Engineering Commons^™

Spin Wave Devices For Embedded Applications And Information Processing, Raisa Fabiha

Theses and Dissertations

Device miniaturization is a prerequisite for modern day electronics. Spintronics offers immense potential in energy efficient data storage, solid states devices, ultrafast computing and other electronic applications because of their low power consumption, non-volatile nature and unique activation mechanism. The conventional nano-antennas used for wireless communication, biomedical and wearable devices and IoT applications are limited by the traditional Harrington limit. As we attempt to miniaturize the antenna size beyond its emitted wavelength (also called “subwavelength” antenna), its gain and efficiency plummet. To overcome this challenge, the researchers have proposed magnetoelectric antennas. The ultra-thin film based magnetoelastic antennas suffer from eddy …

Simulation Of A Pick And Place System For Electronic Cards Using A Yumi Cobot, Derrick Sze, Rosula Sj Reyes, Patricia Angela R. Abu

Electronics, Computer, and Communications Engineering Faculty Publications

Collaborative Robots are one of the main drivers of Industry 4.0, which started as a vision focusing on industrial production. It addresses several challenges in the current manufacturing industry such as performing repetitive work and requiring highly skilled workers. The goal of the research is to be able to simulate a pick and place environment with electronic cards using a YuMi cobot and mobile platforms in Coppeliasim. The mobile robot is responsible for transporting the electronic cards to the target location through path planning implemented using the OMPL plug-in. After arriving at the target location, YuMi will then perform the …

Enhancing Microwave Disinfection: Impact Of Sodium Chloride On Microbial Inactivation, Saleh A. Alfawaz, Ibrahim Nasser I. Alquaydheb, Amirreza Ghadimi Avval, Sara Ghayouraneh, Samir M. El-Ghazaly, Jianhong Zhou

Electrical Engineering and Computer Science Faculty Publications and Presentations

This study explores the role of sodium chloride (NaCl) in enhancing the efficiency of microbial inactivation using microwave energy with two distinct methods: temperature-controlled treatment and predefined cycle. The primary objective is to maintain a stable temperature within the biological samples during treatment. Detailed descriptions of the treatment system’s design and the function of each element are provided. Simulations are conducted to illustrate the heating behavior of liquids with and without NaCl, revealing significant differences in temperature profiles between the two media. The experimental design and the objective behind each iteration are discussed. The experimental design includes three different power …

Cold Climate Heating Alternatives: A Feasibility Study For Heat Pumps In Far Northern Greenland, Sarah Torpie Hutchinson

Dartmouth College Master’s Theses

Building heating in the Arctic is extremely energy intensive. The cold climate of northern Greenland requires heating year-round. Qaanaaq, the northernmost village in Greenland, has 10,128 average annual heating degree days, in Celsius. Current heating relies on fossil fuels, often from an oil boiler or from diesel-powered district heating. Amidst the global transition of energy supply and consumption to reduce the use of fossil fuels, electrically based heating via heat pumps is becoming an increasingly attractive option to heat buildings more efficiently. Several heat pumps are now designed for cold climates specifically. While studies have investigated the potential and performance …

Generalized Conditional Feedback System With Model Uncertainty, Chengbo Dai, Zhiqiang Gao, Yangquan Chen, Donghai Li

Electrical and Computer Engineering Faculty Publications

Model uncertainty creates a largely open challenge for industrial process control, which causes a trade-off between robustness and performance optimality. In such a case, we propose a generalized conditional feedback (GCF) system to largely eliminate conflicts between robustness and performance optimality. This approach leverages a nominal model to design an optimal control in the virtual domain and defines an ancillary feedback controller to drive the physical process to track the trajectory of the virtual domain. The effectiveness of the proposed GCF scheme is demonstrated in a simulation for six typical industrial processes and three model-based control methods, and in a …

Explore Security And Machine Learning Applications In Next Generation Wireless Networks, Haolin Tang

Theses and Dissertations

Next-generation (NextG) or Beyond-Fifth-Generation (B5G) wireless networks have become a prominent focus in academic and industry circles. This is driven by the increasing demand for cutting-edge applications such as mobile health, self-driving cars, the metaverse, digital twins, virtual reality, and more. These diverse applications typically require high communication network performance, including spectrum utilization, data speed, and latency. New technologies are emerging to meet the communication requirements of various applications. Intelligent Reflecting Surface (IRS) and Artificial Intelligence (AI) are two representatives that have been demonstrated as promising and powerful technologies in NextG communications. While new technologies significantly enhance communication performance, they …

