Digital Commons Network^™

Modular Synthesis Of Conjugated Aromatic Systems Via Palladium-Catalyzed Cross-Coupling Reactions, Joden Russell Robinson

Dissertations, Master's Theses and Master's Reports

This thesis describes the development of a modular synthetic route to extended conjugated aromatic systems through iterative palladium-catalyzed Sonogashira crosscoupling reactions. The work was motivated by the challenge of preparing a discrete conjugated molecule in a controlled manner. The synthetic strategy used complementary protected alkyne functionalities that could be selectively activated. This enabled sequential deprotection and coupling reactions to predictably extend the molecular scaffold. Using this approach, a series of conjugated intermediates was prepared and exponentially extended. Spectroscopic characterization by NMR and mass spectrometry supported the structures of the isolated products and the success of the iterative elongation strategy. Overall, …

First-Principles And Thermodynamic Modeling Of Hydrogen Storage In Mxenes, Yi Zhi Chu

Dissertations, Master's Theses and Master's Reports

Hydrogen storage is a critical component of the emerging hydrogen economy, playing a central role in enabling the global transition from fossil fuels to a sustainable, green energy system. With advances in materials research, increasing attention has been directed toward the development of promising hydrogen storage materials. Due to their diverse and advantageous physicochemical properties, MXenes have attracted significant interest in this regard. A fundamental understanding of the hydrogen interactions with the MXenes structure is crucial for explaining and predicting their hydrogen storage performance. In this work, first-principles density functional theory (DFT) combined with a revised thermodynamic model is employed …

Numerical And Experimental Evaluation Of A Simple, Low-Energy Lunar Volatile Separation Technology, Eleanor L. Zimmermann

Dissertations, Master's Theses and Master's Reports

In-situ resource utilization (ISRU) is the practice of finding, extracting, and using the local resources found on extraterrestrial bodies, such as the Moon and Mars. ISRU enables in-situ production of mission consumables—such as rocket fuel and potable water—which will be critical for establishing a sustainable human presence on the Moon, a goal NASA intends to accomplish by 2028 with the Artemis missions. The separation and liquefaction of locally extracted volatiles—such as water, CO₂, and Methane—is an essential component in lunar surface sustainability, but there are very few technologies being developed for this purpose. This report introduces the Radiative …

The Excess Path Length Distribution: A Stochastic Model For Sample-Based Path Planners, Chaz B. Cornwall

Dissertations, Master's Theses and Master's Reports

Through random sampling, sample-based path planners enable autonomous agents to quickly find paths without human intervention. However, due to the paths' randomness, sample-based path planners currently require additional verification, partially nullifying agents' ability to act autonomously. I set out to characterize this uncertainty so humans know what to expect from these path planners and know how to alter the path planner to desired specifications. To ensure the results are theoretical as well as practical, I first create a stochastic model of path length uncertainty using the trade-off between sampling time and optimality. By leveraging this model, my proposed algorithm reduces …

Shm For Incipient Buckling Detection In Overloaded Structures Using Nonlinear System Identification Algorithms On Redundant Data Sets, Padmanabh Shridhar Desai

Dissertations, Master's Theses and Master's Reports

Structural health monitoring (SHM) detects and characterizes damage to predict failure, but failures such as buckling, which are not predicated on traditional damage modalities, are harder to detect. Direct load measurements are costly and difficult to implement (especially for dead loads) as they require copious numbers of sensors, which must be installed before loading is present. Vibration-based detection is a good alternative because it can infer global structural characteristics with relatively few sensors. This dissertation presents an SHM approach for detecting incipient buckling in structures under excessive loads based on non-linear models fit from measurements of small lateral vibrations due …

Measurement Of Wave Elevation Using Piezo-Electric Hydrophone, Ace D. Hobbs

Dissertations, Master's Theses and Master's Reports

Water surface waves exert a pressure oscillation that decreases with depth. Pressure measurements can be used to estimate wave elevation and frequency, which can then be used to (1) implement feedback for wave energy converter control strategies and (2) quantify the potential for converting waterbed pressure fluctuations into electrical energy. This report examines the use of an off-the-shelf piezo-electric hydrophone to estimate wave elevation from pressure data. Experiments were carried out in a wave tank with various wave amplitudes, frequencies, and hydrophone depths. Wave gauges, with a resolution of $\pm 0.5$ mm, measured the wave height above the hydrophone. The …

Experimental Characterization Of Photonic Crystal Based Invisibility Cloak Under Tm-Polarized Microwaves, Muhammad Danyal

