<p>The production of a novel micropump based on the synthetic jet principle is investigated both numerically and experimentally. The proposed micropump consists of a synthetic jet actuator driven by a vibrating diaphragm issuing into an inverted T- shaped channel structure forming the inlet/outlet channels of the pump.</p> <p>The software package Ansys is used to perform numerical investigations of the operation of the proposed micropump. Simulations were performed to study the effect of changing the inlet/outlet channel dimensions as well as the operating frequency, amplitude and duty cycle of the excitation signal. Inlet/outlet channel widths ranging from 200 to 800 μm and operating amplitude and frequency of excitation of the 5 mm square membrane driving the synthetic jet actuator ranging from 20 to 60 μm and from 20 to 60 Hz respectively were investigated.</p> <p>Based on the findings of the numerical simulations, a prototype design was chosen and produced. Prototype production using microfabrication techniques as well as micromachining was investigated. The final prototype was micromachined using plexiglass as the working material. An experimental setup was constructed to test the performance of the produced prototype, which allowed for measuring the produced flow rate, pressure head, actuation amplitude and frequency.</p> <p>The findings of the numerical simulations verified the possibility to produce a working micropump with flow rates of up to 1.3 ml/min. Simulation results also showed the dependence of the produced flow rate on both the inlet and outlet channel widths. An increase in the inlet channel width resulted in a gain in the average flow rate through the pump while an increase in the outlet channel width results in a reduction in the flow rate. Increases in either the actuation amplitude or frequency of excitation both resulted in an improvement in the produced flow rate. Changes in the ejection duty cycle, or the ejection time relative to the suction time during an actuation cycle, were found to influence the flow rate produced by the pump. A shorter ejection time produced a higher flow rate from the pump as compared to a longer ejection time. It was also found that changes in dimensions or operating parameters affected the fluctuations in the flow rate through the pump associated with the pulsating nature of the synthetic jet. Experimental investigations confirmed the findings of the numerical simulations in terms of the flow rate and the trends in the dependence of the flow rate on operating parameters. Values of maximum back pressure of up to 500 Pa were also reported experimentally and membrane driving powers of up to 122 μW were calculated numerically.</p> / Doctor of Philosophy (PhD)

<p>Gallium nitride (GaN) nanowires are high-performance materials with wide, direct bandgaps and superior electronic properties. Although their properties make them of great interest for next-generation technologies, widespread adoption has been limited by expensive production processes. Here, the results of growing GaN nanowires via DC magnetron sputtering at different temperatures and using different metal catalysts are reported.</p> <p>A new substrate heater was designed to minimize contamination from the heater filament and increase the substrate temperature window to in excess of 800°C. Sixteen-mm² (111) silicon samples had one-to-four nm of a metal catalyst deposited on them using evaporation. This metal catalyst layer (gold, platinum, or nickel) was employed to induce catalyst-assisted vapor-liquid-solid nanowire growth. GaN was deposited via a reactive nitrogen DC magnetron sputtering system. Surface morphology and composition were analyzed using both scanning and transmission electron microscopy. Energy-dispersive x-ray spectroscopy (EDS) and electron energy loss spectroscopy were used to measure the presence of gallium and nitrogen in the resulting nanowires, respectively.</p> <p>This furnace significantly reduced tungsten contamination to below the detectable levels of EDS. GaN nanowires were present on gold-catalyzed samples only in the gold-covered region of the silicon substrate exposed to a gallium flux. Nanowire morphology improved as temperature was elevated, but it did so at the cost of lower areal density. Conversely, platinum-coated samples yielded fewer nanowires than their gold-coated counterparts. Samples that had nickel deposited on them displayed the best GaN nanowire growths. They had the best surface morphologies, had negligible oxygen concentrations, and were single crystalline.</p> / Master of Applied Science (MASc)

Advanced oxidation of organic pollutants with TiO2 photocatalysts is limited due to the wide bandgap of TiO2, 3.2 eV, which requires ultraviolet (UV) radiation. When nanosized TiO2 is modified by carbon doping, charge recombination is inhibited and the bandgap is narrowed, allowing for efficient photodegradation under visible light. Here, we propose a flame spray pyrolysis (FSP) technique to create TiO2. The facile process of FSP has been successful in preparing highly crystalline TiO2 nanoparticles. Using the same procedure to deposit TiO2 onto biochar, the photocatalyst was doped by the carbonaceous material. The morphology, crystalline and electronic structure of the FSP TiO2 and TiO2-decorated biochar (TiO2-BC) were characterized by SEM, XRD, TGA, DLS, and diffuse reflectance UV-vis spectroscopy. Photocatalytic performance of TiO2 and TiO2-BC was investigated for model organic contaminants in an aqueous solution under UV and visible light, which will be compared to that of Degussa P25 TiO2 as a control.

