Mechanical Engineering

Permanent URI for this collectionhttps://hdl.handle.net/10315/34419

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Access status: Open Access ,
Laser-Carbonized Graphene and Lignin Films for Sustainable Transient RFID Electronics
(2025-11-11) Khan, Juveiria; Rizvi, Reza
The growing problem of electronic waste calls for new materials that are sustainable and easy to recycle. This thesis focuses on developing conductive films for transient and flexible electronics using two different material systems. In the first part, cellulose paper was used as a biodegradable base. Three types of coatings were prepared: (i) graphene oxide (GO), (ii) GO with ascorbic acid (AA) as a reducing agent, and (iii) GO with a mixture of ascorbic acid and sodium lignosulfonate (Na-Lgs) to provide extra carbon content. After coating, the samples were treated with a laser to create conductive patterns directly on the cellulose. This study shows that cellulose can serve as a compostable material for electronics while still offering useful electrical properties. In the second part, polyethylene terephthalate (PET) films were coated with compressible flow exfoliated (CFE) graphene. PET provided strength and flexibility, while the graphene coating gave an initial conductivity that was further improved by laser carbonization. The PET/CFE system achieved very low sheet resistance, with the best value recorded at 16.17 Ω/sq, showing excellent electrical performance compared to many earlier studies. To evaluate both systems, several techniques were used: SEM to study the surface and cross-section of the films, TGA to test thermal stability, Raman spectroscopy to analyze graphitic structure, FTIR to confirm chemical changes, and sheet resistance measurements to check electrical performance. Overall, the results show two promising directions: cellulose-based films for biodegradable and eco-friendly devices, and PET/CFE graphene films for high conductivity and robust performance. In particular, the PET/CFE graphene system, with its low sheet resistance, shows strong potential for further development towards commercial RFID tags and other high-performance flexible electronic devices.
Access status: Open Access ,
Automated Micro-CT Image Segmentation and Void Analysis of HDPE-HGM Syntactic Foams Using Machine Learning
(2025-11-11) Shiv Shankar, Riya Vasan; Melenka, Garrett; Rivzi, Reza
Syntactic foams are a subclass of composite materials in which the matrix is embedded with hollow microspheres, offering a high strength-to-weight ratio suitable for the aerospace, marine, and automotive industries. The microspheres create porosity, visually indistinguishable from voids caused by manufacturing during imaging, both of which influence mechanical performance. Quantification and classification are, therefore, crucial for quality control and predictive modelling. This thesis proposes an integrated pipeline utilizing micro-CT imaging and unsupervised learning to segment and quantify voids, particles, and matrix in HDPE-HGM syntactic foams. A hybrid segmentation technique leveraging slice-wise thresholding and K-means clustering resulted in an F1 score of 0.92 compared to LabKit for voids. Voids were further classified into raster voids and HGM cavities based on shape descriptors, with subsequent spatial analysis performed using the R-index and clustering coefficients. Morphological features were correlated to Ultimate Tensile Strength and Young's Modulus. A custom GUI enables 3D visualization and segmented mesh export, facilitating the creation of digital twins for enhanced material analysis and process optimization.
