Physical Sciences and Mathematics Commons^™

Static And Dynamic State Estimation Applications In Power Systems Protection And Control Engineering, Ibukunoluwa Olayemi Korede

Doctoral Dissertations

The developed methodologies are proposed to serve as support for control centers and fault analysis engineers. These approaches provide a dependable and effective means of pinpointing and resolving faults, which ultimately enhances power grid reliability. The algorithm uses the Least Absolute Value (LAV) method to estimate the augmented states of the PCB, enabling supervisory monitoring of the system. In addition, the application of statistical analysis based on projection statistics of the system Jacobian as a virtual sensor to detect faults on transmission lines. This approach is particularly valuable for detecting anomalies in transmission line data, such as bad data or …

The Synthesis And Optimization Of Sulfide And Halide Solid Electrolytes For All Solid-State Batteries, Teerth Brahmbhatt

Doctoral Dissertations

Countries and organizations around the world have established ambitious targets to transition away from fossil fuel-based energy sources and devices. The transition is focused on cleaning up power generation by converting coal, natural gas, and oil-based power generation to renewables and nuclear energy. Decarbonizing other sectors of energy use, transportation for example, will require broader electrification. To drive this move away from fossil fuel powered transportation will require portable energy storage devices. Conventional lithium-ion batteries are a popular candidate to lead this shift. However, these batteries often rely on flammable liquid electrolytes and carbon anodes that suffer from low energy …

Thermal Transport Across 2d/3d Van Der Waals Interfaces, Cameron Foss

Doctoral Dissertations

Designing improved field-effect-transistors (FETs) that are mass-producible and meet the fabrication standards set by legacy silicon CMOS manufacturing is required for pushing the microelectronics industry into further enhanced technological generations. Historically, the downscaling of feature sizes in FETs has enabled improved performance, reduced power consumption, and increased packing density in microelectronics for several decades. However, many are claiming Moore's law no longer applies as the era of silicon CMOS scaling potentially nears its end with designs approaching fundamental atomic-scale limits -- that is, the few- to sub-nanometer range. Ultrathin two-dimensional (2D) materials present a new paradigm of materials science and …

Enabling Daily Tracking Of Individual’S Cognitive State With Eyewear, Soha Rostaminia

Doctoral Dissertations

Research studies show that sleep deprivation causes severe fatigue, impairs attention and decision making, and affects our emotional interpretation of events, which makes it a big threat to public safety, and mental and physical well-being. Hence, it would be most desired if we could continuously measure one’s drowsiness and fatigue level, their emotion while making decisions, and assess their sleep quality in order to provide personalized feedback or actionable behavioral suggestions to modulate sleep pattern and alertness levels with the aim of enhancing performance, well-being, and quality of life. While there have been decades of studies on wearable devices, we …

Frontiers In The Self-Assembly Of Charged Macromolecules, Khatcher O. Margossian

Doctoral Dissertations

The self-assembly of charged macromolecules forms the basis of all life on earth. From the synthesis and replication of nucleic acids, to the association of DNA to chromatin, to the targeting of RNA to various cellular compartments, to the astonishingly consistent folding of proteins, all life depends on the physics of the organization and dynamics of charged polymers. In this dissertation, I address several of the newest challenges in the assembly of these types of materials. First, I describe the exciting new physics of the complexation between polyzwitterions and polyelectrolytes. These materials open new questions and possibilities within the context …

Hyperspectral Unmixing: A Theoretical Aspect And Applications To Crism Data Processing, Yuki Itoh

Doctoral Dissertations

Hyperspectral imaging has been deployed in earth and planetary remote sensing, and has contributed the development of new methods for monitoring the earth environment and new discoveries in planetary science. It has given scientists and engineers a new way to observe the surface of earth and planetary bodies by measuring the spectroscopic spectrum at a pixel scale. Hyperspectal images require complex processing before practical use. One of the important goals of hyperspectral imaging is to obtain the images of reflectance spectrum. A raw image obtained by hyperspectral remote sensing usually undergoes conversion to a physical quantity representing the intensity of …

