Theses and Dissertations at Montana State University (MSU)
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/733
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Item Elucidating the impacts of structural heterogeneity on excited state dynamics in solution-processed materials(Montana State University - Bozeman, College of Letters & Science, 2024) Afrin, Sajia; Chairperson, Graduate Committee: Erik Grumstrup; This is a manuscript style paper that includes co-authored chapters.Solution-processed inorganic and organic semiconductors hold enormous promises due to their low manufacturing cost, scalability, and compatibility with flexible substrates. However, solution processing techniques do not require control over crystal growth, which can lead to structural defects within the crystal structure. The defects within solution-processed semiconductors can create significant challenges in optimizing device functionality; therefore, it is crucial to understand the impact of structural defects on photophysical properties. Traditional ensemble measurement techniques can conceal the effects of microscale structural defects on functional properties in the structure-averaged observation of solution-processed materials. The work presented in this dissertation employs time-resolved and spectrally resolved microscopy techniques to investigate the influence of structural heterogeneity on the photophysical properties of microscale solution-processed materials. Measurements collected across multiple discrete and highly crystalline domains of multiple classes of solution-processed materials have helped establish a relationship between the functionality and the local structure of these materials. Initially, the focus was on elucidating anisotropic carrier transport in lead halide perovskites by investigating lattice strain and energetic distribution in microcrystals. Later, the focus shifted towards characterizing and understanding the impact of structural defects on the excited state dynamics in another class of solution-processed material called metal-organic frameworks (MOFs). PCN-222 exhibited rapid exciton transport with time-averaged diffusion coefficients ranging from 0.27 to 1.0 cm2/s and subdiffusive behavior, showing transport slowing on the tens of ps time scale. Subdiffusivity indicated that excited states were rapidly transported through the porphyrin network of PCN-222 before being trapped. Moreover, the first transport measurements and transient absorption microscopic measurements in PCN-222 are reported here. Photoluminescence quenching and heterogeneous relaxation pathways were noted in regions with higher structural heterogeneity. Furthermore, the spectral evolution of porphyrinic PCN-222 MOF was investigated, which revealed excitation-dependent chromophore coupling in the MOF structure. Soret band excitation with enhanced coupling can create more mobile excited states, whereas Q band excitation with reduced coupling will generate fewer mobile excited states. Excitation-dependent chromophore coupling strongly dictates the transport and relaxation properties in MOF microstructures that also illustrate the impact of structural defects on the excited state transport and relaxation dynamics. A significant spectral shift has also been observed in microrods stemming from structural heterogeneity. These findings contribute to a deeper understanding of the impact of structural defects on the photophysical properties of solution-processed materials, facilitating the development of optimized semiconductor devices for various applications. The results reported in this dissertation will not only continue to aid in the characterization of MOFs but will also advance our understanding of excited state dynamics in a variety of solution-processed materials.Item Adapting archetypal analysis to scientific imaging applications(Montana State University - Bozeman, College of Letters & Science, 2022) Potts, Catherine Gabriel; Chairperson, Graduate Committee: Dominique ZossoScientific imaging applications create large sets of high-dimensional data, which may be difficult to process using traditional supervised machine learning representative models. First, many representative models generate computational elements that are difficult to interpret in terms of the scientific application and second, the high embedding dimension of the images often makes generating the models computationally inefficient. We propose using archetypal analysis (AA) as the representative model for these scientific imaging problems, since the computational elements, so called archetypes, resemble members of the original dataset. Specifically, the archetypes are generated as extreme points to an approximation of the convex hull of the data cloud, which means they maintain the structure of individual data points. To improve the computational task of generating the AA model, we propose a sketch-based AA method which projects the data to a lower embedding dimension before calculating the computational elements, lowering computation time for these high-dimensional problems, while at the same time retaining the geometric structure enough so that the computational elements closely match the results of AA. We also applied a primal-dual hybrid gradient (PDHG) solver to the AA algorithm structure attempting to speed up computation. To verify the significance of the interpretation of AA, we applied AA to transient fluorescent calcium images, recorded in the Kunze Neuroengineering lab as videos, in order to determine whether or not adding different nanoparticles changed the way the neurons in culture communicate. We also applied our sketch-based AA method to other sorts of imaging data sets, exploring the differences between our method and the standard AA method. Our experimentation shows the different ways that AA can be adapted to scientific imaging applications, providing a machine learning representation model that is interpretable in the context of the imaging problem and verifies the benefits of the sketch-based method in terms of computation time.Item Microbially induced calcium carbonate precipitation: meso-scale optimization and micro-scale characterization(Montana State University - Bozeman, College of Engineering, 2020) Zambare, Neerja Milind; Chairperson, Graduate Committee: Robin Gerlach and Ellen G. Lauchnor (co-chair); Ellen Lauchnor and Robin Gerlach were co-authors of the article, 'Controlling the distribution of microbially precipitated calcium carbonate in radial flow environments' in the journal 'Environmental science and technology' which is contained within this dissertation.; Robin Gerlach and Ellen Lauchnor were co-authors of the article, 'Spatio-temporal dynamics of strontium partitioning with microbially