Physical Sciences and Mathematics Commons^™

Effect Of Glycol Based Coolant Pollution On Pem Fuel Cells Stack And Recovery Measures, Cong-Yi Zhu, Xiao-Hui Li, Quan-Quan Gan

Journal of Electrochemistry

As the heat conduction medium of fuel cell cooling system, coolant is very important for the thermal management of fuel cell stack. In practical application, coolant leakage into the stack often occurs. Due to the randomness of fault location of components, the location of coolant leakage is uncertain, which may occur on the cathode side or anode side of some or all single cells. The main effects of coolant pollution on fuel cell stack are as follows: the output of open circuit voltage decreases sharply, the consistency of single cells voltage decreases and so on, which seriously affects the normal …

Formation And Morphological Evolution Of Nanoporous Anodized Iron Oxide Films, Jin-Wei Cao, Nan Gao, Zhao-Qing Gao, Chen Wang, Sheng-Yan Shang, Yun-Peng Wang, Hai-Tao Ma

Journal of Electrochemistry

The preparation of iron oxide films with nanoporous structure by anodization has attracted much attention for its potential applications. However, the formation mechanism of porous structure during anodization is still unclear. In this paper, the composition of anodic current during the formation of nanoporous anodized iron oxide film was analyzed in combination with the current density-potential response (I-V curve) and the derivation of Faraday’s law. The results showed that the anodic current consisted of an ionic current (leading to the migration of ions to form oxide) and an electronic current (leading to the oxygen evolution), and the …

Cyclic Voltammetric Simulations On Batteries With Porous Electrodes, Xue-Fan Cai, Sheng Sun

Journal of Electrochemistry

Lithium-ion batteries (LIBs) are among the most widely used energy storage devices. Whole-cell modeling and simulations of LIBs can optimize the design of batteries with lower costs and higher speeds. The Pseudo-Two-Dimensional (P2D) electrochemical model is among the most famous whole-cell models and widely applied in LIB simulations. P2D model consists of a series of kinetic equations to model Li⁺/Li diffusion in working/counter electrodes and electrolytes, which are filled in the porous electrodes and separator, and reactions at the interface of electrolyte and active particles. The traditional applications of P2D model, however, are limited to the cases where …

Functional Sulfate Electrolytes Enable The Enhanced Cycling Stability Of Nati2(Po4)3/C Anode Material For Aqueous Sodium-Ion Batteries, Shu-Jin Li, Zhi-Kang Cao, Wen-Kai Wang, Xiao-Han Zhang, Xing-De Xiang

Journal of Electrochemistry

Aqueous sodium-ion batteries show promising application in fields of large-scale storage of intermittent renewable energies owing to the earth-abundant sodium resources and incombustible aqueous electrolytes. Primary factors determining whether they can be commercially utilized are low cost and long lifetime. Among current electrode materials, NASICON-type NaTi₂(PO₄)₃ arouses wide interests as an anode material for aqueous sodium-ion batteries as it offers a high specific capacity, fast Na-transport ability and reasonable working potential, however, suffering from insufficient cycling performance caused by severe dissolution of active materials in traditional aqueous electrolytes. In this work, a functional sulfate electrolyte …

Influence Of Heat Treatment Time On Cathode Material Cr8O21 For Lithium Battery, Jiu-Kang Teng, Qing-Jie Wang, Liang Zhang, Hong-Mei Zhang, Xiao-Tao Chen, Peng Zhang, Jin-Bao Zhao

Journal of Electrochemistry

Chromium oxide (Cr₈O₂₁) cathode material for lithium batteries was synthesized by thermal decomposition of chromium trioxide (CrO₃) at high temperature. The electrochemical properties of chromium oxide depended on the time and temperature during the heat treatment. Pure phase chromium oxide was prepared, and the effects of heat treatment time on the structures and electrochemical properties of Cr₈O₂₁ were systematically studied. The first discharge mechanism of chromium oxide in lithium batteries was explored, and the results were similar to that in lithium-sulfur batteries. The crystal phases and electrochemical properties of the prepared …

Algorithm For Calculating The Parameters Of A Multi-Position Electromagnetic Linear Mechatronic Module, Nazarov Khayriddin Nuritdinovich, Matyokubov Nurbek Rustamovich, Temurbek Omonboyevich Rakhimov

