RSS 1.02023 - Mines Theses & Dissertations
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Submarine landslide processes, mechanics, and effects investigated through physical experiments, numerical models, and natural samplesRemobilization of sea floor sediments (submarine slope failures) presents a hazard to coastlines and coastal communities through its propensity to damage seafloor infrastructure and generate tsunamis. Submarine slope failures and their deposits (mass transport deposits) have been identified on active and passive continental margins, even on slopes < 2°. Despite the global presence and threat of slope failures, understanding of submarine slope failure mechanisms, including factors controlling initiation, evolution, and tsunamigenesis, is limited. Here, I use flume experiments, geotechnical data, and numerical models to investigate the mechanisms of submarine slope failure initiation and behavior. Benchtop flume experiments were conducted to improve understanding of slope response to overpressure using various combinations of quartz sand, cohesive clay (smectite), and non-cohesive quartz powder (clay-sized particles). Numerical models that are commonly used to evaluate natural slope failure (infinite slope factor of safety analyses) were tested against our controlled system. Comparison between experiment results and factor of safety predictions reveals discrepancies between the models and findings, indicating models may over-predict slope stability when over-pressured. Through these experiments, sediment cohesion was shown to dictate slope failure behavior, with brittleness of slope failure directly related to higher cohesion. Sediment permeability controlled the magnitude of overpressure required to induce slope failure when sediments were 25% clay. At higher clay concentrations, permeability did not affect the overpressure required to induce failure. Additionally, when clay contents were ≥ 25%, repeat failure events were observed in experiments and separate, intact sediment blocks were rafted from parent slopes. Additionally, overpressure was found incapable of producing tsunamigenic landslides but could precondition slopes for future tsunamigenic failure. Increased slope failure hazard was identified for clay-rich (≥ 25% wt.) slopes because of the potential for rafted block development and a potential for repeat failures in locations where failures had previously occurred. This work shows additional investigation of models used for hazard assessment of slope failure and tsunamigenesis is needed to assess differences between prediction and reality. This work also shows that local geology (clay content, surface and subsurface deformation) and hydrology (overpressure) need to be considered in hazard assessments to improve the accuracy of slope failure forecasts and preparations. Extending these findings to the natural environment, the geomechanical properties (shear strength, permeability, consolidation state, and overpressure) of submarine slope failure deposits and surrounding background sediments were characterized for a N-S transect of the Japan Trench. Eleven samples from 10 sites were collected by International Ocean Discovery Program Expedition 386: Japan Trench Paleoseismology using giant piston cores. Undrained direct simple shear and constant rate of strain experiments were performed on these samples. Spatial, lithological, and seismic history trends in sediment shear strengths, permeabilities, consolidation states, and overpressures were investigated No trends were found spatially, lithologically, or with seismic history, suggesting that local heterogeneity may be important for failure and seismic strengthening may not be significant. Feedbacks between peak shear strength, overpressure, shear-weakening, and over consolidation were identified indicating once sediment shearing/remobilization begins, continuation of sediment shearing should require progressively less shear strength. To improve regional forecasting and preparation efforts for future tsunami landfall, including identification of areas-at-risk of slope failure in the Japan Trench, a more robust understanding of Japan Trench sediment stability is required. Finally, physical experiments and natural observations were connected to coastal communities through their implications for risk assessments. The importance of local geology and hydrology in assessing failure likelihood and tsunamigenic potential were communicated in language common to the risk assessment community. Specifically, permeability, overpressure, cohesion, and regional seismic history in slopes in relation to coastal community risk assessment, preparations, and response were characterized. Overpressures were identified as capable of lowering slope stability, triggering non-tsunamigenic slope failures, and preconditioning a slope for tsunamigenic failure. Clay concentrations were identified as determining failure behavior, including tsunamigenic potential, and potential for repeated localized failures. Recommendations for modification of current assessment tools, including numerical models, were made that included these parameters. The importance of these parameters and their ramifications on margins not traditionally concerned with tsunamis was reinforced. This work demonstrated the importance of understanding how a slope might be preconditioned for failure and how inclusion of local geology and hydrology is necessary for a more holistic risk assessment of slope failure and tsunamigenesis.
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Context-sensitive representations, reasoning, and communication for morally and socially competent robotsSocial robots must be able to interact naturally and fluidly with users who lack prior experience with robots. To address this challenge, it is essential to develop robots that are consistent with both the expectations of the interactants and the social conventions of the contexts in which interaction takes place. Moreover, language-capable robots hold unique persuasive power over their human interactants, which offers exciting opportunities to encourage pro-social behavior. However, these capabilities also come with risks, particularly in regard to the potential for robots to accidentally harm human norm systems. Thus, it is not only important to enable social robots with moral and social competence, but also to investigate the impact that these robots have on humans in order to facilitate the successful integration of robots into human society. This dissertation focuses on two overarching key research questions: (1) How can we leverage knowledge of both environmental and relational context to enable robots to understand and appropriately communicate about social and moral norms? (2) How do robots influence humans' moral and social norms through explicit and implicit design? We start by examining the impact of human-robot interaction designs on human behavior, with a special focus on how these designs can influence human compliance with social norms in interactions with robots as well as other humans. We then investigate how to structure human-robot interactions to better facilitate human-robot moral communication. Next, we present computational work on a role-sensitive relational-normative model of robot cognition, which consists of a role-based norm system, role-sensitive mechanisms for using the norm system to reason and make decisions, and the ability to communicate about the decisions on role-based grounds. We then present empirical evidence for how the different forms of explanation enabled by our system practically impact observers' trust, understanding confidence, and perceptions of robot intelligence. Then, we show how to leverage existing moral norm learning techniques to sociocultural linguistic context-sensitive norm learning. As part of this work, we demonstrate how norms of an appropriate level of context specificity can be automatically chosen based on the strength of evidence available. Finally, we present a simple mathematical model of proportionality that could explain how moral and social considerations should be balanced in multi-agent norm violation response generation, and use this model to start a discussion about the hidden complexity of modeling proportionality.
