Digital Commons Network^™

Zno Nanostructures Synthesized By One-Step Sol-Gel Process Using Different Zinc Precursors, Maneerat Songpanit, Kanokthip Boonyarattanakalin, Wisanu Pecharapa, Wanichaya Mekprasart

Journal of Metals, Materials and Minerals

Zinc oxide (ZnO) nanopowders have been widely applied in electronics, optics and photocatalytic applications depending on their morphological structure. In the bottom-up process, it is conceived that the different zinc precursors may result in different formations of ZnO nanostructures with exceptional morphology. This work focuses on ZnO material synthesized via the facile sol-gel synthesis using different zinc slat precursors, including zinc acetate, zinc nitrate, zinc sulphate, and zinc chloride. All zinc salt precursors were incorporated with sodium hydroxide and hexamethylenetetramine (HMTA) under mild thermal energy with consistent conditions to investigate ZnO formation. The as-prepared samples appeared in white powders with …

Recent Advances In Synthesis And Bio-Applications Of Natural Stabilizers For Metal Nanoparticles, Abhishek Sharma, Navneet Kaur, Ayashkanta Nanda, Manvinder Kaur, Rajeev Sharma, Harvinder Singh Sohal

Journal of Metals, Materials and Minerals

Due to their exceptional physicochemical properties, the synthesis and application of metal nano-particles gained significant traction and a grip in industries and scientific fields or regions. However, the thermodynamic instability of metal nanoparticles poses or leads to challenges in their controlled synthesis and stabilization. To address this stability and the immobilization strategies, natural polymers such as cellulose, starch, alginate, chitosan, and hyaluronic acid have been explored for their non-toxic, biodegradable, and environmentally friendly characteristics. Recent advances in nanotechnology have led to an increased focus on these natural polymer’s utilization as effective stabilizers for diverse metal nanoparticles. This review comprehensively examines …

Surface Characteristics Evolution Of 316l Stainless Steel Induced By Tension Loading, Kanokwan Antanam, Surasak Kuimalee, Panya Buahombura, Waraporn Piyawit

Journal of Metals, Materials and Minerals

316L stainless steel has been employed as a medical implant material owing to its advantageous biocompatibility and durability. The microstructure and surface characteristics of 316L play a crucial role in implant application. Diverse processing methods were utilized to modify the surface properties of 316L to customize the characteristics of medical devices. Mechanical deformation induces changes in the microstructure and causes changes in surface topography. In this study, we introduced deformation to 316L by applying uniaxial tension at strain values ranging from 2% to 25%. During sample preparation, electrochemical polishing was employed to eliminate the deformed layers generated by mechanical grinding. …

Bifunctional Cationic Modification Of Modal Fabric For Sustainable In Textile Dyeing With Spent Coffee Grounds, Monthon Nakpathom, Rattanaphol Mongkholrattanasit, Sarute Ummartyotin, Pisutsaran Chitichotpanya, Nattaya Vuthiganond

Journal of Metals, Materials and Minerals

In order to dye cellulose or regenerated cellulose with natural dyes, toxic metal mordants are generally employed. In response to this issue, the novel bifunctional cationic agent was pretreated to modify modal (regenerated cellulose) fabric prior to dyeing to enhance the fiber-dye affinity. The cationization reaction was carried out using a compound containing bicationic sites, N,N'-(oxybis (ethane-2,1-diyl))bis(3-chloro-2-hydroxy-N,N-dimethylpropan-1-aminium. This unique cationic agent is capable of producing nonvolatile amine and has no odor problem. The successful cationic modification was confirmed through FTIR spectroscopy and zeta potential measurement. The cationized process was optimized at a cationic and sodium hydroxide concentration …

Designing Biphasic Nanocellulose Hydrogels To Mimic The Complex Cartilage-Bone Interface, Sairash Sairash, Sirinee Jirajessada, Supansa Yodmuang