Models And Machine Learning Techniques For Improving The Planning And Operation Of Electricity Systems In Developing Regions, Santiago Correa Cardona

Doctoral Dissertations

The enormous innovation in computational intelligence has disrupted the traditional ways we solve the main problems of our society and allowed us to make more data-informed decisions. Energy systems and the ways we deliver electricity are not exceptions to this trend: cheap and pervasive sensing systems and new communication technologies have enabled the collection of large amounts of data that are being used to monitor and predict in real-time the behavior of this infrastructure. Bringing intelligence to the power grid creates many opportunities to integrate new renewable energy sources more efficiently, facilitate grid planning and expansion, improve reliability, optimize electricity …

Improving The Programmability Of Networked Energy Systems, Noman Bashir

Doctoral Dissertations

Global warming and climate change have underscored the need for designing sustainable energy systems. Sustainable energy systems, e.g., smart grids, green data centers, differ from the traditional systems in significant ways and present unique challenges to system designers and operators. First, intermittent renewable energy resources power these systems, which break the notion of infinite, reliable, and controllable power supply. Second, these systems come in varying sizes, spanning over large geographical regions. The control of these dispersed and diverse systems raises scalability challenges. Third, the performance modeling and fault detection in sustainable energy systems is still an active research area. Finally, …

X-Band Phased-Array Weather-Radar Polarimetry Testbed, William Heberling Iv

Doctoral Dissertations

Phased-array weather radar have potential to replace reflector dish radar in major weather radar networks such as NEXRAD, providing faster update times and greater scan flexibility. However, the use of electronic scanning introduces polarization errors on weather radar measurables, requiring polarimetric bias calibration. The sources of polarimetric bias have been described theoretically, but experimental verification is still limited. Additionally, no standard method of calibration for polarimetric bias exists for phased-arrays. Therefore, the University of Massachusetts Amherst (UMass) presents a fully operational X-Band phased-array weather radar polarimetric testbed. The testbed evaluates the calibration of a planar dual-polarization X-band phased-array radar through …

Tailoring Interfaces And Composition For Stable And Efficient Perovskite Solar Cells, Hamza Javaid

Doctoral Dissertations

Metal halide perovskite solar cells (PSCs) have revolutionized the field of thin film photovoltaics. Within a decade, the power conversion efficiencies (PCEs) have increased at a phenomenal rate, rising from 3.8% to more than 25% in single-junction devices, moving them ahead of the current silicon-based technology. The high efficiencies of perovskite solar cells (PSCs) and their other unique properties arise from a combination of organic and inorganic components and electronic-ionic conduction, making them excellent candidates for a plethora of applications. However, PSCs face a significant—and ironic—roadblock to commercialization: these light-harvesting materials degrade under sunlight—the very condition they would need …

Characterization Techniques And Cation Exchange Membrane For Non-Aqueous Redox Flow Battery, Kun Lou

Doctoral Dissertations

The motivation of this work comes from one of the major problems of emerging non-aqueous flow battery (NAFB) that a separator or membrane which facilitates conductivity and blocks redox species crossover does not exist. Although many aspects of principles can be mirrored from mature fuel cell and aqueous flow battery, it is found that some well-defined membrane properties in aqueous systems such as swelling, transport and interactions are different in non-aqueous solvents to some extent. However, the approach of this work does follow the way perfluorosulfonate ion exchange membrane (PFSA) facilitated development of fuel cell and aqueous flow battery in …

Thermoelectric Transport In Disordered Organic And Inorganic Semiconductors, Meenakshi Upadhyaya

Doctoral Dissertations

The need for alternative energy sources has led to extensive research on optimizing the conversion efficiency of thermoelectric (TE) materials. TE efficiency is governed by figure-of-merit (ZT) and it has been an enormously challenging task to increase ZT > 1 despite decades of research due to the interdependence of material properties. Most doped inorganic semiconductors have a high electrical conductivity and moderate Seebeck coefficient, but ZT is still limited by their high lattice thermal conductivity. One approach to address this problem is to decrease thermal conductivity by means of alloying and nanostructuring, another is to consider materials with an inherently low …