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Assessing field-flow fractionation and light scattering for the characterization of extracellular vesicles and polymer colloidsNanoparticle characterization is centered around understanding how properties such as size and composition as well as count correlate with synthetic methodologies, observed behaviors, and end product performances. Current ensemble methods that examine these properties (light scattering, electron microscopy, nanoparticle tracking analysis (NTA), zeta potential, etc.) provide average values and cannot provide important information regarding distributions within the sample. These techniques are also compromised by sample polydispersity and may not be sensitive enough to examine particles that span the range of 1 nm to 1 µm in diameter. To overcome this, samples can be separated to create more monodisperse subpopulations, yet only a few ensemble methods have been readily coupled to separation techniques like field-flow fractionation (FFF). FFF is a family of analytical techniques that has been used to separate and characterize macromolecules and particles since the mid-1960s. Improvements to FFF instrumentation and theory along with the coupling to multiple detectors such as light scattering, differential refractive index, spectrophotometry, and mass spectrometry has enhanced FFF’s capabilities for particle characterization. More recent advancements include nanoparticle tracking analysis (NTA) and on-line Raman spectroscopy for determining the and number/size of nanoparticles as well as composition of polymeric particles, respectively. Together, they represent critical challenges and frontiers for nanoparticle analysis. The work in this thesis takes a different approach by first critically assessing multiangle light scattering (MALS) as a particle counting technique and then exploring the sensitivity of thermal field-flow fractionation (ThFFF) for compositional analyses. The former is particularly relevant as the FFF-MALS platform is now commonly used across disciplines and products. This, in combination with particle counting component of the European Union’s definition of a nanomaterial will undoubtedly lead to an increase in particle counting using MALS for particle counting. However, there has been no work published to date that critically assesses the impact of the uncertainty in nanoparticle refractive indices (a difficult to obtain value for core-shell type structures) and light scattering models used in data analysis to calculate the number of nanoparticles. This work seeks to address this gap in knowledge particularly for complex bioparticles such as outer membrane vesicles (OMVs). The thermal FFF work builds on previously published studies but differs in that the compositional sensitivity of this technique and the use of additives to improve retention and sample recovery are explored. Asymmetrical flow FFF (AF4), coupled to multiangle light scattering (MALS), has recently gained attention for the characterization of bacterial OMVs for nanomedicine and renewable energy applications. A major analytical challenge of OMVs is understanding how particle size and count impact their biogenesis and the cargo sorting proteins in different-sized vesicles. AF4-MALS can be used as an initial separation and enumeration step prior to further analyses with techniques tandem mass spectrometry (i.e., proteomics). While MALS has been used to count biological particles and has shown similar counts to offline methods like NTA, the influence of analyte-dependent parameters (e.g., refractive index (RI) and particle shape/model) with MALS has not been examined. Polystyrene latex standards (known RI and shape) and complex OMVs (unknown RI and shape) were chosen as the model and sample systems. Particle counts from PSL differ upwards of 13 % between sphere or Lorenz-Mie models while OMV particle counts can vary up to 200% depending on the model and refractive index used. Additionally, signal-to-noise in the light scattering signal intensity can lead to erroneous particle counts (i.e., > 1018 particles/mL), which was observed when using the coated sphere model for OMVs. While a promising enumeration technique, the need of particle count standards and accurate RI values impede the determination of absolute particle counts. Thermal FFF (ThFFF) is another technique under the FFF umbrella that can yield particle size as well as composition. The latter differentiates ThFFF from its better-known sibling, AF4. The driving force for ThFFF is imparted by a temperature gradient that is applied perpendicular to the separation axis. Analyte retention is dependent on the Soret coefficient (ST), a ratio of the analytes thermal diffusion coefficient (DT) to its translational diffusion coefficient (D). While ThFFF is mainly done in organic solvents, there is an interest in moving towards aqueous solvents (AqThFFF) in order to characterize aqueous based (biological or synthetic) materials. Two major challenges in performing AqThFFF experiments are the need to use additives (i.e., salts or surfactants) to improve analyte retention and understanding how these additives influence particle thermophoresis. Additionally, little work has been done to assess the compositional sensitivity of ThFFF. To investigate the impact of additives and compositional sensitivity, a model set of butylacrylate: methyl methacrylate: acrylic acid (BA:MMA:AA) particles with subtle differences in acidic comonomer (0-3 %) were examined. A key component of this work was examining the impact of commonly used additives such as tetrabutylammonium perchlorate (TBAP) and FL-70 detergent on analyte retention and recovery. TBAP governed retention of the colloids while the incorporation of FL-70 increased sample recovery. An incremental component of calculating DT values is utilizing accurate D values. Examining D values through DLS (online and offline), via AF4 theory, and transformations from radius of gyration (Rg) data show that flow rates as low as 0.3 mL/min during FFF separations can cause D values to be larger than anticipated. While these changes in D do not impact overall trends across latex samples, they change the overall magnitude of DT. AqThFFF can distinguish between 1 % of acidic comonomer between samples, based on significant differences in DT values and demonstrates a higher sensitivity than the ~9% previously reported in literature. Overall, the work presented in this thesis provides insight into the importance of refractive index on particle counting analyses by MALS as well as subtle nuances and considerations in the data analysis for MALS particle counting. Additives that enhance retention and sample recovery in AqThFFF provide a useful foundation for future advancements and applications. This thesis serves as a platform for future work with biological particles and insight into particle thermophoresis.