Journal of Metals, Materials and Minerals

Osteochondral lesions, which affect both the cartilage and the bone, present significant challenges in treatment due to the complex mechanical and biochemical properties of these tissues. A crucial consideration in developing tissue replacements for these lesions is the simultaneous regeneration of cartilage and calcified cartilage, which forms the transition zone to bone. Our current study aims to fabricate a bilayer polymeric hydrogel designed not only to support cartilage regeneration but also to serve as an interface between cartilage and bone. The bilayer hydrogel was created by combining oxidized bacterial nanocellulose, gelatin, and alginate in one layer, while the other layer …

Field Scale Evaluation Of A Flow-Through Filtration System With Mixed Media To Remove E. Coli From Stormwater, Ankur Debnath

Electronic Theses and Dissertations

The main goal of this research was to establish a field-scale stormwater filtration system which is flow-through and cost-effective in terms of construction and maintenance. The filter is constructed in a downstream drainage of a retention pond where the stormwater goes through the porous space of media so that it maintains low retention time with minimum disturbance in flow. The filter consists of two 20ft long sections with concrete channel and ripraps on the inlet & outlet side. 30% Steel chips and 70% steel slags in the size range of 6.00-12.5 mm have been used as media which has been …

Wavelet-Based Harmonization Of Local And Global Model Shifts In Federated Learning For Histopathological Images, W. Farzana, A. Temtam, K. M. Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Federated Learning (FL) is a promising machine learning approach for development of data-driven global model using collaborative local models across multiple local institutions. However, the heterogeneity of medical imaging data is one of the challenges within FL. This heterogeneity is caused by the variation in imaging scanner protocols across institutions, which may result in weight shift among local models leading to deterioration in predictive accuracy of global model. The prevailing approaches involve applying different FL averaging techniques to enhance the performance of the global model, ignoring the distinct imaging features of the local domain. In this work, we address both …

Development Of A New Green Infrastructure By Using Biochar Amended Topsoil For On-Site Stormwater Runoff Treatment, Ayesha Sadia

College of Graduate Studies: Theses & Dissertations

This Research Project aimed to design, build, operate and maintain, and monitor a new green infrastructure (GI) using biochar-amended topsoil for on-site stormwater runoff treatment in urban areas. The project involved evaluating the removal efficiencies of pollutants from stormwater runoff such as total suspended solid (TSS), nutrients including nitrogen and phosphorous, heavy metals including lead (Pb), zinc (Zn) and copper (Cu) and oil and grease etc. from the media of biochar amended topsoil. In this Project, a full-scale Field Test Site with a total area of 500 and 1 ft depth was built to on-site treat stormwater runoff from a …

Evaluation Of The Physicochemical Properties And Soil Biogeochemistry Of Fire Residues, Lingqun Zeng

Electronic Theses & Dissertations (2024 - present)

Wildland fire is a main driving force in the Earth system and affects ecosystem properties and processes across spatio-temporal scales. The burning of biomass and production of solid fire residues (conventionally termed fire ash) that are a mixture of completely and incompletely burned materials (inorganic ash and pyrogenic carbon), represent the direct and prominent changes by fires. Cycling of the fire residues is an integral component of elemental cycles and can mediate other biogeochemical processes.

This dissertation aims to fill important knowledge gaps in understanding the disturbance of wildland fires to biogeochemical processes in soils. First, this work characterized and …

In Vivo Measurement Of Nadh Fluorescence Lifetime In Skeletal Muscle Via Fiber-Coupled Time-Correlated Single Photon Counting, Kathryn M. Priest, Jacob V. Schluns, Nathania Nischal, Colton L. Gattis, Jeffery C. Wolchok, Timothy J. Muldoon

Biomedical Engineering Faculty Publications and Presentations

Nicotinamide adenine dinucleotide (NADH) is a cofactor that serves to shuttle electrons during metabolic processes such as glycolysis, the tricarboxylic acid cycle, and oxidative phosphorylation (OXPHOS). NADH is autofluorescent, and its fluorescence lifetime can be used to infer metabolic dynamics in living cells. Fiber-coupled time-correlated single photon counting (TCSPC) equipped with an implantable needle probe can be used to measure NADH lifetime in vivo, enabling investigation of changing metabolic demand during muscle contraction or tissue regeneration. This study illustrates a proof of concept for point-based, minimally-invasive NADH fluorescence lifetime measurement in vivo. Volumetric muscle loss (VML) injuries were …

