• Advances in polymeric nanosensor technology for biological analysis

      Cash, Kevin J.; Ferris, Mark S.; Williams, S. Kim R.; Wu, Ning; Neeves, Keith B. (Colorado School of Mines. Arthur Lakes Library, 2019)
      Polymeric nanosensors are a next-generation sensing technology with the promise to improve the way that scientists, engineers, and healthcare professionals collect analyte data. They have a diameter on the order of 100 nanometers, a polyethylene glycol based lipid coating for biocompatibility, and they utilize luminescence techniques for signal transduction which allows for remote and non-invasive sensor read-outs. This makes them ideal for complex in vitro and in vivo applications in biological environments where the currently available sensor technology falls short. However, being an emerging technology, more research and development is needed to address several current limitations. This thesis presents advancements in polymeric nanosensor technology in three key areas of need: (1) attachment strategies and range control methods in enzyme-based detection mechanisms (2) tools for dynamic range control and extension for ionophore-based detection mechanisms, and (3) methods for background noise elimination. These areas of need are addressed through three reports of technological innovation. The first details a novel method for attaching glucose oxidase to polymeric nanosensors through a biotin/avidin approach, with broader implications for any type of enzyme-based (biomolecule-detecting) polymeric nanosensor. It also demonstrates three methods increasing the apparent enzyme activity associated with each nanoparticle and therefore shifting the response range toward lower glucose concentrations: by tuning the amount of biotin groups on the nanosensor surface, by adjusting the amount of biotinylated-glucose oxidase used during synthesis, and by adjusting the amount of avidin linkers used during synthesis. More biotin groups on the nanosensor surface and more biotinylated-glucose oxidase during synthesis both led to lower response ranges, while an optimal amount of avidin (0.22 mg) lead to the lowest response range. The second report details two designs for dual indicator use in ionophore-based (ion-detecting) polymeric nanosensors with supporting theoretical response models for each. This tool is shown control the sensor LogEC50 over 1.5 orders of magnitude and expand the total range span by 47%. The third report details a bulk optode membrane sensor that incorporates persistent luminescent microparticles into an ionophore-based mechanism for sodium detection. The signal from this ‘glow sensor’ can avoid background noise from biological autofluorescence by programming a delay in between sensor excitation and signal collection. The sensor is also shown to reversibly respond to sodium with a response range of 2.4 – 414 mM sodium and a LogEC50 of 52 mM sodium, with selectivity coefficients of -2.2 and -3.3 over the potentially interfering cations potassium and lithium, respectively, and with a shelf-life of at least 14 days. These three developments solve key issues and help push polymeric-nanosensors toward application in real-world settings.
    • Advancing the computational exploration for thermoelectric materials

      Stevanovic, Vladan; Toberer, Eric; McKinney, Robert W.; Zimmerman, Jeramy D.; Ohno, Timothy R.; Brennecka, Geoffrey (Colorado School of Mines. Arthur Lakes Library, 2019)
      In the computational search for new thermoelectric materials, high-throughput, semi- empirical models have proven to be one of the more fruitful approaches. The best models take into account both electronic and thermal properties since good thermoelectric materials must maintain a difficult balance between the two to achieve high efficiency. In this vein, one route which has proven particularly insightful is to rank materials by their intrinsic thermoelectric quality, which takes into account the density of states, the carrier mobility, and the lattice thermal conductivity, all of which are parameters that either do not change or change in a predictable manner when adjusting temperature or Fermi level. Semi-empirical models of the thermoelectric quality factor (β) have proven successful in suggesting new materials as candidates for good thermoelectric performance. The semi-empirical model of β developed by the Stevanović/Toberer research groups relies on purely isotropic models of the density of states effective mass, carrier mobility, and the lattice thermal conductivity. One aspect which is missing from this approach, however, is any account of the electronic component of thermal conductivity (κe). In thermoelectric materials with very low lattice thermal conductivity, the electronic component can often contribute an equivalent amount to the total thermal conduction. To investigate the potential importance of the electronic component of κ, I developed a novel approach to search for materials with potentially low Lorenz number, which is the coefficient that relates κe to the electrical conductivity, σ. Although the Lorenz number is typically calculated assuming a single parabolic band, I showed that by theoretically driving a material’s energy dispersion away from parabolic, specifically by applying the equivalent of a low pass filter to the energy transport, the Lorenz number can be drastically reduced, leading to a significant enhancement in zT over the single parabolic band approximation. Among the mechanisms by which such an affect could occur are the existence of offset multiple bands in conjunction with intervalley phonon scattering. Based on this plausibility argument, I developed a high-throughput search metric, the density of states shape factor, to provide insight in the search for materials with potentially low Lorenz number. By using this metric as a secondary screening tool in conjunction with the existing semi-empirical β, the vast majority of known thermoelectric materials were found to fall within the search parameters. By extension, new materials within the same bounds were identified for further investigation. In addition to enhancing the search for new isotropic thermoelectric materials, the bulk of my research has been devoted to the development of models to screen materials based on anisotropic transport properties. A computational investigation of anisotropic transport within thermoelectric materials had yet to occur. This absence would have neglected materials which have average isotropic performance, but potentially promising properties along one direction. Well-known thermoelectric materials, such as SnSe, Bi2Te3, and Mg3Sb2, are layered materials in which the intrinsic transport would be inherently anisotropic in single crystals, warranting an investigation into anisotropic transport for single-crystal thermoelectric applications. Before thorough investigations into anisotropic transport began, I conducted a survey of materials which we would expect to demonstrate anisotropic single crystal transport. Layered systems, due to their inherent quasi-2D structures, were obvious candidates. Layered thermoelectrics such as SnSe and Bi2Te3 belong to a class of materials which are bound by loose van der Waals (vdW) bonds. A large set of these vdW layered materials had previously been identified through the use of a slab-cutting algorithm. In addition to the vdW layered materials, there exists another set of layered compounds which is of interest to the thermoelectrics community. Compounds such as Mg3Sb2 and the A1B2C2 Zintl thermoelectrics belong to class of layered materials which are more tightly bound than vdW layered materials, due to the existence of an ionically-bound “spacer” elements between the layers. Using a modified version of the slab-cutting algorithm, that I redesigned specifically for the purpose of finding systems belonging to this class, I identified over 1500 of the so-called “ionic” layered compounds, which are often clays. These compounds exhibit inherent structural anisotropy, yet they are a distinct class from the vdW layered compounds because the bonding between layers can range from very weak, near vdW bonding, to very tight, nearly covalent bonding. Additionally, I was able to show that these materials can be structurally linked to the vdW layered materials from which they can be derived by the addition of a spacer element. By conducting an in-depth analysis of the similarities and differences between these two classes of layered systems and assessing the elastic anisotropy, I revealed a rich diversity of anisotropic behavior within this set, which laid the groundwork for further studies of anisotropic transport on this class of materials. Using both the vdW and ionic layered compounds as a material test set, I began the work of building new semi-empirical models for anisotropic transport. The first step was to create a model of anisotropic thermal conductivity. In addition to thermoelectric applications, a model of anisotropic κL is important for any application in which single crystal thermal conductivity is of interest. I created a new anisotropic model for thermal conductivity which achieved an accuracy within a factor of 2 across 5 orders of magnitude. Applying this model to vdW and ionic layered compounds revealed that anisotropy within κL wanes as the minimum value approaches the amorphous limit. Additionally, by examining the high end and low end of thermal conductivity, new potential materials were identified for thermoelectric or power electronic applications based on their predicted κL(θ,φ). The last part of my investigation into anisotropic transport was to build a new model for the prediction of anisotropic carrier mobility. Building upon intuition from the existing semi-empirical model of mobility, I created the new model for directional mobility by using isotropic and anisotropic elastic parameters along with the conductivity effective mass tensor. By fitting the new model to a set of experimental values gathered for over 60 compounds, the new model achieved an accuracy within a factor of 3 across 4 orders of magnitude, which was a significant improvement over the previous isotropic model. Combining the anisotropic mobility and anisotropic lattice thermal conductivity, I was able to create three different metrics by which to rank materials and screen the vdW and ionic layered compounds to search specifically for materials with ideal anisotropic transport.
    • Alteration and mineral paragenesis of the McArthur River and Fox Lake uranium deposits, Athabasca Basin: a new model for the formation of unconformity-related uranium deposits

