Student Research & Publications: Recent submissions
Now showing items 21-40 of 401
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Determining polarity in ferroelectric materials using precession electron diffraction and cepstral analysisUnderstanding local crystallography is necessary for understanding ferroelectric behavior in materials. Key properties to know include lattice parameters, interatomic spacings, and polarity. One tool to learn these properties is scanning transmission electron microscopy (STEM), which can measure a diffraction pattern (kx, ky) at every scan position (x, y). This allows crystallographic properties to be investigated at the nanometer scale. However, diffraction signals can contain artifacts from sample thickness and mistilt. These artifacts may be suppressed with precession electron diffraction (PED), which has the additional benefit of increasing the number of reflections in the diffraction pattern. In this work, we perform analytical calculations to assess the efficacy of using PED combined with cepstral analysis to measure polarity in lead magnesium niobate-lead titanate (PMN-PT). Taking the Fourier transform of the logarithmically scaled diffraction pattern yields the exit-wave power cepstrum (EWPC) which yields interatomic spacings in the crystal. To extract polarity, we use the imaginary component of the transform which contains the antisymmetric information, which is called the exit-wave imaginary cepstrum (EWIC). The EWIC transform is improved by having more higher-order diffraction disks, which is possible through PED. It was found that PED improves the EWIC signal: as precession angle was increased from 0° to 0.5° to 1°, signal noise decreased and dipole moments were better resolved in scenarios with and without mistilt. These results indicate that cepstral analysis of real samples may benefit from PED.
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Rhizomes of ranked posetsWe introduce and study the notion of a rhizome for a ranked, partially ordered set (or poset) where each set of fixed rank is finite. A rhizome is defined as a minimal size subset of the elements of rank n such that each of the elements of rank n + 1 covers at least one element of the rhizome. Given a poset P with ranked parts Pn, we consider the function rP : N → N which gives the size of a rhizome for Pn, and study this function for examples like the Boolean lattice and Young's lattice.
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Machine learning-enabled medical device materials (MLMDM)Machine learning (ML) methods can provide exceptional enhancements to both the performance and manufacturing of medical device materials. Enhanced materials and methods to make them can transform medical device fabrication and healthcare. Improved quality assurance and real-time error detection become feasible with ML algorithms. Fabrication steps can be implemented with greater precision, efficiency, and waste minimization. Production parameters can be fine-tuned, including the prospect of tailoring materials and devices to individuals, enabling personalized care. We highlight three examples of ML technologies under development in our Transdisciplinary Nanostructured Materials Research Team (TNMRT). We are developing Convolutional Neural Networks (CNN) to develop 1) antimicrobial copper surface nanostructures, 2) ferrofluid methods to detect magnetic phases in stainless steel, and 3) optical image analyses to predict alloy formability to fabricate surgical devices.
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Active subspace coarse-graining with spherical harmonicsMany groups of molecules exhibit self-assembly behavior to form large-scale hierarchical structures. Scientists are interested in identifying the molecular basis for self-assembly, but the spatial and temporal resolution of current experimental techniques precludes observation of assembly details at the nanoscale. Meanwhile, conventional all-atom computer simulations remain too costly, and coarse-grained simulations, which trade detailed information for lower computational complexity, remain difficult to apply to macromolecular assembly. We utilize a supervised dimension reduction approach called active subspaces to enable coarse-grained simulations of self-assembling systems at reduced computational cost (compared to all-atom) and increased accuracy (compared to other coarse-grained models). The active subspace method identifies the most important directions in an input parameter space that influence a corresponding output function. The goal of this project is to develop and formalize the active subspace framework to derive coarse-grained models from all-atom data for reversibly aggregating alanine peptides. Our strategy is to explore spherical harmonics as the input parameter space, corresponding to potential energies as the output. Preliminary results indicate that a reduced set of spherical harmonics can provide a descriptive basis useful for coarse-grained modeling and simulation.
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Ambient oxidation dynamics of copper antimicrobial surfacesIn recent years, increased resistance of pathogens to traditional antibiotics has mounted serious health concerns. The development of novel, improved, and non-selective antimicrobial agents is necessary to combat the further spread of infectious disease and protect public health from antibiotic resistant superbugs. Recent advancements in understanding naturally biocidal surfaces have led to the development of nanopatterning techniques aimed at enhancing the antimicrobial properties of metallic substrates like copper. Copper possesses natural antimicrobial activity which can be enhanced by creating nanoscale surface features. Leveraging the heightened biocidal effect of copper substrates holds promise across various applications to address the escalating challenges posed by bacterial resistance and the proliferation of infectious diseases. However, despite its efficacy and common use in antimicrobial applications, copper is susceptible to oxidation in ambient environments. To understand how copper surfaces change when used in biocidal applications, surface oxide thickness on four copper substrates was periodically measured using ellipsometry to characterize the growth of cuprous oxide under ambient conditions. Such analysis aims to quantify oxide layer thickness and delineate the growth kinetics of cuprous oxide under ambient conditions, providing crucial insights into the response of copper substrates to ambient environmental factors. Understanding surface oxidation dynamics is pivotal in evaluating the long-term antimicrobial efficacy of copper and optimizing its applications in combating infectious diseases.
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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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Meet the editorsThe editors are Tyler Pritchard, Editor in Chief, Wyatt Hinkle, Graphic Design Editor, Taylor Self, Technical Sciences Article Editor, James Talbot, Social Sciences Article Editor, McKenna Larson, Content Editor, and Austin Monaghan, Language Editor.
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Evaluation of the Paris Agreement from a realist and liberalist perspectiveOne of the greatest questions in international relations is how states can work together towards common goals despite having competing interests. This issue is central to the international effort to mitigate climate change. To this date, 185 parties have ratified the Paris Agreement to limit the rise in global temperatures to 1.5 to 2 degrees Celsius. Although this agreement has so far received widespread international support, implementation has proven difficult.
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Evaluating eribulin's ability to produce a cytokine immune response in lung cancerThis study aims to examine the ability of Eribulin, a non-taxane microtubule inhibitor, to induce a cytokine immune response similar to that of targeted TKI's in lung cancer cell lines, and furthermore to characterize the cytokine response to general growth arrest therapies compared to specific targeted protein kinase inhibitors such as TKI's.
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Laboratory spotlight CFCCThe Colorado Fuel Cell Center (CFCC) is a laboratory on the Colorado School of Mines campus that specializes in the analysis and development of fuel cell systems.
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Exploring fractional derivatives and trig functionsThe objective of this research is to become familiar with fractional discrete calculus to the extent that fractional derivatives of discrete trigonometric functions can be taken and understood.