Ifn-𝜸 And Il-10 Immunosensor With Vertically Aligned Carbon Nanotube Interdigitated Electrodes Toward Pen-Side Cattle Paratuberculosis Monitoring, Shaowei Ding, Benjamin J. Brownlee, Kshama Parate, Cicero C. Pola, Bolin Chen, Jesse M. Hostetter, Douglas Jones, John Jackman, Brian D. Iverson, Jonathan C. Claussen

Faculty Publications

Highly sensitive vertically aligned carbon nanotube arrays (VANTAs) interdigitated electrode (IDE) arrays are developed for electrochemical biosensing of two cytokines (i.e., interleukin-10 (IL-10) and interferon-gamma (IFN-𝜸)) that are useful for early detection Johne’s disease (Bovine Paratuberculosis) in cattle. The high aspect ratio VANTA-IDEs (50–60 μm in height) are grown through a chemical vapor deposition process from an iron (Fe) catalyst that is lithographically patterned on a silicon wafer with equal finger width and inter-finger spacing of 25 μm. After functionalization with distinct antibodies the VANTA-IDEs are capable of selective detection of both IL-10 and IFN-𝜸 within an actual biological matrix …

Foraging Economies: A Market Based Methodology For Robotic Swarm Foraging, John A. Little

Graduate Theses, Dissertations, and Problem Reports (ETD)

Swarm robotics involves coordinating large groups of autonomous agents to accomplish complex tasks through decentralized, adaptive behaviors, providing a robust and scalable approach suited to dynamic and unpredictable environments. While traditional swarm models frequently draw inspiration from biological systems such as ant colonies or bee foraging, other approaches use techniques from physics, control theory, and economics to achieve effective coordination. This study distinguishes itself by applying economic principles—specifically, market-driven mechanisms like auctions, utility functions based on opportunity cost, and supply-demand dynamics based on fluctuating resource values at a central base—to improve task allocation within a swarm foraging context. This approach …

Changes In Psychiatric Diagnosis Associated With Sars-Cov-2 Infection And Predicting The Development Of New Psychiatric Illness In Covid Patients By Using Machine Learning Approach: A Study Using The Us National Covid Cohort Collaborative (N3c), Asif Rahman

Graduate Theses, Dissertations, and Problem Reports (ETD)

The enduring impact of COVID-19 extends beyond acute illness, with potential long-term psychiatric consequences raising significant concern among healthcare professionals and researchers alike. Emerging evidence suggests a multifaceted relationship between COVID-19 and the development of different psychiatric illnesses like Schizophrenia Spectrum and Psychotic Disorders (SSPD), Depression, Bipolar disorder, Personality disorder, Trauma, and a range of other mental health conditions. Considering these emerging connections, our study endeavors to rigorously assess the associations between COVID-19 and various psychiatric illnesses while simultaneously employing machine learning techniques to predict the development of new psychiatric disorders in individuals affected by the virus. Leveraging the extensive …

Machine Learning-Assisted Multiscale Simulation And Design Optimization Of Composite Jackets Under Low-Velocity Impacts, Masoud Mohammadi

Graduate Theses, Dissertations, and Problem Reports (ETD)

This research presents the development of a data-driven machine learning-assisted approach to simulate and optimize the design of composite materials subjected to low-velocity impacts. It focuses on a specific type of hybrid composite comprised of fiberglass and Kevlar fabrics stitched with Kevlar threads. The study begins by creating a multiscale finite element simulation for the composite under a low-velocity impact, which operates across three scales: microscale, mesoscale, and macroscale. This simulation accepts various inputs, such as different layer configurations and orientations, and provides impact outputs including maximum load and energy absorption capacity and displacement at failure.