Energy Efficient Spintronic Devices For Non-Volatile Memory And Hardware Ai, Walid Al Misba

Theses and Dissertations

Nanomagnetic devices have emerged as a promising alternative to conventional complementary metal-oxide-semiconductor (CMOS) devices due to their low energy dissipation and inherent non-volatility. However, the widespread adoption of these devices requires high-density, high-speed, reliable, scalable, and energy-efficient technologies. This thesis investigates the use of nanomagnetic memory devices as both conventional Boolean memory and multistate memory for hardware AI applications.

Magnetic tunnel junctions (MTJs) are nanomagnetic memory devices that can be switched reliably and energy-efficiently using stress-mediated switching. However, realistic material inhomogeneity and scalability pose challenges for stress-mediated switching of MTJs scaled to lateral dimensions below 50 nm. We demonstrate that …

Hybrid Design Approaches For Reconfigurable Em Structures, Jonathan D. Lundquist

Theses and Dissertations

The modern world is replete with reasons for employing reconfigurable electromagnetic (EM) structures, but some of the most pressing needs require advancements in power consumption, speed, and footprint [1]. Next generation air defense (NGAD) fighters could benefit from new electronic warfare (EW) countermeasures [2], as well as adaptive stealth technology [3], while doctors could benefit from reconfigurable microwave ablation antennas that can modify radiation pattern and input impedance to match changes in tissue during ablation and account for variations in tumor shapes [4]. The future of antennas, filters, and lenses is reconfigurable as real-world matters of life and death may …

Machine Learning Assisted Optimization For Calculation And Automated Tuning Of Antennas, Lauren Linkous

Theses and Dissertations

The Antenna Calculation and Autotuning Tool (AntennaCAT) software suite represents a significant advancement in the field of antenna design by automating the entire design, CAD, simulation, and optimization process compatible with several EM simulation software suites. It is the first comprehensive implementation of machine learning in this context. In particular, this work includes the capability to create and export structured datasets from the aforementioned EM software for iterative improvement and includes an expandable selection of optimizers.

Effect Of Annealing On Photoluminescence From Defects In Gan, Oleksandr Andrieiev

Theses and Dissertations

Annealing is a critical process in modern GaN technology, essential for achieving p-type conductivity by activating the Mg_Ga acceptor, as first demonstrated by Shuji Nakamura in the early 1990s. Despite the omnipresence of hydrogen as an impurity in GaN crystals, the precise mechanisms governing hydrogen diffusion and acceptor passivation remain only partially understood. The presented research investigates the effects of annealing-induced activation and hydrogen passivation on C and Be acceptors in GaN grown by MOCVD, HVPE, and MBE methods. We explored these effects by using several annealing techniques, gas compositions, and thermal regimes. A transient behavior between the C …

Bridging The Gap In Epsilon-Near-Zero Nonlinear Materials, Adam R. Ball

Theses and Dissertations

Studying how light and matter interact has been of interest to humans for thousands of years. From the invention of the first mirror, burning ants with a magnifying glass, to optical fiber communication, light has been central to mankind. Researchers have sought to take this to the extreme with nonlinear optics where intense laser light interacts with materials. The study of this thesis is to understand a new generation of materials that has come to light. Epsilon-near-zero (ENZ) materials have shown promise for ultrafast light manipulation in tandem with modern day CMOS compatible electronics. Here, I seek to bridge the …

Multi-Magnetic Material Transcranial Magnetic Stimulation Coils Development And Electric Field Measurement & Modeling Using Machine Learning, Mohannad Tashli

Theses and Dissertations

Transcranial Magnetic Stimulation (TMS) is a safe, effective, and non-invasive therapy for treating several psychiatric and neurological disorders. TMS is Food and Drug Administration (FDA) approved treatment and is commonly applied to patients who do not respond to medications for the treatment of clinical depression, smoking cessation, obsessive-compulsive disorder and migraine. Recently, there has been an increase in the development of electromagnetic neuromodulation techniques targeted at enhancing the effectiveness of TMS devices for the treatment of mental diseases. In TMS stimulation, focality is an important factor which determines the specificity of the pulses induced in different brain tissues. The electromagnetic …

