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Aerosol-Based Ultrafine Material Deposition for Microelectronics
(North Dakota State University, 2012) Hoey, Justin Michael
Aerosol-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.
Improving Performance Characteristics of Poly (Lactic Acid) (PLA) Based Nanocomposites by Enhanced Dispersion of Modified Cellulose Nanocrystals (CNCs)
(North Dakota State University, 2018) Shojaeiarani, Jamileh
Poly(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.
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, Hesam
In 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.
Simulation-Based Optimization and Artificial Intelligence Techniques for Macromechanical and Micromechanical Characterization of Soft Biological Tissues
(North Dakota State University, 2021) Ramzanpour, Mohammadreza
Traumatic 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.
Experimental and Micromechanical Analysis of Flax and Glass Reinforced Bio-Based Composites
(North Dakota State University, 2015) Hosseini, Nassibeh
Two different novel high-functional bio-based resins from Methoxylated Sucrose Soyate Polyol (MSSP) and methacrylated epoxidized sucrose soyate (MAESS) were used as matrices for composites. Vinyl ester reinforced with flax fiber and E-glass fiber were also produced as the references to highlight the performance of bio-based composites. An appropriate processing conditions for MSSP and MAESS resins using compression molding was established to fabricate high fiber volume content composites. Mechanical properties of composites were assessed by tensile, flexural, interlaminar shear strength (ILSS), nano-indentation, and impact strength. Scanning Electron Microscopy (SEM) of fractured surfaces of flexural specimens were examined to investigate the fiber-matrix interface behavior. MSSP and MAESS resins reinforced with E-glass fiber performed similarly if not superior to previous bio-based and petroleum-based composites studied Tensile strength and modulus of E-glass reinforced MSSP were higher up to 40% and 75% respectively, compared to existing studies. For flexural strength and modulus 130% and 110% improvements were observed. The tensile strength and modules of MAESS and vinyl ester resins reinforced with E-glass fibers are 532 MPa, 36.79 GPa and 536 MPa, 36.40 GPa, respectively. The impact strength of the composites with MAESS resin reinforced with E-glass fibers was 237 kJ/m2, whereas that of the vinyl ester resin reinforced with same E-glass fiber was 191 kJ/m2. Results of SEM images along with flexural strength, interlaminar shear strength and impact tests revealed better wetting of fibers by matrix, stronger adhesion between fiber and matrix and greater interfacial bonding compared to corresponding E-glass/vinyl ester composites. The composites made from flax fiber with MSSP or MAESS resins achieve similar properties to E-glass/MSSP and E-glass/MAESS in terms of specific mechanical properties. Moreover, flax/MSSP and flax/MAESS composites perform similarly, if not superior to previous bio-based and petroleum based composites studied. A micromechanical model and an analytical approach were also developed to predict the stress relaxation response of the flax/MSSP composite material consisting linear viscoelastic flax fiber and bio-based PU matrix. A good agreement between the micromechanical modeling data and experimental results was observed for the linear viscoelastic response of the bio-based composite.
Optimized Evaluation of Bone Tissue Material Properties by Inverse Finite Element Analysis and Femur Fracture Testing
(North Dakota State University, 2015) Javid, Samad
The main objective of this research is to characterize bone inhomogeneous elastic, yield, and post-yield behaviors, using a computational-experimental approach. The current study uses the force-displacement results of one hundred four cadaveric femora that were previously tested to fracture in a fall on the hip loading configuration. Recorded force-displacement data are used to determine stiffness, yield force, and femoral strength values. Finite element (FE) models of the femora are developed from the quantitative computed tomography scans captured before the fracture tests. A power law, or a sigmoid function, is used to determine the elastic modulus from the ash densities for each case modeled. The models are used for FE simulations that mimic the experiments. Inverse finite element analysis is employed to identify the unknown coefficients in the bone density-elasticity relationships. Optimization algorithms are used to minimize the error function between the experimental and FE estimated results in a large subset of female femora. The results of the obtained relationships show a good agreement with the experimental data. This contributes to a coefficient of determination of 70%, which is higher than those of previously proposed density-elasticity relationships on the same set of femora. The parts of the bones with the densities up to 0.5 g/cm3, play an important role in the deformation of the neck and the head of the femur. While power law and sigmoid function show similar correlation in the prediction of stiffness, distribution of stresses and strains are notably different, showing different response in the yield and post-yield behavior. To simulate the material damage, a power density-yield strain relationship is used as the failure criterion in FE models, assuming a ductile and a brittle material behavior for the bone. The unknown coefficients in the density-yield strain relationship are identified for the ductile and brittle material models. The ductile material model shows a more realistic post-yield behavior iv than the brittle model, but it is computationally expensive and may face convergence issues due to nonlinearities. The brittle material model, on the other hand, estimates the bone strength fairly and, due to its simplicity, it seems more applicable for clinical use.