      Monecke, Thomas; Wendlandt, Richard F.; DeDecker, John; Hitzman, Murray Walter; Pfaff, Katharina; Sharp, Jonathan O. (Colorado School of Mines. Arthur Lakes Library, 2019)
      The McArthur River uranium mine in the Athabasca Basin, Canada, hosts the largest high-grade uranium deposit in the world, accounting for 12% of global uranium production in 2015. McArthur River is a Proterozoic unconformity-related uranium deposit, with ore bodies located in the P2 fault zone at the unconformity between conglomerate and metamorphic basement rock, and up to 120 m below the unconformity in basement rock. Oxidized basinal fluids are considered the most likely medium for transporting dissolved UO22+ to the unconformity. The reductant responsible for precipitating UO2 is unknown. Core logging and sample collection were followed by bulk compositional analysis. Optical microscopy, scanning electron microscopy, and electron microprobe analysis were used to establish the mineral paragenesis. Here, a new model for the reduction of uranium at McArthur River is proposed. The observations indicate that the P2 reverse fault is characterized by the abundant presence of fault-hosted pre-ore pyrite veins. The formation of these veins resulted in the illitization of feldspar in the basement rocks. Oxidizing, high-salinity Na-Mg-Ca chloride basinal fluids penetrated into the basement along the P2 fault and oxidized the pre-ore pyrite veins. Pyrite veins were replaced by Fe3+-bearing sudoite. Fe-sudoite altered pyrite shows extreme sulfur isotope fractionation consistent with oxidation of pyrite by thiosulfate disproportionation. It is hypothesized that the reaction of basinal fluids with pre-ore pyrite was responsible for the reduction of UO22+ at McArthur River. A comparative study of the nearby Fox Lake unconformity-related uranium deposit was performed to evaluate the general applicability of the genetic model developed for McArthur River. The Fox Lake uranium deposit is a complex-type unconformity-related uranium deposit 10 km west of McArthur River. The mineralization is located along the C-10 fault zone at the unconformity between the basal conglomerate of the Manitou Falls Formation and metamorphic basement rock. The Fox Lake investigations included extensive drill core logging and systematic sampling. Bulk compositional analyses were performed to complement core logging. A paragenesis was established using optical and scanning electron microscopy, and electron microprobe analysis. Petrographic and sulfur isotope investigations show that the large amount of pre-ore pyrite occurring in sandstone above the C-10 fault was oxidized by thiosulfate disproportionation and replaced by Fe-sudoite and a second generation of pyrite. The evidence suggests that the oxidation of pre-ore sulfide minerals by basinal fluids resulted in the precipitation of uraninite. These results are consistent with the genetic model proposed for McArthur River.
    • Amorphous matrix effects on silicon nanoparticles

      Steirer, K. Xerxes; Pierce, Connor P.; Collins, Reuben T.; Zimmerman, Jeramy D. (Colorado School of Mines. Arthur Lakes Library, 2019)
      The search for new materials is a vital endeavor, as the world demands more from the technologies available, new technologies must be developed. As current semiconductors are pushed to their operating limits, the need for new wider bandgap semiconductor technology has become apparent. In this work, the quantum confinement of silicon quantum dots (SiQDs) in various semiconductor materials was examined. The chosen materials were the wide bandgap semiconductor amorphous silicon carbide (SiC) as well as amorphous silicon synthesized using plasma enhanced chemical vapor deposition (PECVD). Amorphous silicon carbide is an interesting material as it has a similar band structure to silicon while functioning in higher temperature and operating power conditions due to it's larger bandgap. The measurement of confinement of the dots was attempted using photoluminescence (PL) and spectroscopic ellipsometry (SE). In addition to measuring quantum confinement, since SiC had not yet been synthesized using the PECVD system in this work, a literature review was conducted to both determine the feasibility and capabilities of growing the SiC films. After the review was finished, the PECVD system was modied to allow for the growth of SiC films both with and without SiQDs. Once growth of the films was complete, the films had to be characterized to determine if the growths were successful. This was accomplished using Fourier transform infrared (FTIR) spectroscopy and SE. Growth and characterization of the SiC films was successful. Growth of SiC films containing SiQDs was also accomplished in this work, while the measurement of confinement of the SiQDs within yielded varying levels of success. Quantum confinement was successfully observed with the SiQDs bandgap increasing to between 1.2 and 1.3 eV, however no signicant differences in bandgap were observed as the surrounding matrix was changed.
    • Analysis of anorthite dissolution at the microscopic scale