induced calcium carbonate precipitation in porous media flow cells' submitted to the journal 'Environmental science & technology' which is contained within this dissertation.; Robin Gerlach and Ellen Lauchnor were co-authors of the article, 'Co-precipitation of strontium and barium' submitted to the journal 'Environmental science & technology' which is contained within this dissertation.; Nada Naser, Robin Gerlach and Connie Chang were co-authors of the article, 'Visualizing microbially induced mineral precipitation from single cells using drop-based microfluidics' submitted to the journal 'Nature methods' which is contained within this dissertation.Microorganisms have the potential to impact processes on a scale orders of magnitude larger than their size. For example, microbe-mineral interactions at the micro-scale can drive macro-scale processes such as rock formation and weathering. Many bioremediation technologies derive inspiration from microbial mineralization processes. Microbially induced calcium carbonate precipitation (MICP) can produce calcium carbonate (CaCO 3) precipitates which can be utilized as a biological cement to strengthen porous media by reducing fluid permeability in subsurface fractures or as an immobilization matrix to remove metal contaminants dissolved in groundwater. To make MICP a feasible and successful bioremediation technology in the world outside the lab, it is necessary to bridge the gap between the meso-scale research studies and macro-scale applications. This thesis focuses on such meso-scale studies but also contributes to bridging the gap in the other direction, i.e., meso-scale to micro-scale to gain a fundamental understanding of the cellular level processes behind MICP. The research presented here investigates two applications of MICP with a focus on controlling precipitate distribution and process efficiency in target environments. Subsurface precipitate distribution and metal partitioning during MICP were studied in novel reactive transport systems that mimic application-environment conditions. A radial flow reactor was used to study the spatial distribution of precipitates in conditions similar to subsurface injection well environments. The distribution and degree of metal partitioning during MICP was investigated in batch reactors and porous media flow cells to study kinetics and reactive transport effects on kinetics. In the radial flow environment, more precipitates formed away from the center injection zone. Results showed that longer reactant residence times and an equimolar ratio of calcium to urea were able to maximize precipitation efficiency. Metal partitioning could be maximized at low reactant flow rates and low metal concentrations. The novel flow cell set up used revealed a spatial decoupling between ureolysis and precipitation. A micro-scale investigation of the fundamental MICP process itself is presented wherein microbe-mineral interactions are observed at the cell level. A semi-correlative approach to investigating individual precipitates in microdroplets is presented, using a multitude of microscopy and microanalysis techniques. The presented studies capture MICP across a range of scales.Item Improving the two-photon absorption properties of fluorescent proteins for neuroscience(Montana State University - Bozeman, College of Letters & Science, 2020) Molina, Rosana Sophia; Chairperson, Graduate Committee: Thomas Hughes; Yong Qian, Jiahui Wu, Yi Shen, Robert E. Campbell, Mikhail Drobizhev and Thomas E. Hughes were co-authors of the article, 'Understanding the fluorescence change in red genetically encoded calcium ion indicators' in the journal 'Biophysical Journal' which is contained within this dissertation.; Tam M. Tran, Robert E. Campbell, Gerard G. Lambert, Anya Salih, Nathan C. Shaner, Thomas E. Hughes and Mikhail Drobizhev were co-authors of the article, 'Blue-shifted green fluorescent protein homologues are brighter than enhanced green fluorescent protein under two-photon excitation' in the journal 'The Journal of physical chemistry letters' which is contained within this dissertation.; Jonathan King, Jacob Franklin, Nathan Clack, Christopher McRaven, Vasily Goncharov, Daniel Flickinger, Karel Svoboda, Mikhail Drobizhev, Thomas E. Hughes were co-authors of the article, 'An instrument to optimize fluorescent proteins for two-photon excitation' which is contained within this dissertation.Untangling the intricacies of the brain requires innovative tools that power basic research. Fluorescent proteins, first discovered in jellyfish, provide a genetically encodable way to light up the brains of animal models such as mice and fruit flies. They have been made into biosensors that change fluorescence in response to markers of neural activity such as calcium ions (Ca 2+). To visualize them, neuroscientists take advantage of two-photon excitation microscopy, a specialized type of imaging that can reveal crisp fluorescence images deep in the brain. Fluorescent proteins behave differently under twophoton excitation compared to one-photon excitation. Their inherent two-photon properties, namely brightness and peak absorption wavelength, limit the scope of possible experiments to investigate the brain. This work aims to understand and improve these properties through three projects: characterizing a set of red fluorescent protein-based Ca 2+ indicators; finding two-photon brighter green fluorescent proteins; and developing an instrument to screen for improved fluorescent proteins for two-photon microscopy. Analyzing nine red Ca 2+ indicators shows that they can be separated into three classes based on how their properties change in a Ca 2+-dependent manner. In one of these classes, the relative changes in one-photon properties are different from the changes in two-photon properties. In addition to characterizing, identifying and directly improving fluorescent proteins for enhanced two-photon properties is important. Presented here is a physical model of the light-absorbing molecule within the green fluorescent protein (the chromophore). The model predicts that green fluorescent proteins absorbing at higher energy wavelengths will be brighter under two-photon excitation. This proves to be the case for 12 blueshifted green fluorescent proteins, which are up to 2.5 times brighter than the commonly used Enhanced Green Fluorescent Protein. A way to directly improve fluorescent proteins is through directed evolution, but screening under two-photon excitation is a challenge. An instrument, called the GIZMO, solves this challenge and can evolve fluorescent proteins expressed in E. coli colonies under two-photon excitation. These results pave the way for better two-photon fluorescent protein-based tools for neuroscience.