Digital Commons Network^™

Exploring The Feasibility Of Innovative Integration Of Phase Change Materials For Thermo-Adaptive Asphalt Pavements, Farshad Saberi Kerahroudi

Doctoral Dissertations

"Current research examined the feasibility and efficiency of employing phase change materials (PCMs) in asphalt pavement materials to result in thermo-adaptive asphalt pavement. The PCM was introduced to the asphalt materials in three different scales, including asphalt binder, asphalt mastic, and asphalt mixture. After investigating asphalt at different scales, mix blending method was found as the easiest method without any complexity to mix asphalt binder with PCM. The testing results could reveal an improvement in the high temperature performance of asphalt binder without sacrificing the low temperature performance with the presence of PCM and Gilsonite. Also, introducing PCM to asphalt …

Investigation Of The Transport And Plugging Behavior Of Preformed Particle Gels (Ppgs) In Fractures For Conformance Control In Carbonate Reservoirs, Abdulaziz A. Almakimi

Doctoral Dissertations

This study aims to systematically evaluate the performance of preformed particle gels (PPGs) in fractured carbonates mainly through a series of core flooding experiments. Carbonate reservoirs exhibit unique features of heterogeneity and pore geometry, while (PPGs) are known for their plugging efficiency, deformability, and dehydratable nature. The main goal of gel injection in fractured reservoirs is to place a gel pack appropriately into the fracture, diverting injected fluid to the oil-bearing matrix and reducing excessive water production. However, considerable dehydration of (PPGs) is possible at the adjacent matrix and within the fracture, which could lead to a filter-cake formation and/or …

Nano-Micro Engineering For Advanced Energy Devices, Tazdik Patwary Plateau

Doctoral Dissertations

The development of advanced materials and manufacturing techniques for energy storage devices is continuously growing. The research emphasizes micro-engineering, nano-engineering, and advanced materials science, with the goal of enhancing the performance and scalability of manufacturing methods of different materials processing with a view of achieving sustainability. In the micro-engineering domain, novel methods for fabricating thick electrodes with short diffusion paths are introduced, enabling higher mass loading and improved battery performance. Additionally, innovative strategies for optimizing the performance of carbon nanofibers (CNFs) as anode materials in LIBs are explored in the nano-engineering domain. These studies address key challenges such as inter-bonding …

Mindfulness Matters: Addressing Anxiety And Navigating Toward Wellbeing Through Miea Mindfulness Practices, A Mixed-Methods Study Of Lgbtiq Graduate Writing Students, Kim Westerman

Doctoral Dissertations

ABSTRACT

Mindfulness Matters: Addressing Anxiety and Navigating Toward Wellbeing Through MIEA Mindfulness Practices, a Mixed-Methods Study of LGBTIQ Graduate Writing Students

Anxiety has always been a part of the human experience, even before the phenomenon was conceptualized in the 17^th century and named by Freud in the 19th. And human beings have devised many strategies for addressing anxiety: reducing it, ignoring it, distracting oneself from it, despairing over it, medicating it, engaging with it, moving through it, co-existing with it. The current zeitgeist, more than four years into the COVID-19 global pandemic, situates anxiety as a central facet of …

A Physics-Based Material Model Incorporating Strain Gradient Plasticity Formulations In A Mean-Field Framework To Predict Spatial Fluctuation Of Material Properties, Zhangxi Feng

Doctoral Dissertations

With the market expansions and increasing number of scientific explorations, the demands for manufacturing metallic parts to satisfy specific requirements continue to increase. A slight improvement in the manufacturing process can result in great cost savings in time and energy. The research and development time to identify these areas of improvements can be greatly reduced using numerical models. One such model is the mean-field elastoplastic self-consistent (EPSC) framework studied extensively and advanced in this dissertation. In the past two decades, many material behavior formulations were implemented in EPSC, and the model has shown versatility and accuracy in predicting a wide …

“Why You Understand The Why”: A Qualitative Characterization Of The Metacognitive Competence Of Introductory Stem Peer Coaches, Jonathan Kustina

Doctoral Dissertations

The processes of metacognition are vital for students’ development of critical thinking skills and productive learning mindsets, yet many students never receive the direct instruction that would allow them to formally develop their metacognition. As instructors are typically not providing this instruction, there may be an alternate source to facilitate the learning of metacognition to students. This research study will investigate the viability of having peer coaches, undergraduate peer educators who help facilitate learning and problem solving in introductory STEM courses, facilitate metacognition to their students. Specifically, this research study aims to understand and characterize the metacognitive competence of the …