Chemical Technology, Control and Management

Currently, in the world in the field of science, engineering and technology, including in mechatronics and robotics, the creation of multi-coordinate mechatronic systems that perform power and control functions is becoming of paramount importance, this is due to a number of important positive qualities of the systems, such as simplicity and compactness of the design, the possibility of obtaining significant efforts, high accuracy and stability of the establishment of fixed positions, ease of control and high reliability. This article presents the calculation of the parameters of multi-position mechatronic modules based on linear execution elements. In the construction of this model, …

Temperature-Immune Self-Referencing Fabry–Pérot Cavity Sensors, Hengky Chandrahalim, Jonathan W. Smith

AFIT Patents

A passive microscopic Fabry-Pérot Interferometer (FPI) sensor an optical fiber a three-dimensional microscopic optical structure formed on a cleaved tip of an optical fighter that reflects a light signal back through the optical fiber. The reflected light is altered by refractive index changes in the three-dimensional structure that is subject to at least one of: (i) thermal radiation; and (ii) volatile organic compounds.

Comparative Analysis Of Rgb-Based Eye-Tracking For Large-Scale Human-Machine Applications, Brett Thaman, Trung Cao

Posters-at-the-Capitol

Gaze tracking has become an established technology that enables using an individual’s gaze as an input signal to support a variety of applications in the context of Human-Computer Interaction. Gaze tracking primarily relies on sensing devices such as infrared (IR) cameras. Nevertheless, in the recent years, several attempts have been realized at detecting gaze by acquiring and processing images acquired from standard RGB cameras. Nowadays, there are only a few publicly available open-source libraries and they have not been tested extensively. In this paper, we present the result of a comparative analysis that studied a commercial eye-tracking device using IR …

Intracavity Phase Interferometry Based Fiber Sensors, Luke Jameson Horstman

Optical Science and Engineering ETDs

Intracavity Phase Interferometry (IPI) is a detection technique that exploits the inherent sensitivity of a laser's frequency to the parameters of its cavity. Intracavity interferometry is orders of magnitude more sensitive than its extracavity alternatives. This dissertation improves on previous free-space proof-of-concept designs. By implementing the technique in fiber optics, using optical parametric oscillation, and investigating non-Hermitian quantum mechanics and dispersion tailoring enhancement techniques, IPI has become more applicable and sensitive. Ring and linear IPI configurations were realized in this work, both operating as bidirectional fiber optical parametric oscillators. The benefit of using externally pumped synchronous optical parametric oscillation is …

Machine Learning For Stock Prediction Based On Fundamental Analysis, Yuxuan Huang, Luiz Fernando Capretz, Danny Ho

Electrical and Computer Engineering Publications

Application of machine learning for stock prediction is attracting a lot of attention in recent years. A large amount of research has been conducted in this area and multiple existing results have shown that machine learning methods could be successfully used toward stock predicting using stocks’ historical data. Most of these existing approaches have focused on short term prediction using stocks’ historical price and technical indicators. In this paper, we prepared 22 years’ worth of stock quarterly financial data and investigated three machine learning algorithms: Feed-forward Neural Network (FNN), Random Forest (RF) and Adaptive Neural Fuzzy Inference System (ANFIS) for …

Goes-16 Level 2 Land Surface Temperature Product-Filling For Cloud Masked Data, Guadalupe Ortega

Open Access Theses & Dissertations

The GOES-16 satellite ground segment team develops different levels of environmental products and makes them readily available to the public. The level 2 Land Surface Temperature (LST) product aims to provide a remote measurement of the Earth’s surface temperature every hour. LST is of fundamental importance to many aspects of the geosciences, for example, to study the Urban Heat Islands (UHI) effect. The product however, does not provide values for pixels where the satellite imager’s view is obstructed by clouds, as determined by a cloud mask intermediate product. The objective of this thesis is to estimate LST in the cloud …

Advanced Analytics In Smart Manufacturing: Anomaly Detection Using Machine Learning Algorithms And Parallel Machine Scheduling Using A Genetic Algorithm, Meiling He

Theses and Dissertations

Industry 4.0 offers great opportunities to utilize advanced data processing tools by generating Big Data from a more connected and efficient data collection system. Making good use of data processing technologies, such as machine learning and optimization algorithms, will significantly contribute to better quality control, automation, and job scheduling in Smart Manufacturing. This research aims to develop a new machine learning algorithm for solving highly imbalanced data processing problems, implement both supervised and unsupervised machine learning auto-selection frameworks for detecting anomalies in smart manufacturing, and develop a genetic algorithm for optimizing job schedules on unrelated parallel machines. This research also …

