Physical Sciences and Mathematics Commons^™

Metal Zonation And Evolution Of The Bronson Slope Porphyry Cu-Au-Mo Deposit In The Iskut Region Of British Columbia, Canada, Luis Jacobo Yagual

Open Access Theses & Dissertations

Bronson Slope is a Cu-Au-Mo porphyry deposit located within the Stikine Terrane in the Golden Triangle District of northwestern British Columbia, Canada. This deposit represents a complex, multistage magmatic-hydrothermal system emplaced into sedimentary and volcanoclastic rocks of the Triassic Stuhini Group. Bronson has an inferred resource of 517.3 Mt at 0.33 g/t Au, and 0.09% Cu. This study integrates detailed and quick logging from 20 drill holes, totaling 20,296m, SWIR spectral analysis, ICP-MS geochemistry, XRF analysis, magnetic susceptibility measurements, geochronology, and 3D models developed in Leapfrog Geo which define the stratigraphy, intrusive geometry, extension, alteration footprint assemblage, metal zonation, and …

Physics-Guided Strategies For Enhancing Neural Networks Trained With Limited Data, Jose Guadalupe Perez Zamora

Open Access Theses & Dissertations

Deep neural networks excel at a wide range of processing tasks across various disciplines. However, the quantity and quality of data significantly impact network performance. In specialized domains, high-quality datasets are often difficult to gather, interpret, and curate for effective learning. Few-shot learning techniques, including transfer learning, data augmentation, and meta-learning, have emerged to address these constraints.

We propose three physics-guided strategies for enhancing neural networks trained with limited data: (1) combining existing models like LSTMs with Physics-Informed Neural Networks through two-branch architectures that merge their outputs, (2) deriving custom physics-informed data augmentation algorithms to expand limited datasets, and (3) …

Investigating The Redox Properties Of Photoredox Catalysts And Organic Compounds Through Quantum Chemistry, Peter Girnt

Open Access Theses & Dissertations

This dissertation explores the redox behavior of organic and organometallic systems using density functional theory (DFT), focusing on electron transfer mechanisms and structur –property relationships. The first study investigates the two-electron reduction of bianthrone isomers, revealing a potential-inverted ECE mechanism driven by isomerization and electronic destabilization. The second study examines ruthenium photoredox catalysts, showing that ligand fusion positions significantly affect redox potentials due to backbone dearomatization, while p extension has minimal impact. Together, these findings provide insight into redox tuning strategies and support the rational design of advanced catalysts and electroactive materials.

Decoding Anisotropic Porous Medium: A Synergy Of Lattice Boltzmann Modelling And Operator Learning To Predict Permeability As A Function Of Orientation, Soumya Shouvik Bhattacharjee

Open Access Theses & Dissertations

Understanding the directional properties of porous media is essential for accurately predicting flow behavior, reactive transport, and fluid-solid interactions in systems ranging from geothermal reservoirs to energy storage devices and biological tissues. Directional variations in permeability - reflecting a medium's response to flow at different angular orientations - are particularly important for complex, inherently anisotropic geometries. In this study, we employ a Lattice Boltzmann (LBM) model to calculate directional permeabilities from porous media images subjected to varying flow inlet angles. Three classes of porous media were investigated: (1) synthetic media with circular grains, serving as isotropic baselines; (2) synthetic media …

Analyzing The Impact Of Approximate Arithmetic On Deep Neural Network Predictions, Johnatan Garcia

Open Access Theses & Dissertations

In recent times, we have seen the use of artificial intelligence in our daily lives. It helps us solve complicated problems. Some of these problems can be large and complex, requiring large models. As models grow in complexity, they require more computations and energy to be trained and tested. The execution of these models relies on floating-point arithmetic, which imposes constraints due to its finite precision. Due to these limitations, many of these computations are not exact. When this happens, computers are forced to round or approximate. We can use several number formats to circumvent this issue. For example, in …

Effective Transformer Networks For Undersampled Magnetic Resonance Image Reconstruction, Tahsin Rahman

Open Access Theses & Dissertations

The proliferation of data-driven tools for solving problems in every possible domain, coupled with rapid advances in computing technology, has led to an arms race of AI development and application research in industry and academia. One field of research that stands to gain immeasurably from this revolution is medical imaging. It is a critical part of modern diagnostics, and advancements in this area can directly benefit the average person by making healthcare more accessible, accurate, and affordable. Breakthroughs in mainstream image processing and computer vision have long fueled development in medical imaging, and it is now common to see cutting …