Dissertations, Master's Theses and Master's Reports

Electromagnetic invisibility cloaks guide waves around an object so that the transmitted wavefront remains undisturbed. Most experimental microwave cloaking studies have focused on transverse electric (TE) polarization due to established measurement techniques. In this thesis, the experimental realization and characterization of a dielectric photonic crystal cloak operating under transverse magnetic (TM) polarization are presented. A measurement system operating in the X-band was developed to map the electric field distribution of the transmitted waves. Cloaking performance was first evaluated qualitatively by comparing numerical and experimental field distributions, where restoration of a flat wavefront indicated effective cloaking. Quantitative evaluation was performed by …

Computational And Ai Frameworks For Identifying Key Regulatory Genes And Their Target Genes In Plants And Humans, Md Khairul Islam

Dissertations, Master's Theses and Master's Reports

This dissertation presents computational and AI-driven frameworks for identifying key regulatory genes and their downstream targets across plant and human biological systems. Three studies address distinct challenges in genomic regulation using advanced machine learning and bioinformatics approaches.

The first study introduces DyGAF (Dynamic Gene Attention Focus), a dual-attention transformer framework that identifies and ranks disease-relevant biomarker genes by simultaneously modeling independent molecular responses and interdependent regulatory network behavior. Two attention models provide complementary perspectives on gene importance and are fused through a novel combination metric. Applied to COVID-19 nasopharyngeal swab profiles, the attention-weighted representations achieved 94.23% classification accuracy, high sensitivity, …

Changing Snow Hydrology In The Great Lakes And Resilience Through Adaptive Management, Aradea R. Hakim

Dissertations, Master's Theses and Master's Reports

A number of studies have found that global snow cover is generally decreasing, but a closer examination at regional scales shows greater complexity. In the Great Lakes basin, contrasting trends have been identified. While snow cover is generally decreasing basinwide, leeward (downwind) regions have experienced increases in snowfall and snow cover. Changes in snow dynamics are also associated with shifts in runoff timing and volume due to earlier snowmelt and changing precipitation patterns. Streamflow analyses at gauges across the Great Lakes basin indicate trends toward earlier peak runoff and longer runoff periods, although these patterns vary among watersheds and lake …

Path-Conservative Numerical Methods For A Variable-Radius One-Dimensional Arterial-Flow Model, Daniel Henderson

Dissertations, Master's Theses and Master's Reports

This report studies a one-dimensional arterial-flow model with a variable reference radius, the two-component state $U=(a,q)^{\mathsf T}$, and diagnostic pressure. The geometry-dependent momentum term is interpreted with a declared Dal Maso--LeFloch--Murat path along a straight line. A path-conservative finite-volume method (FVM) and a complete modal discontinuous Galerkin (DG) method use the three-stage, third-order strong-stability-preserving Runge--Kutta (SSPRK) scheme SSPRK(3,3), residual-subtracted rest preservation, overintegrated nonlinear volume terms, and mean-preserving area positivity scaling. Code verification uses manufactured solutions with separate dimensionless area and flow errors, temporal refinement, represented-rest fixed-point checks, independent governing-expression evaluations, and an independently assembled DG residual. The smooth degree-three (P3) …

Application Of Reactive Power Theory To Wave Energy Converters Under Multi-Frequency Excitation: Analysis And Experimentation, Mckenna R. Collins

Dissertations, Master's Theses and Master's Reports

There is abundant energy surging in the oceans across the globe. However, there have been technological challenges in extracting that energy for use. Wave energy converter (WEC) technology is being developed to find innovative ways to convert wave kinetic energy into electricity, but there are still efficiency obstacles that inhibit large-scale use. Focusing on heave-point absorber control theory, this thesis continues the work to improve the efficiency of WECs. This is done by leveraging a superposition of linear mass-spring-damper models to analyze a WEC under multi-frequency excitation and applying proportional-derivative gains to each linear model. However, to analyze this system, …

Design And Experimental Evaluation Of A Custom Vision-Guided Approach To 2d Part Localization For Industrial Robots, Faisal Ali

Dissertations, Master's Theses and Master's Reports

Vision-guided robots offer a clear advantage over teach-pendant programming for battery handling, where modern packs hold thousands of cells and teaching each position by hand does not scale. Commercial vision systems address this need, but their calibration, detection, and coordinate-conversion stages are closed to the user, making it hard to incorporate newer learning-based methods. This work presents a modular, custom-built vision-guided system using an Orbbec Gemini 435Le eye-in-hand camera, an NVIDIA Jetson Orin Nano, an Allen-Bradley Micro850 PLC, and a FANUC LR Mate 200iC, communicating over Modbus TCP and EtherNet/IP. A per-hole classification model resolves each known hole into a …

