Electrical and Computer Engineering Commons^™

Investigating The Efficiency Of Ingan P-N-P-N Homojunction Solar Cells, Moath Alhejji, Mohammad Alavijeh, Jacob Kupernik, Mirsaeid Sarollahi, Abbas Jammali, Seyed Taghavi, Reem Alhelais, Md Hel Uddin Maruf, Morgan Ware

Electrical Engineering and Computer Science Faculty Publications and Presentations

This research investigates the development of a novel p-n-p-n homostructure solar cell, through semiconductor simulations using the Nextnano software. InGaN was used as a model system in order to achieve a bandgap with optimized efficiency for a p-n homojunction solar cell. By increasing the uniform doping concentration from 1.5*10(16) cm(-3) to 1.5*10(17) cm(-3), the open circuit voltage (V-oc) increased while the short-circuit current density (J(sc)) decreased, as expected in simple p-n junctions. The p-n-p-n structure achieved a peak efficiency of 32.91% at a doping level of 6.5*10(16) cm(-3), a similar to 7% improvement over a conventional p-n junction's 25.31% efficiency …

Position Sensor Offset Fault Calibration In Speed-Regulated Pmsm Drives, Ujala Anuradhi Maha Gamage

Masters Theses

Speed regulation of electro-mechanically actuated systems is common across broad application segments, including industrial and residential sectors. The increasing demand for efficient energy conversion has made permanent magnet synchronous machines (PMSM) a preferred choice in modern applications. Vector controlled PMSMs in speed regulation mode being the dominant form of control, accurate speed and position measurement is crucial. However, a misalignment in the position sensor with respect to the true rotor zero position in speed regulated PMSM drives leads to inefficient energy conversion with the possibility of unstable motor behavior. The considered position sensor offset error fault, under severe fault modes, …

Extreme Bandgap Al0.63Ga0.37N Quasivertical Schottky Barrier Diodes With A High Baliga Figure Of Merit Of 630 Mw Cm−2, Abdullah Al Mamun Mazumder, Shahab Mollah, Kamal Hussain, Abdullah Mamun, Seongmo Hwang, Tariq Jamil, Grigory Simin, Asif Khan

Faculty Publications

"Extreme bandgap n-Al_0.63Ga_0.37N quasi-vertical Schottky barrier diodes (SBDs) with doping densities of ≈8 × 10¹⁷cm⁻³ (Sample A) and ≈2 × 10¹⁷cm⁻³ (Sample B) are grown on an AlN/sapphire substrate using metalorganic-chemical vapor deposition (MOCVD). Sample A achieves a high forward current density of ≈59.5 kA cm⁻² at 10 V with an I_ON/I_OFF ratio of ≈10⁸ (calculated from the forward current at + 3.8 V and the reverse current at −1 V) and an ideality factor of 2.8. Sample B has a forward current …

Machine Learning Assisted Quality Control In Metal Additive Manufacturing: A Review, Zeqi Hu, Changlin Huang, Lechun Xie, Lin Hua, Yujie Yuan, Lai Chang Zhang

Research outputs 2022 to 2026

Additive manufacturing (AM) promotes the production of metallic parts with significant design flexibility, yet its use in critical applications is hindered by challenges in ensuring consistent quality and performance. Process variability often leads to defects, insufficient geometric accuracy and inadequate material properties, which are difficult to effectively manage due to limitations of traditional quality control methods in modeling high-dimensional nonlinear relationships and enabling adaptive control. Machine learning (ML) offers a transformative approach to model intricate process-structure-property relationships by leveraging the rich data environment of AM. The study presents a comprehensive examination of ML-driven quality assurance implementations in metallic AM. First, …

Lstm Network-Based Scheme For Automatic Characterization Of Power Quality Disturbances, Akram Elmitwally, Mohamed Nader

Mansoura Engineering Journal

Recognition of power quality (PQ) troubles is a critical task in the electrical power industry. Most previous works solve the classification problem using separate feature extraction phase and classification phase. Each phase has its own techniques, and consumes a computation time. This study proposes to utilize the long short-term memory (LSTM) network as a deep learning model to classify the PQ events in one shot. The LSTM network uses its particular processing to classify a PQ event signal directly by reading its time-sequence data. Then, a dedicated post-classification algorithm (PCA) extracts start time, end time, duration, amplitude, and total harmonic …

A Low-Power Mixed-Signal Potentiostat System-On-Chip With Integrated Dual-Slope Adc, Seth Mcrobert