Monitoring biological systems is crucial in healthcare, driving the need for reliable and noninvasive solutions. The proliferation of unverified drugs in the market necessitates reliable methods for their detection and identification, especially amidst advancements in pharmaceuticals. Plasmonic biosensors emerge as a great platform for ultra-sensitive detection, identification, and manipulation of biomolecular systems. This dissertation report addresses the critical need for precise detection and monitoring of biomolecules and drugs, presenting innovative solutions through the design of a plasmonic biosensor to tackle challenges in sensitivity, selectivity, and label-free detection and identification. We introduce a robust and tunable, cavity-integrated plasmonic nanopatterned sensor that exhibits superchiral light in the infrared domain for ultrasensitive detection of chiral molecular concentrations and enantiomeric excesses. The multispectral capability of this system is further harnessed to generate unique chiral fingerprint-based barcodes for the identification of diverse chiral drugs and biomolecules. We further discuss and demonstrate results for a surface-modified plasmonic biosensor operating in the visible-near-infrared realm in detecting viral biomarkers and neurotransmitters directly from complex physiological environments. The system, on coupling with a microfluidic flow setup allows sensitive, selective and rapid detection without requiring complex pre-processing or sample preparation steps. We discuss additional applications of the unique plasmonic sensor, utilizing the property of tunable superchirality to create a dynamic chirality tracking system operating in the near infrared for real-time monitoring of protein dynamics. These techniques aim to revolutionize bio-detection, chiral differentiation, and sorting processes, having extensive applications in medical research and pharmaceutical industries.

Inkjet additive manufacturing is the next step toward ubiquitous manufacturing by enabling multi-material printing that can exhibit various mechanical, electronic, and thermal properties. These characteristics are realized in the careful formulation of the inks and their functional materials, but there are many constraints that need to be satisfied to allow optimal jetting performance and build quality when used in an inkjet 3-D printer. Previous research has addressed the desirable rheology characteristics to enable stable drop formation and how the metallic nanoparticles affect the viscosity of inks. The contending goals of increasing nanoparticle-loading to improve material deposition rates while trying to maintain optimal flow dynamics is the closely held trade secret in formulating these inkjet compositions. We use data from previous experiments and the CRC Handbook of Chemistry and Physics to train machine learning regression models to predict the relevant factors of inkjet printability at a standardized temperature of 25ºC: viscosity, surface tension, and density. These models were used to predict the rheological factors of the main components of a UV-curable inkjet ink formulation: UV-curable monomers and oligomers, photoinitiators, dispersants, and humectants. This paper compares the relative performance of five machine learning algorithms to assess the effectiveness of each approach for chemoinformatics regression tasks.

Study on nanoparticle additives in multiphase systems (liquid, polymer) are of immense interest in developing new product applications. Critical challenges for nanoparticle additives include their synthesis, formulation and characterization. These challenges are addressed in three application areas: nanofluids for engine lubrication, ultrathin nanocomposites for optical devices, and nanoparticle size distribution characterization. Nanoparticle additives in oligomer mixtures can be used to develop extended temperature range motor oils. A model system includes poly(α-olefin) based oligomers with a modest fraction of poly(dimethylsiloxane) oligomers along with graphite as nanoparticle additive. Partition coefficients of each oligomer are determined since the oligomer mixture phase separated at temperatures less than -15 °C. Also, the surface of graphite additive is quantitatively analyzed and modified via silanization for each oligomer. Thus, upon separation of the oligomer mixture, each functionalized graphite additive migrates to its preferred oligomers and forms a uniform dispersion. Similarly, nanoparticle additives in polymer matrices can be used to develop new low haze ultrathin film optical coatings. A model system included an acrylate monomer as the continuous phase with monodisperse or bidisperse mixtures of silica nanoparticles deposited on glass and polycarbonate substrates. Surface (root mean squared roughness, Wenzel’s contact angle) and optical properties (haze) of these self assembled experimental surfaces were compared to simulated surface structures. Manipulating the size ratios of silica nanoparticle mixtures varied the average surface roughness and the height distributions, producing multimodal structures with different packing fractions. In both nanofluid and nanocomposite applications, nanoparticle additives tend to aggregate/agglomerate depending on various factors including the state of nanoparticles (powder, dispersion). A set of well-characterized ceria and titania nanoparticle products from commercial sources along with in-lab synthesized nanoparticles were studied via fractal theory. Fractal coefficients were obtained through two-dimensional images (from electron microscopy) and particle size distributions (from electron microscopy and dynamic light scattering). For some arbitrary collections of aggregated nanoparticle materials, the fractal coefficients via two-dimensional images correlated well to the average primary particle size. This complementary tool could be used along with conventional nanoparticle characterization techniques when not much is known about the nanoparticle surfaces to characterize agglomeration or aggregation phenomena.

