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Item Aerosol-Based Ultrafine Material Deposition for Microelectronics(North Dakota State University, 2012) Hoey, Justin MichaelAerosol-based direct-write refers to the additive process of printing CAD/CAM features from an apparatus which creates a liquid or solid aerosol beam. Direct-write technologies are poised to become useful tools in the microelectronics industry for rapid prototyping of components such as interconnects, sensors and thin film transistors (TFTs), with new applications for aerosol direct-write being rapidly conceived. This research aims to review direct-write technologies, with an emphasis on aerosol based systems. The different currently available state-of-the-art systems such as Aerosol Jet™ CAB-DW™, MCS and aerodynamic lenses are described. A review and analysis of the physics behind the fluid-particle interactions including Stokes and Saffman force, experimental observations and how a full understanding of theory and experiments can lead to new technology such as nozzle designs are presented. Finally, the applications of aerosol direct-write for microelectronics are discussed in detail including the printing of RFID antennas, contacts and active material for TFTs, the top metallization layer for solar cells, and interconnects for circuitry.Item Improving Performance Characteristics of Poly (Lactic Acid) (PLA) Based Nanocomposites by Enhanced Dispersion of Modified Cellulose Nanocrystals (CNCs)(North Dakota State University, 2018) Shojaeiarani, JamilehPoly(lactic acid), (PLA) is a biodegradable and biocompatible polymer which has attracted significant attention as a promising substitute for petroleum-based polymers. To optimize the usage of PLA in a wide range of applications, different methods such as polymer blending and the incorporation of traditional and nanofillers have been extensively explored. Cellulose nanocrystals (CNCs), rod-like nanoparticles with a perfect crystalline structure, are considered as outstanding reinforcing agent owing to the excellent mechanical properties. The optimal characteristics of CNCs as a reinforcing agent in the polymer can be achieved through homogeneous dispersion within the polymeric matrix. However, the strong hydrophilic character of CNCs due to the presence of hydroxyl groups on the surface restricts the uniform dispersion of CNCs in the PLA matrix. In this work, three surface modification treatments along with two different mechanical preparation techniques were employed to improve the dispersion quality of CNCs in the PLA matrix. Polymer adsorption, green esterification, and time-efficient esterification were used as surface modification treatments. Solvent casting and spin-coating method were employed to prepare highly concentrated CNCs masterbatches. Nanocomposites were prepared using melt extrusion, followed by an injection molding process. The morphology of masterbatches indicated better CNCs dispersion through spin-coated thin films, suggesting a high evaporation rate and the effect of centrifugal force and surface tension in the spin-coating process decrease the possibility of CNCs aggregate through the film. Consequently, nanocomposites manufactured using spin-coated masterbatches exhibited higher mechanical strength in comparison with solvent cast ones. In the case of surface modification treatments, the most uniform CNCs dispersion was observed in the nanocomposites reinforced by valeric acid through esterification technique. Higher thermal stability was also achieved through the application of esterification technique. This observation was related to the presence of DMAP on the surface of CNCs which turns into inert materials, prohibiting the thermal degradation. The higher molecular weight and lower molecular number observed in spin-coated samples in comparison with film cast nanocomposites led to the higher damping behavior in spin-coated nanocomposites. This observation indicated the more viscoelastic properties in spin-coated samples owing to the presence of more polymer chain freedom in spin-coated nanocomposites.Item Design and Fabrication of Micro-Channels and Numerical Analysis of Droplet Motion Near Microfluidic Return Bends(North Dakota State University, 2019) Singh, John-Luke BenjaminThree-dimensional spheroid arrays represent in vivo activity better than conventional 2D cell culturing. A high-throughput microfluidic chip may be capable of depositing cells into spheroid arrays, but it is difficult to regulate the path of individual cells for deposition. Droplets that encapsulate cells may aid in facilitating cell delivery and deposition in the return bend of a microfluidic chip. In this study, a low-cost method for fabricating polymer-cast microfluidic chips has been developed for rapid device prototyping. Computational fluid dynamic (CFD) simulations were conducted to quantify how a change in geometry or fluid properties affects the dynamics of a droplet. These simulations have shown that the deformation, velocity, and trajectory of a droplet are altered when varying the geometry and fluid properties of a multiphase microfluidic system. This quantitative data will be beneficial for the future design of a microfluidic chip for cell deposition into 3D spheroid arrays.Item Survey of Methods for Achieving Low Gasoline Fuel-Permeation in Rotationally-Molded Articles(North Dakota State University, 