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Synthesizing morphology-controlled, high entropy perovskite nanomaterials for solid oxide fuel cellsWater splitting is important to a green energy future. Current issues with efficient water splitting include degradation of the fuel cell materials, thermal expansion, and transport through the material. Precise control of nanomaterial composition and morphology are among a materials scientist's tools to design novel low-cost and efficient materials. One way to improve material performance through controlling the composition is to create a high entropy oxide. There has been great interest in high entropy oxide systems because of the ability to combine multiple well-performing cations into one oxide phase, taking advantage of the synergistic effect. This work focuses on Ba, Sr, Ca, Co, Fe, and Mn cations (promising candidates for solid oxide fuel cell electrodes) in the perovskite ABO3 structure. Controlling the synthesis method to achieve single-phase, high entropy materials and maintaining nanomorphology will be discussed in this presentation. Aerogel synthesis is done in an autoclave with pseudo supercritical fluid drying, which allows immediate departure of the solvent and promotes nanomaterial production, resulting in a dry powder. However, subsequent calcination steps to achieve a single-phase oxide often sinters the materials, which removes the desired morphology. Different morphologies are of interest to be used in solid oxide fuel cells because it may improve performance depending on the unique surfaces that are exposed with different free energies.
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SALER@FRIB: superconducting tunnel junctions for sub-keV precision nuclear physics experimentsPrecision beta decay is sensitive to TeV-scale physics via CKM unitarity (V_{ud}) and angular correlations (exotic scalar and tensor currents). However, beta spectroscopy is challenging. Nuclear recoil spectroscopy is sensitive to both, but typically inaccessible because of its low energy. New quantum sensors with great resolution and speed allow probing these energies at high rates. We have worked to characterize the electronics and predict the Standard Model spectrum for the Superconducting Array for Low Energy Radiation experiment, coming soon to the Facility for Rare Isotope Beams.
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Estimating methane emission durations using continuous monitoring systemsUpdates to the EPA's Greenhouse Gas Reporting Program Subpart W will come into effect in January 2025, which include a requirement to report all "maintenance or abnormal emission events." Estimating the duration of emission events is critical for accurate reporting, as the total emitted volume depends heavily on the length of the emission. If an operator is unable to estimate a start and end date for a given emission, a duration of 6 months must be assumed. Infrequent sampling surveys via, e.g., an airplane can provide rough estimates of emission duration, but the minimum duration estimate from this method is bounded by the sampling frequency, which is often quarterly at best. Continuous monitoring systems (CMS), on the other hand, measure methane concentrations in near-real time and hence provide a promising avenue for more robust, measurement-informed emission duration estimates. Here we present a method for creating duration estimates using CMS data. Our proposed method uses a gradient-based spike detection algorithm to cluster enhancements in the concentration time series into events and quantifies uncertainty by assessing the information content of the underlying concentration data as a function of wind direction. We present an evaluation of the method on controlled release data and apply it to a production oil and gas site in the Appalachian basin. We compare duration estimates from our method to estimates provided by infrequent aerial sampling.
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Semiconducting metal oxide-based gas sensorThis research presents the development and characterization of advanced metal oxide semiconductor (MOX) gas sensors designed for the detection of reducing gases, specifically methane and propane. Employing semiconducting n-type oxides such as SnO2, In2O3, and WO3, the study explores the mechanisms by which these materials modulate resistance in response to varying gas concentrations. Through a detailed examination of the preparation methodologies, which include screen printing techniques on alumina substrates equipped with a gold heater for precise temperature control, the research investigates the hypothesis that tungsten oxide may exhibit enhanced performance attributes due to its reduced susceptibility to hydroxylation, compared to its counterparts. This work aims to offer a significant contribution to the field of gas detection technology, underpinning the potential for improved sensor performance and reliability.