Experimental and Theoretical Studies of Nanostructured Electrodes for Use in Dye-Sensitized Solar Cells
(North Dakota State University, 2017) Gong, Jiawei
Among various photovoltaic technologies available in the emerging market, dye-sensitized solar cells (DSSCs) are deemed as an effective, competitive solution to the increasing demand for high-efficiency PV devices. To move towards full commercialization, challenges remain in further improvement of device stability as well as reduction of material and manufacturing costs. This study aims at rational synthesis and photovoltaic characterization of two nanostructured electrode materials (i.e. SnO2 nanofibers and activated graphene nanoplatelets) for use as photoanode and counter electrode in dye-sensitized solar cells. The main objective is to explore the favorable charge transport features of SnO2 nanofiber network and simultaneously replace the high-priced conventional electrocatalytic nanomaterials (e.g. Pt nanoparticles) used in existing counter electrode of DSSCs. To achieve this objective, a multiphysics model of electrode kinetics was developed to optimize various design parameters and cell configurations. The porous hollow SnO2 nanofibers were successfully synthesized via a facile route consisting of electrospinning precursor polymer nanofibers, followed by controlled carbonization. The novel SnO2/TiO2 composite photoanode materials carry advantages of SnO2 nanofiber network (e.g. nanostructural continuity, high electron mobility) and TiO2 nanoparticles (e.g. high specific area), and therefore show excellent photovoltaic properties including improved short-circuit current and fill factors. In addition, hydrothermally activated graphene nanoplatelets (aGNP) were used as a catalytic counter electrode material to substitute for conventionally used platinum nanoparticles. Improved catalytic performance of aGNP electrode was achieved through increased surface area and better control of morphology. Dye-sensitized solar cells using these aGNP electrodes had power conversion efficiencies comparable to those using platinum nanoparticles with I-/I3- redox mediators. Moreover, a multiphysics model at the device level was developed to predict the power output characteristics of DSSC using different electrode materials. The developed model was validated by the experimental data acquired from lab-fabricated DSSCs. Further, parametric simulation was conducted to analyze the effect of series resistance, shunt resistance, interfacial overpotential, as well as difference between the conduction band and formal redox potentials on device performance. This model correlates the maximum power output of DSSC devices to various design and operating parameters, and it also provides insight into the working principles of newly designed devices.
Brain Tissue Mechanical Characterization and Determination of Brain Response under Confined Blasts Explosions
(North Dakota State University, 2015) Rezaei, Asghar
Mechanical experimental tests including stress relaxation, simple monotonic ramps, and impact loads were performed on porcine brain tissues to investigate the response of the brain under different loading scenarios. Linear viscoelastic models were employed to determine the applicability and limitations of the linear mechanical models in tension. In addition the lowest and highest stress values, which can be possibly applied to the tissue due to change in the strain rates, were investigated using stress relaxation experiments to implicitly address the two levels of strain rates. Porcine brainstem samples were tested in six stress relaxation experimental settings at strain amplitudes ranging from 5% to 30% in compression. The lowest stress was directly measured from long-term responses of stress relaxation experiments when the stress values remained constant. The highest stress level was determined by using the quasi-linear viscoelasticity theory and estimating the instantaneous stress of the samples at six strain amplitudes. It was hypothesized that there is a correlation between the two pure elastic behaviors. The hypothesis was true as a strong linear correlation was found between the two elastic responses. The results showed that the instantaneous stress values were 11 times greater than the long-term stress values, practically similar across all strain amplitudes. In the second part of the thesis, a number of computational studies were conducted using a validated human head model. The head model included major components of human head and underwent different blast scenarios in open and confined spaces. The study investigated the effect of reflections from the walls. The results show that when the head was in the vicinity of the wall, the biomechanical parameters were dramatically increased, especially in the corners. Comparing brain biomechanical parameters in confined, semi-confined, and open spaces under blast loads, the brain sustained greater stress and strain values, with larger duration of the loads, in confined spaces. Also, a primary blast injury (PBI) with a tertiary blast injury (TeBI) in a confined space was compared. The results indicated that the PBI due to the incident shock wave was much more injurious than TeBI due to blunt impact.
