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DESIGN AND CONTROL OF REVERSIBLE ADHESION: SWITCHABLE ADHESIVE MOLECULES AND ELECTROCHEMICAL APPROACHES
No full textSmart adhesives are materials that can reversibly gain or lose adhesion in response to external stimuli such as temperature, pH, electric fields, or light. Their switchable and temporary adhesion makes them highly promising for applications in wound healing, manufacturing, and robotic locomotion. Among them, catechol-based polymers have been widely studied for pH- and electro-responsive adhesion, due to their reversible non-covalent crosslinking. However, their performance is limited by irreversible covalent crosslinking reactions and the need for conductive surfaces in electrochemical systems. While boronic acid has been used to protect catechol, its reversibility remains limited. Therefore, new adhesive molecules and system designs are needed to achieve robust, reversible adhesion under broader conditions. This dissertation focuses on developing novel adhesive molecules and electrochemical strategies to overcome these limitations.
Project 1 introduces salicylhydroxamic acid (SHAM) as a new pH-responsive adhesive molecule. SHAM contains phenol and hydroxyl groups, allowing for π–π interactions and hydrogen bonding similar to catechol. Unlike catechol, SHAM avoids irreversible crosslinking and exhibits reversible pH sensitivity. Its work of adhesion decreased by nearly 98% at high pH and fully recovered at pH 5, demonstrating potential for simplified and reversible adhesive systems.
Project 2 explores electrochemical control of SHAM-based adhesion. Since electro-deactivation of catechol involves local pH increase near the cathode, SHAM can similarly lose adhesion via deprotonation. A 1 V charge applied for 30 seconds reduced adhesion by ~84%, which was fully restored after pH 5 treatment. This strategy achieved reversible adhesion without the need for boronic acid protection.
Project 3 addresses the challenge of requiring conductive contact surfaces. By using imidazole-TFSI modified catechol on graphene interdigitated electrodes (IDEs), current was confined within the device. Applying –3 V for 2 minutes decreased adhesion by ~81%, which was fully restored by +3 V for 2 minutes. The imidazole–TFSI coating also enhanced impedance control and protected catechol from irreversible oxidation.
In conclusion, this dissertation establishes novel strategies for designing smart adhesive systems. These findings contribute to the development of tunable, reversible adhesive systems and broaden their potential applications
GEOSPATIAL ANALYSIS FOR URBAN RESILIENCE: GREEN SPACE, FLOOD SUSCEPTIBILITY, AND WETLAND RESTORATION POTENTIAL
No full textThrough the integration of high-resolution geospatial data, hydrologic modeling, and spatial statistics, this research addresses three interrelated topics that are critical to sustainable, equitable, and climate-resilient urban planning. The overall objective of this dissertation is to provide data-driven and machine learning-based geospatial analysis frameworks that enhance our understanding of environmental inequities, flood exposure, and the potential for wetland restoration, with a focus on urban contexts. The study presented in Chapter Two examines the distribution and accessibility of urban green spaces in Detroit, Michigan, using high-resolution geospatial data and geospatial analysis methods, including geographically weighted regression (GWR) and network-based analyses. This study correlates urban green space access inequities with social justice indicators and offers strategies for urban planners to address these inequities. The case study finds that 87% (53%) of buildings lack a park or recreation area within a quarter-mile (half-mile) walking distance, and neighborhoods with higher social vulnerability scores tend to have significantly lower green space availability.
The study presented in Chapter Three assesses urban flood susceptibility using machine learning models to evaluate the influence of topography, land cover, and infrastructure on flood susceptibility in urban environments. Random Forest (RF) and Extreme Gradient Boosting (EGB) models are trained using high-resolution spatial predictors and validated against both FEMA flood insurance claims and Detroit open data flood complaints. The RF method achieves accuracies of 81% and 82% for the flood complaint and FEMA datasets, respectively, and the EGB model achieves accuracies of 57% and 69%. Variable importance analysis reveals that infrastructure-related layers are the most influential in predicting flood complaints, whereas terrain-based variables are dominant in the FEMA model. Additionally, this study reveals significant differences in how flood impacts are distributed in relation to socioeconomic vulnerability.
In Chapter Four, a spatial framework is developed and implemented to identify high-priority wetland restoration sites based on terrain, land cover, and hydrologic potential. A methodology that integrates high-resolution remote sensing data with stochastic depression analysis is used to map potential wetland restoration sites, and the water storage capacity of the identified depressions was quantified. This analysis also incorporates impervious surface and land cover masking, as well as proximity to infrastructure to filter out locations where wetland construction would be infeasible, providing a refined set of viable potential wetland restoration sites.