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Advancing thermal field-flow fractionation for industrial polymer characterizationField-flow fractionation (FFF) is a family of techniques known for its open channel design and ability to separate polymers and colloids. The applied field in an FFF technique determines the physiochemical properties by which the separation occurs. A well-established theory relates retention time to a retention parameter that is defined by the interaction between the analyte and the applied field as well as the analyte’s diffusion coefficient (D). This imparts the ability for FFF techniques to be used as both a separation and characterization tool. In the case of flow FFF, the retention parameter is dependent solely on D which subsequently relates to hydrodynamic size. For thermal FFF (ThFFF), the retention parameter is dependent on the Soret coefficient (ST), a ratio of the thermal diffusion coefficient (DT) and D. Existing studies of the thermophoresis of polymers in dilute solutions have revealed trends that may be utilized to solve challenges in polymer analysis. Specifically, DT has been observed to be molar mass independent (above 103 to 104 Da), polymer-solvent dependent, and recently – dependent on architecture. The polymer-solvent dependence of DT has been leveraged to characterize the composition of di- and tri-block polymer systems. This polymer-solvent dependence, while useful in driving separations, has proven to be challenging when analyzing new polymer chemistries because of incomplete understanding of thermophoresis and the resulting trial-and-error approach to selecting a carrier liquid that imparts sufficient polymer retention. This thesis aims to increase the adoption of ThFFF by expanding the scope of polymer chemistries and architectures studied. The work presented here leveraged a leading polymer thermophoresis model to identify a suitable carrier liquid for characterizing the architecture of bottlebrush polymers. The ST values were calculated from measured ThFFF retention times and their relationships to the degree of polymerization of the brush backbone and sidechains were established. Information about bottlebrush architecture was then obtained using the recently introduced Soret contraction factor (g”), defined as the ratio of the Soret coefficient of a branched polymer (ST,br) to that of linear polymer (ST,lin) with the same molar mass. Linear analogs were not available for these polyacrylates-containing bottlebrush polymers and thus ST,lin values were approximated using models for thermal and translational diffusion. A plot of log g” versus the number of chain-ends of a bottlebrush showed the expected decrease in log g” when the number of chain ends increased from 120 to 400. Differences in log g” were also noticeable between 30% and 100% grafting densities. This work demonstrated the feasibility of estimating ST,lin and opens the door for architecture characterization in the absence of a linear polymer analog. The g” approach described above has been successfully utilized for model polymer systems derived from well controlled synthesis and orthogonal characterization. Ultimately, the question is whether g” can be used to characterize polymers in complex formulations of industrial importance. A polydimethylsiloxane (PDMS) containing formulation was targeted because of its relative ‘greenness’ when compared to petrochemical derived polymers. This PDMS system proved to be challenging on multiple fronts. First, DT calculations did not yield trends useful to solvent selection due to the observed double Hansen Solubility sphere. This yielded two distinct values for DT for each solvent system, both of which were inaccurate (>100% difference). Second, the industrial formulation contained a low (< 10%) amount of crosslinked PDMS amidst a large amount (> 90%) of PDMS diluent as well as gels and microgels. This low level of crosslinked PDMS and the broad size polydispersity required development of a sample preparation procedure. Different sample preparation methods were evaluated using ThFFF-MALS and the molar mass profiles indicated that centrifugation followed by filtration was the most suitable. Next, PDMS samples with different levels of crosslinking were analyzed and the log g” distribution for the more crosslinked sample was observed to extend to lower values (more contraction). This is as expected and showed that the g” approach can be used for a new polymer chemistry, PDMS, and a complex sample mixture. To date, there has been no additional verification of the Soret contraction approach. PDMS offered a unique opportunity to address this gap because this polymer can be depolymerized and GC-MS used to determine products indicative of branching. GC-MS results confirmed the degree of branching trend indicated by g” values and is an important step forward. The final project presented in this thesis explores the link between DT and the glass transition temperature (Tg). This work presents a comprehensive compilation of polymer thermal diffusion data and the first comparison of experimental DT and Tg. Across multiple solvent systems, a strong positive correlation was observed. To understand if there is a physical connection between these two properties, the results of a first principles Tg model were compared to experimental DT values. This work suggests that entropic forces may contribute to DT, a factor which was explicitly ignored in the derivation of the current leading predictive model. In addition, Tg may be an alternative metric for carrier liquid selection for ThFFF analyses. In summary, ThFFF has become an increasingly powerful tool for the characterization of complex polymer systems. This thesis presents the first reported estimation of ST for a linear polymer utilizing leading models of translational and thermal diffusion, which has expanded the accessibility of g” analysis beyond systems with available linear analogs. The scope of architecture studied by g” now includes bottlebrushes and crosslinked networks along with the previously reported branched systems. Analyses of crosslinked PDMS also presents the first application of g” to an industrial polymer system. These results were also the first to be verified by alternative means. In addition, a potential link between DT and Tg was observed that could lead to improvements in predictive models. This relationship may also serve as a simple metric for approximating the relative magnitude of DT for polymers.
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Monitoring large-scale rock slopes for the detection of rockfalls using structure-from-motion photogrammetry at Debeque Canyon, ColoradoThis research investigates the frequent rockfall events in DeBeque Canyon along I-70. It uses the multi-epoch photogrammetric monitoring datasets collected by the Colorado Department of Transportation between 2014 and 2021. The study aims to assess the effectiveness of the direct geo-referencing approach in creating large-scale photogrammetric models without ground control points (GCPs). It also aims to develop a workflow for creating a regional-scale rockfall inventory and characterize the spatial variability of rockfall characteristics. Furthermore, the research seeks to evaluate the impact of pre-existing rockmass structures on rockfall frequencies, sizes, and shapes. Comparison of the developed photogrammetric point clouds created using a direct geo-referencing approach to lidar surveys revealed a good matching precision. The precision was as good as 0.059 m in terms of root-mean-squared (RMS) difference metric. For efficient handling of large-scale, multi-epoch models, the study implemented construction of photogrammetric models for only the first and last acquisition. The corresponding image datasets for intermediate acquisitions were manually reviewed. This approach enabled rapid identification of the temporal occurrence of each rockfall. Segmenting photogrammetric models into smaller segments minimized "bowl-effect" distortion and reduced processing time. The study revealed that rockfall activity vary along DeBeque Canyon corresponding to changes in lithologies, rockmass conditions, and the presence of oversteepened areas. Increased rockfall activity can be attributed to factors such as prevalence of weaker rockmasses, increased degree of fracturing, human interference, and presence of steeper slopes. The temporal rockfall rates increase in years with a higher number of days with snow thickness exceeding 1 inch. The study found that pre-existing rockmass structures influenced rockfall failure mechanisms, shapes, and scaling exponent of the power-law equation. The scaling exponents of the magnitude-cumulative-frequency (MCF) curves were found to be impacted mainly by variations in lithology and degree of fracturing. The expected range of block volumes obtained based on structural mapping was larger than the actual rockfall volumes. This discrepancy occurred due to model resolution limitations for structural mapping. It also resulted from the occurrence of smaller rockfalls due to intact rock failure between mapped joints and rockfalls not bounded by joint sets.