Experimental Investigation Of Photovoltaic Soiling Losses And Aerosol Absorption And Scattering Related To Dust In The Chihuahuan Desert Region, German Rodriguez Ortiz

Open Access Theses & Dissertations

This dissertation explores the interaction between mineral dust and solar radiation in the Chihuahuan Desert, one of the dustiest areas in North America. I focused on two main aspects: (1) the characterization of atmospheric aerosol optical properties during dust events, and (2) the effects of dust deposition (soiling) on the performance of photovoltaic (PV) modules. I characterized the intrinsic optical properties of aerosols in El Paso, Texas during the peak of the 2021 dust season. Ground-level, high-resolution optical and meteorological data were collected at the Black and Brown Carbon (BC^2) study site, whereas particulate matter and additional meteorological parameters were …

A Multi-Modal Method For Synthetic Data Generation In Social Network Analysis, Hortencia Josefina Hernandez

Open Access Theses & Dissertations

Social network analysis (SNA) research is often rife with data collection pitfalls, frequently leading to incomplete and missing data. With the growing use of SNA-based research, researchers must address the challenge of missing data and synthetic data generation in these settings. Missing data occurs due to longitudinal non-response or lack of response to sensitive or difficult-to-answer questions. Synthetic data generation in SNA settings addresses the lack of representation that is often present in large-scale SNA studies. This dissertation investigates synthetic data generation methods to address these challenges and develops a novel algorithm that leverages information from multi-modal data, e.g., databases …

Study On Self-Interaction Errors In Molecular Properties And Magnetic Behaviour Of 2d Materials Under External Stimuli Using Density Functional Theory, Prakash Mishra

Open Access Theses & Dissertations

Density Functional Theory (DFT) has established itself as a practical and versatile method for efficiently studying the properties of materials of solids and molecules. Despite being exact in principle, in practice, DFT calculations rely on an approximation for the exchange-correlation energy functional of the electron density. This results in an erroneous interaction of the electron with itself, known as the self-interaction error (SIE). It arises from the fact that the exchange self-interaction does not exactly cancel out the Coulomb self-interaction. Due to this error, the approximate one-electron potential decays exponentially in the asymptotic region rather than exhibiting the correct ?1 …

High-Frequency Seismic Noise In Desert Environments, Alexis Hernandez

Open Access Theses & Dissertations

This study investigates the generation and modulation of ambient seismic noise in arid environments, with a focus on aeolian processes such as saltation, wind shear, and precipitation events. Using a dense array of three-component seismic nodes co-located with meteorological sensors and a novel particle transport instrument (SANTRI), high-frequency seismic signatures were examined within the Jornada Experimental Range in southern New Mexico. Time-frequency analysis reveals that wind-driven saltation events produce measurable seismic energy enhancements, particularly within the 100-300 Hz band, with clear spectral distinctions between wind-only forcing and particle-laden transport. Additionally, rainfall events were identified by elevated seismic amplitudes in the …

Temporal Partitioning And Coexistence Among Four Sympatric Felid Species In The Northern Jaguar Reserve, Kylie Marie Rezendes

Open Access Theses & Dissertations

Coexistence among sympatric carnivores is shaped by behavioral strategies that mediate competition and mortality risk in heterogeneous landscapes. Understanding how sympatric carnivores, such as felids, use space and time in relation to one another requires models that account for both spatial and temporal overlap across landscapes. Models incorporating time-to-event probabilities provide a powerful framework for detecting behavioral dynamics across shared landscapes. This study evaluated the spatiotemporal responses of two apex predators â?? the jaguar (Panthera onca) and mountain lion (Puma concolor) - and two mesopredators - bobcat (Lynx rufus) and ocelot (Leopardus pardalis) - across five years of camera trap …

Rethinking Iterative Proportional Fitting: Scalable And Hybrid Approaches To Joint Distribution Fitting, William Ofosu Agyapong

Open Access Theses & Dissertations

The Iterative Proportional Fitting (IPF) algorithm is widely used in contingency table estimation, survey weighting, and synthetic population generation due to its simplicity and strong theoretical foundation for matching observed marginal distributions. However, in high-dimensional settings, IPF faces substantial computational and memory demands, as well as statistical instability caused by sparse contingency tables. Moreover, IPF is less useful in modern population synthesis tasks that require both scalability and realism because, despite its superiority in matching known marginal distributions, it cannot produce realistic out-of-sample data points. To address these limitations, we first propose a blockwise IPF framework, in which the feature …