Engineer-Friendly Synergetic Methodology For Surrogate Modeling Of Complex Connections By Modal-Based Low-Fidelity Finite Element Model Updating Approach, Milad Mehrkash

Doctoral Dissertations

Finite element models are widely used to simulate the behavior of structures. They can also be utilized for structural condition assessment and health monitoring. However, due to software limitations, simplifying assumptions, and lack of knowledge about the system properties, the predictions of the numerical models may deviate from laboratory or field measurements of the actual structure. This issue may be further exacerbated by the simplifications applied in modeling complex connections, which is a common practice in numerical modeling to save time and effort. While finite element model updating improves the accuracy of numerical models, physics-based surrogate modeling of connections balances …

Artificial Intelligence Driven Magnetic Materials Discovery: From Data Extraction To Property Prediction, Yibo Zhang

Doctoral Dissertations

This dissertation presents an integrated artificial intelligence framework aimed at accelerating magnetic materials discovery by addressing key challenges in materials science: improving experimental characterization techniques, efficiently extracting structured data from scientific literature, developing comprehensive materials databases, and creating reliable predictive models.

We first develop a UNet-enhanced vector field electron tomography (VFET) approach for three-dimensional magnetic structure reconstruction. This method addresses the missing wedge problem in experimental data collection while maintaining computational efficiency, providing reliable experimental data crucial for materials research.

We introduce GPTArticleExtractor, a novel workflow leveraging large language models to automatically extract key information from scientific literature. Applied to …

Improving Understanding Of Fluvial Reach-Scale Solute Transport And Uptake Using A Particle Tracking Model And Random Forest Machine Learning Model, Jiaying Liu

Doctoral Dissertations

In addition to transporting flowing water, river systems carry dissolved nutrients and pollutants, which can experience chemical reactions, biological uptake, or retention in surface or hyporheic zones. This dissertation enhances our understanding of solute transport and uptake in river reaches through three main components. The first component involves the development of a novel curve-fitting model designed to capture the characteristics of pulse-release breakthrough curves (BTCs) from tracer studies with conservative solutes. The model, which was found to be applicable to a wide range of field studies, enables the rapid comparison of transport parameters among diverse field studies obtained under a …

Deformation-Induced Bonding Of Glassy Polymeric Films And The Diluent Effect, Ajay Vallabh

Doctoral Dissertations

Bonding between two polymer films can be achieved through various heat- or chemical-based methods. Recently, our group has discovered the novel phenomenon of deformation-induced bonding (DIB) for solid-state glassy polymers in time on the scale of a fraction of a second at ambient temperatures substantially below the bulk glass transition temperatures (T_g). DIB is achieved by bulk plastic compression, which triggers the molecular mobility of polymer chains to cause interpenetration across the interface even in a glassy regime.

First, we performed a series of experiments to evaluate solid-state, deformation-induced bonding in organic polymer blends composed of films of hydroxypropyl methylcellulose …

Simulations, Modeling And Data Analysis Of Parity Violating Electron Scattering Experiments, Yufan Chen

Doctoral Dissertations

In the Standard Model (SM) of nuclear and particle physics, parity violation is incorporated through the representation of the weak interaction as a chiral gauge interaction. Only the left-handed components of particles and right-handed components of antiparticles participate in weak interactions in the Standard Model. This implies that parity is asymmetric for the weak interaction. Parity violating electron scattering (PVES) experiments are designed to probe the physics parameters related to the SM, with the possibility to discover physics beyond the SM (BSM) by measuring the parity violating asymmetry 𝐴𝑃𝑉 of longitudinally polarized electrons scattered off unpolarized targets with high precision. …

Float: A Multi-Scale Flood Loss Assessment Tool Developed From Experimentally Derived Material Damage, Anna Katya Opel

Doctoral Dissertations

Current practice of flood loss prediction presents limitations in accurately predicting building flood losses at multiple scales. While whole-building estimates can more accurately predict high-level losses (i.e., large groups of buildings), a significant analysis error is revealed with small-scale (i.e., individual, or small groups of buildings) investigation. The novel approach of collecting experimental flood data to support damage estimation has provided sufficient evidence that current damage models can and do under or overestimate loss. This research has developed a multi-scale approach to assessing flood losses based on experimentally derived material damage. The methodology is stored and accessible in a multi-scale …