Surface integrity of manufactured components has a critical impact on their functional performance. Magnesium alloys are lightweight materials used in the transportation industry and are also emerging as a potential material for biodegradable medical implants. However, the unsatisfactory corrosion performance of Mg alloys limits their application to a great extent. Surface integrity factors, such as grain size, crystallographic orientation and residual stress, have been proved to remarkably influence the functional performance of magnesium alloys, including corrosion resistance, wear resistance and fatigue life. In this dissertation, the influence of machining conditions, including dry and cryogenic cooling (liquid nitrogen was sprayed to the machined surface during machining), cutting edge radius, cutting speed and feed rate, on the surface integrity of AZ31B Mg alloy was investigated. Cryogenic machining led to the formation of a "featureless layer" on the machined surface where significant grain refinement from 12 μm to 31 nm occurred due to dynamic recrystallization (DRX), as well as increased intensity of basal plane on the surface and more compressive residual stresses. Dry and cryogenic burnishing experiments of the same material were conducted using a fixed roller setup. The thickness of the processed-influenced layer, where remarkable microstructural changes occurred, was dramatically increased from the maximum value of 20 μm during machining to 3.4 mm during burnishing. The burnishing process also produced a stronger basal texture on the surface than the machining process. Preliminary corrosion tests were conducted to evaluate the corrosion performance of selected machined and burnished AZ31B Mg samples in 5% NaCl solution and simulated body fluid (SBF). Cryogenic cooling and large edge radius tools were found to significantly improve the corrosion performance of machined samples in both solutions. The largest improvement in the material's corrosion performance was achieved by burnishing. A finite element study was conducted for machining of AZ31B Mg alloy and calibrated using the experimental data. A user subroutine was developed and incorporated to predict the grain size changes induced by machining. Good agreements between the predicted and measured grain size as well as thickness of featureless layers were achieved. Numerical studies were extended to include the influence of rake angle, feed rate and cutting speed on the featureless layer formation.

Liposomal delivery systems hold considerable promise for improvement of cancer therapy provided that critical formulation design criteria can be met. The main objective of the current project was to enable quality by design in the formulation of liposomal delivery systems by developing comprehensive, mechanism-based mathematical models of drug loading, binding and release kinetics that take into account not only the therapeutic requirement but the physicochemical properties of the drug, the bilayer membrane, and the intraliposomal microenvironment. Membrane binding of the drug affects both drug loading and release from liposomes. The influence of bilayer composition and phase structure on the partitioning behavior of a model non-polar drug, dexamethasone, and its water soluble prodrug, dexamethasone phosphate, was evaluated. Consequently, a quantitative dependence of the partition coefficient on the free surface area of the bilayer, a property related to acyl chain ordering, was noted. The efficacy of liposomal formulations is critically dependent on the drug release rates from liposomes. However, various formulation efforts to design optimal release rates are futile without a validated characterization method. The pitfalls of the commonly used dynamic dialysis method for determination of apparent release kinetics from nanoparticles were highlighted along with the experimental and mathematical approaches to overcome them. The value of using mechanism-based models to obtain the actual rate constant for nanoparticle release was demonstrated. A novel method to improve liposomal loading of poorly soluble ionizable drugs using supersaturated drug solutions was developed using the model drug AR-67 (7-t-butyldimethylsilyl-10-hydroxycamptothecin), a poorly soluble camptothecin analogue. Enhanced loading with a drug to lipid ratio of 0.17 was achieved and the rate and extent of loading was explained by a mathematical model that took into account the chemical equilibria inside and outside the vesicles and the transport kinetics of various permeable species across the lipid bilayer and the dialysis membrane. Tunable liposomal release kinetics would be highly desirable to meet the varying therapeutic requirements. A large range of liposome release half-lives from 1 hr to 892 hr were obtained by modulation of intraliposomal pH and lipid composition using dexamethasone phosphate as a model ionizable drug. The mathematical models developed were successful in accounting for the change in apparent permeability with change in intraliposomal pH and bilayer free surface area. This work demonstrates the critical role of mechanism-based models in design of liposomal formulations.