Machine Learning With Topological Data Analysis, Ephraim Robert Love

Doctoral Dissertations

Topological Data Analysis (TDA) is a relatively new focus in the fields of statistics and machine learning. Methods of exploiting the geometry of data, such as clustering, have proven theoretically and empirically invaluable. TDA provides a general framework within which to study topological invariants (shapes) of data, which are more robust to noise and can recover information on higher dimensional features than immediately apparent in the data. A common tool for conducting TDA is persistence homology, which measures the significance of these invariants. Persistence homology has prominent realizations in methods of data visualization, statistics and machine learning. Extending ML with …

Fiber Optic Sensors For Industry And Military Applications, Yiyang Zhuang

Doctoral Dissertations

"Fiber optic sensors (FOSs) have been widely used for measuring various physical and chemical measurands owing to their unique advantages over traditional sensors such as small size, high resolution, distributed sensing capabilities, and immunity to electromagnetic interference. This dissertation focuses on the development of robust FOSs with ultrahigh sensitivity and their applications in industry and military areas.

Firstly, novel fiber-optic extrinsic Fabry-Perot interferometer (EFPI) inclinometers for one- and two-dimensional tilt measurements with 20 nrad resolution were demonstrated. Compared to in-line fiber optic inclinometers, an extrinsic sensing motif was used in our prototype inclinometer. The variations in tilt angle of the …

Approaches To Studying Bacterial Biofilms In The Bioeconomy With Nanofabrication Techniques And Engineered Platforms., Michelle Caroline Halsted

Doctoral Dissertations

Studies that estimate more than 90% of bacteria subsist in a biofilm state to survive environmental stressors. These biofilms persist on man-made and natural surfaces, and examples of the rich biofilm diversity extends from the roots of bioenergy crops to electroactive biofilms in bioelectrochemical reactors. Efforts to optimize microbial systems in the bioeconomy will benefit from an improved fundamental understanding of bacterial biofilms. An understanding of these microbial systems shows promise to increase crop yields with precision agriculture (e.g. biosynthetic fertilizer, microbial pesticides, and soil remediation) and increase commodity production yields in bioreactors. Yet conventional laboratory methods investigate these micron-scale …

Leveraging Conventional Internet Routing Protocol Behavior To Defeat Ddos And Adverse Networking Conditions, Jared M. Smith

Doctoral Dissertations

The Internet is a cornerstone of modern society. Yet increasingly devastating attacks against the Internet threaten to undermine the Internet's success at connecting the unconnected. Of all the adversarial campaigns waged against the Internet and the organizations that rely on it, distributed denial of service, or DDoS, tops the list of the most volatile attacks. In recent years, DDoS attacks have been responsible for large swaths of the Internet blacking out, while other attacks have completely overwhelmed key Internet services and websites. Core to the Internet's functionality is the way in which traffic on the Internet gets from one destination …

Molecular Design Of Organic Semiconductors For Interfacial And Emissive Material Applications, Marcus David Cole

Doctoral Dissertations

This dissertation describes the synthesis and characterization of functional optoelectronically active materials. Synthetic techniques were used to prepare polymers containing perylene diimide (PDI) or tetraphenylethylene (TPE) moieties in the polymer backbone. PDI-based structures were prepared with embedded cationic or zwitterionic moieties intended to tailor organic/inorganic interfaces in thin film photovoltaic devices. The aggregation-induced emission (AIE)-active TPE polymers were synthesized to study how AIE properties evolve in π-conjugated polymers. The syntheses discussed here focused on modulation of molecular architecture to give rise to materials with tailored optoelectronic properties. Chapter 1 provides a brief overview of the field of organic electronics and …

System Efficient Esd Design Concept For Soft Failures, Giorgi Maghlakelidze

Doctoral Dissertations

"This research covers the topic of developing a systematic methodology of studying electrostatic discharge (ESD)-induced soft failures. ESD-induced soft failures (SF) are non-destructive disruptions of the functionality of an electronic system. The soft failure robustness of a USB3 Gen 1 interface is investigated, modeled, and improved. The injection is performed directly using transmission line pulser (TLP) with varying: pulse width, amplitude, polarity. Characterization provides data for failure thresholds and a SPICE circuit model that describes the transient voltage and current at the victim. Using the injected current, the likelihood of a SF is predicted. ESD protection by transient voltage suppressor …