Collectively, this research contributes to the field of civil, environmental, and geospatial engineering by integrating high-resolution spatial data with machine learning and hydrologic modeling to provide frameworks that can be utilized by urban planners and decision-makers. The spatial frameworks developed through this research provide scalable models that can be adapted for use in other regions facing similar challenges, including infrastructure stress, climate impacts, and environmental inequities. By linking physical and social dimensions of urban systems, this dissertation advances data-driven approaches for building more resilient, sustainable, and equitable urban environments
From Riches to Ruin: An Exploration of the Conglomerate Mining Company\u27s Compressor House
No full textThis archaeological investigation revealed new insights about the story of the Lake District Copper Mining Industry through the Conglomerate Mining Company’s compressor house building. This structure once housed the air compressor powering the mine’s rock drills. Combining archaeological and historical data, this research is one of the first investigations into a compressor house at a mine location. Excavations were undertaken in order to investigate the physical structure and remains of the building. This thesis integrates fieldwork and historical data to understand the changes to the social and working landscape of the Keweenaw, such as the change in ethnic groups, and to set up investigations of technological failure. The compressor house was the catalyst for the decline of the prestige for the Cornish population and is an opportunity for understanding failure as a multifaceted challenge in the Keweenaw mining district
Quantum van der Waals Materials: Synthesis, Characterization, and Applications
No full textVan der Waals nanomaterials refer to a class of materials and assemblies of materials
where individual atomic layers are held in place by weak van der Waals forces. In
this work, we examine two types of quantum van der Waals materials: molybdenum
disulfide quantum dots and a novel, tunable, organic quantum dot, and we explore the
potential applications for them both. For the molybdenum disulfide quantum dots,
we report a solar cell using sustainable thin films and our quantum dots with a power
conversion efficiency greater than 5%. For our novel quantum dot, we explore factors
of synthesis, propose a fluorescence mechanism involving strong hydrogen bonding,
and explore biomedical applications via internal functionalization of boron nitride
nanotubes with our new quantum dot
Performance Properties of Treated Jute Fabric Laminated by Electrospun Recycled PET Nanofibers
No full textTransforming from plastic to environmentally friendly materials is essential for both human health and the protection of the environment. In this work, a modified jute fabric (MJF) laminated with electrospun recycled polyethylene terephthalate (rPET) nanofibers with silver nitrate (AgNO3) is presented. The purpose to apply the silver nitrate and rPET nanofiber mat is to enhance the performance properties of packaging materials like mechanical strength, thermal insulation, moisture resistance, and antibacterial properties. The jute fabric was pretreated with alkali to make it compatible with rPET electrospun nanofibers, which improved breathability with a diameter of 24.70 ± 7.79 nm and an average area percentage of fiber-to-fiber gap 17.50%. According to mechanical testing, the final product, MJF with nanofiber coating of rPET (MJNF) sample, satisfied the properties of packaging materials with a breaking force of 15,566 N and an extension of 10.79% at break. Strong thermal stability was indicated by thermal testing, which revealed a radiant heat difference of 26.75°C and thermal conductivity of 0.0607 W m−1·K−1. Excellent water resistance, a crucial characteristic for food preservation, was revealed by moisture management testing. Food safety was improved by antibacterial testing, which showed inhibition zones of 20.2 mm and 18.4 mm against S. aureus and E. coli, respectively. rPET nanofibers were successfully incorporated, as confirmed by fourier-transform infrared spectroscopy (FTIR), and a homogeneous nanofiber network on the jute surface was shown by scanning electron microscopy (SEM). According to these findings, MJNF have promise for environmentally friendly packaging since they successfully solve environmental issues by utilizing both recycled materials and improved antibacterial properties
The Pierre Auger Observatory open data
No full textThe Pierre Auger Collaboration has embraced the concept of open access to their research data since its foundation, with the aim of giving access to the widest possible community. A gradual process of release began as early as 2007 when 1% of the cosmic-ray data was made public, along with 100% of the space-weather information. In February 2021, a portal was released containing 10% of cosmic-ray data collected by the Pierre Auger Observatory from 2004 to 2018, during the first phase of operation of the Observatory. The Open Data Portal includes detailed documentation about the detection and reconstruction procedures, analysis codes that can be easily used and modified and, additionally, visualization tools. Since then, the Portal has been updated and extended. In 2023, a catalog of the highest-energy cosmic-ray events examined in depth has been included. A specific section dedicated to educational use has been developed with the expectation that these data will be explored by a wide and diverse community, including professional and citizen scientists, and used for educational and outreach initiatives. This paper describes the context, the spirit, and the technical implementation of the release of data by the largest cosmic-ray detector ever built and anticipates its future developments
Examining Student and Faculty Perspectives on Hidden Curriculum in Computing Education
No full textHidden curriculum (HC) consists of the assumed behaviors, cultural norms, and collective knowledge that students are expected to know, but never taught. Knowledge such as version control tools, interview and resume skills, and self-regulation can fall into the HC. HC exists in a specific institutional and individual context and can change over time, making it hard to address and examine.
My thesis work is situated around uncovering and addressing HC in computing education. In this thesis I will present relevant background about HC and computing related HC, present my previous work on the College of Computing Resource Hub and the analysis of usage data from its first semester of deployment, and the methods, results, and discussion of a new study that seeks to examine the perspectives of faculty, peer mentors, and students on HC in computing at Michigan Technological University.