Integration Of Blockchain Technology Into Automobiles To Prevent And Study The Causes Of Accidents, John Kim

Electronic Theses, Projects, and Dissertations

Automobile collisions occur daily. We now live in an information-driven world, one where technology is quickly evolving. Blockchain technology can change the automotive industry, the safety of the motoring public and its surrounding environment by incorporating this vast array of information. It can place safety and efficiency at the forefront to pedestrians, public establishments, and provide public agencies with pertinent information securely and efficiently. Other industries where Blockchain technology has been effective in are as follows: supply chain management, logistics, and banking. This paper reviews some statistical information regarding automobile collisions, Blockchain technology, Smart Contracts, Smart Cities; assesses the feasibility …

A Deep Recurrent Neural Network With Iterative Optimization For Inverse Image Processing Applications, Masaki Ikuta

Theses and Dissertations

Many algorithms and methods have been proposed for inverse image processing applications, such as super-resolution, image de-noising, and image reconstruction, particularly with the recent surge of interest in machine learning and deep learning methods.

As for Computed Tomography (CT) image reconstruction, the most recently proposed methods are limited to image domain processing, where deep learning is used to learn the mapping between a true image data set and a noisy image data set in the image domain. While deep learning-based methods can produce higher quality images than conventional model-based algorithms, these methods have a limitation. Deep learning-based methods used in …

Spectral Dependence Of Deep Subwavelength Metallic Apertures In The Mid-Wave Infrared, Heath Gemar

Electronic Theses and Dissertations, 2020-2023

For two decades, extraordinary optical transmission (EOT) has amplified exploration into subwavelength systems. Researchers have previously suggested exploiting the spectrally selective electromagnetic field confinement of subwavelength cavities for multispectral detectors. Utilizing the finite-difference frequency domain (FDFD) method, we examine electromagnetic field confinement in both 2-dimensional and 3-dimensional scenarios from 2.5 to 6 microns (i.e., mid-wave infrared or MWIR). We explore the trade space of deep subwavelength cavities and its impact on resonant enhancement of the electromagnetic field. The studies provide fundamental understanding of the coupling mechanisms allowing for prediction of resonant spectral behavior based on cavity geometry and material properties. …

Risk-Based Machine Learning Approaches For Probabilistic Transient Stability, Umair Shahzad

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Power systems are getting more complex than ever and are consequently operating close to their limit of stability. Moreover, with the increasing demand of renewable wind generation, and the requirement to maintain a secure power system, the importance of transient stability cannot be overestimated. Considering its significance in power system security, it is important to propose a different approach for enhancing the transient stability, considering uncertainties. Current deterministic industry practices of transient stability assessment ignore the probabilistic nature of variables (fault type, fault location, fault clearing time, etc.). These approaches typically provide a conservative criterion and can result in expensive …

Fabricating Nanophotonic Devices Using Nanofabrication Techniques, Scott Cummings

Student Scholar Symposium Abstracts and Posters

Nanofabrication processes are widely used to make the integrated circuits and computer chips that are ubiquitous in today’s technology. These fabrication processes can also be applied to the creation of nanophotonic devices. The ways in which we apply these fabrication techniques in the field of photonics is often constrained by the technologies used for electronics manufacturing which presents an interesting engineering challenge. These limitations include availability and cost of certain fabrication equipment and techniques required to create state-of-the-art nanophotonic devices. Through work with the University of California Irvine nano-fabrication cleanroom, we designed and fabricated various integrated photonic components including grating …

Sigesn Light-Emitting Devices: From Optical To Electrical Injection, Yiyin Zhou

Graduate Theses and Dissertations

Si photonics is a fast-developing technology that impacts many applications such as data centers, 5G, Lidar, and biological/chemical sensing. One of the merits of Si photonics is to integrate electronic and photonic components on a single chip to form a complex functional system that features compact, low-cost, high-performance, and reliability. Among all building blocks, the monolithic integration of lasers on Si encountered substantial challenges. Si and Ge, conventional epitaxial material on Si, are incompetent for light emission due to the indirect bandgap. The current solution compromises the hybrid integration of III-V lasers, which requires growing on separate smaller size substrates …

Multifunctional Programmable Self-Assembled Nanoparticles In Nanomedicine, Yoshie Sakamaki

Graduate Theses and Dissertations

Developing methodologies to control the architecture of nanoparticles (NPs) at the atomic level prevents their inhomogeneity and leads to a variety of expected functions. Rationally designed nanoparticles can either be programmed or crystallized structures into pre-determined structures achieving tunable particle pore size and physiochemistry. In this dissertation, two broad classes of multifunctional nanoparticles are developed, metal-organic frameworks and DNA-NP aggregates.