Access status: Open Access ,
Electrochemical Microfluidic Sensors with Integrated Ion-Selective Polymer Membranes for the Detection of Trace Ions in Water
(2025-11-11) Oseyemi, Ayobami Elisha; Rezai, Pouya
There is an increasing demand for low-cost, portable, and sensitive sensing technologies for detecting trace levels of metal ions in water to support public health, environmental monitoring, and energy applications. Traditional analytical methods, while accurate, are limited by their reliance on bulky equipment, high cost, and complex electrode modification, making them unsuitable for real-time or on-site use. This research addresses these limitations by developing a microfluidic electrochemical sensor platform that integrates in-situ synthesized, stand-alone ion-imprinted polymer (IIP) membranes for the selective detection of sodium (Na⁺), lead (Pb²⁺), and lithium (Li⁺) ions in water. The study employed a stepwise methodology: an ion-selective polymer membrane was first developed to detect salinity, achieving a 28-fold sensitivity improvement and a detection limit of 0.45 ppm. Next, a Na-IIP membrane using 15-crown-5 as an ionophore achieved 58 ppb detection with over threefold sensitivity enhancement. Finally, Pb-IIP and Li-IIP membranes were developed, attaining detection limits of 7.3 ppb and 168 ppb, respectively, with high selectivity over competing ions. All configurations demonstrated high reproducibility, multi-ion selectivity, and recovery rates ranging from 69% to 109% in municipal tap water. The stand-alone membrane design simplifies fabrication, enhances stability, and is compatible with continuous-flow operation. This work advances the development of scalable, point-of-need sensing systems and offers a foundation for future multiplexed and automated water quality monitoring platforms.
Access status: Open Access ,
Low Reynolds Number Settling of Cylindrical Rods with Various Geometries in a Quiescent Fluid
(2025-11-11) Hamidi, Amirhossein; Hanson, Ronald
This dissertation is motivated by the atmospheric transport of microplastic fibres, a growing environmental concern. The atmosphere is recognized as a major pathway for the long-range transport of microfibres. However, many atmospheric simulations simplify fibre geometry, often representing them as volume-equivalent spheres or straight cylinders, despite the more complex shapes observed in microfibre samples from atmospheric deposits. This research aims to enhance our understanding of the settling behavior of curved, V-shaped, U-shaped, and S-shaped cylindrical rods within the Reynolds number and aspect ratio range associated with the atmospheric transport of microfibres. A series of experiments were conducted using millimeter-scale metal rods with aspect ratios ranging from 10 to 120, settling in a quiescent water-glycerin chamber to replicate Reynolds numbers below 7. A stereo-PTV system was employed, with two side cameras tracking terminal settling velocities and orientations, while a bottom camera captured potential spinning motions. Using a three-dimensional calibration algorithm, the terminal velocities and orientations of the rods were determined in real-life space. Results demonstrate that curved and V-shaped rods settle faster than straight rods of the same dimensions, with V-shaped rods settling only slightly faster than curved rods of equivalent projected length. U-shaped rods exhibit a transition in orientation from vertical to oblique above a critical Reynolds number or below a critical middle arm length ratio. They consistently settle faster than straight rods because of their non-zero inclination angle. Furthermore, their terminal velocity either peaks at a specific aspect ratio or remains constant due to a trade-off between side arm length and rod inclination. S-shaped rods exhibit spinning motions at a constant rate while settling at the same velocity as the straight rods of identical dimensions. Their spinning rate peaks at an intermediate middle arm length ratio, which was experimentally and theoretically investigated. New models were developed to estimate the terminal velocity of rods with these geometries, which can also be applied to predict the terminal velocity and the horizontal travel distance of microfibres of various shapes. This study highlights the crucial role of fibre morphology in determining vertical terminal velocity and, consequently, horizontal dispersion in the atmosphere.