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Basis for change: approximate stationary models for large spatial dataIn geostatistics, traditional spatial models often rely on the Gaussian Process (GP) to fit stationary covariances to data. It is well known that this approach becomes computationally infeasible when dealing with large data volumes, necessitating the use of approximate methods. A powerful class of methods approximate the GP as a sum of basis functions with random coefficients. Although this technique offers computational efficiency, it does not inherently guarantee a stationary covariance. To mitigate this issue, the basis functions can be "normalized" to maintain a constant marginal variance, avoiding unwanted artifacts and edge effects. This allows for the fitting of nearly stationary models to large, potentially non-stationary datasets, providing a rigorous base to extend to more complex problems. Unfortunately, the process of normalizing these basis functions is computationally demanding. To address this, we introduce two fast and accurate algorithms for the normalization step, allowing for efficient prediction on fine grids. The practical value of these algorithms is showcased on both simulated and observed climate data, where significant computational speedups are achieved. While implementation and testing is done specifically within the LatticeKrig framework, these algorithms could be adapted to other basis function methods operating on regular grids.
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Development of a very weak analog sandstone for brittle instability modelling in underground excavationAn unusually very weak (ISRM, 1981) brittle analog sandstone is developed. Brittle analog sandstone specimens are prepared, conforming to mortar mixing terminology. Base mix constituents used are Type I/II Portland cement, F-75 Ottawa sand, and distilled water. The developed sedimentary rock is isotropic, homogenous, and densely compacted. Engineering treatments to the mixture were found to improve the brittleness.
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Metal loading dynamics in the hyporheic zone as a result of acid mine drainageAcid mine drainage (AMD) and acid rock drainage (ARD) pose significant environmental challenges, as the acidic, metal-laden drainage seeps into surface and groundwater systems, often resulting in substantial ecological damage. The hyporheic zone, where surface and groundwater meet, serves as a natural filtration system, where biogeochemical reactions occur that influence metal retention and transformation. By analyzing changes in metal concentrations and phases throughout time and space, valuable information can be gained in regards to the mechanisms at work within the hyporheic zone. This knowledge is critical for the development of remediation plans for AMD and ARD affected sites, such as Coal Creek, the source of drinking water for the town of Crested Butte, Colorado. The ability to protect the potability of Coal Creek is vital for both safeguarding public health as well as maintaining ecosystem integrity. In order to better understand the complexities of this dynamic system, hyporheic sediment and sediment from planted control soil columns were sampled on a seasonal basis. Samples were analyzed for phase changes via XRD and sequential extractions created using the samples were analyzed via ICP-OES for elemental fraction concentrations. Preliminary results show the retention and release of metals, particularly iron, through various phase changes occurring within the hyporheic zone. These changes are seasonally dynamic and vary from site to site along the creek, illustrating the capacity of the hyporheic zone to act as a filter for AMD at different points throughout the year.
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Fluid saturation estimation using Full Waveform Inversion (FWI): a controlled laboratory experimentThis study explores the use of Full Waveform Inversion (FWI) and fluid substitution analysis to estimate fluid saturation in a laboratory setting, focusing on monitoring fluid injection processes crucial for enhanced oil recovery, hydraulic fracturing, and carbon capture and storage (CCS). Employing time-lapse FWI (4D FWI) in a controlled experiment, the study aims to detect changes in fluid saturation within a Berea Sandstone sample and evaluate the effectiveness of traditional methods like Gassmann fluid substitution in capturing the complexities of fluid-rock interactions under partially saturated conditions. The research outlines a meticulous experimental procedure for acoustic data acquisition, mesh creation, data preprocessing, and the application of FWI to obtain high-resolution P-wave velocity models. These models challenge the conventional expectations set by Gassmann's theory, particularly noting unexpected P-wave velocity reductions post brine injection, which are attributed to factors such as patchy saturation and wave-induced fluid flow (WIFF). Concluding with insights and recommendations for future research, the thesis advocates for the refinement of FWI parameters, the development of more accurate fluid substitution models, and the adoption of advanced computational techniques. This work represents a significant contribution to the field, demonstrating the potential of 4D FWI in laboratory experiments for enhancing fluid injection monitoring and reservoir characterization.