A Parallel Direct Method For Finite Element Electromagnetic Computations Based On Domain Decomposition, Javad Moshfegh

Doctoral Dissertations

High performance parallel computing and direct (factorization-based) solution methods have been the two main trends in electromagnetic computations in recent years. When time-harmonic (frequency-domain) Maxwell's equation are directly discretized with the Finite Element Method (FEM) or other Partial Differential Equation (PDE) methods, the resulting linear system of equations is sparse and indefinite, thus harder to efficiently factorize serially or in parallel than alternative methods e.g. integral equation solutions, that result in dense linear systems. State-of-the-art sparse matrix direct solvers such as MUMPS and PARDISO don't scale favorably, have low parallel efficiency and high memory footprint. This work introduces a new …

Software-Defined Infrastructure For Iot-Based Energy Systems, Stephen Lee

Doctoral Dissertations

Internet of Things (IoT) devices are becoming an essential part of our everyday lives. These physical devices are connected to the internet and can measure or control the environment around us. Further, IoT devices are increasingly being used to monitor buildings, farms, health, and transportation. As these connected devices become more pervasive, these devices will generate vast amounts of data that can be used to gain insights and build intelligence into the system. At the same time, large-scale deployment of these devices will raise new challenges in efficiently managing and controlling them. In this thesis, I argue that the IoT …

Function And Dissipation In Finite State Automata - From Computing To Intelligence And Back, Natesh Ganesh

Doctoral Dissertations

Society has benefited from the technological revolution and the tremendous growth in computing powered by Moore's law. However, we are fast approaching the ultimate physical limits in terms of both device sizes and the associated energy dissipation. It is important to characterize these limits in a physically grounded and implementation-agnostic manner, in order to capture the fundamental energy dissipation costs associated with performing computing operations with classical information in nano-scale quantum systems. It is also necessary to identify and understand the effect of quantum in-distinguishability, noise, and device variability on these dissipation limits. Identifying these parameters is crucial to designing …

A Multicarrier Technique For Monte Carlo Simulation Of Electrothermal Transport In Nanoelectronics, Tyler J. Spence

Doctoral Dissertations

The field of microelectronics plays an important role in many areas of engineering and science, being ubiquitous in aerospace, industrial manufacturing, biotechnology, and many other fields. Today, many micro- and nanoscale electronic devices are integrated into one package. e capacity to simulate new devices accurately is critical to the engineering design process, as device engineers use simulations to predict performance characteristics and identify potential issues before fabrication. A problem of particular interest is the simulation of devices which exhibit exotic behaviors due to non-equilibrium thermodynamics and thermal effects such as self-heating. Frequently, it is desirable to predict the level of …

Ferrite Characterization Techniques & Particle Simulations For Semiconductor Devices, Nicholas Erickson

Doctoral Dissertations

"This dissertation is divided into three papers, covering two major topics. The first topic, techniques for ferrite characterization, is discussed over the course of two papers. The second topic, particle simulations for semiconductor devices, is discussed in the last paper. In the first paper, the method for extracting permeability from ferrite materials is discussed for the Keysight 16454A permeability extraction fixture, where the ferrite material to be characterized is assumed to be homogeneous. Then the method is updated to account for layered materials. The updated method is verified through full-wave simulations. In the second paper, a planar printed circuit board …

Deep Neural Network Learning-Based Classifier Design For Big-Data Analytics, Krishnan Raghavan

Doctoral Dissertations

"In this digital age, big-data sets are commonly found in the field of healthcare, manufacturing and others where sustainable analysis is necessary to create useful information. Big-data sets are often characterized by high-dimensionality and massive sample size. High dimensionality refers to the presence of unwanted dimensions in the data where challenges such as noise, spurious correlation and incidental endogeneity are observed. Massive sample size, on the other hand, introduces the problem of heterogeneity because complex and unstructured data types must analyzed. To mitigate the impact of these challenges while considering the application of classification, a two step analysis approach is …