Access status: Open Access ,
Revitalizing Simulations of Colloidal and Interfacial Systems: From Atomistic Trajectories to Data-Centric Insights
(2025-11-11) Imani Parashkooh, Hasan; Jian, Cuiying
This dissertation advances methodological frameworks for investigating complex systems characterized by competing interactions. Structured around three interrelated themes, the research develops methods to tackles challenges in water-in-oil emulsions, chemical inhibition in asphaltene aggregation, and adsorption energy prediction. While each theme addresses unique challenges, they all contribute to quantitative understanding of interactions across scales, integrating structural, thermodynamic, and energetic perspectives to establish governing principles for system behavior. The first theme elucidates the interplay between asphaltene aggregation and water-in-oil droplet coalescence. Molecular Dynamics (MD) simulations conducted in pentane solvents reveal the mutual influences of asphaltene and water droplets, highlighting a nonmonotonic trend in polyaromatic stacking with increasing droplet sizes. An innovative in-house tool is introduced to analyze droplet coalescence modes, demonstrating that droplet growth predominantly occurs around a nucleation site, which is the largest droplet. In the second theme, a novel approach for calculating partial molar volumes (PMVs) directly from MD simulation trajectories is presented. This approach has been validated against experimental data, yielding an average error of 4.41%. When applied to systems containing model asphaltenes, organic solvents, and chemical inhibitors, the PMV analysis elucidates molecular-level inhibition mechanisms. Specifically, it shows that inhibitors enhance solubility by altering nanoaggregate size and number, with their polar and nonpolar segments interacting with different regions of the asphaltene molecules and the solvent. The third and final theme highlights the critical need for efficient and accurate adsorption energy predictions, a fundamental aspect of catalysis, materials design, and a key factor in mitigating asphaltene deposition. Traditional methods of calculating adsorption energy such as Density Functional Theory (DFT) are computationally demanding, particularly for large, complex adsorbates like aromatics. To overcome these limitations, this work applies pretrained graph neural networks (GNNs) with a directional message passing architecture. The model is trained to capture geometric relationships between small adsorbates and metallic or metal oxide surfaces, linking them to energy and atomic forces. Here, it is fine-tuned to adapt these learned interactions for larger molecules, including aromatics. Two curated datasets, a diverse adsorbate-substrate collection and a specialized aromatic subset, are employed to balance generalizability with specificity. Results indicate that the sheer volume of fine-tuning data has a greater impact on model adaptation than using smaller but more domain-specific datasets. Moreover, the results show that selectively fine-tuning the early layers, which focus on geometric features, achieves performance comparable to full model retraining. This highlights the crucial role of geometric feature adaptation. Collectively, these themes contribute to the refinement of data-driven methodologies for complex interfacial and amorphous systems, providing actionable insights into structural, thermodynamic, and energetic properties that were previously inaccessible. Nano-scale simulations with extensive temporal and spatial sampling are essential, as competing interactions make it impossible to predict dominant factors without comprehensive analysis. By reutilizing existing simulation data, the innovations presented here enhance sustainability and efficiency, with broad implications for physical chemistry, materials science, and industrial applications.
Access status: Open Access ,
Vision Tracking System for In-Situ Tissue Bioprinting
(2025-11-11) Zakharova, Kateryna Viktorivna; Czekanski, Aleksander
Maintaining printing accuracy despite the constant motion is one of the main difficulties in printing on moving surfaces. Traditional 3D printers are made for stationary platforms. Changing them to work on dynamic surfaces calls for the creation of new control algorithms and methodologies. In-situ (from Latin: in its original place) printing refers to a process where bioprinting or additive manufacturing technologies are used directly at the site of application. The core component of our vision tracking system is a real-time algorithm powered by a Deep Learning model that monitors the printing surface – a harmed part of the human body. This system relies on advanced Computer Vision technologies to accurately track the moving surface's position and orientation. Our experiments in simulations proved the concept of the robot's ability to adjust to a dynamic environment. A multi-camera system and a 6-DOF robot arm are included in the experimental setup of this research.
Access status: Open Access ,
Improvements in Microfabrication of Integrated Collagen Scaffolds Containing Embedded Microchannels Inside 3D Extracellular Matrix with 2D Basement Membrane Linings
(2025-11-11) Ali Maghzian; Rezai, Pouya
Collagen's biocompatibility, biodegradability, and cell-adhesive properties make it vital for developing biomimetic scaffolds in tissue engineering. This thesis enhances the microfabrication of collagen scaffolds with micro-conduits, mimicking the Extracellular Matrix (ECM). These scaffolds feature a 3D porous collagen sponge, mimicking the interstitial matrix, with embedded microchannels with varying widths (70-1000 μm) resembling veins and vessels and micropatterns, as well as a 2D collagen film lining the microchannel walls that mimic the basement membrane. Through soft lithography, freeze-drying, and contact printing, scaffolds with enclosed macrochannels in multiple layers were created and reinforced with composite effects of components and crosslinking. Characterization methods included microscopy, ImageJ analysis, optical profilometry, flow studies, and SEM imaging. Factors influencing scaffold flatness and achievable microchannel dimensions were investigated in a parametric study. Preliminary cultures evaluated scaffold viability for culturing mice brain tissue and studying various cell behaviors, including HEp2, HEp2D and HEK 293T cell lines. These scaffolds offer customizable physical characteristics for diverse tissue applications, facilitating blood vessel modeling, cell co-culture, and drug delivery studies.