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Synthesis of metal sulfide compounds for solid-state electrolytes using metathesis reactionsSolid-state batteries hold promise for improved energy density and safety for short-term storage or electric vehicles compared to conventional lithium-ion batteries. The most promising class of inorganic solid electrolytes are the sulfide-based materials due to their high lithium-ion conductivity and ease of processing. However, the cost of the requisite metal-sulfide precursors constrains the large-scale production of sulfide-based solid electrolytes. In this work, scalable approaches to synthesize precursors – in particular Li2S and SiS2 – from metathesis reactions of Na2S and metal salts are developed and applied to the synthesis of sulfide solid-state electrolytes. First, the production of the Na2S reagent was developed. It was found that anhydrous Na2S can be produced from purification of technical-grade Na2S hydrate flakes or synthesized directly. Low cost Na2S hydrate was purified by drying, then reacting with H2 gas at elevated temperatures. Alternatively, Na2S was formed by reacting H2S gas with a sodium methoxide solution. The H2S reagent was completely abated, and H2 was generated during the methoxide preparation from Na metal and methanol. The Na2S was recovered from solution by solvent evaporation. The resulting Na2S was characterized with a complementary suite of techniques showing purity similar, if not superior, to commercially obtained anhydrous Na2S. Next, Li2S metathesis was developed. In this process Na2S is reacted with LiCl to form a solution of Li2S and solid NaCl byproduct, with ethanol being the preferred solvent. Removal of the NaCl precipitate and evaporation of the supernatant yields Li2S that retains significant levels of solvent-related impurities. A slow, step-wise annealing process was devised to remove or decompose these impurities resulting in Li2S that was significantly purified but still retained residual levels of oxygenated impurities such as Li3OCl, Li2CO3, LiOH, and Li2O. The resulting Li2S was used to synthesize the argyrodite Li6PS5Cl, the prototype sulfide solid-state electrolyte. While Li2S impurities manifested as side-products in the final electrolyte, ionic conductivity was still similar to or better than electrolyte synthesized from commercially-available battery-grade Li2S, with room-temperature conductivities over 4 mS cm-1. Next, the mechanism of impurity formation in metathesis-derived Li2S was investigated. It was discovered that the impurities likely result from the thermal decomposition of ethoxide compounds that form as a result of the reaction of Na2S with ethanol, which proceeds in parallel with the intended metathesis reaction. With this mechanism in mind, several approaches to iv purify the metathesis Li2S were formulated. The optimal approach was to dry the Li2S material at 80 °C under an H2S environment, which resulted in removal of solvent impurities and retention of the desired nanocrystalline morphology which is lost at elevated annealing temperatures. Li6PS5Cl argyrodites synthesized from this approach exhibited phase-purity with state-of-the-art ionic and electronic conductivity (3.1 and 6.4•10-6 mS cm-1, respectively). Finally, the concept of cascaded metathesis was proposed and demonstrated. Li2S is a powerful metathesis reagent that can be used to synthesize nearly any metal sulfide from the appropriate metal chloride, including those that are unstable in protic solvents. When coupled to the first metathesis reaction, LiCl and the solvents are recycled and reused, resulting in metal sulfide synthesis from low cost Na2S and metal chloride salts. Cascaded metathesis was demonstrated through the first solution-based synthesis of SiS2. Li2S was reacted with SiCl4 in ethyl acetate to generate SiS2 and a LiCl byproduct, which precipitates from solution. The latter was then used to regenerate the Li2S reagent, and it was shown that over 90% of the lithium could be recovered and recycled along with the solvents employed to repeat a second reaction cycle. The metathesis-derived Li2S and SiS2 were then used to synthesize the glassy solid electrolyte 60Li2S•40SiS2, which exhibited an ionic conductivity of 0.11 mS cm-1 in good agreement with literature reports. In principle, cascaded metathesis could be used for the synthesis of nearly any metal sulfide, which are employed in numerous applications including energy storage/conversion, catalysis, opto-electronics, and solid-state lubricants.
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Informal and semi-formal electrical and electronic waste (e-waste) management: a socio technical study of risks, perceptions, interventions, and educational opportunitiesThe expansion of technology in the 21st century is accompanied by a growing production of electrical and electronic equipment (EEE), including laptops, cellphones, refrigerators, kitchen appliances, and toys. The global consumption of EEE is increasing annually by 2.5 million metric tons, generating one of the fastest-growing waste streams in the world, known as “e-waste” or “WEEE.” Throughout the last decade, because of the complexity of its management and the toxicity and high relevance of many materials in EEE, e-waste was prioritized in the agendas of various international organizations. Furthermore, this waste stream is becoming an increasingly important source of income for many vulnerable communities. In this context, research has begun to focus on the environmental and health risks for informal e-waste workers, their families and neighbors. While most projects and studies have assessed effects on women and children in Africa or Asia, very few have aimed to assist low-income workers in Latin America to apply the best management practices and reduce risks with a simultaneous positive impact on their economies. To contribute to filling this gap, through a mixed-methods and participatory approach, this thesis identifies chemical risks and risk perceptions in two informal and semi-formal e-waste management scenarios in Buenos Aires (Argentina). Then, it proposes risk reduction interventions based on the NIOSH Hierarchy of Controls and the Engineering and Sustainable Community Development criteria. Targeting five main audiences (workers, governmental officials, scholars, professors, and students), this study motivates the incorporation of e-waste as a topic for engineering education and encourages research and action toward occupational safety in non-formal settings. Finally, it recommends a focus on not only the environmental and health protection of workers and their communities but also the socio-economic development of these “invisibilized waste management heroes.”