Terrane Accretion In The Trollheimen And Dovrefjell Regions Of The Scandinavian Caledonides, Norway, Stephanie Georgevich

Open Access Theses & Dissertations

Following closure of the Iapetus Ocean, the paleocontinents of Laurentia and Baltica collided to form the Caledonian Orogeny. During this closure and subsequent collision, island arc terranes and microcontinents were accreted and subducted underneath the Norwegian continental margin. These terranes are preserved in central Norway, specifically in the Dovrefjell and Trollheimen mountain ranges. The order in which these terranes accreted to the continent and when this occurred is not well understood. To determine this stacking order, I will be using P-T path modeling, U-Pb zircon dating, and structural position. Knowing the degree, progression, and geologic age of metamorphism, and tectonostratigraphic …

The Origin And Geologic History Of Dolostones Associated With The Moab Valley Salt Wall, Paradox Basin, Utah, Charles Ojodale Igomu, Charles Ojodale Igomu

Open Access Theses & Dissertations

This thesis investigates the origin and geologic context of dolostones associated with the Moab Valley salt wall in southeastern Utah, a feature within the broader Paradox Basin that offers an exceptional opportunity to study the interplay between carbonate sedimentation, diagenesis, and salt diapirism. The fundamental research question focuses on evaluating whether dolostones observed in the Moab Valley are all depositional, diagenetic or structurally reworked components of deeper stratigraphy, and how their presence and geometry relate to the halokinetic processes that shaped sedimentation across the Moab Valley. This study tested the hypothesis that dolostones within Moab Valley represent a mixed assemblage …

Simultaneous Selection Of Inflations And Variables In Multiple Inflations Poisson Model (Mip), John Koomson

Open Access Theses & Dissertations

Count data frequently arise in biomedical, economic, and social science research and are often characterized by structural excesses at specific count levels. To accommodate such patterns, Su et al. (2013), among others, introduced the Multiple-Inflation Poisson (MIP) model, which allows for multiple inflated counts within the distribution. However, two critical challenges remain in modeling such data: (i) identifying the true inflation points where excess counts occur, and (ii) selecting the relevant covariates that explain variation in the inflation and count process. This dissertation addresses these issues by advancing the MIP model through a novel methodology that enables the simultaneous selection …

Aluminum Doped Tin Sulfide Thin Films For Solar Cell Applications, Gabriel Rodriguez Guijarro

Open Access Theses & Dissertations

Tin sulfide (SnS) is theorized to be a suitable material for solar cells, but there are some difficulties that have not been overcome when making thin films that have the properties needed to compete with other materials. This work investigates the structural and optoelectronic properties of aluminum-doped SnS thin films, deposited via magnetron cosputtering physical vapor deposition at different temperatures. To characterize the films a variety of techniques were used: Raman spectroscopy, SEM, TEM, X-Ray Reflectivity, and UV-Vis spectroscopy. The results show that the target stoichiometry is a relevant parameter to take into account when growing SnS thin films, the …

A Digital Engineering Framework For Ai-Driven Trade-Off Evaluation And Predictive Component Classification, Alejandro Silva Au

Open Access Theses & Dissertations

This thesis introduces a digital engineering tool designed to help engineers make smarter decisions when choosing actuators. At its core, the system brings together machine learning (specifically XGBoost) and a decision-making method called Multi-Utility Attribute Theory (MUAT). The goal is to support engineers in picking components based on what really matters for their designs, whether that's speed, cost, durability, or any other performance factor. What makes this tool stand out is its user-friendly interface that lets people interact with the system directly. It takes a set of actuator performance data, classifies each one into a relevant use category, and then …

Laser Scan Path Design For Controlled Microstructure In Additive Manufacturing With Integrated Reduced-Order Phase-Field Modeling And Deep Reinforcement Learning, Augustine Twumasi

Open Access Theses & Dissertations

Laser Powder Bed Fusion (L-PBF) is a well-established additive manufacturing technique for fabricating intricate metal components with exceptional precision. A significant challenge in L-PBF is the formation of complex microstructures that influence final material properties. We propose a physics-guided, machine learning-aided approach to optimize scan paths for desired microstructure outcomes, such as equiaxed grains. We employed a phase-field method (PFM) to model the evolution of the crystalline grain structure. To reduce computational costs, we trained a surrogate machine learning model, a 3D U-Net convolutional neural network, using single-track phase-field simulations with varying laser powers to predict crystalline grain orientations based …