      Navarre-Sitchler, Alexis K.; Malenda, Margariete GeorgeAlan; Gorman, Brian P.; Spear, John R.; Squier, Jeff A.; Yin, Xiaolong (Colorado School of Mines. Arthur Lakes Library, 2019)
      Constraining the processes behind feldspar dissolution is imperative in understanding the how these reactions facilitate carbon dioxide (CO2) sequestration in ongoing efforts to mitigate climate change. Yet attempts to quantify the kinetics behind these processes typically result in major discrepancies between the field and laboratory observations used to inform models that predict this dissolution. Many of these discrepancies are the result of not properly accounting for the distributions of flow rate, flow path, and solution chemistry from field to laboratory scale of observations. Here we are able to control solution flow rate, flow path and chemistry with a new degree of accuracy at the pore scale using microfluidic devices that are both free of solute build-up and contain an entire flow network comprised of the reactive mineral of interest. In this study, we have analyzed anorthite dissolution using pH 3, 4, and 5 influent solutions at flow rates of 0.56, 1.13, and 2.25 μL min-1, and measured Ca2+ fluxes ranging from 5.53×10-8 to 6.44×10-7 mg min-1 and reaction rates ranging from 7.47×10-10 to 8.83×10-9 mol m-2 sec-1. Our results are among previously measured plagioclase dissolution rates measured at similar pH’s. Furthermore, we have extended the correlation between dissolution rates and residence times (τ), in that our reaction rates are orders of magnitude greater than other rates from the literature while our τ are orders of magnitude lower. This relationship between τ and plagioclase dissolution rates is maintained, in some cases, despite differences in temperature and influent composition from study to study. These observations lead us to consider that residence time, as impacted by flow rate and flow geometry, is a strong control on plagioclase dissolution rates across observation scales. Understanding influences on residence time and its role in mineral dissolution is key as we address climate change with carbon sequestration development in geologic reservoirs.
    • Analysis of Velocity Variation with Azimuth (VVAZ) for natural fracture and stress characterization, Vaca Muerta Formation, Neuquén Basin, Argentina

      Sonnenberg, Stephen A.; Tura, Ali; Benitez, Pablo E.; Carr, Mary; Simmons, James (Colorado School of Mines. Arthur Lakes Library, 2019)
      The upper Tithonian – lower Valanginian Vaca Muerta Formation, located in the Neuquén Basin, Argentina, is one of the most prolific unconventional shale plays in the world. It spans an area of around 30,000 km2, covering four different provinces, Neuquén, Mendoza, La Pampa, and Rio Negro. Because the unit requires multistage horizontal wells in order to produce commercially, detailed analysis of the regional stress and natural fractures of the area is needed. Previous studies have shown that both the Neuquén Basin and the Vaca Muerta Formation are highly affected by stress due to their proximity to the Andes chain, and also that the unit may present a high density of natural fractures. This study is located in a block operated by Wintershall Holding GmbH, where previous research projects focused on natural fractures analysis from well images, seismic inversions for mechanical parameters prediction, and well based anisotropic geomechanical models. Using well log and wide-azimuth seismic data, analysis for natural fractures and stress characterization was performed. Well based anisotropic geomechanical models were built for the three wells in the area using well logs, laboratory measurements and completion data. Stresses were calculated and calibrated with fracture data. For the studied block, the stress regime in the Vaca Muerta Formation is mainly strike-slip (SH>SV>Sh), with local areas showing normal (SV>SH>Sh) and thrust (SH>Sh>SV) regimes. In this thesis, the Lower Vaca Muerta section is recommended as a possible landing zone based on stress and fracability analysis, and considering previous studies and current practices in the basin. Anisotropy and azimuthal analysis from wide-azimuth seismic data showed that maximum horizontal stress is oriented between 105º and 120º. It also proved the presence of two sets of extensional fractures oriented at 50º and 150º, formed at different stages during the development of the basin. All these observations show a reasonable calibration with log and microseismic data. Finally, following the azimuthal analysis and results from the geomechanical models, new drilling areas and landing points are suggested for the studied block.
    • Anisotropic analysis of unconventional reservoirs using rock physics model: Eagle Ford shale case study

      Simmons, James; Durmus, Ufuk; Tura, Ali; Shragge, Jeffrey; Miskimins, Jennifer L. (Colorado School of Mines. Arthur Lakes Library, 2019)
      Eagle Ford shale has been of importance in the oil and gas industry with the new advent of unconventional technology in recent years. Previous studies have shown that Eagle Ford shale is a world-class source rock. Rock physics models help characterize the elastic properties of conventional and unconventional reservoirs. In this thesis, I present a novel rock physics model for organic-rich shales. The extended Maxwell homogenization scheme is utilized as a rock physics model for transversely isotropic media. Since shales have complex structures, different components of the rock are modeled as multiple inclusions. First, I estimate the anisotropic clay matrix. This is then used as the host matrix, and quartz, calcite, kerogen, and fluid-filled pores are modeled as inclusions with different aspect ratios. Representation of multiple inhomogeneities with different aspect ratios is non-trivial. Yet, I suggest a solution to the representation difficulty using this new model. The Maxwell homogenization scheme honors the aspect ratio of each inclusion embedded in an effective inclusion domain. Combined rock physics models have been used to obtain elastic properties of clays and shales. Notwithstanding, there is no consistent method for modeling both. The developed rock physics model and workflow thoroughly handle the estimation of elastic stiffness coefficients of both clays and shales in anisotropic media. This study shows that this rock physics model can be readily applied to other unconventional reservoirs. Dipole sonic log and core measurements of the Eagle Ford shale field are utilized to constrain the modeling results. I process and interpret dipole sonic logs to obtain elastic stiffness coefficients C33, C55 and C66. Subsequently, I use these coefficients to validate the outcomes of the Maxwell homogenization scheme. To my knowledge, this is one of the first studies that verify the robustness of this rock physics template with field data. After obtaining the elastic stiffness tensor of the Eagle Ford shale in VTI media, I estimate the Thomsen parameters (i.e. anisotropy parameters). Anisotropy parameters epsilon, gamma and delta, on average, are 0.19, 0.29 and 0.04, respectively based on my modeling results in Eagle Ford shale. Anisotropic modeling results exhibit a good correlation with dipole sonic logs. Both dipole sonic log analysis and rock physics results demonstrate that clay content is the main driver of anisotropy in the field, and there is a direct relationship between clay volume and anisotropy parameters of epsilon and gamma. In addition, kerogen and fluid-filled pores have second-order influence on anisotropy in shales. Anisotropic analysis is of importance in this study because neglecting anisotropy can lead to erroneous seismic interpretation, processing, and imaging in the area of interest. This new model allows one to estimate geomechanical properties as well as seismic properties. The directional dependence of geomechanical properties should be taken into account in order for operators to optimize hydraulic fracture design and to develop the field more efficiently. In addition, I investigate implications of the modeling results on multicomponent seismic data. Amplitude variation with angle (AVA) analysis shows increasing anisotropy in the reservoir could result in significant variation in P-wave, C-wave and S-wave datasets. I show that the isotropic assumption results in deviation at the mid and far angles.
    • Anthropogenic impacts on the water and energy balance of an urban semi-arid environment