Functional Monitoring For Run-Time Assurance Of A Real-Time Cyber Physical System, Matthew W. Gelber

Theses and Dissertations

As cyber-physical systems (CPS) become more integrated into everyday life, the security of these systems must also be considered during their development due to their ever-increasing importance. With the growth of physical components in the system, more autonomous control requirements, and increased dependence on proper functionality, verifying system safety and correct operation becomes increasingly difficult. CPS have become more complex through the combination of additional hardware and the resulting interconnected software in many layers, each requiring unique security solutions. One example of such a safety-critical CPS embedded system is the Flight Control System (FCS) of an Unmanned Aerial System (UAS). …

External Runtime Execution Monitoring Of A Cyber Physical System Via Trace Interfaces, Peter Vaughan Truslow

Theses and Dissertations

In the past two decades, Unmanned Aerial Systems have progressed from expensive military hardware or one-off custom builds, to include off-the-shelf drones that can be purchased for a rather affordable price and flown by nearly anyone. As the technology and performance have improved, the door is opened to applications that require operation in environments where the consequences for failure are high, such as operating in the navigable airspace or in urban environments, or with human passengers. This requires a great deal of trust in the reliability and integrity of the control systems of the aircraft. A method of monitoring the …

Towards The Automation Of Post-Processing Of Additive Manufacturing Using Collaborative Robots, Logan Schorr

Theses and Dissertations

Despite the incredible potential that collaborative robots have, they are underutilized in several industries that could benefit greatly. These specialized fields, such as additive manufacturing, face challenges that can be solved with the use of robotics, including advanced computer vision, end-effector tooling, and process refinement. My research aims to utilize collaborative robots in an effort to solve the above stated problems, for the specific fields of additive manufacturing. Specifically within this field is the automation of post-processing; this is normally completely manual, as the tools for automation are not sufficiently developed to handle the flexibility required for additive manufacturing. This …

Magnetotransport Properties Of Dirac Semimetal Taco2te2 And Ferromagnetic Weyl Semimetal Co3sn2s2, Samuel Pate

Graduate Research Theses & Dissertations

This dissertation investigates the magnetotransport properties of topological semimetals, specifically focusing on the Dirac semimetal TaCo2Te2 and the Weyl semimetal Co3Sn2S2. In TaCo2Te2, I observed extremely large magnetoresistance that violates Kohler’s rule. Extended Kohler’s rule can be applied with a calculation of Hall factor at low temperatures. I also explored the applicability of the two-band and four-band models of carrier analysis and correlate the region where Kohler’s rule is obeyed to the four-band model. In Co3Sn2S2, I explored the angle-dependent anomalous Hall effect (AHE) near the Kagome plane, revealing a tunable AHE under applied fields and an abrupt disappearance of …

Estimation Of Methyl Orange Dye's Molar Absorptivity Using A Photoresistor-Based Photometer, Patricia M. Ludovice, Ramon M. Delos Santos

Physics Faculty Publications

The need to further develop solar cell technology, particularly on dye-sensitized solar cells (DSSCs), drives absorption studies of various chemical species. In this study, absorbance analysis of methyl orange (MO) dye was performed using the adapted and modified photoresistor-based photometer of Adams-McNichol et al. [1]. The research aims to improve the stability of the reference setup, while maintaining the accuracy of absorbance results it yields. The methodology includes photometer fabrication, MO dye sample preparation, and the evaluation of MO dye's molar absorptivity in an aqueous solution. Results show that the estimated molar absorptivity of MO using the voltage readings from …

Design And Fabrication Of Quantum Cascade Laser Tree Arrays, Luke Milbocker

Graduate Thesis and Dissertation 2023-2024

Quantum cascade lasers (QCLs) are semiconductor lasers that can be designed to emit over a very broad wavelength range from the mid-wave infrared (MWIR) to terahertz frequencies. Their compact size and ability to output several watts of MWIR or long-wave infrared (LWIR) radiation makes them ideal sources for directional infrared counter measures (DIRCM). This application is fueling demand for ever more powerful QCLs, but power gains from single QCLs have largely stagnated in recent years. Novel waveguide geometries such as tree-arrays seek to increase output power delivered in a single high-quality beam. InGaAs/AlInAs tree array QCLs based on ridge waveguides …