Access status: Open Access ,
Design, Fabrication, and Experimental Characterization of a Focusable Solar Simulator for High and Low Flux Solar Thermal Applications
(2025-07-23) Badaloo, Rajiv Motilal; Cooper, Thomas
High-flux solar simulators (HFSS) advance solar thermal research but are traditionally costly and complex, limiting access for smaller institutions. This thesis presents a low-cost, adaptable solar simulator using commercially available xenon arc cinema searchlights and Fresnel lenses for dynamic irradiance control. The system was characterized through direct flux measurements with a pyranometer and indirect flux mapping via a CMOS camera, enabling detailed analysis of irradiance distribution, temporal stability, and efficiency. Experimental results showed an average irradiance of 2819 W/m² over a 12×12-inch area, peak irradiance of 2348 kW/m² with Fresnel lens concentration, and efficiencies up to 22.4% at full intensity. Real-world tests on radiative cooling coatings confirmed the simulator's capability to replicate concentrated solar conditions accurately. This study demonstrates a scalable, practical alternative to traditional HFSS, enhancing accessibility for smaller research facilities and laying a foundation for future multi-lamp and advanced optical configurations.
Access status: Open Access ,
The Impact of Entrepreneurship Education on the Development of Entrepreneurial Intention Among Engineering Students: The Mediating Role of Entrepreneurial Mindset and Self-Efficacy.
(2025-07-23) Seyedalikhani, Fatemehsadat; Maxwell, Andrew L.
This thesis explores how entrepreneurship education (EE) influences the development of entrepreneurial intention (EI) among engineering students, specifically examining the mediating roles of entrepreneurial mindset (EM) and entrepreneurial self-efficacy (ESE). Considering the growing global importance of innovation and entrepreneurial skills, the study investigates the degree to which EE enhances EI by fostering EM and strengthening ESE. Using a quantitative survey of 431 engineering students at York University’s Lassonde School of Engineering, the study applied structural equation modeling to examine the direct and indirect effects of EE on EI through EM and ESE. Our findings show that EE significantly enhances EI, with both EM and ESE positively mediating this relationship. In this research, we investigated the impact of entrepreneurship education on entrepreneurial mindset and on entrepreneurial intention. In reality this relationship is more complex, and causality might be in the opposite direction. Future research should investigate the interplay between these entrepreneurial components and the iterative nature of their evolving relationships. This highlights the value of integrating EE into engineering curricula to develop the EM needed in today’s technology-driven world. The research contributes to existing literature by quantifying EE's impact on EI and offers practical implications for educational policy and curriculum development, advocating for the continued inclusion of EE to effectively prepare engineering students for entrepreneurial careers and foster economic innovation and growth.
Access status: Open Access ,
Comprehensive Lifecycle Assessment of Direct Air Capture Systems for Carbon-Dioxide Removal from the Atmosphere
(2025-07-23) Eke, Victor Obinna; O'Brien, Paul G.