Measurement Of Multi-Jet Ratios In The Atlas Experiment, Zahra Farazpay

Doctoral Dissertations

This dissertation presents a comprehensive study of multi-jet cross-section ratios using proton-proton collision data collected by the ATLAS detector during Run 2 of the Large Hadron Collider (LHC) at a center-of-mass energy of √ s = 13TeV. By examining these ratios across different energy scales, the analysis provides valuable insights into the running of the strong coupling constant, αs, a fundamental parameter in Quantum Chromodynamics (QCD) that dictates the strength of the strong interaction. The running of αs—its variation with energy—is crucial for understanding QCD, yet it remains one of the least precisely known aspects of the theory. In this …

Computational Design Of Complex Concentrated Alloys, Hamid Sharifi

Doctoral Dissertations

A high-throughput parameterization of modified embedded atom model (MEAM) interatomic potentials for combinations of Cu, Ti, Ni, Cr, Co, Al, Fe, and Mn was carried out using a genetic algorithm. Unary systems were parameterized based on DFT calculations and experimental results. MEAM potentials for 28 binary and 56 ternary combinations of the elements were parameterized to DFT results that were carried out with semi-automated frameworks. Specific attention was made to reproduce properties that impact compositional segregation, material strength, and mechanics. Utilizing the MEAM interatomic potentials and a Monte Carlo scheme, phase segregation in the CrNiCo, CuNiCr and CuNiCo fcc alloys …

Effectiveness Of Virtual Reality Training Environments, Lindsay Kristina Gouedy

Doctoral Dissertations

As technology has evolved so has training methodology in many applied fields. Training of aviation professionals is adapting by including technology features that allow for safer and less costly training methods. Pilot training is expensive given the number of flight hours and all that is included in the cost of flying an airplane. The main goal of this project is to assess the efficacy of the use of virtual reality environments as a valid training tool. Based on our literature review, we hypothesized that trainees perform simulated flight tasks more efficiently, with fewer errors, when trained using VR technology. The …

Land Conservation Planning For Flood Resilience In New Hampshire's Coastal Watershed, Michal Zahorik

Doctoral Dissertations

Land conservation plays an important role in managing flood risk. It enhances community resilience and supports multiple ecosystem functions. This qualitative study investigates how local and regional land conservation strategies advance flood resilience in New Hampshire’s coastal watershed. Focusing on the institutional context, this thesis analyzes the effectiveness of local land conservation planning efforts, explores cross-scale interactions between local and regional planning, and identifies barriers and opportunities for flood-focused conservation projects. The data for this research were collected through semi-structured interviews with representatives of municipalities, public and private conservation organizations, regional planning commissions, partnership organizations, and landowners. The secondary data …

Neural Retrieval Through Entities And Text Understanding, Pooja Himanshu Oza

Doctoral Dissertations

For various artificial intelligence systems, automatic text understanding algorithms that go beyond mere pattern recognition are helpful. For instance, understanding web pages is beneficial for Information Retrieval (IR) systems to retrieve relevant information. In the most common form, IR systems retrieve relevant information as entities or documents in response to keywords-based queries. Traditional IR models use lexical matching between the query terms and document terms to identify relevant documents. With the emergence of neural networks, Neural IR approaches utilize deep learning techniques to learn high-dimensional representations of documents and queries that go beyond term matching.

On the other hand, with …

Development Of A Layered Unsupervised Classifier Of Plasma Regions And A Bootstrap-Ensemble Neural Network Bow Shock Mode, James Andrew Edmond

Doctoral Dissertations

The use of supervised methods in space science have demonstrated powerful capability in classification tasks, but purely unsupervised methods have been less utilized for the classification of spacecraft observations. We use a combination of unsupervised methods, being principal component analysis, self-organizing maps, and hierarchical agglomerative clustering, to classify THEMIS and MMS observations as having occurred in the magnetosphere, magnetosheath, or the solar wind. The resulting classification are validated visually by analyzing the distribution of classifications and studying individual time series as well as by comparison to the labeled dataset of a previous model, against which ours has an accuracy of …

Evaluation Of Rockfall Trajectories Using Smart Rocks And Measurement While Drilling, Bruma Morganna Mendonca De Souza