      Hogue, Terri S.; Maxwell, Reed M.; Reyes, Bryant; Hering, Amanda S.; McCray, John E.; Peters-Lidard, Christa Dianne, 1969- (Colorado School of Mines. Arthur Lakes Library, 2019)
      As the world rapidly urbanizes, a grasp of water resources within an urban context becomes crucial to both the policy and scientific communities. Yet many of the operational and management models used to inform these policies lack vital parameterizations needed to simulate the hydrologic system holistically. Anthropogenic processes and changes to the hydrologic cycle caused by urbanization (land use change, denser building patterns, increases in imported water and water use, increased surface imperviousness, increased subsurface infrastructure, etc.) are known to have significant and interacting impacts on the hydrologic system as a whole; only recently has the hydrologic community been able to quantify these effects and understand their behavior. The work presented here assesses the processes simulated by an integrated, coupled land surface and hydrologic model at various spatial scales in the urban domain. Throughout this work data pertaining to Ballona Creek watershed in Los Angeles, California is used in both model building and analysis. The watershed contains highly urbanized and diverse portions of the cities of Santa Monica and Los Angeles, along with more natural land surfaces in the northern portions of the watershed, with a wide range of urban land cover and land use scenarios in a semi-arid environment. We begin this work by utilizing two land cover datasets for the City of Los Angeles: (1) the National Land Cover Database (NLCD) dataset at a 30-m resolution; and (2) an ultra-high-resolution dataset at a 0.6-m resolution. Various permutations and resolutions of the model are simulated for a spin-up and two-year study period. The impact of the highly organized, yet heterogeneous, land cover typical of the urban domain is shown to impact the runoff/runon process characteristics of these domains, creating variations in overland flow and evapotranspiration (ET). Spatial scaling land surface and hydrologic parameters creates systematic diurnal biases in the surface energy budget in contrast to the seasonal biases causes by lateral flow processes. In addition to creating land surface parameters for the widely used NLCD urban land covers, this work illustrates nonlinear issues of scale and resolution and improves understanding of how these processes affect the surface energy and hydrologic budgets. Next, remotely sensed observations of land surface temperature and land cover are paired with domestic water use data to assess the direct impact of outdoor water use. We find a decrease of up to 3.2±0.02 Kelvin between low and high irrigation areas of similar land cover; simulations are able to capture this difference but underestimate absolute values throughout. Model simulations show that irrigation timing has a small impact on ET and runoff and that relatively low irrigation volumes push the semi-arid urban environment of Ballona Creek into a sub-humid regime. Finally, we utilize a range of land surface and hydrologic models applied at a high spatial resolution (1-km) to quantify some of the deficiencies seen in the simulation of semi-arid urban environments and to provide a framework for future work in the field.
    • Application and integration of ruthenium catalysts for water treatment and resource recovery