The enhancement of strength of nanoscale materials such as face-centered cubic metal nanowires is well known and arises largely from processes mediated by high energy surface atoms. This leads to strong size effects in nanoscale plasticity; ,smaller is stronger. Yet, other factors, such as crystalline defects also contribute greatly to the mechanical properties. In particular, twin boundaries, which are pervasive and energetically favorable defects in face-centered cubic metal nanowires, have been shown to greatly enhance the strength, furthermore this increase in strength has been shown to be directly influenced by the twin density. However, attempts to control the introduction of beneficial defects remains challenging. Additionally, even minor local variations in the crystalline structure or size of metal nanowires may have drastic effects on the yielding of metal nanowires, which are difficult to measure through tensile and bending tests. In this study, atomic force microscopy based nanoindentation techniques are used to measure the local plasticity of Ni-Au bimetallic as well as Cu and Ag metallic nanowires. In the first part of the thesis the hardness of bimetallic nanowires synthesized through template-assisted electrodeposition is measured and found to show significant size-effects. It was found that the nanoindentation hardness was governed by materials properties, the observed indentation size effects were dependent on geometrical factors. The second part of this thesis presents a methodology to control the crystal structure of Ag and Cu nanowires through direct electrodeposition techniques, which were tested directly as grown on the substrate to limit effects of pre-straining. Ag nanowires showed marked size-effects as well as two distinct modes of deformation which we attribute to the defects that arise during crystalline growth. We also show control of the surface microstructure in Cu nanowires which leads to strengths that are more than doubled compared to single crystalline Cu nanowires. Finally, we present support from classic crystal growth theory to justify that the observed plasticity in Ag and Cu nanowires is largely dependent on defects that are nucleated through changes in the growth environment.

Biomolecules on cell surfaces play critical roles in diverse biological and physiological processes. However, conventional bulk scale techniques are unable to clarify the density and distribution of specific biomolecules in situ on single, living cell surfaces at the micro or nanoscale. In this work, a single cell analysis technique based on Atomic Force Microscopy (AFM) is developed to spatially identify biomolecules and characterize nanomechanical properties on single cell surfaces. The unique advantage of these AFM-based techniques lies in the ability to operate in situ (in a non-destructive fashion) and in real time, under physiological conditions or controlled micro-environments. First, AFM-based force spectroscopy was developed to study the fundamental biophysics of the heparin/thrombin interaction at the molecular level. Based on force spectroscopy, a force recognition mapping strategy was developed and optimized to spatially detect single protein targets on non-biological surfaces. This platform was then translated to the study of complex living cell surfaces. Specific carbohydrate compositions and changes in their distribution, as well as elasticity change were obtained by monitoring Bacillus cells sporulation process. The AFM-based force mapping technique was applied to different cellular systems to develop a cell surface biomolecule library. Nanoscale imaging combined with carbohydrate mapping was used to evaluate inactivation methods and growth temperatures effects on Yersinia pestis surface. A strategy to image cells in real time was coupled with hydrophobicity mapping technique to monitor the effect of antimicrobials (antimicrobial polymer and copper) on Escherichia coli and study their killing mechanisms. The single spore hydrophobicity mapping was used to localize the exosporium structure and potentially reconstruct culture media. The descriptions of cell surface DNA on single human epithelial cells potentially form a novel tool for forensic identification. Overall, these nanoscale tools to detect and assess changes in cell behavior and function over time, either as a result of natural state changes or when perturbed, will further our understanding of fundamental biological processes and lead to novel, robust methods for the analysis of individual cells. Real time analysis of cells can be used for the development of lab-on-chip type assays for drug design and testing or to test the efficacy of antimicrobials.