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

This thesis presents the design and characterization of a low-power mixed-signal potentiostat that was integrated with a 65 nm core in a SoC for low-power electrochemical sensing applications. The system integrates a low-noise transimpedance-based potentiostat front end with a 12-bit dual-slope analog-to-digital converter (ADC) for accurate current-to-digital conversion. The potentiostat core—comprising the control amplifier, current-mirror network, and transimpedance amplifier—consumes 38.2 µA from a 2.5 V supply (95.5 µW) and achieves an input-referred noise floor of 113 µVRMS over a 330 Hz bandwidth, while having an input current range from 1 nA to 20 µA and a noise-limited sensitivity of 56.4 …

Optimal & Robust Control Of A Bidirectional Dc-Dc Converter In Ev Systems, Yasser Ayeva

Electrical Engineering and Computer Science Faculty Publications and Presentations

This paper analyzes the performance of PI, LQR, and H∞ controllers for the regulation of a bidirectional buck boost converter in electric vehicle systems. To get the system state space equations, a continuous conduction average model is linearized. For analysis a PI controller will be used as baseline, the LQR controller will be used to improve transient response, and the H∞ controller will be used for the system robustness and disturbance rejection. The simulation results show that the advanced controllers surpass the PI controller in terms of overshoot, settling time, and voltage ripple, with the H∞ controller offering the best …

Cattlefever: An Automated Cattle Fever Estimation System, Trong Thang Pham, Ethan Coffman, Beth Kegley, Jeremy G. Powell, Jiangchao Zhao, Ngan Le

Electrical Engineering and Computer Science Faculty Publications and Presentations

Farmers face the critical challenge of monitoring cattle well-being for both ethical and economic success, relying on signals like body temperature and facial expressions to assess their animals' health. However, these indicators have traditionally relied on human observation with manual measurement, which is time-consuming and subjective. Despite this clear need, no automated system currently exists for monitoring cattle body temperature, and available datasets remain limited in scope. To address these challenges, we make two key contributions: (i) We introduce CattleFace-RGBT, a novel RGB-Thermal (RGB-T) Cattle Facial Landmark dataset consisting of 2,300 paired RGB and thermal images (4,600 images in total), …

Extremum-Seeking Approach For Real-Time Self-Healing Of Position Sensor Offset Error In Non-Salient Pmsms, Ramitha Kalhara Dissanayake Ralalage

Masters Theses

The inherent advantages of permanent magnet synchronous machines (PMSMs), such as high efficiency, has led to their frequent use in industry, including safety-critical applications, such as transportation electrification. The accurate measurement of the rotor position is key to achieving efficient and reliable field-orientation-based torque regulation. With the high reliance on the rotor position measurement, position sensor fault diagnosis and mitigation facilitate a layer of safety. Conventional methods for compensating position sensor offset errors in electric drives typically depend on accurate knowledge of motor parameters. However, these parameters are often subject to variation due to temperature changes, system aging, and other …

Series Resonant Converters With Medium Voltage Sic Mosfets For Electric Aircraft Applications, Xinyuan Du

Graduate Theses and Dissertations

To develop high-performance high- power-density MV power converters, the emerging silicon carbide (SiC) devices are more attractive than their silicon (Si) counterparts, since the fast switch frequency brought by the SiC can effectively reduce the volume and weight of the filter components and thus increase the converter power density. From the converter topology perspective, with the MV dc distribution, the single stage isolated dc/dc converter are suitable for next-generation electric aircraft system due to soft switching and high power density. In this work, comprehensive static and dynamic characterizations were conducted for the latest 6.5 kV silicon carbide (SiC) MOSFETs from …

Implementation Of A Three-Port Solar Converter With A Battery Energy Storage System, Maison Christopher Phipps

Graduate Theses and Dissertations

The increasing deployment of distributed solar and energy storage systems has created the need for integrated power converters that can efficiently manage photovoltaic (PV) generation, battery energy storage, and grid-tied AC output. This thesis presents the implementation and validation of a 5kW non-isolated Three-Port Converter (TPC) adapted for residential solar applications. The converter consolidates three power stage into a high-frequency, compact architecture: a unidirectional boost converter for PV input, a bidirectional interleaved buck-boost converter for battery energy storage, and a configurable DC/AC inverter for 120Vac single-phase output. The system is controlled using a central controller implemented on a TI C2000™ …

Optical Characterization Of Ge And Gesn Grown In Aspect Ratio Trapping Structures For Enhanced Emitter Performance, Abdulla Said Ali

Graduate Theses and Dissertations

Silicon (Si) began dominating the electronics industry since 1960s, the dominance came due to its affordability and well developed fabrication processes. But when it comes to light emitting devices and photonics devices in general, the indirect bandgap of Si has caused many scientists to search for alternative semiconductor materials that can deliver better light emission, materials that can also improve wavelengths detection which is also very limited when it comes to Si, reduce losses and greater light amplification, all this while still being affordable. Despite these limitations, Si has been widely used in Complementary Metal Oxide Semiconductor (CMOS) manufacturing and …