Bayesian Analysis Of Nominal Outcomes With Missing Values Using Multinomial And Multivariate Multinomial Probit Models, Suwash Silwal

Dissertations, Master's Theses and Master's Reports

Nominal outcomes frequently arise in health sciences, transportation, economics, market research, and related fields. These data often contain missing values, while longitudinal and panel studies generate multiple correlated nominal responses. Bayesian estimation of multinomial probit (MNP) and multivariate multinomial probit (MMNP) models provides a flexible framework for analyzing such data but remains computationally challenging due to high-dimensional likelihood integration, restrictive covariance identification constraints, and poor mixing of Markov chain Monte Carlo (MCMC) algorithms, particularly in the presence of missing data. This dissertation develops parameter-expanded data augmentation (PX-DA) methods for MNP and MMNP models with missing nominal outcomes by incorporating parameter …

Beyond Receptive Measures: Development And Validation Of The Spatial Grid Drawing Assessment (Sgda) As A Productive Measure Of Spatial Skill, Katrina L. Carlson

Dissertations, Master's Theses and Master's Reports

Spatial skills are vital in many STEM disciplines, starting at or prior to university training, and often extending throughout one’s career. The most widely used spatial ability measures (e.g., PSVT: R, MRT) rely on what I refer to as receptive skills: examining an object or design, mentally transforming it, and comparing it to given alternatives. But because work in many STEM disciplines also involves productive spatial skill such as drawing, I hypothesize that a productive measure of spatial skill may predict distinct aspects of spatial ability. This research investigates the relationship between traditional receptive Spatial Visualization (SV) assessments, such as …

Applied Forest Restoration And Conservation In Michigan: Advancing American Beech Restoration And Documenting A Historical Insect Collection, Thomas E. Panella

Dissertations, Master's Theses and Master's Reports

Forest restoration and conservation require both practical management approaches and the preservation of biological resources that support future research. This dissertation presents applied research conducted in Michigan that advances American beech (Fagus grandifolia) restoration in response to beech bark disease (BBD) while documenting an important historical entomological resource. Chapters 1–3 focus on overcoming practical barriers to American beech restoration. Restoration protocols were developed and refined for identifying BBD-resistant trees, graft propagation, rootstock collection, container production, and the field establishment of grafted BBD-resistant trees. A greenhouse experiment evaluated the influence of growing media and fertilization on container stock quality, …

Novel Chiral Interstellar Molecules: Quantum Anharmonic Ir And Vcd Predictions, Meredith Paik

Dissertations, Master's Theses and Master's Reports

The 2016 discovery of the chiral molecule propylene oxide (C₃H₆O) in the interstellar medium (ISM) has opened new avenues into explaining the origin of biomolecular homochirality on Earth. Thus, studies of chiral molecules in the ISM may be able to reveal more about the mechanism behind homochirality. However, while the search for chiral molecules in space has become an active field of study, astrochemical researchers have yet to detect other chiral molecules in the ISM. For this purpose, numerous characteristics for detectability have been outlined that may facilitate the discovery of other interstellar chiral molecules. With …

First-Principles Investigation Of Quasi-One-Dimensional Van Der Waals Magnets For Advancing Low-Dimensional Spintronics, Alyssa Horne

Dissertations, Master's Theses and Master's Reports

Van der Waals (vdW) magnets have been of great interest for advancing low- dimensional spintronics. A notable example is the quasi-one-dimensional (Q1D) vdW CrSbSe₃, as it is composed of individual one-dimensional units that are held together by the vdW forces. Finding other Q1D vdW magnets that exhibit non-metallic behavior together with long range ferromagnetic ordering is critical in developing next generation spintronics. Here in, using first-principles density functional theory (DFT), we investigate the compositional effects on electronic and magnetic behavior of Cr_1–xMn_xSbSe₃ (x = 0, 0.5, 1). When 50% of Cr is replaced …

Using Automotive Lidar To Reduce The Energy Consumption Of An Ego Autonomous Vehicle, Logan P. Schexnaydre