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Enabling direct use of control spalled substrates through fracture control and planarizing overgrowth via hydride vapor phase epitaxyControlled spalling is a promising low-cost substrate reuse technique for epitaxial growth substrates; however, the spalling fracture produces large facets on (100)-oriented GaAs because the fracture is constrained to low-energy planes that are oriented at a high degree to the substrate surface. This facet formation has so far made spalling GaAs infeasible for wafer reuse without costly polishing steps. This thesis demonstrates control of the fracture behavior and planarizing overgrowth that may enable use of spalled GaAs substrates without surface repreparation. First, design rules are developed for nanoimprint lithography patterned interlayers to enable facet suppression. We demonstrate facet suppression using a pattern that follows these design rules, resulting in a surface that is potentially suitable for growth without polishing. Next, the dependence of the faceting behavior on spall direction, substrate orientation (including (100), (110) and (211)), and offcut is investigated. We develop an equation to describe the excess surface area produced via faceting and use it to show that low-energy planes available in the spall direction will support faceting when the surface energy scaled by the excess surface created does not exceed the fracture energy parallel to the substrate surface. Facet free surfaces are achieved on (110) and (211)-oriented substrates, however, we observe offcut and spall direction effects on the stability of the fracture along the flat plane. Finally, planarizing overgrowth via hydride vapor phase epitaxy (HVPE) is studied to determine growth conditions that may enable in situ planarization of GaAs facets. A screening design analysis is used to efficiently probe the complex parameter space and we show that high GaCl and low AsH3 partial pressure are favorable for planarization. We then determine the governing growth mechanisms for planarization and demonstrate device-quality growth directly on a spalled substrate. This thesis shows that these techniques have significant promise for enabling controlled spalling as a low-cost substrate reuse technique. The studies of fracture control also show behaviors that have not been previously reported or characterized, and the studies of growth rate anisotropy in HVPE give insight to the difference in growth on different planes and build a foundation for growth morphology control on any surface.
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Givenness-hierarchy-informed document planningRobots that use natural language in collaborative tasks must refer to objects in their environment. Recent work has shown the utility of the linguistic theory of the Givenness Hierarchy (GH) in generating appropriate referring forms. But before referring expression generation, collaborative robots must determine the content and structure of a sequence of utterances, a task known as document planning in the natural language generation community. This problem presents additional challenges for robots in situated contexts, where described objects change both physically and in the minds of their interlocutors. In this work, we consider how robots can “think ahead” about the objects they must refer to and how to refer to them, sequencing object references to form a coherent, easy to follow chain. Specifically, we leverage GH to enable robots to plan their utterances in a way that keeps objects at a high cognitive status, which enables use of concise, anaphoric referring forms. We encode these linguistic insights as a mixed integer program within a planning context, formulating constraints to concisely and efficiently capture GH-theoretic cognitive properties. We demonstrate that this GH-informed planner generates sequences of utterances with high inter-sentential coherence, which we argue should enable substantially more efficient and natural human-robot dialogue. This thesis is an extension of work originally presented at the International Conference on Intelligent Robots and Systems (IROS) 2022 [1]. Content from the original work is reused in this thesis with permission. See Appendix C for information on the original publication and copyright permissions.
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Efficient modeling and waveform inversion of multicomponent seismic data for anisotropic mediaAccurate modeling of elastic wavefields is crucial for seismic imaging and inversion applications. Incorrect handling of the boundary conditions can distort the wavefield solutions, especially the horizontal displacement and velocity components, which may have serious implications for elastic reverse time migration (ERTM) and elastic full-waveform inversion (EFWI). For ERTM and EFWI, another important factor to consider is the computational speed of the modeling engine because inefficient algorithms are impractical for industrial applications. This thesis aims to develop efficient elastic wave propagators using mimetic finite-difference (MFD) operators and fully staggered grids (FSGs). Also, I present an EFWI framework based on these propagators and discuss inversion strategies for estimating the parameters of coupled fluid/solid VTI (transversely isotropic with a vertical symmetry axis) media using multicomponent ocean-bottom data. First, I develop a graphics processing unit (GPU)-based MFD+FSG algorithm to efficiently model elastic wavefields in anisotropic media. The CUDA Aware MPI framework is used to handle communication across GPU nodes. The weak- and strong-scaling tests on up to eight DGX NVIDIA A100 nodes (64 GPUs in total) demonstrate the efficiency of the algorithm. Numerical tests for large-scale anisotropic models with more than 1.7$\times$10$^{\rm 10}$ grid points indicate that the algorithm achieves a quasilinear computational speedup with over 98\% efficiency. Comparison with results from the spectral-element method (SEM) demonstrates the high accuracy of the algorithm. Next, this methodology is extended to a coupled fluid/solid medium to accurately handle the boundary conditions at the seafloor for marine seismic applications. Numerical experiments reveal wavefield distortions caused by erroneously assuming the seafloor to be a welded boundary. The proposed algorithm is also less computationally expensive than the conventional ``welded" approach, and comparisons with SEM solutions again confirm the accuracy of the MFD+FSG implementation. For handling nonflat bathymetric surfaces, I use a vertically deformed coordinate system to transform the irregular grid into a regular Cartesian grid in a generalized coordinate system. Then, a tensorial approach is employed to directly solve the wave equation in the transformed coordinate system. A semianalytic coordinate mapping is employed for computationally- and memory-efficient implementation of the fluid/solid boundary conditions. Numerical tests confirm that the MFD+FSG algorithm can accurately handle undulating bathymetric surfaces overlying structurally complex anisotropic media. Then, I develop a framework for anisotropic elastic full-waveform inversion of multicomponent ocean-bottom data using the coupled fluid/solid MFD+FSG propagator. The adjoint fluid/solid coupled system and the gradient of the objective function are derived by employing the adjoint-state method. Several inversion strategies using individual data components and their combinations are investigated using a multiscale algorithm. Synthetic tests show that using a sequential strategy by operating with a single data component at a time improves the overall accuracy of the inverted parameters. Also, the inversion benefits from including the horizontal displacement or particle-velocity components, especially for heterogeneous underwater models. Finally, I develop a mesh-free approach for solving the acoustic wave equation using physics-informed neural networks (PINNs). The physical laws governing the partial differential equations (PDEs) are used as regularization terms in the loss function. The initial conditions are enforced in a hard manner instead of including them as an additional regularization term. A Fourier neural network (FNN) is used to address the spectral bias commonly observed in PINNs based on fully connected neural networks (FCNNs). The developed PINN approach is not as prone to numerical errors and is less restrictive than the traditional numerical methods such as the MFD+FSG method developed in this thesis. It provides a potential alternative for wavefield modeling in imaging and waveform-inversion algorithms.