Doctoral Dissertations

This doctoral research investigates rockfall movement under laboratory and field-controlled conditions as well as in situ natural field environments in an effort to better understand the movement described by falling blocks. Although previously published research identified several factors that affect rockfall movement (block characteristics, ground characteristics, and impact kinematics), the lack of a standardized methodology to evaluate rockfall behavior upon impact on different ground materials increases the difficulty of establishing realistic parameters in modeling approaches and ultimately in selecting representative model input parameters. In order to measure rockfall movement under different test conditions, concrete fabricated test blocks ranging in mass …

Sustainable Energy Transition In Grid Connected And Off-Grid Communities, Roozbeh Ghasemi

Doctoral Dissertations

Decentralized energy systems, such as solar PV and wind, are often seen as key to improving the sustainability and resilience of energy systems in both urban and remote communities. This research aims to enhance the sustainability of adopting these systems in both grid-connected and off-grid contexts. In urban communities, a choice experiment model was developed for Boston, MA, and Atlanta, GA, and the results were analyzed using latent class analysis to understand household preferences for two decentralized renewable energy systems. For islanded communities, a process-based dynamic model was developed to simulate the operation of the decentralized energy system on Appledore …

Innovative Approaches To Dna-Based Materials: Development Of Bottlebrush Polymers, Supramolecular Hydrogels, And Psoralen-Enhanced 3d Printing Of Dna Bioinks, Nicholas Pierini

Doctoral Dissertations

This thesis explores innovative approaches to enhancing the functionality and applications of DNA-based materials through the development of DNA bottlebrush polymers (BBPs), DNA-intercalating supramolecular hydrogels (DISHs), and psoralen-based 3D printing techniques. The first chapter presents the synthesis and characterization of linear and cyclic DNA BBPs using a grafting-to approach. Plasmid DNA (pDNA) is used as the polymeric backbone, grafted with polyethylene glycol (PEG) side chains of varying molecular weights (750 Da, 2000 Da, and 5000 Da) to improve stability and functionality. Achieving high graft densities, up to 24% for mPEG750-CEA, and purifying the PEG-DNA conjugates were significant challenges addressed through …

Oscillatory Boundary Layer And Sediment Dynamics Over And Within Mobile Rippled Beds, Savannah Devoe

Doctoral Dissertations

In nearshore environments, small-scale bedforms, or ripples, are important contributors to net morphologic change by means of bedload and suspended load sediment transport. In this dissertation, new characterizations of boundary layer and sediment dynamics are made using high-resolution observations of mobile, rippled beds subjected to oscillatory flow for the purpose of evaluating existing parameterizations of bedload transport. The spatiotemporal distribution of shear stress at and within a mobile, rippled bed is obtained via the derivation and application of a new Momentum Integral Method (“MIM”) expression for bed shear stress to data from a two-phase Large Eddy Simulation and Discrete Particle …

Advancing Electrochemical Microsensors For Multiplexed Neurotransmitters And Environmental Toxins Detection, Sanjeev Billa

Doctoral Dissertations

Electrochemical sensors have emerged as a promising solution for monitoring neurotransmitters and heavy metals, which could ensure good health and safety in the environment. This dissertation focuses on advancement in the field of electrochemical microsensors by improving the electrode properties and sensor metrics such as rapid response time, multiplexing, high sensitivity, high selectivity, and accuracy for the real-time monitoring of neurotransmitters (glutamate and GABA) and heavy metals (cadmium and lead). In this dissertation, a novel silicon (Si) multifunctional biosensor probe with four platinum ultramicroelectrodes (UMEs) and an on-demand in situ calibration (ODIC) microfluidic channel was optimized for sub-second simultaneous real-time …

Micropatterning Of Biologically Derived Surfaces With Functional Clay Nanotubes, Nisha Lama

Doctoral Dissertations

In this study, we have generalized an assembly of 50 nm diameter clay nanotubes on larger 20-50 μm diameter biological microfibers such as human hair (protein), cotton (cellulose) and synthetic polyethylene terephthalate- PET. We developed a common set of parameters and nanoclay coating techniques on these naturally different microfibers. We exploited and optimized the electrostatic interaction of the components through strategic adjustments in the solvent pH, employing polycation treatment, as well as selectively modifying the halloysite nanotubes with silanes. For 5 mins, a 5 wt% aqueous dispersion of halloysite nanotubes were applied to get approximately 1-2 μm thick fiber coating …