Electrochemistry Behind Pfas: Mechanistic And Analytical Approach For Sensing And Degradation Strategies, Jonathan Josue Calvillo Solis

Open Access Theses & Dissertations

Understanding the fundamental electrochemistry of perfluoroalkyl substances (PFAS) is key to developing effective water remediation and sensing strategies. This work explores the thermodynamics and kinetics of perfluorooctanoic acid (PFOA) electroreduction, focusing on C-F bond cleavage. These insights were applied to design a highly sensitive electrochemical sensor for detecting trace levels of PFOA in water. This dissertation focuses on the electrochemical investigation of the reduction reaction of PFOA in aqueous and organic media employing different electrode materials. This exploration allows to understand the defluorination reaction of PFAS to further propose potential strategies for water treatment and PFOA electrosensing. Through electrochemical, spectroscopical …

Advanced Study Of Nickel-Titanium Alloy: Effects Of Point Defects On Mechanical And Thermodynamic Properties, Diego Armando Juarez Rosales

Open Access Theses & Dissertations

High-throughput first-principles calculations of point defects are emerging as a powerful tool to accelerate materials discovery in applications [1]. Substitutional, antisite, and vacancy defects can play an important role in the mechanical and thermal properties of intermetallic alloys [2]. In this present work I compute the thermal and mechanical properties of shape-memory alloy nickel-titaniun (NiTi) in the B19â?? martensitic and B2 austenitic phases from molecular dynamics (MD), using a second nearest neighbor (2NN) modified embedded atom method (MEAM) [3] classical potential in the temperature range from 200K to 600K and composition range from 45 atomic percent to 55 atomic percent …

Optimal Experimental Plan For Multi-Level Stress Testing Under Progressively Hybrid Censoring, David Kojo Amakye

Open Access Theses & Dissertations

Reliability analysis is essential for understanding how products perform over time, particularly in environments where failure data is limited or costly to obtain. One effective approach is multi-level stress testing, where test units are subjected to varying levels of stress to accelerate failures and extract more information within constrained timeframes. This study presents a novel optimization-based framework for designing life-testing experiments under progressively Type-II hybrid censoring, assuming Weibull lifetime distributions. Leveraging a Variable Neighborhood Search (VNS) algorithm, we determine efficient allocations of test units and censoring parameters across multiple stress levels to enhance the precision of estimates of the model …

Electrodeposition Of Gallium Nitride_Unraveling The Role Of Precursors, Deposition Conditions, And Substrate Effects For Semiconductor Applications, Mauricio Azier Leyva Aranzabal

Open Access Theses & Dissertations

Gallium nitride (GaN) is a wide-bandgap semiconductor noted for its remarkable optoelectronic and structural characteristics, rendering it a potential material for high-power, high-frequency, and optoelectronic device applications. This dissertation investigates the electrochemical synthesis of GaN thin films by potentiostatic and galvanostatic electrodeposition techniques using aqueous solutions of gallium nitrate (Ga(NO3)3), ammonium nitrate (NH4NO3), and auxiliary agents like potassium nitrate and urea. The main aim is to examine the essential elements affecting nitrogen incorporation and film shape while assessing electrochemical performance on various conductive substrates.A thorough investigation was performed to evaluate the impacts of electrodeposition duration, electrolyte pH, precursor molar concentrations, …

A Study Of End-Cut Preference In Tree-Based Modeling, Xiangya Wang

Open Access Theses & Dissertations

Decision trees, particularly those built using the Classification and Regression Trees (CART) algorithm, are widely used for their interpretability and flexibility. However, the greedy nature of the CART splitting procedure gives rise to the end-cut preference (ECP) phenomenon, wherein split points near the extremes of predictor ranges are favored. This study offers a comprehensive investigation of ECP, exploring its theoretical underpinnings, practical manifestations, and implications for both single decision trees and ensemble methods such as Random Forests. Through theoretical analysis and simulation studies, we examine how ECP affects tree structure, variable selection, and predictive accuracy across tree-structured, linear, and nonlinear …

Navigating The Challenges Of Coccidioides Surveillance: Insights From The Environment Of El Paso County, Texas, Tanzir Hossain