The Physico-Chemical Investigation of Interfacial Properties in Natural Fiber/Vinyl Ester Biocomposites
(North Dakota State University, 2012) Huo, Shanshan
Bast fibers are one of most widely used types of cellulosic natural fibers. Flax fibers, a specific type of bast fiber, have historically been used as reinforcements in composites because they offer competitive advantages, including environmental and economic benefits, over mineral-based reinforcing materials. However, the poor interfacial properties due to the hydrophilicity of flax fibers and the hydrophobicity of most polymer matrices reduce the mechanical performance of flax thermoset composites. On the other hand, the structure of flax fiber is more complex than synthetic fibers, which causes most of traditional mechanical tests from the transverse direction to evaluate the interfacial properties of flax composites are not valid. In this study, the physical and chemical properties of flax fibers, vinyl ester resin and their composites are investigated. A comprehensive understanding of flax fiber, vinyl ester systems and their composites has been established. Surface modifications to the flax fiber and chemical manipulations on vinyl ester systems have been studied to improve the interfacial properties of flax/vinyl ester biocomposites. A new chemical manipulation method for vinyl ester system has been invented. The specific interlaminar shear strength of alkaline treated flax/VE with 1.5% AR shows approximately 149% increase than untreated flax/VE composites. NaOH/Ethanol treated flax/VE with AR shows 33% higher in specific flexural modulus and 73% better in specific flexural strength than untreated flax/VE composites. In addition, AR modified alkaline treated flax composites performs approximately 75% better in specific tensile modulus and 201% higher in specific tensile strength than untreated flax/VE composites. Flax/VE composite with high elastic modulus, which is higher than their theoretically predicted elastic modulus, was achieved. The effects of thermal properties of flax fibers and vinyl ester resin systems on the interfacial properties of their biocomposites were also studied. The theory of modifying the thermal properties of flax and vinyl ester to improve the interfacial adhesion has been proved by the study of the thermal residual stresses in their composites by XRD techniques.
High-Performance Simulations for Atmospheric Pressure Plasma Reactor
(North Dakota State University, 2012) Chugunov, Svyatoslav
Plasma-assisted processing and deposition of materials is an important component of modern industrial applications, with plasma reactors sharing 30% to 40% of manufacturing steps in microelectronics production [1]. Development of new flexible electronics increases demands for efficient high-throughput deposition methods and roll-to-roll processing of materials. The current work represents an attempt of practical design and numerical modeling of a plasma enhanced chemical vapor deposition system. The system utilizes plasma at standard pressure and temperature to activate a chemical precursor for protective coatings. A specially designed linear plasma head, that consists of two parallel plates with electrodes placed in the parallel arrangement, is used to resolve clogging issues of currently available commercial plasma heads, as well as to increase the flow-rate of the processed chemicals and to enhance the uniformity of the deposition. A test system is build and discussed in this work. In order to improve operating conditions of the setup and quality of the deposited material, we perform numerical modeling of the plasma system. The theoretical and numerical models presented in this work comprehensively describe plasma generation, recombination, and advection in a channel of arbitrary geometry. Number density of plasma species, their energy content, electric field, and rate parameters are accurately calculated and analyzed in this work. Some interesting engineering outcomes are discussed with a connection to the proposed setup. The numerical model is implemented with the help of high-performance parallel technique and evaluated at a cluster for parallel calculations. A typical performance increase, calculation speed-up, parallel fraction of the code and overall efficiency of the parallel implementation are discussed in details.

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