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Ecosystem impacts of critical material recovery and processing: ecotoxicity testing on DGA extractantsModern technologies are heavily dependent on the critical material (CM) used to construct them. Emerging CMI research evaluates the effectiveness of new recovery and treatment processes, but there is some concern about the waste generated from these efforts. Our project goal is to assess the environmental toxicity of the newly developed CM processing and recovery technologies to avoid producing emerging environmental contaminants. Our experimental platform includes a series of ecological toxicity tests to assess the potential environmental impacts of new critical material recovery or recycling technologies. This will include rare earth element complexing DGAs such as TODGA, DGA6, DMODGA, and the process-relevant solvents, Isopar-L and 1-octanol. The ecotoxicity indicators chosen include the wastewater bacerium Nitrosomonas europaea, the small crustacean Daphnia magna, and the green alga Raphidocelis subcapitata (formerly known as Selenastrum capricornutum). Preliminary data on the ecotoxicity impacts of DGAs and a comparative analysis of complexants will be presented. This data will be benchmarked against the current standard of CM recovery that uses reagent PC-88A. This knowledge can be used to identify critical material processing techniques with a lower impact and / or waste remediation strategies to reduce environmental toxicity. Our project benefits society by providing a basis for understanding how critical material recovery affects the environment and how remediation strategies can aid in the detoxification of processing waste.
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Critical mineral recovery from unconventional sources: developing a workflow to evaluate placer tailings for critical mineral potentialCritical minerals are vital to the economy and national security of the United States due to their essential functionality and vulnerable supply chains. The U.S. is significantly dependent on other countries for many of these minerals, making the transition to domestic production of these materials a strategic priority. Critical minerals are also essential to sustainable development and are crucial to renewable energy technologies. As such, there is an urgent need to develop multi-disciplinary, techno-economic workflows for critical mineral recovery from unconventional sources such as mine waste (tailings). To work towards these goals, I am conducting a case study of gold placer mine tailings in Flat, Alaska to determine the viability of reprocessing tailings and extracting critical elements. The town of Flat is a historic gold mine in the Kuskokwim Mountains that consists of fluvial placer deposits on creeks that flank a mineralized granitic intrusive body. The Flat tailings present potential critical element contents of tungsten, arsenic, chromium, and tin, as well as other non-critical elements. These elements are associated with or occur within the structure of various mineral phases. The first stage of this project involves mineral processing and analytical techniques to define a workflow for processing tailings and determining bulk geochemistry, volume, and weight percentage of minerals present. Critical mineral recovery from mine tailings has the potential to contribute to the achievement of sustainable development goals and a circular economy, the reduction of mining waste, and the mitigation of environmental hazards associated with tailings.
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Distinguishing deltas and fluvial fans on MarsAncient lakes on Mars and the deltas that occur along their shorelines offer attractive targets for mission landing sites due to their habitability and biosignature preservation potential. Furthermore, the presence of deltas is used to map paleoshorelines for paleo-oceans and lakes on Mars. Jezero Crater was chosen as the NASA Perseverance landing site because the fan-shaped channel network here was interpreted as a delta. However, on Earth, fan-shaped channel networks may also form in fluvial fans which are inland terrestrial landforms that can form 1000s of kilometers from shorelines. We demonstrate that morphometric criteria are needed to identify fan-shaped landforms for potential future landing sites accurately. The goal of this research project is to differentiate deltas and fluvial fans on Mars by quantifying fan-shaped paleochannel network morphometrics. We map Martian fan-shaped paleochannel networks using images from the Mars Reconnaissance Orbiter (MRO) photomosaics using ArcGIS. The outcomes of this project will improve our ability to choose appropriate landing sites in search of life and to map paleo-shorelines on Mars. Preliminary results suggest that most fan-shaped channel networks on Mars resemble fluvial fans, while the channel network at the Eberswalde crater resembles a delta. Fluvial fan formation has been linked to large sediment and water discharges, and to fluctuations in discharge because of highly seasonal precipitation in climatic settings that promote marked seasonal and interannual hydrological changes, leading to variable discharge regimes and exceptional flood events. Alternative evidence is required to identify paleo-shorelines as fluvial fans may also form along shorelines.