Open Access Theses & Dissertations

Coccidioidomycosis, or Valley fever, is a fungal infection resulting from the inhalation of spores from the Coccidioides species (C. immitis and C. posadasii), native to arid areas of the Western Hemisphere. Coccidioidomycosis presents considerable health hazards and can be fatal. It affects between 206,000 and 360,000 individuals annually, leading to 700 to 1,100 fatalities in the United States alone. In response to these issues, extensive research has concentrated on therapeutic goals for this infectious disease. Nonetheless, more limited research has focused on the environmental detection of its causative fungi, which is crucial for forecasting treatment needs and formulating preventive strategies. …

Comparative Study Of Non-Iterative Seqential Method For Biot's Poroelasticity Model, Jeff Frimpong Amponsah

Open Access Theses & Dissertations

Linear poroelasticity theory describes the interaction between the motion of fluids and deformation of porous media. The theory serves various applications in a wide range of science and engineering fields, such as soil mechanics, oil reservoir modeling, and bio-medical applications. Partial differential equations are used to model the complex interaction between fluid flow and solid deformation in porous media. Since analytical solutions to these equations are rarely available for realistic problems, we resort to numerical solutions. One major advantage is their ability to provide accurate approximations of the solutions. Various numerical methods have been proposed to solve Biot's poroelasticity system. …

Synthesis, Characterization, And Redox Properties Of Select 1,4-Diazocine-6,11-Diones Towards An Electrochromic Dye-Set, Jeffrey Scott Richards

Open Access Theses & Dissertations

The daily consumption of personalized digital visual information depends on the current purview of electronic-based displays. Present manufacturers utilize modern technologies, such as LCD, OLED, QLED, and electronic ink, or "E Ink," in their devices to display text, pictures, and other forms of media to individual users. However, as modern society continues to rely on the use of digital displays, the demand for low-power alternatives will continue to rise as their application in varying scenarios is realized. Currently, "E Ink" technology continues to grow as the dominant solution in the e-readers and digital signage marketplace, and can even be seen …

Kernel Density Estimation And Convolution, Nicholas Tenkorang

Open Access Theses & Dissertations

Kernel Density Estimation (KDE) is a widely used technique for estimating the probability density function of a random variable. In this study, we revisit KDE through the lens of convolution and extend this perspective to special cases such as positive, bounded and heavy tailed random variables. Building on this foundation, we propose a novel simulation-based density estimation method that generates new data by adding noise to observed values and then smoothing the resulting histogram using splines. A minor adjustment to natural cubic splines is required to ensure nonnegative estimates. The noise is drawn from a class of bounded polynomial kernel …

Impact Of Magnetic Fields On Cosmic Ray Density In Molecular Clouds, Byron Jesus Encinas Velazquez

Open Access Theses & Dissertations

We investigate the effects caused by Cosmic Rays (CRs) in a Molecular Clouds (MCs) environment and the effects of varied magnetic field configurations in the core (r = 1 Pc ) of a MC. We take as initial conditions for the interstellar medium a product of various supernova explosions as injected initial perturbation and observe the evolution during the timescale of ~4.5 Myrs. We compute the CR reduction factor R as a measure of the density of a distribution of particles traveling with a guiding center along randomized field lines near the core and discuss their impact on the ionization …

A Profile Wald Test In M-Estimation, Reagan Kesseku

Open Access Theses & Dissertations

Despite the growing popularity of machine learning-based inference, classical statistical inference remains highly relevant in modern data science due to its interpretability and theoretical rigor. Among its core tools, the likelihood ratio test, Wald test, and score test are foundational methods for hypothesis testing within the maximum likelihood framework. Although these tests are asymptotically equivalent under regularity conditions, each offers distinct advantages depending on the context, computational demands, and the availability of parameter estimates. In this dissertation, we introduce a fourth method, the Profile Wald Test (PWT), within the broader M-estimation framework. The PWT is based on profile estimators of …

From Text To Utility: Distance-Aware Contrastive Learning For Detection-Ready And Shareable Malware Descriptions, Ivan Alejandro Montoya Sanchez

Open Access Theses & Dissertations

The rapid rise of sophisticated malware variants poses significant challenges for cybersecurity analysts, particularly due to the scarcity of data on newly emerging threats. Due to privacy, legal, and operational constraints, malware samples are often not shareable; instead, organizations publish cyber threat intelligence (CTI) in natural language. However, these reports are typically unstructured and inconsistent, limiting their utility in machine learning (ML) models. This thesis explores whether high-fidelity, shareable threat intelligence can be automatically generated from structured malware behaviors to supplement ML models when direct access to malware samples is limited. Two central questions are addressed:(i) How can descriptions be …