      Strathmann, Timothy J.; Huo, Xiangchen; Pylypenko, Svitlana; Higgins, Christopher P.; Trewyn, Brian; Cath, Tzahi Y.; Ciobanu, Cristian V. (Colorado School of Mines. Arthur Lakes Library, 2019)
      Water contaminants in oxidized form can be preferably removed or transformed to less harmful species by chemical or biological reduction. Hydrogenation metal-catalyzed reduction has emerged as a promising treatment technology for oxidized pollutants (e.g., oxyanions, halo- and nitro-organics). To date, Pd-based catalysts have received significant attention and demonstrate good activity and stability in reducing a number of contaminants relevant to drinking water or groundwater, but the deployment of catalytic reduction systems remains limited, in large part, by the high cost and volatile market price of this metal. The narrow focus on Pd-based materials also hinders the advancement of catalytic reduction technology because other hydrogenation metals are being overlooked which may have exhibited higher activity for specific contaminants. In addition, demonstrating catalytic activity with multiple metals can reduce uncertainty in the cost of the technology by allowing for metal substitution during market price spikes. Thus, it is necessary to expand catalyst “toolbox” for the water treatment applications and to integrate catalysts with other technologies (e.g., separations processes) to advance the development of practical water catalysis technologies. To develop alternative hydrogenation metal catalysts for water purification, several supported platinum group metals catalysts were assessed with a suite of representative oxyanion pollutants. Rh, Ru, Pt and Ir were found to exhibit higher activity, wider substrate selectivity or variable pH dependence in comparison to Pd. A detailed investigation, coupling experiments with computational work, was then conducted to identify mechanisms controlling nitrate and nitrite reduction by supported Ru catalysts. Pseudo-first-order rate constants and turnover frequencies were determined for carbon- and alumina-supported Ru, and this work demonstrated Ru’s high activity for hydrogenation of nitrate at ambient temperature and H2 pressure. Pretreatment of the catalysts was found to enhance nitrate reduction activity by removing catalyst surface contaminants and exposing highly reducible surface Ru oxides. Ru reduces nitrate selectively to ammonia and nitrite to a mixture of ammonia and N2, with the product distribution determined by the initial aqueous nitrite concentrations. Experimental observation and Density Functional Theory calculations together support a reaction mechanism wherein sequential hydrogenation of nitrate to nitrite and NO is followed by parallel pathways involving the adsorbed NO that lead to ammonia and N2. The activity of supported Ru catalysts was further evaluated for reducing N-nitrosamines, including the toxic disinfection byproduct N-nitrosodimethylamine (NDMA) and other organic water contaminants. Using NDMA as a representative contaminant, commercial Ru/Al2O3 catalyst showed high activity with an initial turnover frequency (TOF0) of 58.0 ± 7.0 h-1. A second Ru/Al2O3 catalyst was synthesized using an incipient wetness impregnation technique, and this catalyst exhibited higher initial pseudo-first-order rate constant than the commercial catalyst due to higher dispersion of Ru nanoparticles on the catalyst support. NDMA was reduced to dimethylamine (DMA) and ammonia end-products, and a small amount of 1,1-dimethylhydrazine (UDMH) was detected as a transient intermediate. Experiments with a mixture of five N-nitrosamines spiked into tap water (1 g L-1 each) demonstrated that Ru catalysts are very effective in reducing a range of N-nitrosamine structures at environmentally relevant concentrations. These results encourage the further development of Ru catalysts as part of the water purification and remediation toolbox. Supported Ru catalyst was then integrated into a hybrid catalytic hydrogenation/membrane distillation process to improve nitrate-contaminated ion exchange waste brine management and recover valuable nitrogen resources. The ability of a commercial Ru/C catalyst to reduce concentrated nitrate was demonstrated in a semi-batch reactor under typical waste brine conditions. Nitrate hydrogenation exhibited zero-order kinetics, attributed to saturation of available surface reaction sites, and the apparent rate constant was influenced by both solution chemistry and reaction temperature. The resulting ammonia product was efficiently recovered using membrane distillation. At low temperatures (<35 °C), solution pH showed significant impact on ammonia mass transfer coefficient by controlling the free ammonia species fraction. Ammonia recovery efficiency was not affected by salt levels in the brine, indicating the feasibility of membrane distillation for recovering ammonia from waste ion exchange brine. The hybrid catalytic hydrogenation/membrane distillation process was also applied to a real ion exchange waste brine and demonstrated high nitrate hydrogenation and ammonia recovery efficiency. These findings provide alternative catalyst for catalytic treatment of ion exchange waste brine and design option of efficient, low footprint system for nitrogen resource recovery from waste ion exchange brines. In addition, the efforts of catalyst and process development were extended to the field of bio-renewable energy. Leveraging fuel property predictive models, a non-cyclic branched C14 hydrocarbon (5-ethyl-4-propylnonane) was identified to be a potential target molecule for renewable diesel applications. This target molecule is accessible from butyric acid through sequential catalytic reactions of acid ketonization, ketone condensation, and hydrodeoxygenation. Catalytic activity, product selectivity, and catalyst stability for individual conversion step were first evaluated, followed by demonstration of hydrocarbon blendstock production from butyric acid through integrated conversion process scheme. Experimental fuel property testing of the conversion product validated its suitability for use as diesel blendstock.
    • Application of geostatistical methods for the quantification of multiple-scale uncertainty due to aleatory geologic variability, The

      Walton, Gabriel; Trainor-Guitton, Whitney; Boyd, David Lane; Santi, Paul M. (Paul Michael), 1964-; Mooney, Michael A.; Smits, Kathleen M. (Colorado School of Mines. Arthur Lakes Library, 2019)
      Tunneling projects in rock are characterized by a high degree of spatial uncertainty, which is due in part to the natural, random (aleatory) variability the rock possesses. Some degree of variability is intrinsic to all rock, and is present due to the complex nature of its deposition or emplacement and subsequent tectonics. This variability is present at multiple spatial scales, from heterogeneous grains to the project scale, where tectonics cause variability in discontinuity properties. As this variability contributes to overall uncertainty in tunneling projects, it is critical to understand and characterize this variability at multiple relevant scales. This research isolated the component of spatial uncertainty associated with aleatory geologic variability and evaluated statistical and geostatistical methods for quantification and characterization of this variability. Geostatistics has been commonly used in natural resource extraction and other data-sparse environments, and has been used extensively in this research as a means by which to better predict, characterize or quantify spatial uncertainty associated with aleatory geologic variability. As the first contribution of this thesis, 2-D covariance maps were generated for rock core specimen photos and were analyzed to identify the number of specimens required in order to adequately represent rock strength. This contribution identified a method by which to quantify this without testing large numbers of specimens at great cost. Next, sequential indicator cosimulation was used to integrate sparse borehole data with a geologist’s interpretation of subsurface lithology, identifying the value added by having a geologist’s interpretation over borehole data alone in uncertainty quantification. This identifies uncertainty in a geologist’s interpretation for use in tunneling projects, whereas geologist interpretations do not typically reflect spatial uncertainty besides boundary uncertainty (besides qualitative indications of confidence in specific parts of geologic boundaries). Finally, indicator kriging was used to quantify uncertainty in ground conditions both prior to and during excavation of the Caldecott Fourth Bore Tunnel in California, USA, demonstrating an approach by which engineers and geologists could quantify uncertainty to inform high-level decision making. The completion of these works provides valuable insight into aleatory variability at multiple spatial scales and demonstrates novel approaches to integrate different types of geotechnical data, including subjective and interpreted, into geostatistical algorithms to better understand spatial uncertainty in the context of tunneling.
    • Applied machine learning for multi-sensory robot perception

      Zhang, Hao; Zhang, Ziling; Petruska, Andrew J.; Williams, Thomas (Colorado School of Mines. Arthur Lakes Library, 2019)
      In recent years, advances in autonomous robotics have begun to transform how we work and live. Unmanned Aerial Vehicles (UAV) and Unmanned Ground Vehicles are helping us to deliver goods, conduct surveys of construction sites, and perform search and rescue alongside first responders. However, designing robots with this level of autonomy is often challenging due to the complexity of the real-world environment. Multi-sensory perception is a critical component to address this challenge and develop robust autonomous robotic systems. By combining multiple inputs from sensors, the system can eliminate a single point of failure from sensor degradation and generate new insights to make better decisions integrating information from dierent sensor modalities. Recent breakthroughs in Machine Learning, especially the Deep Neural Network(DNN) based deep learning perception pipelines have been proven effective in a number of robot perception tasks. However, the significant computation cost for Deep Neural Networks is prohibiting their deployment on a robot system with limited power budget and real-time performance requirement. It is important to bridge this gap by optimization to deploy state-of-the-art machine learning models to a real-world robot systems. This work investigates the viability to develop robust multi-sensory robot perception systems enhanced by machine learning models in three different chapters. First, I explore the effectiveness of DNN perception pipelines in object detection and semantic segmentation tasks, then experiment on various model optimization techniques to enhance the efficiency of these perception models, achieving real-time performance on robot system with a limited power budget. Then I elucidate the design and implementation of a thermal sensing robot system that performs sensor fusion of a thermal camera and an RGB-Depth Camera to automatically track occupants in a building, measuring their forehead temperature, providing fine-grain information for better decision making in intelligent Air Conditioning (AC) system. Finally, I explore camera pose estimation using rectangular to spherical image matching, enabling a robot to quickly grasp a scene with spherical camera, and allow other robots to localize themselves within the scene by matching rectangular sensor images to the spherical image.
    • Applying mathematical models of human circadian rhythms for experimental design and data analysis