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Effects of prior microstructure on quenched and partitioned steelsQuenching and partitioning (Q&P) produces microstructures of metastable retained austenite (RA) and tempered martensite through a process consisting of austenitization or intercritical (IC) annealing, quenching to produce a calculated fraction of martensite, and partitioning C from martensite to stabilize the remaining austenite. Prior microstructure effects on Q&P heat treatment were investigated in terms of microstructural length scale, chemical banding, and the presence of carbides in ferrite/pearlite, martensitic, and finely spheroidized prior microstructures. Because the austenitization or IC annealing step at the beginning of the Q&P process is the only opportunity to reduce chemical banding and dissolve carbides, prior microstructure effects on Q&P were primarily investigated in terms of microstructural development during this step and on-cooling to the initial quench temperature (QT). Three experiments were developed to understand: 1) The effects of prior microstructures and Cr/Nb additions on austenitization rate and cementite dissolution during IC annealing and full austenitization prior to Q&P. 2) High-temperature microstructure conditions after IC annealing and full austenitization and how they affect ferrite formation on-cooling at rates of 12, 35, and 100 °C∙s-1 to the QT. 3) How high-temperature microstructure conditions lead to local differences in microstructural development during Q&P processing as a function of QT. Through these experiments it was found that fine microstructural length scales and fast carbide dissolution led to rapid austenite formation and less variation in the high temperature microstructures before Q&P processing. In terms of bulk alloy composition, Cr additions dramatically slowed cementite dissolution and solute redistribution, providing control over chemical heterogeneity in the high temperature microstructures through choice of prior microstructure and annealing conditions before Q&P. Understanding these chemical heterogeneities through modeling and experimental observations, it was found that ferrite formation on-cooling was most rapid in regions with low C, Mn, and Cr contents. IC ferrite retained from the prior microstructures led to extensive ferrite growth on-cooling due to a reduced requirement to nucleate fresh ferrite. In terms of Q&P processing, ferrite formation on-cooling and chemical heterogeneity in the high-temperature microstructures led to local differences in martensite start temperature (Ms). These differences affected microstructural development during the quenching and partitioning steps of Q&P heat treatment. In regions of the microstructure with low Ms temperatures, blocky RA and martensite/austenite constituent (MA) were identified after Q&P due to limited martensite formation during the initial quench. In regions with high Ms temperatures, however, extensive martensite formation during the initial quench led to microstructures of tempered martensite and film-like RA after Q&P. These results illustrated that annealing conditions could be designed to create predictable distributions of austenite stability prior to Q&P.
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Quantifying heterogeneity in sedimentary units at multiple scales: an investigation into the complex depositional record of the Ventura and Powder River basinsSedimentary basins record important changes in climate and tectonic activity throughout Earth history. These basins contain valuable natural resources and the extraction of these mineral and hydrocarbon deposits have changed the course of human history. The depositional record contained within these basins is often cryptic and incomplete, and localized changes in sediment routing, deposition rates or erosional processes can be evidence of large-scale changes in tectonics or climate. Sedimentary rocks can exhibit large-scale heterogeneity over the distance of an ocean basin, small-scale geochemical changes in the pore space between grains and even temporal changes and research requires multiple scales of investigation. This thesis investigates heterogeneity in sedimentary basins at multiple scales by 1) reinterpreting the tectonic history of the Ventura basin by quantifying changes in the U-Pb zircon dates, automated mineralogy and provenance; 2) demonstrating lateral and vertical heterogeneity in the depositional architecture of a submarine-channel element outcrop using drone photogrammetry and 3) documenting how the scale of investigation effects the interpretation of x-ray fluorescence spectrometry (i.e., elemental geochemistry) data. The multi-disciplined approach of this research integrates methods that are useful at quantifying heterogeneity at different scales and develops new analogs for depositional and tectonic changes. These analogs are valuable to the exploration of important natural resources and to predicting future changes in the depositional record.