Python and MATLAB scripts …

4d Epr Oximetry Imaging For 4d Bioprinting And Tissue Engineering, Sajad Sarvari

Graduate Theses, Dissertations, and Problem Reports (ETD)

Bioprinting, akin to 3D printing, employs cell-laden hydrogels such as GelMA (Gelatine Methacrylate) and Alginate instead of plastic or resin to create biological structures. The printing process followed by subsequent tissue maturation is known as 4D bioprinting, where the fourth dimension is time. Ensuring adequate and consistent oxygen, O2, supply within 3D bioprint volume over the entire maturation period process is crucial, as even transient hypoxia can impact cellular behavior and phenotypes. However, printing of fully developed vasculature remains an unresolved technical challenge. Several approaches to chemically (peroxides) or biologically (photosynthesis) generate oxygen during bioprint maturation have been proposed. However, …

Enhancing Pipeline Simulations Through Artificial Intelligence And Machine Learning: A Smart Proxy Modelling Approach, Afeez Shittu

Graduate Theses, Dissertations, and Problem Reports (ETD)

ABSTRACT

Enhancing pipeline simulations is essential for improving operational efficiencies and effectively managing risks in the oil and gas industry. Traditional pipeline simulators, relying heavily on mathematical modeling assumptions, often face limitations due to their high energy and computational demands. This thesis addresses these challenges by introducing an innovative approach that integrates artificial intelligence (AI) and machine learning (ML) through a smart proxy model, offering a more efficient, cost-effective, and flexible alternative to conventional full-physics models used in pipeline simulation software.

The primary aim of this research is to develop and implement a smart proxy model capable of accurately predicting …

Cleaning And Characterization Of Chemical Vapor Deposited Graphene For Nanoelectronic Device Development, Sakib Ishraq

Graduate Theses, Dissertations, and Problem Reports (ETD)

Nanoelectronic devices based on graphene are a promising technology that combines the sensitivity and specificity of ion and element recognition with the accuracy and precision of electronics. The detection principle is based on the interaction of the target molecules with the nanodevice surface, which generates a measurable electrical signal. In the current study, graphene and its derivatives, synthesis and fabrication of high quality, good uniformity, and low defects graphene have been investigated as they are critical for high-performance and highly sensitive devices. Among many synthesis methods, chemical vapor deposition (CVD), have been used that needs to be transferred from the …

Implementation Of Bayesian Statistics To Answer Diverse Engineering Questions: Applications In Cancer Immunology And Engineering Education, Anika C. Pirkey

Graduate Theses, Dissertations, and Problem Reports (ETD)

Quantitative Systems Pharmacology (QSP) refers to a mechanistic modeling approach used for assessing potential therapeutics by linking the molecular and cellular level mechanisms of the disease and therapeutic to the system-wide dynamics and clinical endpoints relevant to the disease. Although the field of QSP is still in its relative infancy, the mathematical methodology employed to predict the kinetics of these systems are not new and can be applied to a wide variety of systems. For instance, similar to QSP’s goal of guiding the development of novel therapeutics for various disease states, there exists a need to develop novel interventions in …

Inherently Porous Metal Structures With Sufficient Mechanical Properties Through Direct Writing Of Bio-Based Inks, Havva Eda Aysal

Graduate Theses, Dissertations, and Problem Reports (ETD)

There is currently a burgeoning interest in developing 3D printed metal structures with inherent porosity and sufficient mechanical properties for mass customization in the biomedical field. Current approaches for 3D printing of biocompatible metals rely on powder-bed fusion methods which are energy intensive and utilize large amounts of metal powder that is challenging to recycle. In addition, such methods aim on producing dense parts and porosity generation, within the printed part, is challenging due to the complex physics of the melting pool. Here, a relatively new and promising approach is undertaken to study the 3D printing of inherently porous structures …

Active Uncertainty Representation Learning: Toward More Label Efficiency In Deep Learning, Salman Mohamadi

Graduate Theses, Dissertations, and Problem Reports (ETD)

