The growth of photovoltaic technology depends on high efficiency and cost reductions. III-V photovoltaics have demonstrated the highest conversion efficiencies, but are limited by their high cost. To reduce the significantly high cost of epitaxy, the absorbing layer can be thinned to form so-called “ultrathin” solar cells. Ultrathin cells have low optical absorption and therefore a lower short circuit current density (JSC). Light-trapping methods can increase absorption and JSC, but nearly all existing methods of fabricating light-trapping structures for III-V materials require ex situ processing that can be time, labor, and cost intensive. In contrast, fully in situ methods of fabricating light-trapping structures support higher industrial throughput and cost reduction by utilizing existing capital equipment, i.e., a growth reactor, to generate the light-trapping structures after device growth without removal from the reactor. This thesis discusses the development of a fully in situ method of fabricating light-scattering structures for III-V materials that utilizes the phenomenon of redeposition during vapor phase HCl etching to generate a rough, textured surface morphology. It is shown that a rough morphology only forms by inducing the hydride-enhanced hydride vapor phase epitaxy growth mode. Compositional analysis identifies the redeposited morphology as highly Ga-rich GaInP, and it is shown that the redeposition is crystalline and has epitaxial registry to the substrate. The kinetic and thermodynamic mechanisms causing redeposition of Ga-rich material are explained. GaAs solar cells with a 270-nm absorber are textured in situ following device growth and the textured devices are compared to planar devices with the same cell architecture. The JSC is 5.1% higher on average in the textured devices, yielding a maximum of 21.84 mA/cm2 with no loss in open circuit voltage or fill factor. This performance enhancement is achieved with only a 60 s treatment, demonstrating the high-throughput viability of this texturing method.

The decision to supplement conventional energy generation with an on-site microgrid consisting of a mix of distributed generation resources and energy storage devices is motivated by several factors, including reducing costs, increasing sustainability, and improving the resilience and reliability of an energy system. The procurement and operational costs of installing distributed generation are traditionally the impetus behind long-term decisions. While costs remain a key component, decision-makers are now interested in other benefits such as improved resilience and reliability, reduction in emissions, and public sentiment. An open-sourced webtool, REopt, is a mixed-integer linear program that exists to provide users the ability to conduct parametric analysis under many scenarios. Often commercial optimization software struggles to obtain fast and reliable solutions. Therefore we develop a Matheuristic that yields objective function values within 5% of an exogenously produced optimal in fewer than 30 seconds for 90% of test cases compared to only 10% by a traditional optimization solver. We then embellish REopt, to explore the tradeoffs between cost and resilience for a coastal wastewater treatment facility. We find that the facility can reduce life-cycle energy costs by 3.1% through the installation of a hybrid combined-heat-and-power, photovoltaic, and storage system. Furthermore, when paired with existing diesel generators, this system can sustain full load for seven days while saving $664,000 over 25 years and reducing diesel fuel use by 48% compared to the diesel-only solution. Finally, we extend the concepts of the first two works by incorporating emerging technologies (fuel cells) into a distributed generation multi-objective model that simultaneously minimizes costs while ensuring a communities' critical load is satisfied during a utility service disruption. This extension requires the incorporation of challenging non-linear constraints that inhibit state-of-the-art optimization software from finding solutions within 15%, on average, after two hours for realistic instances encompassing five technologies and a year-long time horizon at hourly fidelity. We devise a multi-stage methodology resulting in, on average, an 8% decrease in objective function value. Additionally, solutions obtained using our methodology result in fuel cell utilization three times more often than solutions obtained with commercial solvers.

Motion planning is an important problem in many contexts of robotics. Heterogeneous computing systems in robots are able to run tasks on different processing units in varying orders, but with different impacts on the robot's state and performance. Currently existing sampling-based motion planning frameworks explore a state space through typically random sampling to create a path to a goal region, but only consider physical obstacles in their way such as walls, and do not consider the constraints of computational requirements on the path or the impacts of choosing different schedules for computation. We introduce a novel system which uses Petri nets as a modeling system on the computational requirements, and uses constraint solvers to find computation schedules for the motion planning tasks. This allows us to select motions based not only on their physical validity, but also computation-related parameters. We subdivide a space of constraints on the system into regions, enabling schedule reuse in order to improve the algorithm's efficiency. We also discuss the use of Petri nets to model another aspect of computation in a heterogeneous environment, memory contention. Our system enables us to consider physical dynamics such as heat and power in a way that prior systems are not capable. We demonstrate that our system can handle a variety of constraints of different severities, and can avoid computational obstacles more effectively than na\"ive planning systems which do not consider computational constraints and instead disallow regions as though they are physical obstacles.