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Nuclear track analysis: a method for quantitation and localization of fissionable elements in 3D samplesActinides are chemically and radiologically toxic elements, which have relevance in nuclear power, space exploration, medicine, and defense. One actinide, plutonium (Pu), is of great interest for biochemical studies because it is not easily excreted from mammals and, over time, the radioactivity of Pu in a person or animal can cause cancers. In vivo methods for studying Pu biochemistry are challenging due to the amounts of Pu required by current detection methods being too radiotoxic for the cells during the exposure time. In this work, nuclear track analysis (NTA) was used to detect Pu by imaging the paths of fission fragments emanating from Pu containing 3D samples (PC-12 Adh mammalian cells incubated in vitro) that were immobilized on 2D solid state nuclear track detectors (SSNTDs). The use of morphologically similar standards made by encapsulating serial dilutions of known quantities of Pu in giant unilamellar vesicles (GUVs) was used to obtain a detection efficiency curve for Pu in varying sizes of vesicles by the SSNTD. The fractional detection efficiency of the smallest sizes of GUVs was an order of magnitude higher than 1, but it dropped to a plateau near 0.2 as the GUV sizes increased. The serial dilutions were used to obtain a calibration curve for fission tracks per GUV per µm2 for Pu concentrations (10, 1, 0.1, and 0.05) µM. The calibration curves were used to calculate the amount of Pu taken up by PC-12 Adh cells incubated in 0.2 µM transferrin bound Pu, which was 0.14 µM Pu per cell, or 7.4 attograms Pu per cell (~19000 atoms of Pu). The NTA method was also used in this work to map the Pu locations within the cell by adding a second SSNTD to sandwich the sample and detect both fission fragments. However, the SSNTD pairs were unable to be aligned to such a fine detail that the fission fragment pairs can be found. Further development of SSNTD manufacturing is needed for precise realignment and further testing of this technique.
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Investigation of electrostatic discharge using indirect electrical and direct optical measurement techniquesElectrostatic discharge has been studied for many years, but due to the complexity of the dynamics, sparks are still a rich subject of investigation. In the presence of a strong electric field, random seed electrons lead to avalanche breakdown. As the electrons begin to shield the field, a streamer forms producing a conductive channel. The main arc carries the bulk of the stored charge and energy across the channel. A shock wave propagates outwards as the charge depletes, leaving a conductive ionized core behind. This dissertation describes a multi-faceted approach to experimentally explore the dynamics of spark discharges during many of these phases. In literature, there are several commonly used models that relate the nonlinear spark resistance to the integrated current, each of which makes different assumptions about energy dissipation in the spark. The validity range of the models is explored by measuring the spark resistance and observing the plasma conditions. Indirect electrical measurements provide information on the time-dependent spark resistance and on how energy transferred to a series ‘victim’ resistive load scales with gap length, capacitance, and victim load size. These measurements generally show good agreement with the Rompe and Weizel model, put forth in 1944. A novel dual storage capacitor design was implemented to measure the longer time scale resistance. For the first time to our knowledge, these measurements show that the channel remains conducive for over 150uμs, well after most of the direct emission has disappeared. Direct optical emission measurements give detailed information on the species evolution and the spark plasma’s channel size. Finally, performing 2-color interferometry measurements provides information about shock expansion in the gas and also informs on the degree of ionization and the time-dependent size of the conductive channel. Since knowing physical limits for how much damaging energy can be transferred to a device or a combustible system is crucial for safety analysis, this work provides information valuable to those concerned with quantifying risks. For those who are developing models and simulations of these complicated phenomena, the measurements give important benchmarks to help test their validity.
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Contextually drilling with geology and local capacity a study of the train-the-trainer model's impact on manual borehole implementationAccess to safe drinking water and sanitation are fundamental human rights recognized by the United Nations. However, many developed countries have achieved this ideal but millions of people around the world, especially in rural areas, still lack access to clean water due to various challenges. In Benin, Africa, there are increasing populations, surface water contamination issues, and declining rainfall all of which have decreased surface and groundwater resources in the region, driving the need for alternatives to meet the growing water demand. This study focuses on understanding the potential of manual drilling methods as a cost-effective solution to expand groundwater extraction and contribute to the demand of potable water. This project seeks to show the benefits of a sociotechnical approach in a manual borehole drilling project that combines education and co-implementation to develop a more successful project. In addition, geoscientific applications are integrated to inform drilling methods and site selection to reduce the uncertainty of the subsurface. Educational objectives include presenting best practices of manual wellbore drilling projects and community development practices to provide a framework for developing manual borehole drilling water projects. To better manual borehole drilling education implementation, this study evaluates the impact of a train-the-trainer model integrated with Humanitarian Engineering and Science themes through a case study description and analysis. The expected outcome is to provide a better understanding of how focusing on education, and co-implementation can aid water relief projects and promote self-reliance on water resources.
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Dynamic strength and fragmentation of silicon carbideThis study investigates the rate-dependent compressive failure and fragmentation of two armor ceramics. Specifically, the uniaxial compressive response of two formulations of silicon carbide, SiC-N and SiC-X1, have been investigated at quasi-static rates of 10-4 s-1, using a universal testing machine, and dynamic rates of 102 s-1, using a Kolsky (split-Hopkinson) bar. The loading and failure have been investigated using high-speed imaging and Digital Image Correlation (DIC). Fragmentation has been shown to be an important factor in understanding the performance of advanced ceramics. Consequently, the dynamic fragments from individual experiments of each formulation have been quantified for their cumulative size distributions. Results from the compression experiments suggest that SiC-N and SiC-X1 have statistically comparable strengths of over 4 GPa, at both quasi-static and dynamic rates, with both materials exhibiting a slight compressive strength rate-sensitivity. Results from the high-speed imaging show that the failure mode of SiC-N and resulting fragment morphology match previously reported experiments in literature. However interestingly, SiC-X1 exhibits a clear shift to a lower average fragment size, likely due to microstructural features.
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Behavior of a chiral condensate around astrophysical-mass Schwarzschild and Reissner-Nordström black holesIn this work, we develop a perturbative method to describe the behavior of a chiral condensate around a spherical black hole whose mass is astrophysically realistic. We use the inverse mass as the expansion parameter for our perturbative series. We test this perturbative method in the case of a Schwarzschild black hole, and we find that it agrees well with previous numerical results. For an astrophysical-mass Schwarzschild black hole, the leading order contribution to the condensate is much larger (in most of space) than the next-to-leading order contribution, providing further evidence for the validity of the perturbative approach. The size of the bubble of restored chiral symmetry is directly proportional to the size of the black hole. Next, we apply this perturbative method to a Reissner-Nordstrom (RN) black hole. We find that, as the charge-to-mass ratio increases, the bubble of restored chiral symmetry becomes larger relative to the black hole. This effect is particularly pronounced for near-extremal RN black holes. The case of an extremal RN black hole provides an interesting counterexample to the standard thermal explanation for the formation of a bubble of restored chiral symmetry around a black hole.