Volume Status Detection With Integral Pulse Frequency Modulation Model Of Peripheral Venous Pressure, Jeremiah Rhys Wimer

Graduate Theses and Dissertations

This thesis studies the effectiveness of utilizing a modified integral pulse frequency modulation (IPFM) algorithm to synthesize peripheral venous pressure (PVP) waveforms for the detection of several physiological conditions using logistic regression. PVP waveforms are collected from 18 human patients and 4 porcine subjects. Human data are used to train models for determining the hypovolemic status of the patient, while the porcine data are used to train models for determining level of anesthesia and detecting internal hemorrhaging. In the human dataset, the waveforms collected from the 18 patients are classified into two groups according to serum chloride levels: resuscitated (≥100 …

Design Of Phase Shifter And True Time Delay Gan Mmics For High-Temperature Ku-Band Applications, Michael Lee Thompson

Graduate Theses and Dissertations

This thesis presents the design, implementation, and high-temperature characterization of Gallium Nitride (GaN) monolithic microwave integrated circuits (MMICs) developed for beamforming and phased-array systems operating in the Ku-band (12-14 GHz). Two integrated circuits were designed: a 3-bit digital phase shifter and a 3-bit true time delay (TTD), both optimized for high linearity, low insertion loss, low phase error, and stable operation at elevated temperatures up to 300°C. Developing both a phase shifter and a TTD enabled a direct comparison of their beamforming performance and the evaluation of beam squint effects over frequency, a critical factor in wideband array design. The …

Flood-Level Estimation Using Aerial Imagery, Yisen Zhang

Electrical & Computer Engineering Projects for D. Eng. Degree

Reliable flood-level estimation using aerial UAV (Unmanned aerial vehicle) imagery is essential for effective post-disaster assessment and rapid emergency response. This study utilizes a UAV-based dataset, referred to as the UVA dataset, which integrates multiple public datasets and manually labeled UAV images, together with a multi-stage vehicle-centric framework for flood-depth estimation. The UVA dataset integrates images from multiple public sources, including Unmanned Drone Water Assessment (UDWA), Unmanned Aerial Vehicle Detection and Tracking (UAVDT), Car Parking Lot (CARPK), and additional UAV-view images collected from the internet, followed by manual annotation for water depth, viewing angle, and altitude labels. In the proposed …

Power Distribution Controller For Formula Sae Vehicles, Michael Yuen

Electrical Engineering

The Power Distribution Controller (PDC) is designed for low-voltage (12V) automotive applications, specifically Formula SAE vehicles. It aims to replace the current and outdated MOSFET-based system, which suffers from inefficiencies such as lossy current sense resistors and limited configurability. Instead, this new system uses a PROFET-based architecture controlled over the Controller Area Network (CAN) and an updated microcontroller, enabling intelligent power management and data logging.

Designed with FSAE regulations in mind, the PDC not only enhances the reliability of low-voltage systems but also provides a quickly adaptable solution to fuse boxes. It achieves this by providing firmware-adjustable overcurrent protection, incorporating …

Few-Shot Anomaly Detection And Classification Through Reinforced Data Selection With A Combinatorial Reward, Xiaolei Hn, Depeng Xu, Shuhan Yuan, Xintao Wu

Electrical Engineering and Computer Science Faculty Publications and Presentations

Due to the scarcity of anomalies, deep anomaly detection models are typically trained in an unsupervised or semi-supervised manner, depending on the availability of a small number of labeled samples. Currently, most unsupervised approaches detect anomalies by identifying the deviant patterns from normal samples, and some semi-supervised studies also use labeled anomalies to improve performance. However, few studies have focused on how to take advantage of potential anomalies in an easily obtained and large-scale unlabeled dataset. Meanwhile, in a semi-supervised setting, although we assume there will be a small number of labeled anomalies, the task of anomaly classification is under-exploited, …

A Study On Utilizing Coherently Coupled Orbital Angular Momentum Beams For Maritime Sensing And Communication, Evan Robertson

All Dissertations

A large portion of the world is covered in water which introduces a couple of key challenges in communication and sensing systems. The impact of particulates in the water will limit the ability to successfully transmit information through the water. The study of how the channel impacts specific frequencies and the ability to transmit more information at a single time can limit the impact of this environment in how it degrades an optical communication system. In sensing applications, it is important to detect information related to an object’s motion which will either be towards or away from a system, or …

