges spanning multiple disciplines. Free and open-source software libraries have streamlined the model implementation process, but the design complexity remains. In order better navigate and understand the machine learning design space, model information needs to be organized and contextualized. In this work, instances of chemical property models and their associated parameters were stored in a Neo4j property graph database. Machine learning model instances were created with permutations of dataset, learning algorithm, molecular featurization, data scaling, data splitting, hyperparameters, and hyperparameter optimization techniques. The resulting graph contains over 83,000 nodes …


Electric Field Control Of Fixed Magnetic Skyrmions For Energy Efficient Nanomagnetic Memory, Dhritiman Bhattacharya Jan 2020

Electric Field Control Of Fixed Magnetic Skyrmions For Energy Efficient Nanomagnetic Memory, Dhritiman Bhattacharya

Theses and Dissertations

To meet the ever-growing demand of faster and smaller computers, increasing number of transistors are needed in the same chip area. Unfortunately, Silicon based transistors have almost reached their miniaturization limits mainly due to excessive heat generation. Nanomagnetic devices are one of the most promising alternatives of CMOS. In nanomagnetic devices, electron spin, instead of charge, is the information carrier. Hence, these devices are non-volatile: information can be stored in these devices without needing any external power which could enable computing architectures beyond traditional von-Neumann computing. Additionally, these devices are also expected to be more energy efficient than CMOS devices …


Leveraging Peer-To-Peer Energy Sharing For Resource Optimization In Mobile Social Networks, Aashish Dhungana Jan 2020

Leveraging Peer-To-Peer Energy Sharing For Resource Optimization In Mobile Social Networks, Aashish Dhungana

Theses and Dissertations

Mobile Opportunistic Networks (MSNs) enable the interaction of mobile users in the vicinity through various short-range wireless communication technologies (e.g., Bluetooth, WiFi) and let them discover and exchange information directly or in ad hoc manner. Despite their promise to enable many exciting applications, limited battery capacity of mobile devices has become the biggest impediment to these appli- cations. The recent breakthroughs in the areas of wireless power transfer (WPT) and rechargeable lithium batteries promise the use of peer-to-peer (P2P) energy sharing (i.e., the transfer of energy from the battery of one member of the mobile network to the battery of …


Adhesion At Solid/Liquid Interfaces, Neda Ojaghlou Jan 2019

Adhesion At Solid/Liquid Interfaces, Neda Ojaghlou

Theses and Dissertations

The adhesion at solid/liquid interface plays a fundamental role in diverse fields and helps explain the structure and physical properties of interfaces, at the atomic scale, for example in catalysis, crystal growth, lubrication, electrochemistry, colloidal system, and in many biological reactions. Unraveling the atomic structure at the solid/liquid interface is, therefore, one of the major challenges facing the surface science today to understand the physical processes in the phenomena such as surface coating, self-cleaning, and oil recovery applications. In this thesis, a variety of theory/computational methods in statistical physics and statistical mechanics are used to improve understanding of water adhesion …


Straintronic Nanomagnetic Devices For Non-Boolean Computing, Md Ahsanul Abeed Jan 2019

Straintronic Nanomagnetic Devices For Non-Boolean Computing, Md Ahsanul Abeed

Theses and Dissertations

Nanomagnetic devices have been projected as an alternative to transistor-based switching devices due to their non-volatility and potentially superior energy-efficiency. The energy efficiency is enhanced by the use of straintronics which involves the application of a voltage to a piezoelectric layer to generate a strain which is ultimately transferred to an elastically coupled magnetostrictive nanomaget, causing magnetization rotation. The low energy dissipation and non-volatility characteristics make straintronic nanomagnets very attractive for both Boolean and non-Boolean computing applications. There was relatively little research on straintronic switching in devices built with real nanomagnets that invariably have defects and imperfections, or their adaptation …


Metallic Systems At The Nano And Micro Scale: Bimetallic Nanoparticles As Catalysts And Mcraly Bond Coats In Thermal Barrier Coatings, Kenneth Kane Jan 2019

Metallic Systems At The Nano And Micro Scale: Bimetallic Nanoparticles As Catalysts And Mcraly Bond Coats In Thermal Barrier Coatings, Kenneth Kane

