Theses and Dissertations at Montana State University (MSU)

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    Illuminating dynamic phenomena within organic microstructures with time resolved broadband microscopies
    (Montana State University - Bozeman, College of Letters & Science, 2024) Hollinbeck, Skyler Robert; Chairperson, Graduate Committee: Erik Grumstrup; This is a manuscript style paper that includes co-authored chapters.
    Materials derived from organic chromophore subunits are currently at the forefront of academic and industrial interest. This strong interest is driven in part by the tunability of their extant properties through engineering of both the intra-molecular and inter-molecular structure. The structure of organic materials affects optoelectronic properties because organic chromophores are sensitive to dipole-dipole and charge-transfer coupling interactions. This sensitivity presents both opportunities for tuning functional properties through designing specific packing geometries, and liabilities arising from the disruptive effects of structural disorder. Many organic materials are built from weak noncovalent interactions between chromophores, leading solid-state deposition, and crystallization to be susceptible to microscopic variations in environmental conditions. Structural heterogeneity is regularly intrinsic to organic materials, and even self-assembled systems of covalently linked chromophores exhibit defects. Ergo, in order to disentangle the effects of structural heterogeneity from the inherent properties of the material, the study of organic materials must be anchored with techniques that are capable of correlating optoelectronic properties and excited state evolution with microscale morphological characteristics. We have employed broadband pump-probe microscopies, in conjunction with steady-state and time resolved fluorescence techniques, to examine the effects of structure and coupling on excited state dynamics in solid-state organic microstructures. The study of perylene diimide (PDI) materials revealed that kinetically trapping PDI (KT-PDI) enhanced long-range ordering and led to distinct excited state evolution, delocalized charge-transfer states and long-lived charge separated species. In the MOF PCN-222, excitation energy dependent excited state behavior was observed. Pumping the first excited state (Q-band) led to immobile excited states that were relatively unaffected by local defect densities, whereas pumping the second excited state (Soret-band) led to mobile subdiffusive excited state species whose lifetimes are significantly impacted by morphologically correlated defect sites. Finally, we present progress made toward the construction and utilization of a frequency modulated-femtosecond stimulated Raman microscope, yielding spectra that resolve the location of photoinduced anion formation in KT-PDI. The work presented herein highlights broadband time-resolved microscopy as a potent tool for studying the structure-function relationship and photophysical behavior in molecular solids, deepening our understanding of how structural characteristics influence excited state evolution.
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    Numerical modelling of nanoparticle diffusion and microstructure formation during selective laser melting process
    (Montana State University - Bozeman, College of Engineering, 2022) Alam, Taosif; Chairperson, Graduate Committee: M. Ruhul Amin
    Selective laser melting (SLM) is a popular metal additive manufacturing technique that has a wide range of industrial applications lately. This additive process allows the development of new metal matrix nanocomposites by fusing metallic powders with nanoparticles. However, the molten pool flow generated by a moving laser heat source has complex fluid dynamics which redistribute the nanoparticles. Consequently, the microstructures of the solidified molten pool are affected by the local distribution of nanoparticles, which is reflected in their mechanical properties. Smaller grains can increase the strength and isotropic behavior of the solid layers. Therefore, the current research aims to numerically investigate the relationships among the SLM process parameters, nanoparticle transport, and microstructure evolution to explore the formation of nanocomposites. The current study formulated a three-dimensional computational fluid dynamics (CFD) model of the SLM process in a commercial software package, ANSYS FLUENT. A volumetric laser heat source model melted the aluminum alloy powders and the underlying solid substrate. The difference between the powder and the solid or liquid state of the metal alloy was defined using an effective thermal conductivity model. Lagrangian particle transport calculation was performed to track TiB 2 nanoparticles in the molten pool. This model was coupled with a 2D Cellular Automata (CA) model to simulate the solidified microstructure using MATLAB. Finally, a detailed parametric analysis was conducted to study the effects of varying laser power, scanning speed, and preheating temperature. The numerical results showed that the maximum temperature and Marangoni convection in the molten pool increased at higher laser powers, higher preheating temperatures, and lower scanning speeds. The particle-voided region was significantly large with high Marangoni convection but decreased with weaker Marangoni convection. The simulated microstructure was dominated by large columnar grains when nanoparticles were not considered. The introduction of nanoparticles disrupted the columnar grain growth by promoting small, randomly oriented, equiaxed grains. A decrease of 30%-40% in average grain diameter was measured at the cross-section of the solidified layer when nanoparticles were present. The qualitative comparison of the microstructures showed that the grains were smaller in the uniformly distributed particle region compared to the particle-voided region.