      Diniz Behn, Cecilia; Stack, Nora E. H.; Pankavich, Stephen; Leiderman, Karin; Norrgran, Cynthia (Colorado School of Mines. Arthur Lakes Library, 2019)
      The adult human circadian pacemaker has an intrinsic period just over 24 h that entrains to a 24 h day by environmental cues such as light, eating, and exercise. Dynamic phenomenological mathematical models of the human circadian pacemaker have been developed to simulate the pacemaker's response to light. These models have been widely used for applications such as minimizing jet lag and optimizing experimental protocol design. This thesis is focused on applying mathematical models to account for the interindividual differences that are inherently present in humans and therefore also in circadian data. We optimized an experimental protocol to ensure robust performance across individuals with varying intrinsic circadian periods. Next, we developed novel MCMC-based methodology to use phase shift data to determine the mean intrinsic circadian period of a group of study participants. Finally, we investigated parameter sensitivity of a circadian pacemaker model and applied this knowledge to an adolescent data set where distinct behavior within the cohort was observed. This thesis highlights the utility of human circadian pacemaker models in a variety of contexts and establishes new insights into properties of these models and their influence on behavior.
    • Atom probe tomography of small-molecule organic semiconducting materials

      Zimmerman, Jeramy D.; Proudian, Andrew P.; Gorman, Brian P.; Diercks, David R.; Sellinger, Alan; Collins, Reuben T. (Colorado School of Mines. Arthur Lakes Library, 2019)
      For organic electronics, film morphology is crucial to device performance, requiring techniques with both high spatial resolution and chemical sensitivity that are suitable for these materials. This work demonstrates that atom probe tomography (APT) is well-suited to this purpose. It can provide sub-dalton mass resolution, detection thresholds of less than 100 ppm, and spatial distribution of molecules with better than nanometer precision. These capabilities mean that APT can successfully analyze systems of interest to the organic electronics community, revealing new morphological information that can enable better devices through improved understanding of structure-property relationships. To demonstrate the power of APT to uncover structure-property relationships in organic systems that have proven extremely difficult to probe using existing techniques, three examples are discussed: (1) a model organic photovoltaic system in which a chemical reaction occurs at the heterointerface, explaining a change in open circuit voltage; (2) a model organic light-emitting diode (OLED) system in which molecular segregation occurs in the emissive layer bulk, which has ramifications for efficiency; and (3) controlled ultraviolet exposure of an OLED emitter in which photodegradation occurs, quantifying degradation product hierarchies. These examples illustrate the power of APT to enable new insights into organic molecular materials. Additionally, a new tomographic reconstruction method is presented that corrects for near field trajectory aberrations. It does so by correcting for detector density fluctuations in an unbiased way that generates an ensemble of solutions. This is demonstrated with a simulated sample of amorphous Si with small B clusters, a system in which there is a large field difference that can completely obscure clustering signal. Comparing this new method with the standard commercial protocol, the new method improves the accuracy of reconstruction and allows for better spatial signal recovery. This enables analysis of more challenging materials systems with APT. APT creates numerous opportunities for studying organic electronic systems. As a result of its spatially resolved chemical information, APT allows for quantitative understanding of composition, morphology, phase behavior, device physics, and device degradation. APT is invaluable for furthering our understanding of organic electronic systems and enables us to collect information that was previously inaccessible.
    • Atomic norm algorithms for blind spectral super-resolution problems

      Wakin, Michael B.; Helland, Jonathan W.; Tang, Gongguo; Vincent, Tyrone (Colorado School of Mines. Arthur Lakes Library, 2019)
      This thesis focuses on the development of atomic norm based algorithms for particular instances of blind super-resolution problems appearing in wireless communications, modal analysis in sensor networks, and target localization in radar signal processing. Blind super- resolution problems are a harder version of canonical super-resolution problems in that they include more degrees of freedom that must be resolved due to additional sources of blurring via unknown linear transformations. Our atomic norm algorithms focus on leveraging special sparsity structure with respect to certain dictionaries inherent in the signals of interest. We first provide a relatively self-contained introduction to and review of the atomic norm’s use in non-blind and blind super-resolution problems. We then develop theoretical tools towards establishing guaranteed blind super-resolution for a problem which we refer to as multi-band line spectral estimation – an extension of line spectral estimation to signals whose composite waveforms occupy continuous frequency bands rather than discrete spikes. We introduce a generic signal model that can be used to model multi-sensor blind super- resolution problems, which are of particular interest in radar signal processing and sensor networks. We establish some theoretical results about computationally tractable techniques for computing the atomic norms that arise from our proposed multi-sensor signal models. We next apply our multi-sensor atomic norm algorithm to the problem of modal analysis from vibrational measurements – a blind super-resolution problem arising in structural health monitoring and acoustics. We finally apply our multi-sensor atomic norm algorithm to the problem of extended target localization in stepped-frequency radar signal processing. This problem is relevant to near-field radar imaging including through-the-wall radar imaging.
    • Automated methods for generating least privilege access control policies