The primary goal of this dissertation is to investigate and improve the efficiency of deep learning algorithms, especially within computer vision problem domains, from the perspective of label-efficiency. This investigation showed that deep learning algorithms are mostly notorious for the lack of uncertainty representation. Accordingly, we aimed to develop an array of deep learning frameworks rich with uncertainty representation. These frameworks are mainly within two current pillars of machine learning, deep active learning and self-supervised learning. These frameworks include deep active ensemble sampling for efficient sample selection within deep active learning, a two-stage ensemble-based general self-training approach for existing visual …

Transparent And Conductive Gallium Oxide Electrode For Simultaneous Recording And Optogenetic Stimulation, Christopher Patrick Carey

Graduate Theses, Dissertations, and Problem Reports (ETD)

Neural electrode technology has been around for centuries since the times of Galvani. In early electrophysiology experiments metal wires were used to induce contractions in dissected animals. The metal wire electrode has since been a standard tool to both stimulate and record neural activity. In the past two decades, a new strategy for neural stimulation has been formulated based on the emergent field of optogenetics. Optogenetics refers to the use of light-sensitive proteins genetically imbedded in the membrane of a neuron to elicit neural activity. This technique offers more selectivity in the stimulation of neurons. Typical optogenetic neural electrodes, or …

Cellular Structure Mediated Dislocation Regulation In Additively Manufactured Refractory High Entropy Alloy, Changxi Liu, Lechun Xie, Lai-Chang Zhang, Liqiang Wang

Research outputs 2022 to 2026

A Ti1.5Nb1Ta0.5Zr1Mo0.5 (TNTZM) refractory high entropy alloy (HEA) with a cellular structure was successfully fabricated by laser powder bed fusion (L-PBF). Compression testing and cyclic deformation testing results revealed that, in the cellular structure, the cell walls could store dislocations. Furthermore, the local chemical order (LCO) plays a crucial role in controlling dislocations within the cell wall region. The LCO not only facilitates dislocation slip but also generates additional lattice distortion upon stress-induced LCO destruction to enable dislocation pinning. This work offers novel insights into the microstructure of additively manufactured refractory HEAs and uncovers a distinct dislocation regulation mechanism.

A Natural Hydrogen Seep In Western Australia: Observed Characteristics And Controls, Krista Davies, Emanuelle Frery, Ausama Giwelli, Lionel Esteban, Alireza Keshavarz, Stefan Iglauer

Research outputs 2022 to 2026

Natural hydrogen (H2) is a promising resource for the energy industry’s transition to zero-carbon fuels. However, its extent and feasibility for exploitation remain unclear. A key step towards discovering subsurface dihydrogen accumulations is detecting H2 seeps. This study presents the first autonomous, multi-gas monitoring of a natural hydrogen seep in Australia, where dihydrogen, carbon dioxide, and hydrogen sulphide were measured together. The research revealed significant H2 seepage on the Yilgarn Craton in Western Australia, with seasonal fluctuations: high emissions after dry summers and reduced emissions following rainfall due to increased groundwater levels. Groundwater appears to act as a seasonal inhibitor …

Advancing Natural Hydrogen Exploration: Headspace Gas Analysis In Water-Logged Environments, Krista Davies, Lionel Esteban, Alireza Keshavarz, Stefan Iglauer

Research outputs 2022 to 2026

Natural hydrogen has gained prominence as a potential contributor to the low-carbon energy landscape; however, exploration techniques are still evolving. Current methods primarily rely on dry soil gas studies or gas vent measurements. Because gas vents are scarce and groundwater inhibits hydrogen gas flux from the soil, other field detection techniques are necessary. This research paper presents a novel approach for advancing natural hydrogen exploration through the analysis of headspace gas of agitated groundwater extracted from dedicated shallow boreholes to better estimate the hydrogen gas flux and its variations with time. Several shallow boreholes were drilled in Western Australia on …

2023 Scholarly Productivity Report, Missouri University Of Science And Technology

Civil, Architectural and Environmental Engineering Scholarly Productivity Reports

No abstract provided.