Dissertations, Master's Theses and Master's Reports

There is significant potential to reduce the energy consumption of the transportation sector through autonomous vehicles. Prior work on autonomous vehicle energy efficiency focuses on the whole system or the control subsystem. Yet, the sensing and processing components, which have direct and indirect effects on net energy use, are less explored. This dissertation fills this gap by modeling and evaluating these effects for lidar sensors, which provide high-resolution spatial data at the cost of high power and processing demands. I apply lidar to the energy-saving tasks of automated vehicle following and road surface profiling. For automated vehicle following, I model …

Analytical And Data-Driven Modeling And Control Of Nonlinear Point Absorber Wave Energy Converters With Application To Cone–Cone Buoy Geometries, Houssein Yassin

Dissertations, Master's Theses and Master's Reports

This dissertation develops analytical modeling, numerical simulation, experimental validation, and data driven control methods for nonlinear point absorber wave energy converters, with particular emphasis on cone--cone buoy geometries. Geometry dependent nonlinear force models are first derived using pressure field and displaced volume formulations. These models show how buoy geometry produces nonlinear Froude--Krylov and restoring forces, including the dominant cubic behavior of cone--cone geometries.

The derived models are incorporated into a feedback linearization framework that compensates selected nonlinear dynamics while retaining the incident wave terms. An analytical optimal control formulation is also developed to maximize harvested energy in nonlinear, nonautonomous systems …

Slip Kinematics And Structural Analysis Of The Keweenaw Fault System From Lake Linden To Hancock, Michigan, Katherine M. Langfield

Dissertations, Master's Theses and Master's Reports

The Keweenaw fault is a crustal-scale fault spatially associated with Mesoproterozoic rocks of the Midcontinent Rift System. Along the fault, older Portage Lake Volcanics have been thrust southeastward over younger Jacobsville sandstone. Ideas on the fault’s origin, from oldest to most recent, include that it is: (1) a reverse fault, (2) a normal fault formed during midcontinent rifting that was reactivated and inverted to a reverse fault during the Grenville orogeny, and (3) a detached thrust fault system initiated during the Grenville orogeny.

This thesis is based on a U.S. Geological Survey EdMap grant to remap a portion of the …

Gender Differences In Mental Rotation And Visualisation Across Adolescence: Large Scale Evidence From The United States, Ireland, And Austria With Single-Paper Meta-Analyses, Jeffrey Buckley, Sheryl Sorby, Gavin Duffy, Günter Maresch, Jason Power

Research Outputs: 2025-Present

Spatial ability has been identified as an essential cognitive ability for educational performance broadly in science, technology, engineering, and mathematics (STEM) education. Further, children with higher levels of this ability are more likely to choose STEM educational pathways. It is theorised that a benefit of spatial ability lies in affording young people further capacity to think and reason effectively in diverse problem-solving contexts, which translates into desirable educational outcomes. However, substantial evidence has identified a gender gap favouring boys particularly in the mental rotation spatial factor, and there is less evidence for any similar gender gaps for other spatial factors, …

Real Time Waste Classification Using Deep Learning: Comparing Mobilenetv2 And Resnet 18 With Transfer Learning And Fine Tuning, Abdul Moaiz

ICT

Waste contamination is a major problem all over the world. The Environmental Protection Agency reports that over two thirds of waste found in general household and commercial bins could have been placed in the recycling or organic waste bins instead in Ireland, with food waste and plastics being the most common misplaced items. This project presents a deep learning solution to classify nine categories of waste from camera images in real time with the goal of helping users sort waste correctly at the source. Following the CRISP DM framework, two convolutional neural network architectures were trained and compared, MobilenetV2 and …

Bitcoin Prediction System Usind Machine Learning Techniques, Carolina Azevedo De Castro

ICT

This project investigated the use of machine learning techniques to predict short-term Bitcoin price direction using historical market data obtained from Yahoo Finance. Following the CRISP-DM methodology, the dataset was analysed, prepared, and transformed through feature engineering techniques including moving averages, volatility indicators, return measures and price position metrics. Multiple classification algorithms were evaluated, including Bayesian Classification, K-Nearest Neighbour, Decision Tree, Random Forest, Logistic Regression, Support Vector Machine and XGBoost. Several optimisation strategies were also tested, including feature selection, hyperparameter tuning, feature scaling and class weight balancing. Results showed that predicting short-term Bitcoin price movements remains challenging, with most models …