This thesis evaluates the environmental performance of Direct Air Capture (DAC) technologies through a review of life cycle assessments (LCA), focusing on low-temperature systems integrated with solar energy for adsorbent regeneration. The methodology combines ISO-standardized LCA modeling with experimental validation using silica-supported polyethyleneimine adsorbents under photothermal regeneration conditions. Three heating configurations (natural gas, solar-thermal, and hybrid solar-electric) were evaluated across diverse geographical regions. Results show solar-based systems significantly outperform conventional systems, with potential emissions reductions up to 290 kg CO₂-eq per ton of CO₂ captured. Laboratory experiments demonstrated thermal system desorption required 3.0 GJ/kg CO₂ (0.07% efficiency), while the photothermal system required 707 MJ/kg CO₂ (0.29% efficiency), confirming photothermal regeneration's feasibility for low-energy DAC operation. While regeneration energy dominates environmental impact, infrastructure, transport, and storage collectively contribute significantly. DAC deployment should prioritize regions with abundant solar resources and clean electricity grids, with policy frameworks incentivizing these optimal configurations.
Access status: Open Access ,
Experimental and Analytical Investigation of an Array of Sessile Droplets Behaviour on Heated and Unheated Substrates
(2025-07-23) Azzam, Ahmed Elsaid; Amirfazli, Alidad
**Summary (194 words):** This thesis investigates the evaporation and interaction dynamics of sessile droplets, crucial for applications in thermal management, microfluidics, and surface wetting. A novel and computationally efficient **Point Source Model (PSM)** was developed to predict droplet evaporation on isothermal and heated surfaces. By simplifying complex mass transfer processes, the PSM provides accurate results with minimal computational cost. Initially, the PSM modeled quasi-steady, **purely diffusive evaporation** of two droplets, capturing the effects of **separation distance** and **evaporation modes**—Constant Contact Angle (CCA) and Constant Contact Radius (CCR)—with deviations under 9% compared to experiments. A **critical separation ratio (L/d ≥ 10)** marked the onset of independent behavior. To address heated substrates, the model incorporated **natural convection** via a new empirical correlation. For **Ra·L/d < 400**, diffusion dominates, while for **Ra·L/d > 2400**, convection stabilizes. Further experiments explored **vapor-mediated interactions** between water and propylene glycol-water droplets at 24–135°C. Significant increases in droplet velocity and fragmentation were observed, especially at **20% PG**, driven by surface tension gradients. Finally, the PSM was extended to a **three-droplet array**, revealing enhanced **vapor shielding** and a new isolation threshold (**L/d > 20**), emphasizing the impact of droplet geometry on evaporation behavior.
Access status: Open Access ,
Thermal and Hydraulic Characterization of Hook-Shaped Fins and Dimples
(2025-07-23) Alrefaey, Karim; Kempers, Roger
In forced convection, extended surface arrays enhance heat transfer by increasing surface area, promoting fluid mixing, and generating turbulence. Their thermal-hydraulic performance can be modified by introducing tip clearance or adjusting the attack angle. This study quantifies the heat transfer coefficient and pressure drop of GRIPMetal arrays – hook-shaped fins with dimples – under varying tip clearances and attack angles. Experiments with water-cooled GRIPMetal surfaces explored Reynolds numbers (Re) from 600 to 12,000, while simulations examined attack angles (α) from 0° to 90°. Results showed that GRIPMetal significantly outperforms smooth surfaces, with Nusselt number (Nu) enhancements of 2.4 to 5.7 times higher, despite increased pressure drop. Accounting for the pressure drop penalty, the overall performance factor remained above 1.4. Numerical findings revealed that α = 22.5° improved Nu by 44% at Re = 5000, and some configurations reduced pressure drop. These results highlight GRIPMetal’s potential as a cost-effective heat transfer enhancement method.
Access status: Open Access ,
Capture of Free-Floating Targets Using End-to-End Reinforcement Learning: Theoretical Foundations and Ground Demonstrations
(2025-07-23) Beigomi, Bahador; Zhu, George Z.H.