      Yue, Chuan; Sanders, Matthew W.; Camp, Tracy; Tilton, Nils; Wu, Bo; Yang, Dejun (Colorado School of Mines. Arthur Lakes Library, 2019)
      Access controls are the processes and mechanisms that allow only authorized users to perform operations upon the resources of a system. Using access controls, administrators attempt to implement the Principle of Least Privilege, a design principle where privileged entities operate using the minimal set of privileges necessary to complete their job. This protects the system against threats and vulnerabilities by reducing exposure to unauthorized activities. Although access control can be considered only one area of security research, it is a pervasive and omnipresent aspect of information security. But achieving the Principle of Least Privilege is a difficult task. It requires the administrators of the access control policies to have an understanding of the overall system, each user's job function, the operations and resources necessary to those job functions, and how to express these using the access control model and language of the system. In almost all production systems today, this process of defining access control policies is performed manually. It is error prone and done without quantitative metrics to help administrators and auditors determine if the Principle of Least Privilege has been achieved for the system. In this dissertation, we explore the use of automated methods to create least privilege access control policies. Specifically, we (1) develop a framework for policy generation algorithms, derive metrics for determining adherence to the Principle of Least Privilege, and apply these to evaluate a real world dataset, (2) develop two machine learning based algorithms for generating role based policies and compare their performance to naive methods, and (3) develop a rule mining based algorithm to create attribute based policies and evaluate its effectiveness to role based methods. By quantifying the performance of access control policies, developing methods to create least privilege policies, and evaluating their performance using real world data, the projects presented in this dissertation advance the state of access control research and address a problem of great significance to security professionals.
    • Autonomous navigation in GPS denied environments using MPC and LQR with potential field based obstacle avoidance

      Petruska, Andrew J.; Steele, John P. H.; Appapogu, Rahul Dev; Zhang, Hao; Zhang, Xiaoli (Colorado School of Mines. Arthur Lakes Library, 2019)
      Workers in mining industry are posed with hazardous environments due to the nature of the work inside a mine. Gas leaks, explosions, rock falls, entrapment, long exposure to dust are all potentially fatal conditions for the workers. Although solutions for the problems are being implemented, they are not sufficient and mostly are very expensive. \newline Autonomous robots can reduce the risk for miners by taking over potentially dangerous tasks for them. For instance, an autonomous robot can carry operations like air quality assessment, inspection of dangerous mine conditions and even perform search and rescue tasks in disaster situations. \newline This thesis presents robots that can traverse through the mine environment with on board sensors collecting data without any human intervention. Control and Obstacle avoidance algorithms are designed and presented in this thesis for the robots, ground and aerial platforms. A Model Predictive Control (MPC) approach is presented which includes pre-packing of necessary terms that would help decrease the computation costs. A Linear Quadratic Regulator (LQR) approach is also presented and its performance against the Model Predictive Control approach is presented in presence and absence of obstacles. A Potential Fields based obstacle avoidance approach is presented which makes use of octomaps. \newline Experimental results are promising as both aerial and ground platforms perform navigation without any GPS and avoid obstacles if any, in a simulation. Fast solve times on the order of hundreds of micro seconds are obtained and the results are compared with other existing techniques and presented. A real-time implementation of the ground robot has been made in various GPS denied environments and the results are presented. In real-time as well, the robot performs navigation avoiding obstacles in all cases.
    • Benchmarking isosopin symmetry breaking in ab initio nuclear theory via the isobaric multiplet mass equation in T = 1 superallowed β decay systems

      Leach, Kyle; Martin, Matthew S.; Sarazin, Frederic; Holt, Jason D. (Colorado School of Mines. Arthur Lakes Library, 2019)
      Searching for physics Beyond the Standard Model (BSM) has become a central focus in physics research over the past few decades. One way to do this is through precision measurements of superallowed 0+ → 0+ Fermi β decay. These decays give the most precise measurements of the vector coupling constant of the weak interaction, an important step in calculating the up-down element of the Cabibbo-Kobayashi-Maskawa (CKM) matrix. CKM unitarity, if broken, would imply significant physics BSM. However, the extraction of the vector coupling constant assumes perfect isospin symmetry in nuclei, requiring theoretical isospin symmetry breaking (ISB) corrections to be applied. The ISB corrections can be calculated using ab initio nuclear many body methods using interactions from chiral effective field theory. However, before these corrections can be used reliably for BSM physics searches, they must be benchmarked against known results. In this Thesis, ab initio methods are used to calculate the coefficients of the isobaric multiplet mass equation (IMME) for T = 1 superallowed 0+ → 0+ Fermi β decay systems. The implications of the IMME coefficients to ISB corrections are also discussed.
    • Breathing new life into postmortem analysis: the testing and formalization of a methodology for the identification of key failure modes in dry holes

      Milkov, Alexei V.; Samis, Jack M.; Trudgill, Bruce, 1964-; Koch, Phillip S. (Colorado School of Mines. Arthur Lakes Library, 2019)
      The petroleum exploration industry relies on various subsurface data and interpretations to minimize risk and uncertainties and maximize gains. Dry holes provide a wealth of useful subsurface information. However, far too often a company drills a dry hole and either does not conduct a postdrill analysis (postmortem), or incorrectly determines the failure mode. The purpose of this study is to formalize and test the applicability of a postdrill methodology (a decision tree) that helps identify the main failure mode for dry segments tested by conventional wells. Use of this decision tree allows the interpreter to evaluate and identify specific failure modes such as reservoir presence, reservoir deliverability, structure, seal, source maturity, and migration. The decision tree was tested on three exploration wells drilled in the Taranaki Basin, offshore New Zealand. Each segment’s key failure mode was identified based on the comprehensive, integrated evaluation of both pre- and postdrill reports, seismic data, well logs, geochemical analysis of gases and source rocks, and other materials freely available through the New Zealand government. Each individual segment’s unique failure mode has been carefully identified and compared to the failure mode(s) presented by the original operator of the well. It is my hope that this decision tree, or its customized versions, will become the best practice in postdrill analysis across the exploration industry. However, the acceptance and utility of the decision tree is tied largely to its applicability and ease of use. With that being said, the methodology described has met all of the objectives of this study’s evaluation, but should continue to be tested on other exploration wells from a variety of sedimentary basins.
    • Bulk compositional controls on mineral assemblages in metamorphosed ore deposits: an example from the LaRonde-Penna gold-rich VHMS deposit, Quebec, Canada