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Water resources sustainability considering climate change and future demands in five Peruvian watershedsClimate change and increases in human activities are constantly threatening water availability in Peru. This study provides a tool for the evaluation of future scenarios on five watersheds located in the Arequipa Region, southern Peru. Future climate change analysis using calibrated hydrologic models for available streamgages and reservoir volumes is provided. A semi-distributed approach was executed for each watershed and an innovative simulation splitting approach was used, which allowed having different starting dates for the simulations using all available data obtained from different sources. Furthermore, water uses for each watershed were evaluated against predicted reservoir inflows and streamflows for near and far future periods. In addition to the above, 12 climate change models with four Shared Socioeconomic Pathways (SSP) were ensembled for the five watersheds. The results indicate that the region expects increased flows during the wet season, and no significant changes occur during the dry season. This pattern is similar for all five watersheds, which is expected because of the large spatial resolution of the climate change models. Reservoir inflows are expected to increase by up to 42\% and 216\% for the lowest and highest greenhouse gas emission SSP evaluated, respectively. Similarly, streamflows were predicted to increase by up to 295 and 704\% for these two different SSPs. Future hydrology simulations combined with future water demands suggest that significant water deficits are not expected for the watersheds under study. This could not be true because the flows were found to be higher during the wet season and steady during the dry season. Moreover, important volumes of water can be lost during the wet season by natural drainage; hence, if future water sustainability is desired, storage and irrigation efficiencies need to be improved.
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Temperature dependent dynamic response of open-cell polyurethane foamsPolyurethane foams have many uses ranging from comfort fitting seats and shoes to protective inserts in helmets and sports equipment. This study aims to analyze the thermomechanical uniaxial compression behavior of two different polyurethane based foam helmet liner pads. These experiments were conducted under strain rates of 10$^2$ s$^{-1}$ and under temperature conditions ranging from -20 to 40\textdegree{C}. This temperature range was chosen to simulate desert and arctic conditions, with a strain rate regime chosen to represent loads that would occur often throughout the life of the helmet, such as drops, bumps from riding in a vehicle, or even falling after a parachute landing. These loads are deemed blunt impacts. Multiple experimental apparatuses were used in this study, including a Shimadzu TCE-N300 thermostatic chamber (used to create the varying temperature environments) and a custom-built drop-test system (used to induce intermediate strain rates). Every experiment was paired with a high-speed camera used for Digital Image Correlation (DIC) to analyze sample deformation. Using the resulting stress-strain curves generated, the foam's mechanical response and energy absorption properties were investigated. Additionally, each foam composition was analyzed with X-ray computed micro-tomography (XCT) to investigate microstructure properties pre- and post-mortem. In depth analysis allowed for accurate modeling of the foam storage properties and the rate dependency behavior as a function of temperature. The XCT was used to probe qualitative microstructure damage. It was found that the energy absorption capability of the low density composition decreased by 48\% as temperature went from 40 to -20\textdegree{C}. The high-density composition saw an inverse response, as energy absorption increased by 53\% as the temperature for the experiment decreased. A comparison between the loading response and the material density characteristics reveal that these particular foam protective properties are heavily dependent on strain rate, as well as temperature.
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Kinetics and mechanisms of hydrated electron reactions during advanced reduction processesAdvanced reduction processes (ARPs) are a class of water treatment technologies that have great potential in remediating recalcitrant contaminants that are resistant towards traditional oxidation methods such as chlorinated solvents, toxic oxyanions, and more recently, per- and polyfluoroalkyl substances (PFASs). Although ARPs have been shown to completely mineralize persistent organic pollutants, their operation efficiency is highly dependent on sourcewater composition since the reactive species, hydrated electron (???−), can be rapidly quenched by non-target constituents present in natural water. Current means of optimizing ARP reaction conditions involve UV photolysis experiments that require performing multiple batch experiments which can be time and resource intensive. Moreover, means of measuring fundamental kinetics values of ???− reactions (i.e., k2; M-1 s-1) such as laser flash photolysis (LFP) and pulse radiolysis contradict results in photolysis experiments and values vary widely in the literature. Kinetic models are an alternative approach for gaining quantitative information regarding the photochemistry dictating ARP treatment results. This work investigates the kinetics and mechanisms of ???− reactions during ARPs for the development of a photochemical model to quantitatively predict PFAS degradation in diverse environments. The first objective of this thesis focused on measuring kinetics and elucidating mechanisms of PFAS degradation by ???− using laser flash photolysis (LFP) and density functional theory (DFT). Reactivity of the compounds in the dataset varied widely despite their structural similarities and it was proposed that polyfluorinated carboxylates can undergo non-degradative reaction pathways posing additional challenges for treating diverse PFAS mixtures. The second objective involved quantitatively describing the effect of solution pH and acid-base speciation of common water constituents on ???− availability during ARPs. Carbonate species, ubiquitous in natural waters, were found to significantly inhibit PFAS degradation, and species-specific k2 values were determined using LFP and nonlinear regression analysis. The third and final objective was to develop a photochemical model for predicting PFAS degradation during UV-sulfite treatment using the kinetics values and mechanistic insights obtained in the first two objectives. This model facilitates the (1) quantitative interpretation of the effect of system and solution parameters on treatment efficacy, (2) reconciliation of UV photolysis and LFP/pulse radiolysis methodologies, and (3) prediction of PFAS degradation during UV-sulfite treatment in different environments based on geochemical solution conditions and UV light source.