Theses and Dissertations

The dissertation is split into two parts. The first part will be focused on changes in material properties found at the nanoscale, as miscibility and electronic structure can change significantly with size. The formation of classically-immiscible bimetallic nanoparticles (BNPs) becomes favorable at the nanoscale and novel catalytic properties can emerge from the bimetallic alloying. The formation of alloyed and non-alloyed BNPs is achieved through pulse laser ablation (PLA) and a significant increase in catalytic activity is observed for both. Recently discovered, the increased activity in the non-alloyed BNPs, deemed multicomponent photocatalysis, is examined and the proposed mechanism discussed. The second …


Experimental Evaluation Of Uranyl Transport Into Mesoporous Silica Gel Using Fluorescence, Brandon M. Dodd Jan 2018

Experimental Evaluation Of Uranyl Transport Into Mesoporous Silica Gel Using Fluorescence, Brandon M. Dodd

Theses and Dissertations

This research investigated parameters that can affect the use of nanoporous silica gel as a media for accumulating a detectable amount of uranium. The unique fluorescence of the Uranyl (UO22+) ion was used to evaluate the transport kinetics and accumulation within silica gel in a static fluid and under pressure driven flow. The addition of fluid flow decreased the time constant from on the order of an hour to approximately 2s with a very low fluid velocity of 0.36cm/s. The 0.36cm/s fluid velocity was found to be the critical velocity above which there was no gain in …


Neutronics Studies On The Nist Reactor Using The Ga Leu Fuel, Kyle A. Britton Jan 2018

Neutronics Studies On The Nist Reactor Using The Ga Leu Fuel, Kyle A. Britton

Theses and Dissertations

The National Bureau of Standards Reactor (NBSR) located on the National Institute of Standards and Technology (NIST) Gaithersburg campus, is currently underway of fuel conversion from high enriched uranium (HEU) fuel to low enriched uranium (LEU) fuel. One particular challenging part of the conversion of the NBSR is the high average flux level (2.5×1014 n/cm2-s) required to maintain experimental testing capabilities of the reactor, without significant changes to the external structures of the reactor. Recently the General Atomics (GA) Training Research Isotopes General Atomics (TRIGA) fuel has shown some promising features as a LEU candidate for the …


Material Thermal Property Estimation Of Fibrous Insulation: Heat Transfer Modeling And The Continuous Genetic Algorithm, Elora Frye Jan 2018

Material Thermal Property Estimation Of Fibrous Insulation: Heat Transfer Modeling And The Continuous Genetic Algorithm, Elora Frye

Theses and Dissertations

Material thermal properties are highly sought after to better understand the performance of a material under particular conditions. As new materials are created, their physical properties will determine their performance for various applications. These properties have been estimated using many techniques including experimental testing, numerical modeling, and a combination of both. Existing methods can be time consuming, thus, a time-efficient and precise method to estimate these thermal properties was desired. A one-dimensional finite difference numerical model was developed to replicate the heat transfer through an experimental apparatus. A combination of this numerical model and the Continuous Genetic Algorithm optimization technique …


Consuming Digital Debris In The Plasticene, Stephen R. Parks Jan 2018

Consuming Digital Debris In The Plasticene, Stephen R. Parks

Theses and Dissertations

Claims of customization and control by socio-technical industries are altering the role of consumer and producer. These narratives are often misleading attempts to engage consumers with new forms of technology. By addressing capitalist intent, material, and the reproduction limits of 3-D printed objects’, I observe the aspirational promise of becoming a producer of my own belongings through new networks of production. I am interested in gaining a better understanding of the data consumed that perpetuates hyper-consumptive tendencies for new technological apparatuses. My role as a designer focuses on the resolution of not only the surface of the object through 3-D …


Photoluminescence From Gan Co-Doped With C And Si, Mykhailo Vorobiov Jan 2018

Photoluminescence From Gan Co-Doped With C And Si, Mykhailo Vorobiov

Theses and Dissertations

This thesis devoted to the experimental studies of yellow and blue luminescence (YL and BL relatively) bands in Gallium Nitride samples doped with C and Si. The band BLC was at first observed in the steady-state photoluminescence spectrum under high excitation intensities and discerned from BL1 and BL2 bands appearing in the same region of the spectrum. Using the time-resolved photoluminescence spectrum, we were able to determine the shape of the BLC and its position at 2.87 eV. Internal quantum efficiency of the YL band was estimated to be 90\%. The hole capture coefficient of the BLC …