Metal-organic frameworks are a novel class of highly porous crystalline materials built from organic linkers and metal cluster-based secondary building units. However, applications in bioremediation have not been developed very well especially in applications regarding drug delivery systems (DDS). The …

Investigation Of Optical And Structural Properties Of Gesn Heterostructures, Oluwatobi Gabriel Olorunsola

Graduate Theses and Dissertations

Silicon (Si)-based optoelectronics have gained traction due to its primed versatility at developing light-based technologies. Si, however, features indirect bandgap characteristics and suffers relegated optical properties compared to its III-V counterparts. III-Vs have also been hybridized to Si platforms but the resulting technologies are expensive and incompatible with standard complementary-metal-oxide-semiconductor processes. Germanium (Ge), on the other hand, have been engineered to behave like direct bandgap material through tensile strain interventions but are well short of attaining extensive wavelength coverage. To create a competitive material that evades these challenges, transitional amounts of Sn can be incorporated into Ge matrix to form …

Interplay Between The Lattice And Spin Degrees Of Freedom In Magnetoelectric And Magnetic Materials, Temuujin Bayaraa

Graduate Theses and Dissertations

This dissertation contains several investigations on the cross-coupling between structural and spin degrees of freedom in multiferroic and ferrimagnetic compounds by means of first-principles calculations and ab-initio-based Monte-Carlo simulations. We start with the reviews of magnetoelectricity, ferrimagnetism, strain engineering, followed by a brief introduction to first-principles computational methods, magnetic effective Hamiltonians, and other techniques that are utilized here. The results section of the dissertation can be divided into two parts. The first half focuses on magnetoelectric effects arising from different sources, while the second half is about the ferrimagnetic nature of materials. In the first part, we examine the epitaxial …

Evaluating Deep-Learning Models For Debris-Covered Glacier Mapping, Zhiyuan Xie, Vijayan K. Asari, Umesh K. Haritashya

Electrical and Computer Engineering Faculty Publications

In recent decades, mountain glaciers have experienced the impact of climate change in the form of accelerated glacier retreat and other glacier-related hazards such as mass wasting and glacier lake outburst floods. Since there are wide-ranging societal consequences of glacier retreat and hazards, monitoring these glaciers as accurately and repeatedly as possible is important. However, the accurate glacier boundary, especially the debriscovered glacier (DCG) boundary, which is one of the primary inputs in many glacier analyses, remains a challenge even after many years of research using conventional remote sensing methods or machine-learning methods. The GlacierNet, a deep-learning-based approach, utilized the …

Evaluation Of Robust Deep Learning Pipelines Targeting Low Swap Edge Deployment, David Carter Cornett

Masters Theses

The deep learning technique of convolutional neural networks (CNNs) has greatly advanced the state-of-the-art for computer vision tasks such as image classification and object detection. These solutions rely on large systems leveraging wattage-hungry GPUs to provide the computational power to achieve such performance. However, the size, weight and power (SWaP) requirements of these conventional GPU-based deep learning systems are not suitable when a solution requires deployment to so called "Edge" environments such as autonomous vehicles, unmanned aerial vehicles (UAVs) and smart security cameras.

The objective of this work is to benchmark FPGA-based alternatives to conventional GPU systems that have the …

Directional Spectral Solar Energy For Building Performance: From Simulation To Cyber-Physical Prototype, Joseph Del Rocco

Electronic Theses and Dissertations, 2020-2023

The original research and development in this dissertation contributes to the field of building performance by actively harnessing a wider spectrum of directional solar radiation for use in buildings. Solar radiation (energy) is often grouped by wavelength measurement into the spectra ultraviolet (UV), visible (light), and short and long-wave infrared (heat) on the electromagnetic spectrum. While some of this energy is directly absorbed or deflected by our atmosphere, most of it passes through, scatters about, and collides with our planet. Modern building performance simulations, tools, and control systems often oversimplify this energy into scalar values for light and heat, when …

Analysis Of Deep Learning Methods For Wired Ethernet Physical Layer Security Of Operational Technology, Lucas Torlay