Deterministic Methods To Improve The Field-Of-View For Direction Finding Using Sparse Digital Arrays, Nolan J. Egging

Master's Theses

Direction finding algorithms are used with digital phased arrays to determine the incoming angle of arrival (AoA) of an incident signal. These algorithms, and direction finding as a whole, have a wide range of civilian and military applications from radar, electronic reconnaissance, mobile communication, et cetera. However, for situations where the spacing between antenna elements needs to be large, gating lobes appear in the radiation pattern of analog arrays. This work demonstrates that for digital beamforming algorithms, the field of view (FoV) of a uniform linear digital array matches the grating lobe free range of a similarly spaced analog array. …

Application Of Natural Language Processing And Machine Learning For Analyzing Mining Accident Reports And Automating The Process Of Root Cause Analysis, Siddhartha Agarwal, Y. P. Chugh, Atul Singh, Vikram Sakinala, Ayan Mukherjee, Balbir Prasad, Cihan Dagli, Yuhao Zou

Engineering Management and Systems Engineering Faculty Research & Creative Works

Coal mining accidents are a major concern worldwide, necessitating effective safety measures and comprehensive analysis to prevent future accidents. Our proposed solution is the first attempt for Indian mines, inspired by the potential of Natural Language Processing (NLP) that can read and analyze vast repositories of accident records in seconds. In combination with machine learning (ML), NLP algorithms can extract unstructured text by eliminating manual data entry errors, reading poorly scanned reports, and understanding multiple versions of the event and cluster documents based on types that would otherwise take months to collate. In the case of accident records, it can …

Realization Of Deterministic Quantum Circuits For Non-Deterministic Or Incompletely Specified Quantum State Machines, Manjith Kumar, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

In classical logic design, there are machine learning methods based on converting a set of input-output traces to non-deterministic automata that are then converted to deterministic automata and synthesized using logic gates. This approach has not yet been extended to quantum automata. In this paper, we present a method to convert a set of input-output traces to a non-deterministic automaton, which is then converted to an incompletely specified multi-output Boolean function. The existing logic synthesis approaches for designing quantum circuits are insufficient to handle incompletely specified functions. So, we present a novel algorithm to synthesize logic functions with don’t cares …

Feed Network Design For Passive Beamforming In Hemispherical Phased Arrays, Daniel Flores

Theses and Dissertations

This thesis presents the design, fabrication, and evaluation of a four-element microstrip patch antenna array with a passive 1 to 4 corporate feed network operating at 5 GHz. A single inset-fed patch was developed on Rogers DiClad 880 to ensure accurate tuning and mechanical flexibility, achieving a measured resonance of 5.009 GHz with excellent return loss. The corporate feed network, synthesized using T-junction dividers and quarter-wave transformers, demonstrated strong impedance matching, balanced amplitude distribution, and broadside realized gain near 10 dBi when integrated with the array.

Beam steering was examined through simulation-based phase control, revealing effective scanning up to approximately …

Rapid Prototyping Of Low-Cost Sensor Systems Towards A Platform For Upper Limb Posture Estimation, Russell Rathbun

Electrical Engineering and Computer Science Undergraduate Honors Theses

Physical therapy requires patients to perform repeated actions to achieve meaningful results in rehabilitation. This thesis explores production methods and various sensor systems by utilizing rapid prototyping, inertial measurement units (IMUs), and capacitive sensor arrays (CSAs). CSAs can be made from a wide ar- ray of materials and techniques including 3d printing and laser ablation–to rapidly create CSAs that can be custom fit to enable proximity, force, and touch detection. IMU and CSA systems individually are able to track upper limb movements, ges- tures, and positions. This combination of sensors enables accurate upper limb pos- ture estimation of patients. This …

Reinforcement Learning Based Security Schemes For Distributed Ai Systems, Ashan Chamath Gunawardena

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

Distributed machine learning (DML) is a component of modern intelligent systems, enabling collaborative training across devices such as mobile clients, vehicles, and edge networks. However, the decentralized nature of these systems introduces vulnerabilities, particularly data poisoning attacks that compromise model integrity and degrade performance. Traditional defenses, such as statistical filtering, robust aggregation, and privacy-preserving techniques, often struggle to adapt to overwhelming adversaries or operate under strict privacy and real-time constraints. This dissertation proposes the use of reinforcement learning (RL) and deep reinforcement learning (DRL) based misbehavior detection schemes that dynamically identify poisoning attempts in distributed AI systems, including federated learning, …

Rapid State-Of-Health Estimation Of Batteries Using Machine Learning With Limited Eearly-Discharge Voltage Data, Mohammad Bakhtiari