This doctoral research addresses the challenge of autonomously capturing free-floating, tumbling space debris using robotic manipulators for debris removal in space. Space debris poses a growing risk to near-Earth operations and satellite services. The dissertation explores autonomous grasping of non-cooperative debris in microgravity through Deep Reinforcement Learning (DRL) and advanced robotic manipulation. A high-fidelity simulation environment is developed using the PyBullet physics engine with domain randomization to train and evaluate DRL agents under realistic dynamics. The agents use hierarchical control strategies, combining curriculum-based learning for path planning and tactile sensor feedback for force regulation to minimize disturbances to the target. Simulation studies of multiple DRL algorithms, including Soft Actor-Critic, show success rates over 90% in grasping tasks with varying debris shapes and conditions. A Hardware-in-the-Loop testbed at York University, with dual Fanuc robots and active gravity compensation, further tests these policies, while additional experiments at the University of Luxembourg’s Zero-G Lab confirm the system’s adaptability in microgravity. Results demonstrate that the agents can align and capture free-floating targets without destabilizing forces. Hardware tests verify high grasp stability even with spinning debris, showcasing the potential for autonomous space debris removal. This research advances space robotics by integrating DRL methodologies with experimental validation, enabling safer, more efficient future debris removal missions.
Access status: Open Access ,
Design and Fabrication of Microfluidic Electrochemical Sensor for Lead Detection in Drinking Water
(2025-07-23) Shapour Jafargholinejad; Rezai, Pouya; Gora, Stephanie
This research aimed to enhance microfluidic electrochemical sensors for water quality analysis by simplifying fabrication and leveraging secondary flow effects. Using low-cost materials and laser-cutting techniques, sensors were constructed and characterized. Graphene-carbon paste electrodes were utilized. Through statistical analysis, curved channels significantly improved sensor response due to Dean vorticity formation, enhancing analyte-electrode interaction. Square wave voltammetry demonstrated superior lead detection in curved-channel sensors over straight channels, confirmed by calibration curves using deionized and real water samples. For lead detection, the curved-channel sensor achieved a detection limit of 2.26 µg/L and a sensitivity of 0.0332 µA/(µg/L), surpassing the straight-channel sensor's performance. This research offers a cost-effective, easy-to-fabricate, and modifier-free option for heavy metal detection, particularly lead, in drinking water.
Access status: Open Access ,
Ultrasonic Fouling Mitigation for Renewable Energy Powered Reverse Osmosis Desalination Systems
(2025-07-23) Horrigan, Liam; Freire-Gormaly, Marina
This thesis examines the use of ultrasound to mitigate the performance degradation of reverse osmosis membrane filtration systems due to the accumulation of contaminants on membrane surfaces known as fouling. Numerical models of the phenomena responsible for the fouling mitigation effects of ultrasound were produced. An approach by which ultrasound could be applied to fouling mitigation within commercially available reverse osmosis modules was developed. Relationships between the application of ultrasound and temperature distributions within the fluid contained in filtration modules were investigated for instrumentation and performance assessment purposes. A novel ultrasonic horn was developed and theoretically verified for enhancing the effectiveness of ultrasonic fouling mitigation within commercially available reverse osmosis modules. An experiment was also designed to assess the effectiveness of the approach developed, for which an experimental setup was developed and constructed. Preliminary experiments have been conducted. Future research will focus on detailed experimental analysis.