Developing A Cyberterrorism Policy: Incorporating Individual Values, Osama Bassam J. Rabie Jan 2018

Developing A Cyberterrorism Policy: Incorporating Individual Values, Osama Bassam J. Rabie

Theses and Dissertations

Preventing cyberterrorism is becoming a necessity for individuals, organizations, and governments. However, current policies focus on technical and managerial aspects without asking for experts and non-experts values and preferences for preventing cyberterrorism. This study employs value focused thinking and public value forum to bare strategic measures and alternatives for complex policy decisions for preventing cyberterrorism. The strategic measures and alternatives are per socio-technical process.


Synthesis, Characterization, And Enhanced Magnetic Properties Of Iron Carbide Nanomaterials, Brent M. Williams Jan 2017

Synthesis, Characterization, And Enhanced Magnetic Properties Of Iron Carbide Nanomaterials, Brent M. Williams

Theses and Dissertations

Permanent magnets are classified as hard magnetic materials with the main purpose of generating flux for applications such as electric motors, turbines, and hard drives. High coercivity, magnetic remanence, and saturation values with high stability are some of the requirements for permanent magnets. Rare-earth magnets including neodymium and samarium based magnets are known to have superior magnetic properties due to their high magnetocrystalline anisotropy. However, due to the price of rare-earth materials development of alternate permanent magnets composed of inexpensive materials is an ongoing process. Previously cobalt carbide (CoxC) have shown promise as a potential rare-earth free magnet …


Tuning Optimization Software Parameters For Mixed Integer Programming Problems, Toni P. Sorrell Jan 2017

Tuning Optimization Software Parameters For Mixed Integer Programming Problems, Toni P. Sorrell

Theses and Dissertations

The tuning of optimization software is of key interest to researchers solving mixed integer programming (MIP) problems. The efficiency of the optimization software can be greatly impacted by the solver’s parameter settings and the structure of the MIP. A designed experiment approach is used to fit a statistical model that would suggest settings of the parameters that provided the largest reduction in the primal integral metric. Tuning exemplars of six and 59 factors (parameters) of optimization software, experimentation takes place on three classes of MIPs: survivable fixed telecommunication network design, a formulation of the support vector machine with the ramp …


Preparation And Application Of Catalysts For The Stereospecific Reduction And Photooxygenation Of Olefins In Continuous Operations: A Novel Method For The Production Of Artemisinin, Daniel C. Fisher Jan 2017

Preparation And Application Of Catalysts For The Stereospecific Reduction And Photooxygenation Of Olefins In Continuous Operations: A Novel Method For The Production Of Artemisinin, Daniel C. Fisher

Theses and Dissertations

Over the last two centuries, the discovery and application of catalysts has had a substantial impact on how and what chemicals are produced.Given their broad significance, our group has focused on developing new catalyst systems that are recoverable and reusable, in an attempt to reduce concomitant costs.

Our efforts have centered on constructing a recyclable chiral heterogeneous catalyst capable of effecting asymmetric hydrogenations of olefins with high stereoselectivity. A class of phosphinoimidazoline ligands, developed by researchers at Boehringer-Ingelheim, known as BIPI ligands, have proven efficacious in the asymmetric reduction of alkenes. However, these chiral ligands are homogeneous and coordinated to …


Design & Analysis Of A Computer Experiment For An Aerospace Conformance Simulation Study, Ryan W. Gryder Jan 2016

Design & Analysis Of A Computer Experiment For An Aerospace Conformance Simulation Study, Ryan W. Gryder

Theses and Dissertations

Within NASA's Air Traffic Management Technology Demonstration # 1 (ATD-1), Interval Management (IM) is a flight deck tool that enables pilots to achieve or maintain a precise in-trail spacing behind a target aircraft. Previous research has shown that violations of aircraft spacing requirements can occur between an IM aircraft and its surrounding non-IM aircraft when it is following a target on a separate route. This research focused on the experimental design and analysis of a deterministic computer simulation which models our airspace configuration of interest. Using an original space-filling design and Gaussian process modeling, we found that aircraft delay assignments …