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Helium recovery from natural gas over porous organic cage membranesAlthough helium is a valuable inert gas available in abundance in the earth's atmosphere, the major source of helium is from natural gas reservoirs. Membrane based separation processes pose many advantages like being cost effective and non-energy intensive. In this current study, we have successfully demonstrated the synthesis of continuous Porous Organic Cage: CC3 membranes to separate equimolar helium methane mixture with permeance of 4.45 x 10−7 mol/ (m2 s Pa) and separation selectivity (α) as high as 8. We also compared the diffusion coefficients of the gases through the membrane to evaluate the dominant mechanism for separation. Lastly, we compared the performance of our membranes to the state-of-the-art membranes with the help of a Robeson plot and found that our membranes outperformed the upper bound.
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Understanding charge carrier mobility in Hg₂GeTe₄High charge carrier mobility in semiconductor materials is desirable across a broad range of fields ranging from light-emitting devices to thermoelectrics. Electronic mobility is driven by both the intrinsic electronic band structure of the material as well as the energy dependent electron scattering mechanisms. Semiconductors with excellent mobility span a large chemical space: transparent conductor CdO, topological insulator HgTe, and Zintl compound KAlSb4. Therefore, engineering high mobility from chemistry alone is difficult if not impossible. Relating chemistry and synthetic processing to their impact on mobility is highly desirable, but experimentally difficult. Adding a fourth thermomagnetic measurement, the Nernst coefficient, to the traditional thermoelectric transport measurement suite (resistivity, Hall coefficient, Seebeck), allows the experimentalist to derive a carrier lifetime/scattering parameter as a function of temperature. We design a custom apparatus to measure the Nernst effect and perform initial model measurements to address the question of what scattering mechanisms limit the mobility of several potential thermoelectric materials. In our design, we test different sample and sample holder geometries to optimize reproducibility. For the model materials we measure the Nernst signal at low magnetic field (µB < 1) in addition to traditional Hall coefficient, Seebeck, and resistivity. We employ the method of four coefficients to determine four electronic parameters: µ, n, m*DOS, and λ (scattering factor). By utilizing the method of four coefficients, we can decouple effects from electronic band structure from energy-dependent scattering effects, and therefore design optimal thermoelectric materials and validate the scattering predictions from computational methods.
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Applications of post-quantum cryptography - survey and application of machine learningQuantum Computing poses a considerable threat in the world of cyber security. Policy makers are largely unprepared for a post-quantum world, significantly due to a lack of understanding and awareness. The goal of this paper is to improve understanding and provide a new and effective way to analyze post-quantum cryptography, for researchers and security engineers alike. This is done by providing a background of quantum computing, a survey of the state of technologies and relevant policies, and a novel application of machine learning to perform analysis of quantum-ready encryption. The machine learning research will provide a Multinominal Naïve Bayes for discrete analysis of the RSA and CRYSTAL-Kyber encryptions.
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Reversible solid oxide electrochemical system as seasonal energy storage in ultra-high renewable energy grid scenariosThe electrochemical production of hydrogen by surplus variable renewable energy (VRE) can reduce the cost of future energy systems. Supported by favorable electric grid conditions and increasing research and development investments, large-scale power-to-gas (P2G) plants are increasingly being deployed worldwide. Techno-economic and energy planning analyses involving hydrogen production and energy storage typically take either "price-taker" or "production cost" modeling approaches, with the "price-taker" approach being predominant. However, given the increasing development and deployment of P2G plants, price-taker models based on the fundamental assumption that the presence of an individual P2G plant will not affect electric grid conditions are no longer valid. To address this issue, the present research uses a production cost model that minimizes the electric grid's total energy generation cost to capture the benefits of operating a utility-scale, grid-connected reversible electrolyzer plant. A generic methodology to analyze seasonal energy storage operating in an ultra-high VRE grid (> 90% integration levels) is developed, and a newly developed seasonal storage modeling methodology is then implemented to analyze the integration of a reversible solid-oxide electrolyzer system with such highly penetrated VRE grid scenarios. This research shows that the reversible solid-oxide system operating in an ultra-high VRE grid can reduce the annual electricity generation cost by 5-15% (subject to grid conditions).