A Spatiotemporal Analysis Of Organic Pollutants Contamination In Ciliwung River, Indonesia, Mochamad Adhiraga Pratama, Dorothy Marsha Constantine

CSID Journal of Infrastructure Development

Ciliwung River is one of many rivers on Java Island which is polluted by waste from domestic, commercial/industrial, and agricultural activities. The rapid population growth caused changes in land use. Along with population growth and the development of human activities in various sectors, river pollution became a serious problem for humans. The purpose of this study is to conduct a spatiotemporal analysis of the concentration of pollutant in Ciliwung River and its correlation with the trend of land use changes to determine the factors that dominantly influence river pollution. The analysis was carried out on the parameters of organic pollutants …

Seasonal Variability On Microplastic Polutions In Water And Sediment Of Ciliwung River, Hefty Clarissa Wilyalodia, Elgrytha Victoria Tybeyuliana, Alloysius Pamurda Dhika Mahendra, Mochamad Adhiraga Pratama, Suphia Rahmawati, Fajri Mulya Iresha, Setyo Sarwanto Moersidik

CSID Journal of Infrastructure Development

Microplastics, recognized as emerging contaminants, have been detected in numerous rivers globally. This study focuses on the Ciliwung River in Jakarta, examining the influence of seasonal variations—specifically the rainy and dry seasons—on microplastics' concentration, types, and colors. Sampling was conducted during November 2022 (dry season) and March 2023 (wet season) using a plankton net for water (10 liters) and an Ekman grab sampler for sediment (400 mililiters). Microplastic abundance was analyzed following the National Oceanic and Atmospheric Administration (NOAA) adaptation method, and their material characteristics were identified using Fourier Transform Infrared Spectroscopy (FTIR) testing. Results revealed a notable seasonal impact: …

Human Genome Analysis And Encryption: A Cloud Prototype Model Using Aws And Aes, Priyanka Kunte, Rachana Shanbhogue, Sanjana S. Nayak, Neelima Bayyapu, Manjunath K N, Neha S. Gandhi

Manipal Journal of Science and Technology

SecureDNA presents a robust solution for safeguarding genetic data in cloud storage through the implementation of AES-256-CBC encryption. This innovative system, designed with a user-friendly interface, guides users seamlessly through DNA data upload processes, ensuring confidentiality and integrity. Utilizing AWS services such as RDS, VPC, and EC2, SecureDNA establishes a secure infrastructure for data storage and user interaction. By encrypting DNA records before storage and leveraging cloud computing benefits, this system not only protects sensitive genetic information but also offers scalability and accessibility. SecureDNA stands as a pivotal advancement in ensuring the privacy and reliability of genetic data in the …

Borophene And Graphene For Non-Enzymatic Biosensor- Ab-Initio Study, Omar A. Ismail

Theses and Dissertations

Non-enzymatic glucose sensing holds promise to overcome limitations associated with glucose oxidase, such as oxygen dependence and short shelf life. This study explores the potential sensing capabilities of borophene and graphene through direct interaction with various compounds, including β-glucose, uric acid, ascorbic acid, fructose, and acetaminophen. Using Density Functional Theory (DFT), we calculated binding energies and the respective Density of States (DOS) for these adsorbates on both graphene and borophene surfaces. Preliminary results suggest that borophene might exhibit nearly twice the affinity for β-glucose compared to graphene. Moreover, the calculated Density of States reveals distinct distortions in the electronic states …

The Effect Of Walnut Shell Ash On The Properties Of Cement Paste And Mortar: A Study On Partial Replacement Of Cement, Ali Shebli, Jamal Khatib, Adel Elkordi

BAU Journal - Science and Technology

In the pursuit of a more sustainable future, the utilization of agricultural waste in cementitious products has emerged as a popular and effective solution. The current study explores the feasibility of incorporating ash derived from walnut nutshells, considered agro residues, into eco-friendly blended cement paste and mortars to examine its impact on their properties. A range of blended cement mixtures was formulated by incorporating walnut shell ash (WSA) in three varying proportions of 5%, 10%, and 15% relative to the weight of the cement. Tests were conducted to investigate the properties of the blended cement paste and mortar incorporating WSA, …