Effective Magnetic And Electric Response Of Composite Materials, Mona Hassan Alsaleh

Doctoral Dissertations

Metamaterials (MMs) are nanocomposite materials consisting of metal-dielectric resonators much smaller in size than the wavelength of the incident light. Common examples of metamaterials are based on split ring resonators (SRRs), parallel wires or strips and fishnet structures. These types of materials are designed and fabricated in order to provide unique optical responses to the incident electromagnetic radiation that are not available in naturally existing materials. The MMs can exhibit unusual properties such as strong magnetism at terahertz (THz) and optical frequencies. Additionally, negative index materials (NIMs) can provide negative index of refraction which can be used in many applications …

Electromagnetic Wave-Matter Interactions In Complex Opto-Electronic Materials And Devices, Raj Kumar Vinnakota

Doctoral Dissertations

This dissertation explores the fundamentals of light-matter interaction towards applications in the field of Opto-electronic and plasmonic devices. In its core, this dissertation attempts and succeeds in the the modeling of light-matter interactions, which is of high importance for better understanding the rich physics underlying the dynamics of electromagnetic field interactions with charged particles. Here, we have developed a self-consistent multi-physics model of electromagnetism, semiconductor physics and thermal effects which can be readily applied to the field of plasmotronics and Selective Laser Melting (SLM). Plasmotronics; a sub-field of photonics has experienced a renaissance in recent years by providing a large …

Cmos Compatible Memristor Networks For Brain-Inspired Computing, Can Li

Doctoral Dissertations

In the past decades, the computing capability has shown an exponential growth trend, which is observed as Moore’s law. However, this growth speed is slowing down in recent years mostly because the down-scaled size of transistors is approaching their physical limit. On the other hand, recent advances in software, especially in big data analysis and artificial intelligence, call for a break-through in computing hardware. The memristor, or the resistive switching device, is believed to be a potential building block of the future generation of integrated circuits. The underlying mechanism of this device is different from that of complementary metal-oxide-semiconductor (CMOS) …

Leveraging Eye Structure And Motion To Build A Low-Power Wearable Gaze Tracking System, Addison Mayberry

Doctoral Dissertations

Clinical studies have shown that features of a person's eyes can function as an effective proxy for cognitive state and neurological function. Technological advances in recent decades have allowed us to deepen this understanding and discover that the actions of the eyes are in fact very tightly coupled to the operation of the brain. Researchers have used camera-based eye monitoring technology to exploit this connection and analyze mental state across across many different metrics of interest. These range from simple things like attention and scene processing, to impairments such as a fatigue or substance use, and even significant mental disorders …

Parallel Algorithms For Time Dependent Density Functional Theory In Real-Space And Real-Time, James Kestyn

Doctoral Dissertations

Density functional theory (DFT) and time dependent density functional theory (TDDFT) have had great success solving for ground state and excited states properties of molecules, solids and nanostructures. However, these problems are particularly hard to scale. Both the size of the discrete system and the number of needed eigenstates increase with the number of electrons. A complete parallel framework for DFT and TDDFT calculations applied to molecules and nanostructures is presented in this dissertation. This includes the development of custom numerical algorithms for eigenvalue problems and linear systems. New functionality in the FEAST eigenvalue solver presents an additional level of …

Hybrid Black-Box Solar Analytics And Their Privacy Implications, Dong Chen

Doctoral Dissertations

The aggregate solar capacity in the U.S. is rising rapidly due to continuing decreases in the cost of solar modules. For example, the installed cost per Watt (W) for residential photovoltaics (PVs) decreased by 6X from 2009 to 2018 (from $8/W to $1.2/W), resulting in the installed aggregate solar capacity increasing 128X from 2009 to 2018 (from 435 megawatts to 55.9 gigawatts). This increasing solar capacity is imposing operational challenges on utilities in balancing electricity's real-time supply and demand, as solar generation is more stochastic and less predictable than aggregate demand. To address this problem, both academia and utilities have …