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Integrating full-field optical methods, inverse techniques and traditional mechanical testing for damage tolerancing in CFRPs under impact fatigueComposite structures are susceptible to transverse loading due to their inherent layered structure, particularly when under impact. Under low energy repetitive impacts (LERI), little is understood regarding damage mechanisms, damage accumulation, and the post-mortem global response of the composite material under different loading configurations. In this study, we examine carbon fiber-reinforced composite (CFRC) plates subjected to low energy repetitive impacts of 2 J to investigate their behavior under impact fatigue. Post-mortem specimens are then investigated using three main methods: digital image correlation (DIC), the virtual fields method (VFM) and compression-after-impact (CAI) tests. DIC is used to extract surface kinematics under an applied static load to observe the evolution of strain fields under bending as the number of impacts accumulate. This data is then used as input for VFM analysis which is used to reveal local gaps in mechanical equilibrium, allowing it to be used as an indicator of damage. Next, ASTM standard CAI tests are performed on the impacted specimens to compare ultimate compression strength values. X-ray computed tomography (XCT) is also used to corroborate damage detection provided by the equilibrium gap method and identify catastrophic microstructural damage pre-cursors. Using quasi-isotropic 8-ply CFRC plates, XCT results showed that interlaminar cracking appeared in as little as 10 impacts. At 100 impacts, extensive matrix cracking and delaminations were observed. After 300 impacts, severe delaminations were imaged using XCT, while barely visible surface cracks were imaged on the rear face of the specimen.
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Elucidating algal extracellular polymeric substance structures with asymmetrical flow field-flow fractionation and light scatteringExtracellular polymeric substances (EPS) from algae are complex, secreted, aquatic heteropolymers (comprised of carbohydrate and proteins), possibly functioning as carbon sinks. EPS has tremendous potential to be utilized as high-value coproducts, e.g. hydrocolloids or biobased polymers, and playing a significant role in the overall aquatic ecology (feeding a healthy microbiome) during cultivation. Unfortunately, the structural elucidation of these polymers is elusive in literature making the design of custom applications difficult. We must characterize these polymers on a chemical, structural, and physical level to understand their biological significance and industrial potential. The first step is to reduce the complexity of EPS with a size-based separation such as asymmetrical flow field-flow fractionation (AF4). When coupled to multi-angle light scattering (MALS), AF4 can provide the separation and characterization needed to determine the molecular weight and size of different populations in the sample. This work evaluates the different size populations present in the EPS of Chlorella vulgaris using AF4-MALS. Fractions were collected and analyzed to probe differences in compositional analyses between the different size populations. The separation investigates aggregate behavior at different ionic strengths to better understand the interactions of these biopolymers in their native, higher salinity, environments. The EPS of C. vulgaris has demonstrated diverse molecular weight populations ranging from 4x104 – 3x108 Daltons. We observed a reduction of fractogram features at high ionic strength indicating polymer aggregation. This work aims to be the first step in complete structural determination of EPS while probing fundamental separation observations on polymer behavior at different salt concentrations.