      Kelly, Nigel; Thomas, Helen; Monecke, Thomas; Kuiper, Yvette (Colorado School of Mines. Arthur Lakes Library, 2019)
      The hydrothermal processes driving alteration during the formation of VHMS deposits, and therefore the overall geochemistry, mineralogy, and geometry of alteration halos, are reasonably well understood. However, less is known about the effects of metamorphism on altered rocks and the resulting metamorphic mineral assemblages that develop in different alteration zones. Exploration for VHMS deposits is typically targeted at the alteration halos, which can extend for considerable distances compared to the deposits themselves. However, in terranes of greenschist grade and above exploration can be complicated by the effects of metamorphism and deformation, which may have changed the original mineralogy and geometry of alteration zones. To address these issues, research targeted the link between pre-metamorphic alteration halo zonation and resulting mineral assemblages by integrating detailed characterization of mineral assemblage and geochemical zoning with phase equilibria modeling of footwall rocks to the LaRonde-Penna VHMS deposit. The work aimed to further our understanding of the bulk compositional controls on mineral assemblage development during metamorphism, and to test whether a phase diagram approach is a viable method to assist future exploration for VHMS deposits in metamorphosed terranes. The LaRonde-Penna Au-rich VHMS deposit (71 Mt of Au at 3.9 g/t), located in the southern Abitibi greenstone belt in Quebec, Canada, is a well-characterized metamorphosed VHMS deposit. Two transects through the altered rhyodacitic-rhyolitic footwall to the main (20N) ore lens were selected, with each transect preserving contrasting mineral assemblages that have previously been interpreted to reflect different alteration types. Within Transect 1, garnet-bearing, aluminosilicate-absent assemblages show an increase in size, abundance, and Mn content of garnet, inferred to reflect increased alteration intensity as the ore lens is approached. Alteration intensity in the footwall area of Transect 1 is characterized by increases in Mn, Fe, Mg, and K, and decreases in Si, Na, and locally Ca. In Transect 2, aluminosilicate-bearing assemblages with or without garnet and staurolite are developed in altered rocks, and assemblages show a broad increase in porphyroblast size and intensity of schistosity as the ore lens is approached. Alteration intensity in the footwall in Transect 2 is similarly characterized by increases in Fe, Mg, and K, and decreases in Si and Na. Mn is not enriched. The results from this study indicate that garnet stability is distinctly influenced by Mn content and relative proportions of Fe and Mg. In addition, with sufficient enrichment in rock Mn contents, garnet may be stabilized to temperatures as low as ~270°C (in altered metarhyolite), significantly lower than temperatures required to stabilize biotite-bearing assemblages. In addition, biotite-bearing assemblages are stabilized to lower temperatures in rocks with elevated Ti, and the persistence of chlorite to higher temperatures is likely controlled by rock Mg concentrations. The similarity in bulk rock aluminum content between rocks from both transects, despite the high abundance of aluminosilicates in Transect 2 (but absence in Transect 1), indicates that aluminosilicate mineral stability is influenced by bulk compositional factors other than aluminum. Conventional thermobarometry and constraints from P-T pseudosections indicate that peak P-T conditions during metamorphism at LaRonde-Penna were approximately 510-530ºC and 3.8-4.2 kbar, with absolute maximum temperatures constrained by the absence of sillimanite in Transect 2 rocks. Also in Transect 2 rocks, inclusion trails in andalusite define a foliation that is parallel to an external foliation defined by biotite and kyanite (with or without staurolite) that may wrap andalusite porphyroblasts. In addition, sillimanite locally forms fringes on biotite and kyanite. These data support the interpretation that metamorphism progressed along a prograde clockwise loop with a limited excursion into sillimanite-stable conditions. The progression of textures involving multiple mineral assemblages that define foliations in the rocks suggests that the rocks experienced regional metamorphism. This is further supported by the lack of any assemblage zoning with respect to nearby intrusions that would indicate the presence of a contact aureole. Inconsistencies between mineral assemblage and inferred pre-metamorphic alteration zone imply that the mineralogical differences within metamorphosed VHMS deposit footwalls may not be obvious reflections of bulk rock geochemistry. Outcomes from this study confirm the applicability of phase equilibria modeling as a predictive tool to effectively describe the relationship between pre-metamorphic alteration zone mineral assemblages and their metamorphosed equivalents.
    • Characterization of galvanized/galvannealed sheet steel defects towards enabling defect free zinc coatings

      De Moor, Emmanuel; Seetharaman, Sridhar; Plessinger, Ryan; Bourne, Gerald; Yu, Zhenzhen (Colorado School of Mines. Arthur Lakes Library, 2019)
      As more emphasis is being placed on reducing the weight of vehicles while increasing safety ratings through advanced high strength steels allowing use of thinner metal gauge corrosion properties become more important. To protect these steels against corrosion, a hot-dip galvanizing process is used. An additional annealing step may follow to produce galvannealed (GA) steels. The present thesis characterized microstructure and chemistry of defects in four industrially produced steels, 3 GA steels and one galvanized (GI) steel. Material A was shown to have a streaking type defect in a GA coating. Light optical microscopy (LOM) showed macroscopic periodicity of 1.5-2 mm between streaks. Time of flight secondary ion mass spectrometry (TOF-SIMS) analysis showed the presence of Mn rich oxides at the steel-coating interface. Two mechanisms were attributed to defect formation, the Zn pot sink roll micro-grooved surface and Mn rich oxides were shown to affect coating thickness. Material B was received as having acne type defects in a GI coating. Scanning electron microscopy (SEM) showed a uniform coating, and the steel-coating interface was planar. TOF-SIMS showed that the areas associated with the defects were Zn rich, and no evidence of chemical contribution to coating formation. The defect formation mechanism was unclear, however it appeared to be a Zn splash and a function of processing parameters e.g.. air knife operating conditions. Two ends of an identical coil were received for Material C: one showing a flame pattern defect, and one end exhibiting a defect free coating. SEM showed the coating surface exhibited a temper roll surface finish, and that the coating thickness for the end without defects was thinner than the end with defects. Defect formation may relate to the difference in temper roll response from the coil and/or Zn solidification growth due to difference in substrate microstructure. Material D was received as having a striped defect, denoted “tiger stripes”. The stripes could be observed in the hot rolled, as-pickled, cold rolled, and GA condition. SEM analysis showed that the coating in areas associated with the stripe was approximately half as thick as areas without stripes. Chemical analysis showed that high levels of Cr, Mn and Si were found within area associated with the stripe in the cold rolled condition. Defect formation may relate to insufficient oxide removal by pickling.