Access status: Open Access ,
Development of Acrylamide/Acrylic acid Superabsorbent Polymer (SAP) Particles for Water Applications
(2025-04-10) Tabesh, Ehsan; Rezai, Pouya
Water contamination, particularly from bacterial sources, poses significant risks to public health and environmental safety. Low bacterial concentrations in water samples often go undetected by conventional methods, increasing these risks and highlighting the need for efficient sample enrichment techniques. This research investigates the use of superabsorbent polymer microparticles (SAP-MPs) and their nanocomposites with MXene nanosheets for enriching bacterial samples. The study first focuses on developing innovative microfluidic platforms for real-time characterization of SAP-MPs. Subsequently, advanced MXene/SAP-MP nanocomposites are introduced for enhanced bacterial enrichment and water analysis. The study is structured into four objectives. The first objective involves the design and fabrication of a novel microfluidic device for high-resolution, real-time characterization of SAP-MPs. This device enables detailed single particle analysis of swelling behaviors, including volume swelling ratio (VSR) and swelling rate (SR). The second objective investigates the effect of particle size, crosslinker concentration, acrylic acid concentration, and neutralization degree on the swelling behavior of SAP-MP. Results revealed a ~40% and ~300% reduction in equilibrium VSR (VSReq) and SR with increased crosslinker concentration, respectively, while increasing acrylic acid concentrations enhanced VSReq and SR by ~200%. A ~300% increase in VSReq was observed with smaller particle sizes, marking the first single-particle-scale study of this phenomenon. The third objective demonstrates the synthesis of MXene/SAP-MP nanocomposites using the Breathing-In-Breathing-Out (BI-BO) method, achieving successful integration of MXene nanosheets without compromising swelling behavior. Finally, the fourth objective evaluates bacterial enrichment performance, revealing a 10-fold enrichment efficiency and 90% recovery efficiency under optimized conditions. This research advances the fundamental characterization of SAPs and their applications, including water treatment, biosensing, and environmental monitoring.
Access status: Open Access ,
Cell Imprinted Polymers Integrated with Microfluidic Biosensors for Electrical and Electrochemical Detection of Bacteria in Water.
(2025-04-10) Akhtarian, Shiva; Rezai, Pouya; Brar, Satinder
There is a growing demand for sensors that enable rapid, cost-effective, and laboratory-free detection of microorganisms in clinical, food and environmental samples. Traditional methods are slow, expensive, and require specialized personnel. Biosensors offer a promising alternative but face challenges like instability, high cost, short lifespan, and complex synthesis of the biorecognition elements. Molecularly imprinted polymers (MIPs) provide a more robust, cost-effective solution by embedding the target analyte's imprint into a polymer matrix. While MIPs are effective for small molecules, designing them for biological cells is more complex due to their structural diversity. Noncovalent interactions, preferred in synthesizing cell-imprinted polymers (CIPs), enable easier binding and dissociation. Selecting suitable functional monomers is crucial, as their interactions with cell surface molecules determine imprinting success. However, the effects of CIP composition on the bacterial capture efficiency remain unexplored. Furthermore, integrating CIPs into microfluidic and electrochemical sensing platforms is vital for portable, real-time detection systems. This research aimed to improve the understanding of the CIPs’ effectiveness in capturing bacteria to develop effective bacteria-sensing platforms using microfluidic devices. In Objective 1, we optimized a polymerization methodology for uniform functionalization of stainless steel microwires reproducible CIP coatings, imprinted with E. coli as the template. In Objective 2, we assessed E. coli rebinding performance which demonstrated 76±5 % uptake efficiency with the optimized composition. In Objective 3, we integrated CIPs into a conductometric-based microfluidic sensor. Resistance changes normalization and subsequent analysis of the dose-response curve revealed a dynamic range of 10^4 to 10^7 CFU/mL, with a limit of detection (LOD) of 2.1×10^5 CFU/mL. Specificity experiments demonstrated the specificity of the sensor towards imprinted E. coli cells. Further improvements were made by modifying the sensor design to a three-electrode configuration and employing electrochemical impedance spectroscopy (EIS). The charge-transfer resistance changes normalization and the subsequent analysis revealed an enhanced LOD of 2× 10^2 CFU/mL, with a broader dynamic range of 10^2 to 10^7 CFU/mL. The proposed sensor has the potential to offer a cost-effective, durable, portable, and real-time solution for the detection of waterborne pathogens. Future impacts include enhancing bacterial detection in environmental monitoring, food safety, and healthcare.