2018) Nerenz, BrentThe establishment of governmental regulations on the evaporative emission performance of fuel system components has caused molders and their material suppliers to develop innovative materials and processes by which to meet such requirements. Rotational molding is a common processing choice for fuel containers given its ability to produce complex, hollow geometries with consistent wall thickness. A number of strategies have been devised for meeting fuel permeation requirements in rotationally molded containers, each demonstrating significant benefits and detriments to the processor. Single, homogeneous materials have difficulty in simultaneously providing adequate fuel permeation, durability, and affordability. The ability of rotational molding to create containers having a plied, multi-polymer architecture allows molders to create articles which exhibit exceptional performance in each aspect. Multi-layer processing creates unique challenges for the rotational molder; however, different technologies have been demonstrated which enable multi-layer articles to be produced from a single material introduction, thereby maximizing processing efficiency.Item Numerical Simulations of Electrohydrodynamic Evolution of Thin Polymer Films(North Dakota State University, 2015) Borglum, Joshua ChristopherRecently developed needleless electrospinning and electrolithography are two successful techniques that have been utilized extensively for low-cost, scalable, and continuous nano-fabrication. Rational understanding of the electrohydrodynamic principles underneath these nano-manufacturing methods is crucial to fabrication of continuous nanofibers and patterned thin films. This research project is to formulate robust, high-efficiency finite-difference Fourier spectral methods to simulate the electrohydrodynamic evolution of thin polymer films. Two thin-film models were considered and refined. The first was based on reduced lubrication theory; the second further took into account the effect of solvent drying and dewetting of the substrate. Fast Fourier Transform (FFT) based spectral method was integrated into the finite-difference algorithms for fast, accurately solving the governing nonlinear partial differential equations. The present methods have been used to examine the dependencies of the evolving surface features of the thin films upon the model parameters. The present study can be used for fast, controllable nanofabrication.Item Experimental Studies of Pulsatile Flow Passing Side Wall Biological Cavities and Flow Enhancement Using Hydrophobic Surfaces(2020) Eichholz, Benjamin KirkUnderstanding the hemodynamics of the cardiovascular system and associated diseases is important for mitigating health risks. We applied flow diagnostic techniques to investigate pulsatile flow characteristics past sidewall cavities, which have implications to two biomedical problems in the cardiovascular system: sidewall aneurysms and the left atrial appendage. Superhydrophobically-coated mesh diverters and synthetic slippery surfaces were studied for their effects on flow diversion and cavity flow enhancements. The study of pulsatile flow over a coated mesh diverter showed that the formation of the primary vortex was prevented which prevents flow stagnation and downwash flow in the cavity. The second study indicates that the healthy heart cycle is essential to reducing flow stasis inside the left atrial appendage. After applying a synthetic slippery surface to the interior of a side wall cavity model, this surface reduced the wall shear stress and allowed vortical flow to reach deeper into the cavity.Item A Review of Flow Diagnostic Methods and Applications(North Dakota State University, 2023) Dale, MatthewscottThis work provides an overview of common flow velocimetry and diagnostic techniques, including their working principles and the application of these techniques. Probe velocimetry techniques such as pitot tubes and hot wire anemometry are discussed along with unintrusive techniques such as Laser Doppler Velocimetry and Particle Image Velocimetry. Density, pressure, and temperature diagnostic methods are also examined, in particular shadowgraph/schlieren imaging, pressure/temperature sensitive paints, and infrared thermography. Benefits and drawbacks of each method are examined as well as the applications. The goal of this review is to provide the reader with a basic understanding of the methods discussed, as well as to give insight as to which methods are particularly useful and applicable to engineering measurements.Item Computational Biomechanics of Blast-Induced Traumatic Brain Injury: Role of Loading Directionality, Head Protection, and Blast Flow Mechanics(North Dakota State University, 2015) Sarvghad-Moghaddam, HesamIn this dissertation, blast-induced traumatic brain injury (bTBI) is studied with respect to the blast wave directionality, mitigation capability of helmet/faceshield, and blast flow mechanics using finite element (FE) and computational fluid dynamics (CFD) schemes. For the FE study, simulations are performed on a detailed FE head model using LS-DYNA, and CFD simulations are carried out using the ANSYS-CFX to examine the underwash development by analyzing the behavior of blast flow from different directions. The following tasks are conducted. First, the effects of the loading direction on the mechanical response of the head and brain