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    Fiber shape effects on the compressive strength of unidirectional carbon fiber composites: a computational study
    (Montana State University - Bozeman, College of Engineering, 2020) Clarke, Ryan; Chairperson, Graduate Committee: David A. Miller
    The tensile strength tends to be much higher than the compressive strength for carbon fiber reinforced polymer composites because of a change in failure modes. Current research activities are looking at novel precursors for reducing overall costs of carbon fiber production. The potential cost savings in new precursor carbon fiber make it economically feasible to use in large structural components. Some fiber precursors and manufacturing methods produce carbon fibers that have a kidney-shaped cross-section whereas traditional carbon fiber is circular. The aim of this study is to investigate the differences in compressive failure responses between fiber shapes in carbon fiber composites. A finite element micromechanical model was developed in ABAQUS of a single carbon fiber embedded in a square matrix with periodic boundary conditions. Two fiber cross-sectional geometries were examined: circular and kidney shaped. Three factors that affect the compressive failure response of carbon fiber reinforced polymers were investigated. These include fiber misalignment, volume fraction, and multiaxial loading. The results showed negligible differences between the compressive failure response of fibers with different cross-sectional shapes. Compressive strength was shown to have a decaying sensitivity to increasing fiber misalignment. Decreasing the volume fraction did decrease the compressive strength but also increased the compressive failure strain. In addition, adding in-plane shear loads proved detrimental to the compressive load-carrying capacity of a composite structure. This research showed minimizing fiber misalignment in manufacturing processes is only beneficial for high tolerance processes. In addition, decreasing volume fraction could be beneficial for highly flexible structures. Finally, the results demonstrated the need to minimize multiaxial loading for optimal composite compressive response.
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    Ultra high-throughput fluorescence detection for single cell applications in drop microfluidics
    (Montana State University - Bozeman, College of Engineering, 2016) Schaefer, Robert Willman; Chairperson, Graduate Committee: Connie Chang
    Conventional methods in microbiology can be limited by assay execution and analysis times, phenotypic dominance within bulk communities, reagent volumes, and single-use supply costs. These limitations can be overcome using drop-based microfluidics. In this discipline, pico-liter sized, water-in-oil emulsions serve as independent 'test tubes,' allowing for the compartmentalization of community constituents and interrogation at the single cell level. Furthermore, two-phase, continuous flow microfluidic devices enable drop populations to be manipulated and analyzed at kilohertz rates according to experimental needs. In this research, a fluorescence-based method for drop analysis and sorting was developed and applied, in conjunction with other microfluidic techniques, to perform assays in microbiology. The applications explored include cell dormancy within P. aeruginosa subpopulations, microalgae lipid accumulation for the production of biofuels, optimization of microbially-induced calcite precipitation (MICP), and human norovirus infectivity. Results from each application include: 1. The hibernation promoting factor (Hpf) was found to play a key role in the maintenance of P. aeruginosa viability during planktonic starvation. 2. Progress was made on a Nile Red based, ultra high-throughput, single cell algal lipid detection platform. 3. MICP was demonstrated at the single cell level. 4. A drop based human norovirus infection platform was attempted using human B cells as the viral host.
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    Micromechanical analysis of energy expenditure in snow fracture
    (Montana State University - Bozeman, College of Engineering, 2017) LeBaron, Anthony Michael; Chairperson, Graduate Committee: Daniel Miller
    A microstructure-based evaluation of snow combining experimental and analytical approaches was performed. Shear tests were performed on both homogeneous and layered samples of un-notched snow. Force and displacement during loading were recorded. Immediately after testing, small subsamples of snow were subjected to micro-CT scanning to capture 3D microstructure details. Microstructure was then modeled as a grain-bond network. The grain-bond network was subject to minimum energy fracture path calculations as well as discrete element modeling. The discrete element model showed good agreement with experiments. Taken together, results from models and experiments show a widespread damage accumulation process in snow. A large fracture process zone (FPZ) is observed, even in samples with weak layers. Evidence indicates that even in snow avalanches, there is likely significant energy dissipation within the slab.