Women Strength: Using Photovoice To Explore Female Chinese International Students’ Experiences, Yue Cai

Doctoral Dissertations

Female Chinese international students face discrimination and stereotypes in Western academia based on race and gender, yet they possess unique “Women Strength” characterized by agency, resilience, and self-advocacy. This study explores how these students navigate cultural differences and develop their strengths while studying in the U.S. Drawing upon “Women Strength” as a theoretical framework, including Community Cultural Wealth, Critical Feminist Theory- Chinese feminism, decolonial feminism, and transnational feminism, transformative agency, resilience theory, and self-advocacy theory, this research employs a qualitative approach, including Photovoice and autoethnography. Three research questions guide the study: 1) What cultural differences do female Chinese international students …

Impact Of Student Beliefs And Self-Efficacy On Performance In Higher Education Stem Courses, Lauren Nicole Fogg

Doctoral Dissertations

In engineering education, students often face feelings of inadequacy, leading to academic struggles and potential dropout. This dissertation investigates the impact of interactive course materials on students' confidence and self-efficacy in problem-solving, focusing on an Engineering Materials class at Louisiana Tech University. Over four quarters, involving seven sections and 218 students, a 13-question Likert scale survey was administered repeatedly, alongside demographic data and textbook usage surveys. The study aims to compare students’ attitudes and beliefs when not using a textbook versus when using an interactive web-native book. Hypotheses suggest that the interactive book will enhance problem-solving beliefs, confidence, and grades. …

Phase Interface Dynamics And Heat Transfer Mechanisms In Evaporating Droplet And Pool Boiling Processes, Md Tanbin Hasan Mondal

Doctoral Dissertations

Despite the significant importance and widespread use of phase-change cooling techniques, there are still fundamental questions about the microscopic processes that govern the heat transfer mechanisms. In order to gain a better understanding of the underlying physics involved, it is essential to have information at the microscale regarding the surface temperature distribution with time as well as the location and speed of the moving contact line (MCL). A comprehensive understanding of heat transfer mechanisms and phase-interface behavior during phase-change cooling is crucial for improving heat transfer models, optimizing surface engineering, and maximizing overall effectiveness. Firstly, this dissertation presents a capacitance-based …

The Effects Of Online Mind Mapping On The Cognitive Outcomes Of Students And Their Perceptions In The Collaborative Prewriting Stage, Yen Thanh Hai Duong

Doctoral Dissertations

In language acquisition, writing is the most challenging skill that English learners must master. Students often struggle at the beginning of their writing process with idea generation. Due to students’ low academic achievement and their struggles, online mind mapping is suggested as a useful tool to support language students’ brainstorms and idea organization during the writing process. The purpose of this mixed-method study was to investigate how online mind mapping can help students collaboratively brainstorm and organize their ideas during the prewriting process. This study focused on the effects of online mind-mapping intervention on student academic writing performance and perceptions …

The Effectiveness Of Mind Maps As An Instructional Approach For Developing Critical-Thinking Skills And Dispositions: A Meta-Analysis, Carmen De Jesus

Doctoral Dissertations

Mind mapping is the most flexible visual learning and active instructional approach. It has many applications, such as brainstorming, taking notes, memorizing, and conceptualizing complex topics using associations between images and keywords, colors, and visuospatial characteristics. Students can elaborate mind maps individually and collaboratively, digitally or nondigitally. Teachers can also elaborate mind maps for studying purposes. This meta-analysis aims to investigate the effectiveness of mind mapping as an instructional approach for developing critical-thinking skills and dispositions. With 22 studies (20 of which are international) and 1,535 participants, all employing a quasi- experimental study design, this meta-analysis is a comprehensive exploration. …

Emergence: Social Movements, Law Enforcement, And Defending The Sanctity Of Life, Diana Elizabeth Aroche

Doctoral Dissertations

This study examines the aftermath of national social movements advocating for police reforms and accountability, with San Francisco emerging as a pivotal city at the forefront of criminal justice and policing transformations. Rebuilding community trust and implementing substantive police reforms aimed at preserving lives has proven to be a formidable challenge. The convergence of interests among all stakeholders, driven by a shared commitment to dismantling institutional racism and implementing reforms that fostered trust with communities of color and law enforcement, played a pivotal role.

A significant aspect of this reform process has been the development of social movement convergence, where …