Structural Construction And Surface Modification Of Copper Current Collectors For Lithium Metal Batteries, Yaohua Liang

Electronic Theses and Dissertations

Graphene, a prevalent anode material in commercial lithium-ion batteries, has reached its theoretical capacity limit. The imperative is to develop high-capacity anode materials to meet the growing demand for energy density. Lithium metal, renowned for its exceptionally high theoretical specific capacity density (3680 mAh g-1) and low reduction potential (-3.04 V, relative to the standard hydrogen electrode), is commonly dubbed the "Holy Grail" for negative electrode materials in high-energy-density batteries. However, practical advancements in lithium metal anodes face obstacles like low Coulombic efficiency, limited cycle life, and heightened reactivity to the electrolyte and internal short circuits resulting from lithium dendrite …

Evaluating The Impact Of Perceptual Loss In Generative Adversarial Models And Diffusion Models For Document Image Enhancement, Farzaneh Karimpour

Electronic Theses and Dissertations

Documents often suffer from various types of degradation which make them difficult to read and restrict OCR performance. This study investigates the effectiveness of perceptual loss in enhancing document image cleanup by comparing a GAN-based model and a diffusion model. In our experiments, we utilized the DE-GAN model as a GAN-based model and the NAF-DPM model as a diffusion model, both enhanced by incorporating perceptual loss. We then compared the results of both models and evaluated them by using the DIBCO 2013, DIBCO 2017, and H-DIBCO 2018 datasets revealed that our approach consistently outperforms existing state-of-the-art methods. Results showed that …

Comparative Analysis Of Deep Learning-Based Anomaly Detection Models For Gps Spoofing Detection, Hasan Mirzakhaninafchi

Electronic Theses and Dissertations

As autonomous vehicles (AVs) become integral to modern transportation, their susceptibility to cyber-attacks, particularly GPS spoofing, presents a serious security threat. This study addresses these challenges by applying a suite of deep learning models to enhance the detection of anomalous GPS signals. Focusing on autoencoder-based architectures, the proposed models such as long short-term memory-based variational autoencoder (LSTM-VAE), LSTM-based autoencoder (LSTM-AE), multilayer perceptron-based variational autoencoder (MLP-VAE), MLP-based Autoencoder (MLPAE), Stacked LSTM-based variational autoencoder (Stacked-LSTM-VAE), stacked LSTM-based autoencoder (Stacked-LSTM-AE), memory-augmented-LSTM-VAE (Mem-LSTM-VAE), and time-series-anomaly-detection-generative-adversarial-networks (TadGAN) were trained exclusively on authentic GPS data. This unsupervised learning approach which used for the above-mentioned models enables …

An Integrated Hybrid P2p-Dr Networks For A Transactive Energy Market Platform Considering Electricity Network Constraints, Sheroze Liaquat

Electronic Theses and Dissertations

No abstract provided.

Moisture-Controlled Triboelectrification During Coffee Grinding, Joshua Méndez Harper, Yong-Hyun Kim, Robin E. Bumbaugh, Connor S. Mcdonald, Christopher H. Hendon, Elana J. Cope, Leif E. Lindberg, Justin Pham, Multiple Additional Authors

Electrical and Computer Engineering Faculty Publications and Presentations

Triboelectrification is the physical process where materials acquire surface charge from frictional interactions at their interfaces.The magnitude of charge depends on the interfacial material composition and can be harnessed in emergent technologies for energy generation.

The mechanism of electrostatic accumulation is complex and is further obscured in granular materials where collisions are sufficiently energetic to cause fracturing. In this “fractoelectric” regime, crack initiation and propagation are thought to charge particles through transfer of electrons and/or ions at the hot crack interface.