is investigated through impact and blast induced loading on the head. Due to the differences in the shape, function, and tolerance of brain components, the response of the head/brain varies with the direction of the impact and blast waves. In identical situations, the head shows to have lower tolerance to side loading. Second, the inclusion of the faceshield as a potential head protective tool against blast threats is evaluated with respect to blast direction. The helmet-faceshield and helmeted assemblies are shown to be most efficient when the head is exposed to blast from the front and top sides, respectively. Faceshield is observed to be effective only in front blast as it might impose either adverse or no effects in other directions. The shockwaves are seen to form a high pressure region in head-helmet-faceshield gap (underwash effect) which induces elevated pressures on the skull. Third, the underwash effect’s mechanism is investigated through CFD simulations of supersonic shockwave flow around the helmeted head assemblies. CFD results reveals that the backpressure is produced due to the creation of a backflow in the exterior flow on the outgoing interior flow. The bottom and side shockwave directions predict the highest underwash overpressures, respectively. Finally, the ICP and shear stress of the brain is evaluated in case of underwash incidence. FEA results show that underwash overpressure greatly changes with the blast direction. It is concluded that underwash clearly altered the tissue response of the brain as it increases ICP levels at the countercoup site and imparts elevated skull flexure.Item Simulation-Based Optimization and Artificial Intelligence Techniques for Macromechanical and Micromechanical Characterization of Soft Biological Tissues(North Dakota State University, 2021) Ramzanpour, MohammadrezaTraumatic brain injury (TBI) is a serious health and socioeconomic issue which affects thousands of lives annually in the United States. Computational simulations play an important role in better understanding of the TBI and on how it happens. Having accurate material properties of the brain tissue and the elements of the brain will help with more accurate computational simulations. Material characterization is therefore the line on which lots of research have been conducted. In recent years, the emerge of data driven approaches has led to better and more accurate soft tissue characterization. In this dissertation, a metaheuristic search optimization method together with simulation-based optimization framework, and artificial intelligence-based approaches have been employed for macromechanical and micromechanical characterization of brain tissue. First, a constrained particle swarm optimization (C-PSO) technique has been established for soft tissue characterization that overcomes the shortcomings of the classical optimization methods. Through the application of the inherent constraints in the hyperelastic and visco-hyperelastic models, it became possible to reduce the time complexity of this optimization algorithm. Subsequently, the developed constrained optimization method was employed to create simulation-based optimization frameworks for characterizing the micro-level constituents of human brain white matter including axons and extracellular matrix using the hyperelastic and visco-hyperelastic constitutive models. This simulation-based optimization framework helps the researchers to go around the complexities involved with the experimental techniques on micro-level characterization of soft tissues. The final part of this dissertation is devoted to the development of the machine learning and deep learning techniques for classifying the tissue stiffness out of the finite element (FE) simulation results. Through the training of a regularized logistic regression and deep learning convolutional neural networks, it became possible to correctly predict more than 91% of the cases of tissues with high stiffness. The tissues with high stiffness are usually indicative of the pathology and hence are important from medical perspective. The outcome of this part of the work could be useful for qualitative description of the soft biological tissue stiffness and pathology diagnosis which can be used as an alternative to the inversion algorithms.Item Computational Investigation of Low-Pressure Turbine Aerodynamics(North Dakota State University, 2015) Flage, Alexander PaulThe design of today’s gas turbine engines is heavily reliant on accurate computational fluid flow models. Creating prototype designs is far more expensive than modeling the design on a computer; however, current turbulence and transitional flow models are not always accurate. Several turbulence and transition models were validated at North Dakota State University by analyzing the flow through a low pressure turbine of a gas turbine engine. Experimental data for these low pressure turbines was provided by the University of North Dakota. Two separate airfoil geometries are analyzed in this study. The first geometry is a first stage flow vane, and the second geometry is an incidence angle tolerant turbine blade. Pressure and heat transfer data were compared between computations and experiments on the turbine blade surfaces. Simulations were conducted with varying Reynolds numbers, Mach numbers, and free stream turbulence intensities and were then compared with experiments.