All Theses

The cybersecurity of power systems is jeopardized by the threat of spoofing and man-in-the-middle style attacks due to a lack of physical layer device authentication techniques for operational technology (OT) communication networks. OT networks cannot support the active probing cybersecurity methods that are popular in information technology (IT) networks. Furthermore, both active and passive scanning techniques are susceptible to medium access control (MAC) address spoofing when operating at Layer 2 of the Open Systems Interconnection (OSI) model. This thesis aims to analyze the role of deep learning in passively authenticating Ethernet devices by their communication signals. This method operates at …

Feel And Touch: A Haptic Mobile Game To Assess Tactile Processing, Ivonne Monarca, Monica Tentori, Franceli L. Cibrian

Engineering Faculty Articles and Research

Haptic interfaces have great potential for assessing the tactile processing of children with Autism Spectrum Disorder (ASD), an area that has been under-explored due to the lack of tools to assess it. Until now, haptic interfaces for children have mostly been used as a teaching or therapeutic tool, so there are still open questions about how they could be used to assess tactile processing of children with ASD. This article presents the design process that led to the development of Feel and Touch, a mobile game augmented with vibrotactile stimuli to assess tactile processing. Our feasibility evaluation, with 5 children …

Let's Read: Designing A Smart Display Application To Support Codas When Learning Spoken Language, Katie Rodeghiero, Yingying Yuki Chen, Annika M. Hettmann, Franceli L. Cibrian

Engineering Faculty Articles and Research

Hearing children of Deaf adults (CODAs) face many challenges including having difficulty learning spoken languages, experiencing social judgment, and encountering greater responsibilities at home. In this paper, we present a proposal for a smart display application called Let's Read that aims to support CODAs when learning spoken language. We conducted a qualitative analysis using online community content in English to develop the first version of the prototype. Then, we conducted a heuristic evaluation to improve the proposed prototype. As future work, we plan to use this prototype to conduct participatory design sessions with Deaf adults and CODAs to evaluate the …

Single-Molecule Localization Microscopy Of 3d Orientation And Anisotropic Wobble Using A Polarized Vortex Point Spread Function, Tianben Ding, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Within condensed matter, single fluorophores are sensitive probes of their chemical environments, but it is difficult to use their limited photon budget to image precisely their positions, 3D orientations, and rotational diffusion simultaneously. We demonstrate the polarized vortex point spread function (PSF) for measuring these parameters, including characterizing the anisotropy of a molecule’s wobble, simultaneously from a single image. Even when imaging dim emitters (∼500 photons detected), the polarized vortex PSF can obtain 12 nm localization precision, 4°–8° orientation precision, and 26° wobble precision. We use the vortex PSF to measure the emission anisotropy of fluorescent beads, the wobble dynamics …

Novel Approach To Integrate Can Based Vehicle Sensors With Gps Using Adaptive Filters To Improve Localization Precision In Connected Vehicles From A Systems Engineering Perspective, Abhijit Vasili

USF Tampa Graduate Theses and Dissertations

Research and development in Connected Vehicles (CV) Technologies has increased exponentially, with the allocation of 75 MHz radio spectrum in the 5.9 GHz band by the Federal Communication Commission (FCC) dedicated to Intelligent Transportation Systems (ITS) in 1999 and 30 MHz in the 5.9 GHz by the European Telecommunication Standards Institution (ETSI). Many applications have been tested and deployed in pilot programs across many cities all over the world.

CV pilot programs have played a vital role in evaluating the effectiveness and impact of the technology and understanding the effects of the applications over the safety of road users. The …

Aptamer-Based Voltammetric Biosensing For The Detection Of Codeine And Fentanyl In Sweat And Saliva, Rosa Lashantez Cromartie

FIU Electronic Theses and Dissertations

Despite the many governmental and medicinal restrictions created to combat the opioid epidemic in the United States, opioid abuse and overdose rates continue to rise. The development of an aptamer-based voltammetric sensor and biosensor is described in this dissertation. The aim was to develop a low-cost, sensitive, and specific aptamer-based sensor for on-site, label-free determination of codeine and fentanyl in biological fluids. To do this, the surfaces of screen-printed carbon electrodes (SPCE) were modified with gold nanoparticles (AuNPs), followed by the addition of single-stranded DNA aptamers. These were covalently bound to the electrode surface. Operations of the sensors were collected …