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Quantifying channel network morphometrics at Jezero and Eberswalde cratersAncient lakes on Mars and the river deltas which occur along their shorelines offer attractive targets for mission landing sites due to their habitability and high biosignature preservation potential. Deltas are promising targets for finding organic molecules and other signatures of life because on Earth deltas have biodiverse and rich ecosystems. Furthermore, the presence of deltas are used to map paleoshorelines for ancient oceans and lakes on Mars. For instance, Jezero Crater was chosen as the NASA Perseverance landing site because the fan-shaped channel network at the edge of the crater was interpreted as a delta. However, on Earth, fan-shaped channel networks may also form in fluvial fans that are inland terrestrial landforms that can form 1000s of kilometers from shorelines. We demonstrate that morphometric criteria are needed to accurately identify fan-shaped landforms for potential future landing sites. The goal of this research project is to differentiate deltas and fluvial fans on Mars by quantifying fan-shaped paleochannel network morphometrics. To accomplish this, we map Martian fan-shaped paleochannel networks using images from the Mars Reconnaissance Orbiter (MRO) High Resolution Imaging Science Experience (HiRISE) and Contex Camera (CTX) photographs in combination with ArcGIS. Morphometric data is statistically analyzed using python and other open-source data visualization libraries. The outcomes of this project will improve our ability to choose appropriate landing sites in search of life, and to map paleo-shorelines on Mars. Preliminary results suggest the channel network at Jezero resembles a fluvial fan, while the landform at Eberswalde crater resembles a delta. Fluvial fan formation has been linked to large sediment and water discharges, and to fluctuations in discharge as a result of highly seasonal precipitation in climatic settings that promote marked seasonal and interannual hydrological changes, leading to variable discharge regimes and exceptional flood events. Alternative evidence is required to identify paleo-shorelines as fluvial fans may also form along shorelines. On Earth, fluvial fans are less sensitive to sea-level rise and coastal hazards than deltas and react differently from deltas due to changing sea levels.
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Temporal downscaling for solar radiationGlobal and regional climate model projections are useful for gauging future patterns of climate variables, including solar radiation, but data from these models is often too spatio-temporally course for local use. Within the context of solar radiation, the changing climate may have an effect on photo-voltaic (PV) production, especially as the PV industry moves to extend plant lifetimes to 50 years. Predicting PV production while taking into account a changing climate requires data at a resolution that is useful for building PV plants. Temporal and spatial downscaling of solar radiation data is widely studied. We present a novel method to downscale global horizontal irradiance (GHI) data from daily averages to hourly profiles, while maintaining spatial correlation of parameters characterizing the diurnal profile of GHI. The method focuses on the use of a diurnal template which can be shifted and scaled according to the time or year and location. Variability in the profile is later added to account for clouds if the daily average value indicates a cloudy day. This analysis is applied to data from the National Solar Radiation Database housed at the National Renewable Energy Lab and a case study of the mentioned methods over California is presented. This method will later be applied to future projections of solar radiation from bias-corrected regional climate models to create a massive dataset that projects solar radiation for future years across the United States.
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Failure conditions and triggers of the Achoma landslide, central Andes region, Arequipa PeruThe Colca River valley in southern Peru is the longest waterway of the Pacific Peruvian hydrologic basins, starting in the Perú Altiplano, and crossing the western Andean Cordillera to the Pacific Ocean. The area has been regularly impacted by large landslides of the valley slopes, and geologic evidence documents intense, recurrent, and catastrophic events, like landslides, debris avalanches, and floods. On June 18, 2020, more than 5,400,000 m3 of soil and weak rock slid into the Colca River valley near the town of Achoma. The rotational slide involved 40 hectares of land that was displaced 500 meters. The event destroyed the agricultural land, impacting the economy of many families, and the displaced material over the Colca River created a dam that increased the risk of flooding for the towns upstream. The exact factors that led to the landslide in Achoma, including triggering factors, are uncertain. The activity of farms, most of which are currently irrigated or have been irrigated in the past, and the presence of a large water transportation canal upslope of the landslide are the most likely causes of the increase in ground-water levels leading to failure. The purpose of this work is test various groundwater and infiltration scenarios to estimate the amount of water involved in the destabilization and triggering of the Achoma landslide, using numerical simulation of changing groundwater conditions. While not definitive, our early work indicates that, even though the landslide occurred during the dry season and before the irrigation began for the year, we cannot yet rule out irrigation as a contributing factor. On the other hand, increasing ground-water levels from leakage from the water conveyance canal appears to be a necessary component to cause slope failure.