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    A microstructural investigation of radiation recrystallized snow layers
    (Montana State University - Bozeman, College of Engineering, 2016) Walters, David John; Chairperson, Graduate Committee: Edward E. Adams
    Radiation recrystallized snow is a pervasive weak layer of snow that, once buried, increases the threat of snow avalanches. While much is known about the conditions required to form radiation recrystallized snow layers, little is understood about the microstructural intricacies that develop resulting in decreased macro-scale mechanical stability. This study utilizes the Subzero Science and Engineering Research Facility at Montana State University to recreate clear daytime meteorological conditions to induce near surface metamorphism in snow. This metamorphic process develops radiation recrystallized layers of faceted crystals in the top 1-2 cm of snow over the course of 12 hours. Mechanical testing is performed before and after recrystallization to compute the relative change in mechanical properties of the recrystallized snow sample. Near surface samples are also extracted and imaged at regular intervals using computed tomography. Imaging results in a 3-D reconstruction of representative snow microstructures recording the temporal evolution of faceted crystal formation. The microstructural data is utilized in two modeling approaches which seek to describe the macro-scale mechanical properties of the snow. A previously developed homogenization approach, which computes macro-scale effective stiffness properties using micromechanical interactions and texture, is enhanced by incorporating measures of individual grain shapes and differing textural measures. Another approach leverages the microstructure directly by simulating the response of macro-scale loads on a geometric mesh of the imaged microstructure using finite element methods. Following recrystallization, physical mechanical testing demonstrated that the metamorphism process forms a stiff and strong sublayer capped by a weaker layer of faceted snow that is 75-80% less stiff in shear and 80-90% less stiff in compression than the strong layer below it. Microstructural analysis revealed multiple fine layers of unique crystal morphologies existing within the faceted region. Homogenization reflected reasonable trends in relative changes of effective stiffness properties but suffered from volumetric scale problems when analyzing the faceted layer. Finite element methods also reasonably computed the relative change in macro-scale effective properties as a result of changes to the microstructural geometry. Additionally, the finite element method estimates changes to effective strength and the location of mechanical failure within the faceted layers.
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    Fabric tensors and effective properties of granular materials with application to snow
    (Montana State University - Bozeman, College of Engineering, 2011) Shertzer, Richard Hayden; Chairperson, Graduate Committee: Edward E. Adams
    Granular materials e.g., gravel, sand, snow, and metallic powders are important to many engineering analysis and design problems. Such materials are not always randomly arranged, even in a natural environment. For example, applied strain can transform a randomly distributed assembly into a more regular arrangement. Deviations from random arrangements are described via material symmetry. A random collection exhibits textural isotropy whereas regular patterns are anisotropic. Among natural materials, snow is perhaps unique because thermal factors commonly induce microstructural changes, including material symmetry. This process temperature gradient metamorphism produces snow layers that can exhibit anisotropy. To adequately describe the behavior of such layers, mathematical models must account for potential anisotropy. This feature is absent from models specifically developed for snow, and, in most granular models in general. Material symmetry is quantified with fabric tensors in the constitutive models proposed here. Fabric tensors statistically characterize directional features in the microstructure. For example, the collective orientation of intergranular bonds impacts processes like conduction and loading. Anisotropic, microstructural models are analytically developed here for the conductivity, diffusivity, permeability, and stiffness of granular materials. The methodology utilizes homogenization an algorithm linking microscopic and macroscopic scales. Idealized geometries and constitutive assumptions are also applied at the microscopic scale. Fabric tensors tying the granular arrangement to affected material properties are a natural analysis outcome. The proposed conductivity model is compared to measured data. Dry dense snow underwent temperature gradient metamorphism in a lab. Both the measured heat transfer coefficient and a developing ice structure favored the direction of the applied gradient. Periodic tomography was used to calculate microstructural variables required by the conductivity model. Through the fabric tensor, model evolution coincides with measured changes in the heat transfer coefficient. The model also predicts a different conductivity in directions orthogonal to the gradient due to developing anisotropy. Models that do not consider directional microstructural features cannot predict such behavior because they are strictly valid for isotropic materials. The conclusions are that anisotropy in snow can be significant, fabric tensors can characterize such symmetry, and constitutive models incorporating fabric tensors offer a more complete description of material behavior.
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