Access status: Open Access ,
Electro-Microfluidic Sensor for Quantitative Detection of Microplastics in Saline Freshwater
(2025-04-10) Warraich, Haider Tahir; Rezai, Pouya
This thesis investigates a DC microfluidic sensor incorporating a Wheatstone bridge and MXene-coated microwires to detect and quantify microplastics in freshwater with varied salinity. The study addresses the limitations of traditional detection methods, particularly in higher freshwater salinity where microplastics exhibit reduced electrophoretic mobility. The sensor's performance was evaluated across a range of microplastic concentrations (1–25 ppm) suspended in saline solution with varying NaCl concentrations (0–1000 ppm) to assess sensitivity and detection limits. Results demonstrated a significant reduction in electrical resistance as microplastics accumulated at the anode, indicating successful detection at lower salinities. However, at higher salt concentrations, microplastic accumulation and sensor sensitivity declined. Modifications, including constant current application and MXene functionalization, enhanced accumulation rates, and detection performance. Future research is required to investigate diverse microplastic types, shapes, and biological interferences to improve real-world applicability. This work provides a foundation for low-cost, sensitive microplastic detection in aquatic environments.
Access status: Open Access ,
Droplet Impact on a Solid Surface: Analytical Modeling and Experimentation for Spreading Phase
(2025-04-10) Hu, Yating; Amirfazli, Alidad
A normal droplet impacting a flat, stationary, solid surface exhibits symmetric spreading. A key aspect of this symmetric spreading, particularly during deposition at low Weber numbers, is the formation of a rim along the lamella edge. The rim is crucial for predicting maximum spreading, and its dynamics can be captured using a set of ordinary differential equations in numerical calculations. However, establishing a reasonable initial condition remains challenging. In addition to symmetric spreading, various studies have explored how to disrupt symmetry for industry demands, for example, reducing contact time for anti-icing purposes. However, no attempts to date have been conducted to restore symmetry from asymmetric spreading, such as spreading over an inclined or moving surface, where tangential velocity naturally breaks the symmetry. To address these issues, this thesis investigates: 1) the rim genesis for a normal impact at low Weber numbers; 2) a model that elaborates how wettability can be manipulated to guide an asymmetric lamella towards a symmetric shape; and 3) experimental validation of this model. This work demonstrates that rim formation is driven by a developing motion at the lamella edge — the rim region — induced by deceleration due to capillary forces. The dynamic pressure from this motion creates a difference in curvature, and hence the dynamic pressure must be balanced by the Laplace pressure within the rim region. The rim forms when the rim region becomes thicker than the lamella. An analytical model was developed to predict the time when the rim starts to form and the configuration of the droplet at this moment, validated by OpenFOAM simulations and experimental recordings. Experimental results also support the proposed model for symmetry restoration based on the Taylor-Culick theory, demonstrating that manipulating wettability can accelerate the receding of the stretched contact line to counteract the stretch. A method for fabricating a patch with tunable wettability contrast has been developed for surface design to achieve symmetry restoration. Experimental results confirm the effectiveness of this patch design in correcting asymmetric spreading for water droplets impacting a surface under the following Weber number conditions: Wen ≤ 300, Wet ≤ 300, and 0.51 ≤Wen ⁄ Wet≤2.04.
Access status: Open Access ,
Design, Development, and Validation of an End-User Photo-Thermal Sensing Platform for Rapid Detection and Quantification of Analytes in Fluidic Samples
(2025-04-10) Hayden, Derek William; Tabatabaei, Nima
The ability to detect the presence of specific analytes and quantify their titers in fluidic samples is essential in many industries, spanning from food industries to law enforcement to healthcare and beyond. The existing technologies used for this purpose require the use of specialty equipment by trained professionals in a laboratory setting to function (e.g., mass spectrometry or ELISA) which greatly increases the cost and time taken to receive actionable results. Portable and inexpensive tests exist – Lateral Flow Immunoassays – however these tests are only qualitative and frequently have an inferior limit of detection. To date, several sensing devices have been designed to interrogate these LFIAs and decrease their limit of detection, however, these devices are often prohibitively expensive. This thesis outlines attempts to design and validate a sensing platform which could inexpensively enhance the limit of detection of LFIAs.The prototype is then validated through both lab-based and human experiments.

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