The study uses survey methods to collect a view of possible HC at Michigan Technological University\u27s Computer Science Department using literature as a basis. The study then uses semi-structured interviews to deeply examine the specifics of observations and experiences of HC. The interviews and surveys include all three perspectives: student, faculty, and mentor. The surveys and interview are examined to generate possible future angles for research and serve as a pilot study for my dissertation work
Accidents analysis of mining industry through semantic text representation and dimensionality reduction: An integrated clustering framework
No full textDespite significant improvements in worker health and safety in recent decades, the mining industry still experiences fatal and non-fatal accidents. This underscores the critical need for a more nuanced understanding of accident causation patterns through accident data analysis. While conventional analytical approaches have yielded valuable insights, the extensive information embedded within text-based accident narratives remains underutilized. To address this gap, this study presents an artificial intelligence (AI)-based framework that integrates transformer-based natural language processing, nonlinear dimensionality reduction, and unsupervised machine learning to analyze and cluster accident narratives from the U.S. mining industry. Specifically, this study uses Sentence-BERT (SBERT), a sentence embedding model based on Bidirectional Encoder Representations from Transformers (BERT), to extract the high-dimensional semantical representation of accident narratives. These embeddings are then mapped to a low-dimensional space using the Uniform Manifold Approximation and Projection (UMAP) technique, followed by clustering with the k-means algorithm and subsequent hazard-focused cluster analysis. The primary contribution to AI lies in demonstrating the effectiveness of combining modern sentence embedding techniques with dimensionality reduction and clustering for the semantic analysis of safety-related narratives. From an engineering standpoint, this framework enables the identification of latent accident patterns that can inform hazard detection and guide safety interventions in the mining industry. The resulting clusters reveal diverse accident patterns across mining operations. In clusters associated with underground mining, a high proportion of incidents (ranging from 84 to 98 %) involved no equipment, with distinct injury patterns: torso injuries (67 %) from over-exertion, lower extremity injuries (58 %) from slips/falls, and upper extremity injuries from over-exertion (95 %) and material handling (85 %). Equipment-related clusters revealed strong associations with drilling tools (92 %), loaders (98 %), and bolting equipment (96 %). Clusters associated with strip/quarry/open pit operations exhibited a high frequency of vehicle-related accidents (98 % transportation, 99 % loaders), often resulting in multiple body part injuries. Milling operation clusters show 52–97 % no-equipment accidents, with injury patterns similar to those in underground mining. Additionally, noise-induced hearing loss (96–97 %) was observed in clusters spanning all mining operation types. These findings offer actionable insights for safety professionals and support data-driven, targeted interventions in the mining industry
A Comprehensive Framework for Assessing Terrestrial Analogue Field Sites for Ocean Worlds
No full textField studies at terrestrial analogue sites represent an important contribution to the science of ocean worlds. The value of the science and technology investigations conducted at field analogue sites depends on the relevance of the analogue environment to the target ocean world. We accept that there are no perfect analogues for many of the unique environments represented by ocean worlds but suggest that a one-to-one matching of environmental characteristics and conditions is not crucial to the success or impact of the work. Instead, we must determine which processes and parameters are required to map directly to the target ocean world environment with high fidelity to address the science question. In this review paper, we discuss the outcomes of a workshop aimed at developing a new framework for evaluating the suitability of analogue field locations for ocean worlds research. Here we present a two-step approach to (a) identify the most crucial processes and parameters associated with a given science question and (b) assess the fidelity of these processes and parameters at a proposed field site to those expected for the target ocean world. We demonstrate this approach in a test case evaluating three types of ocean world analogue environments with respect to a science question. The consensus document presented here equips veteran and new investigators with valuable tools to better assess and justify their analogue site selections
Polarization purity and cross-channel intensity correlations
No full textWe consider the question of monitoring polarization purity, that is, measuring deviations from orthogonality δτ and δε of an ostensibly orthogonal polarization basis with a reference channel of ellipticity ε and tilt τ. A simple result was recently derived for a phase-sensitive receiver observing unpolarized radiation [IEEE Trans. Geosci. Remote Sens. 62, 2003610 (2024)]: with ρ(1) denoting the Pearson complex correlation coefficient between channel complex fields, it states that ∓ cos(2ε)δτ ± iδε ≈ ρ(1) when δτ,ε 1. However, phase-sensitive (in-phase and quadrature) data are seldom available at optical frequencies. To that end, here we generalize the result by deriving a new equation for the polarization “alignment” error: cos2(2ε)δτ2 + δε2 ≈ ρ(2), where ρ(2) is the intensity cross-correlation coefficient. Only the measurement of the (real) intensity cross-correlation coefficient is needed when observing unpolarized light. For the special case of a linearly polarized basis, the tilt error is simply δτ ≈ pρ(2), and for the circular basis case, with ellipticity deviation δε from circular helicity π/4 (the reference channel of opposite helicity), δε ≈ pρ(2). These results provide simple means to gauge the quality of polarimeters and depolarizers