Whether a material’s charging is dominated by tribo- or fractoelectrification, fracture-generated granular flows often comprise particles whose surface charge …

Psu Esi Review (Doe-Psu-0000922-6), Tylor Slay, Jaime Kolln, Robert B. Bass

Electrical and Computer Engineering Faculty Publications and Presentations

A guide to developing an Energy Service Interface (ESI) was created as part of the Grid Modernization Laboratory Consortium 2.5.2 ESI project. The approach applies device-agnostic and service-oriented ESI principles and leverages documents such as the Interoperability Maturity Model and Common Grid Service Definitions to provide a methodology to review, develop, and update standards and profiles to engage distributed energy resources to provide grid services. This document evaluates the ESI developed by Portland State University’s Power Engineering Group under the Electric Grid of Things project funded by the U.S. Department of Energy. The evaluation explores the compliance of this specific …

Trust Model Utilization For Energy Grid Communication, N. Sonali Fernando, John M. Acken, Robert B. Bass

Electrical and Computer Engineering Faculty Publications and Presentations

The internet information that is used by the Energy Grid of Things requires both preventative security measures as well as surveillance measures. The preventative security measures include certificates, encryption, and all of the basic security protocols as defined by published standards. The surveillance measures include monitoring information flow activities and evaluating these messages for indications of potential security attacks. We describe in this paper the utilization of a Distributed Trust Model that was developed specifically for monitoring communication within an Energy Grid of Things. The goal for the Distributed Trust Models is to provide a level of aggregate trust that …

Mud Acoustics, Charles W. Holland, Stan E. Dosso, Jason D. Chaytor

Electrical and Computer Engineering Faculty Publications and Presentations

Imaging the ocean requires an understanding of how different seafloor sediments interact with sound waves.

A Transverse-Flux Constant Force Mechanism, Gozde Sivka, Bertrand Dechant, Colton Bruce, Jonathan Z. Bird

Electrical and Computer Engineering Faculty Publications and Presentations

A new type of constant force magnet mechanism is presented that relies on the interaction of magnets alone to create a constant force over a prescribed stroke length. It is demonstrated that by using a transverse field path a very uniform radial field along the travel length is created. This can then be used to create a constant force over a long stroke length. The constat force value is shown to be adjustable through the rotation of the stator relative to the translator. The operating principle of the presented transverse-flux constant force mechanism is validated by using 3-D finite element …

An Analysis Of Precision: Occlusion And Perspective Geometry’S Role In 6d Pose Estimation, Jeffrey Choate, Derek Worth, Scott Nykl, Clark N. Taylor, Brett J. Borghetti, Christine M. Schubert Kabban

Faculty Publications

Achieving precise 6 degrees of freedom (6D) pose estimation of rigid objects from color images is a critical challenge with wide-ranging applications in robotics and close-contact aircraft operations. This study investigates key techniques in the application of YOLOv5 object detection convolutional neural network (CNN) for 6D pose localization of aircraft using only color imagery. Traditional object detection labeling methods suffer from inaccuracies due to perspective geometry and being limited to visible key points. This research demonstrates that with precise labeling, a CNN can predict object features with near-pixel accuracy, effectively learning the distinct appearance of the object due to perspective …

Semiconductor Physics Based Signal Integrity Analysis For 3d Ic, Ze Sun

Doctoral Dissertations

"Three-dimensional integrated circuits (3DICs) are becoming increasingly popular in high-speed electrical systems. 3DICs are made by stacking multiple dies vertically and connecting them with through-silicon vias (TSVs). In this dissertation, three studies were carried out to model the performance of 3DICs in extreme working conditions and the signal integrity (SI) performance of 3DICs.

First, an in-house Monte Carlo particle simulator was developed to characterize extreme working conditions (ESD/EMP) for ICs at the microscopic level instead of the macroscopic level. The ability of the simulator was demonstrated by modeling a voltage regulator diode under forward and reverse bias. The diode simulation …

Deep Reinforcement Learning Based Strategies For Inverter Dominated Microgrids, Oroghene Oboreh-Snapps

Doctoral Dissertations

The integration of inverter-based distributed generators (IBDGs) in modern power systems has ushered in a new era of renewable energy utilization, prompting the rise of Microgrid (MG) architectures. Nevertheless, as IBDG penetration increases, a host of challenges surface. Foremost among these challenges are issues related to frequency stability stemming from the inherent lack of inertia in IBDGs, and inaccurate sharing of reactive and active power, particularly evident in parallel IBDG networks with mismatched feeder impedance. This research presents novel solutions to these challenges by adopting deep reinforcement learning (DRL), specifically, the twin delayed deep deterministic policy gradient (TD3) algorithm, to …