Predictive Maintenance For Manufacturing Equipment, Paloma De Andrade Batista

ICT

Unplanned equipment downtime is a significant challenge in manufacturing, resulting in substantial productivity losses and operational costs. Predictive maintenance, enabled by machine learning and big data analytics, offers an opportunity to identify potential equipment failures before they occur and improve maintenance efficiency. This report extends a previous capstone project that applied Random Forest and Logistic Regression to the AI4I 2020 Predictive Maintenance Dataset. The current study expands the analysis by incorporating XGBoost, systematic hyperparameter optimisation, cross-validation, and SHAP-based model interpretability. In addition, SWOT and PESTLE analyses, alongside a legal and ethical assessment, examine the broader strategic and responsible implementation of …

Predicting Loneliness Among Older Adults In Ireland Using Supervised Machine Learning, Ariadne Chaves Miranda

ICT

Over the last two decades, technology has grown exponentially and has facilitated communication that helps individuals remain connected. However, this has also contributed to social isolation and lack of physical interaction. One consequence of this phenomenon is loneliness, which is understood as an unpleasant subjective state of discrepancy between the desired amount of companionship or emotional support and what is available in the person’s environment (Prohaska and Burholt, 2020). In the European context, Ireland has emerged as the loneliest country in Europe with 20% of its population that have reported feeling lonely most or all the time (Schnepf et al., …

Southern Adventist University Annual Report 2025-2026, Southern Adventist University

Annual Reports

The Annual Report for Southern Adventist University for 2025 to 2026.

High Temperature Creep Deformation Mechanism Of Fe28.2ni18.8mn32.9al14.1cr6 High Entropy Alloy And Its Modified Alloys, Edwin S. Jiang, I. Baker

Dartmouth College Ph.D Dissertations

Fe28.2Ni18.8Mn32.9Al14.1Cr6 eutectic high entropy alloy exhibits a good combination of room-temperature and high temperature properties, including tensile strength, ductility, and corrosion resistance, making it a promising candidate for structural applications in extreme environments. However, the creep deformation behavior of this alloy— and high-entropy alloys (HEAs) in general—remains insufficiently understood. This dissertation systematically investigates the high-temperature creep deformation mechanisms of Fe28.2Ni18.8Mn32.9Al14.1Cr6 and its derivatives.

Creep mechanisms and associated microstructural changes were examined across a wide range of strain rates using strain-rate jump and constant-stress tests. Two dominant regimes were identified: dislocation glide/solute-drag at low strain rates, and dislocation climb at high …

Active Galactic Nuclei Across Scales: From Blazar Jets To Dark Matter Halos, Stephanie Ann Podjed

Dartmouth College Ph.D Dissertations

Within ΛCDM, galaxies form and evolve within dark matter halos, with both central and satellite galaxies contributing to the total stellar mass content. Virtually every massive galaxy harbors a supermassive black hole (SMBH) at its center, with a small fraction of the population growing by actively accreting material; we call this an active galactic nucleus (AGN). The processes giving rise to an AGN phase (i.e., growth of a SMBH) releases enormous amounts of energy in the form of radiation, outflows, and relativistic jets that are able to significantly affect the formation and evolution of galaxies. Blazars are an extreme class …

Early-Time/High-Frequency Electromagnetic Induction Sensing For Minimal-Metal And None-Metallic Subsurface Targets, Michele Louise Maxson

Dartmouth College Ph.D Dissertations

Conventional electromagnetic induction (EMI) systems operate within the quasi-static regime, where measurements are dominated by conduction currents and are primarily sensitive to highly conductive targets and bulk soil properties. As a result, these systems exhibit limited sensitivity to low-conductivity and layered media, such as permafrost, composite materials, and minimum-metal landmines, where diagnostically relevant information resides in early-time/high-frequency electromagnetic responses, generally above 100 kHz. This limitation reflects a mismatch between conventional EMI system design and the underlying target physics, restricting the ability of standard EMI approaches to resolve fine-scale non-metallic subsurface structure.

In this thesis, I investigate early-time/high-frequency sensitivity as a …

Designing Narrative-Based Ai Assistance For Sensemaking In Collaborative Environments: Case Studies In Education And Dementia Care, Dylan Edward Moore

Dartmouth College Ph.D Dissertations

This thesis addresses a gap in the human-computer interaction literature regarding the design, development, and evaluation of narrative-based AI assistance for collaborative, complex problem solving. I explore this design space through three case studies across the domains of education and dementia care. This work encompasses multi-year industry partnerships and longitudinal fieldwork, user-centered design, dataset curation, model training, and system evaluation.

Specifically, the first case study considers a story-based web platform for teaching AI literacy through peer-generated, personalized narrative scaffolding. Learners on the platform showed significant knowledge gains and other learning-related outcomes. To describe the novel design of this system, I …