The Edvard Grieg field was discovered in 2007 in the Norwegian North Sea and in an active development phase as operator Aker BP and partners, OMV and Wintershall DEA, monitor the production and injection. Production began in November 2015, and water injection began in July 2016. Three OBC 4C seismic surveys were acquired in 2016, 2018, and 2020. The oil bearing reservoir is composed of composed of aeolian sands, fluvial sands, alluvial conglomerates, and shallow marine sands and bounded by unconformities as most of deposition occurred subareally. The reservoir is capped by a regionally extensive chalk unit. This thesis conducts conventional PP pre-stack inversion and joint PP-PS pre-stack inversion on time-lapse seismic data to improve the S-impedance. Introducing the converted wave improves both P- and S-impedances in our final results as joint inversion shows that the S-impedance is not sensitive to saturation changes. We introduce a new workflow which converts impedances to reservoir dynamic properties. We extracted the maximum values from 4D effects to calibrate to pressure and saturation changes. By calibrating the results of inversion to reservoir dynamic properties, this can lead to more detailed conversations among asset teams as they determine reservoir compartmentalization, monitor injected fluids, identify un-swept areas of the field, and alter depletion plans. From the calibration process, there were four identified 4D changes: saturation increase, saturation decrease, pressure increase, and pressure decrease. Using five specified cases, the observed 4D effects were classified as one of the 4D changes. Between 2016 and 2020, the water saturation (saturation increase) of the field has increased on average from a maximum of 38% to 45%. The pressure decrease responds to production and grows in relation to development over the years. With the addition of a new seismic vintage since this project was last analyzed, the geologic interpretations were updated. Previously, the interpretation identified a baffle blocking water flow between two injectors. This research found contradictory evidence as the 2020 survey shows water breakthrough, indicating this area is a zone of lower permeability than the surrounding areas.

Per- and polyfluoralkyl substances (PFAS) are one of the most recalcitrant anthropogenic chemicals that can bioaccumulate and have carcinogenic properties. Their ubiquity in environmental matrices and resistance toward traditional disposal techniques pose a serious threat to the environment and public health. This thesis serves as a preliminary analysis of a novel source of PFAS, the disposal of munitions. Most munitions contain energetic compounds, to serve as the source of energy in detonation events, and fluoropolymers, to bind formulations as a means of stabilization, to seal the formulation away from the elements, or to serve as a fluorine source in pyrolants. Energetic compounds degrade through a variety of pathways, but the major pathways involve the formation of radicals and extreme heat. Despite the extreme recalcitrance of fluoropolymers, the conditions of detonation events are more than sufficient to initiate thermal decomposition in even the most robust fluoropolymers. The thermal decomposition of fluoropolymers involves highly reactive radical intermediates too. Since both energetic compounds and fluoropolymers undergo radical degradation mechanisms, PFAS radical recombination products are expected to be formed. There is little known about such potential PFAS products since they contain functionalities not seen in other sources of PFAS, so a summary of the synthesis and degradation reactions that these species are known to undergo from synthesis work is provided. This work also contains a detailed computational investigation of chemical bonding in such potential PFAS products from the pyrolysis of fluoropolymers in the presence of energetic compounds. Such investigations provide insight to the mechanisms of PFAS production and the types of functional groups to expect which provide guidance to the future analytical work by narrowing the scope of the system. The more that computational work is able to mimic experimental results, the more efficient future laboratory work will be. Thus, this thesis concludes by proposing possible future directions for this work, which includes a wide variety of ways to expand the system to be a more comprehensive representation of reality.

Remobilization 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.  

Nanoparticle 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.

This 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.

This study aims to examine the ability of Eribulin, a non-taxane microtubule inhibitor, to induce a cytokine immune response similar to that of targeted TKI's in lung cancer cell lines, and furthermore to characterize the cytokine response to general growth arrest therapies compared to specific targeted protein kinase inhibitors such as TKI's.

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