Durham School of Architectural Engineering and Construction: Dissertations, Theses, and Student Research

The utilization of lithium-ion batteries has been rapidly expanding across diverse sectors, including electric transportation, stationary energy storage systems, and the built environment. Ensuring a high level of reliability in these applications is essential, as the performance and safety of such systems depend strongly on the accurate assessment of the battery’s State of Health (SOH). Conventional SOH estimation techniques—often based on complex electrochemical models or extensive laboratory testing—tend to require a large number of measurements, advanced instrumentation, and high computational cost. These factors make them impractical for large-scale deployment or real-time monitoring. This study introduces a simplified machine-learning-based approach for …

Lace Network Firmware: A Polarfire Fpga Network For Data Routing And Command Interfacing In Space Applications, Kade C. Howes

All Graduate Theses and Dissertations, Fall 2023 to Present

Modern small spacecraft rely on powerful yet efficient onboard compute devices to process data from sensors in real-time due to tight power and volume constraints. This work explores a new compute device system built from PolarFire Field-Programmable Gate Arrays (FPGAs), which are power-efficient, reprogrammable chips well-suited for space applications. The system connects via a central controller FPGA with one or multiple companion processing FPGAs, allowing sensor data to be quickly received and shared across the network. Standardized data formats and interfaces increase compatibility with spacecraft computers. By simplifying data handling and using high-speed communication links, this architecture makes it easier …

Ai-Driven Electromagnetic Design And Performance Prediction Of Microstrip Antennas, Eduardo Javier Vazquez

Theses and Dissertations

This thesis investigates the application of Deep Learning to automate and accelerate microstrip antenna inverse design. The initial investigation was to predict microstrip antenna performance from its geometry parametric input, and found out that forward prediction with adopted geometric representation results in ill-posed scenario, high ambiguity and unstable mapping. The study later mostly focuses on the inverse prediction by machine learning from S11 parameter input to predict antenna patch geometry parameters instead.

A dataset of 5,000 ANSYS HFSS simulated antennas (later filtered to 4,136 valid samples) was generated using cubic spine -described geometry profiles. Multiple neural architectures were adopted for …

Extreme Bandgap Recessed-Gate Metal Oxide Semiconductor Heterostructure Field Effect Transistors With Drain Current 0.28 A Mm−1 And Threshold Voltage −1.5 V, Abdullah Al Mamun Mazumder, Abdullah Mamun, Kenneth Stephenson, Kamal Hussain, Tariq Jamil, Grigory Simin, Asif Khan

Faculty Publications

Herein, the first demonstration of hybrid high-k oxide (ZrO2-Al2O3) incorporation into extreme bandgap (EBG) Al_0.87Ga_0.13N/Al_0.64Ga_0.36N metal-oxide-semiconductor heterostructure field-effect transistors (MOSHFETs) is presented, with both planar and recessed-gate designs on the same AlN/sapphire template with a state-of-the-art low contact resistance of 1.4 Ω mm (contact resistivity, ρc ≈ 5.7 × 10−6 Ω cm2). The recessed-gate MOSHFETs achieve a threshold voltage shift of ΔVTH = 5.8 V, highlighting improved channel control. Static output measurements reveal a peak drain current (IDS) of 340 mA mm⁻¹ for the planar …

Complementary Color Laser Illumination For Perceptual Contrast Enhancement In Structurally Colored Samples, Tomoshree Dash

All Theses

Structural color, a phenomenon arising from nanoscale interaction between light and materials, has the potential to unveil biological, chemical, physical, and mechanical characteristics of the sample. It enables direct visualization of the sample by human users with high spatiotemporal resolution. However, its impact is often constrained by challenges in the perceptual differentiation of subtle color variations. This thesis introduces complementary color laser illumination (C²LI) as an imaging technique that enhances color perception of the Human Visual System (HVS) by accessing the psychophysical non-linearities in chromatic color perception. C²LI offers a platform optimized for the HVS by …

Measurement-Based Dynamic Load Model Parameterization Via A Stacked Long Short-Term Memory - Deep Neural Network, Zach H. Smith

All Theses

Increases in distributed generation and changes to predominate load types in modern power systems are driving the need for updated or newly developed dynamic load models. Accurate load modeling is necessary for transmission planning and operation, post-mortem analysis, and inter-regional transfer studies. The most widely used dynamic load model is the WECC Composite Load (CMLD). The CMLD model is an aggregation of substation impedance, under voltage and frequency controls, dynamic motor loads, and static loads. Parameterizing dynamic load models, especially composite models with high parameter counts like the CMLD, is can be difficult. This work proposes a measurement-based, machine learning …