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At least 1,315 records · Page 73

Rare earth elements of fly ash from Wyoming's Powder River Basin coal

The advancement and increasing interests in green energy production and environmental protection technologies have spurred the demand for rare earth elements. On the other hand, the U.S. has to rely 100% on import of these materials as the industry was crashed because of the environmental issues associated with mining and processing, and more importantly lack competitiveness. As rare earth elements have many applications in defense and national security sectors, some of the elements were listed as strategic materials or critical materials because of the uncertainties in supply and prices. Therefore, it has become imperative in searching for alternative resources for supplying rare earth elements including unconventional resources. With the strong incentive, coal fly ash is identified as one of the candidates among them. In this study, we present rare earth element data for the 42 ash samples (all derived from Powder River Basin coal) that we collected from seven states (UT, WY, IO, WI, ND, CO, and MI) representing 158 million tons of fly ash. Overall, the results indicate scattered distributions of rare earth elements with concentration ranging from 156 to 590 ppm although all the ash samples originated from the same coal basin (Powder River Basin). The rare earth element resource in these ashes is estimated between 74000 and 106000 t. The ash samples were also characterized by elemental analysis, XRD, SEM-EDS and BET surface area. The characterizations of the ashes were discussed as they might have implications in the subsequent rare earth element extraction processes. In summary, fly ash may represent a potential resource for rare earth element production.

01 COAL, LIGNITE, AND PEAT↗

Analysis of Sludge Batch 10 Samples from Tank 51H (HTF-51-18-94, -95)

Savannah River National Laboratory characterized sludge samples from Tank 51H that is being used to generate Sludge Batch 10. The composite slurry sample from Tank 51H was analyzed and determined to contain a concentrated salt solution with a sodium concentration of 5.79 M (1.33E+05 mg/L) and insoluble sludge solids content of 7.20 wt% (using all nine replicates from the 3 wt% total solids measurements). Hydroxide is the main anionic species in the salt solution with a concentration of 3.00 M followed by nitrate (0.728 M) and nitrite (0.657 M). The sum of the major cations versus the sum of the major anions from the analysis of the filtered supernatant liquid phase shows a difference of <5% indicating good data quality. The results from the analysis of the digestions of the well mixed composite slurry sample show sodium to be the main component of the total dried solids of the sample followed by aluminum, iron, manganese, and thorium. Additional measurements of the weight percent total solids and density using hand shaking of the sample bottle and recirculation through a peristaltic pump indicate both methods provide adequate mixing of the sludge slurry sample.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

CAMERA: A method for cost-aware, adaptive, multifidelity, efficient reliability analysis

Estimating probability of failure in aerospace systems is a critical requirement for flight certification and qualification. Failure probability estimation involves resolving tails of probability distributions, and Monte Carlo sampling methods are intractable when expensive high-fidelity simulations have to be queried. Here, we propose a method to use models of multiple fidelities that trade accuracy for computational efficiency. Specifically, we propose the use of multifidelity Gaussian process models to efficiently fuse models at multiple fidelity, thereby offering a cheap surrogate model that emulates the original model at all fidelities. Furthermore, we propose a novel sequential acquisition function based experiment design framework that can automatically select samples from appropriate fidelity models to make predictions about quantities of interest at the highest fidelity. We use our proposed approach in an importance sampling setting and demonstrate our method on the failure level set and probability estimation on synthetic test functions and two real-world applications, namely, the reliability analysis of a gas turbine engine blade using a finite element method and a transonic aerodynamic wing test case using Reynolds-averaged Navier-Stokes equations. We show that our method predicts the failure boundary and probability more accurately and at a fraction of the computational cost compared with using just a single expensive high-fidelity model. Finally, we show that our sequential approach is guaranteed to asymptotically converge to the true failure boundary with high probability.

97 MATHEMATICS AND COMPUTING↗

Geology of the Icy Galilean Satellites: Understanding Crustal Processes and Geologic Histories Through the JIMO Mission

Knowledge of the geology, style and time history of crustal processes on the icy Galilean satellites is necessary to understanding how these bodies formed and evolved. Data from the Galileo mission have provided a basis for detailed geologic and geo- physical analysis. Due to constrained downlink, Galileo Solid State Imaging (SSI) data consisted of global coverage at a -1 km/pixel ground sampling and representative, widely spaced regional maps at -200 m/pixel. These two data sets provide a general means to extrapolate units identified at higher resolution to lower resolution data. A sampling of key sites at much higher resolution (10s of m/pixel) allows evaluation of processes on local scales. We are currently producing the first global geological map of Europa using Galileo global and regional-scale data. This work is demonstrating the necessity and utility of planet-wide contiguous image coverage at global, regional, and local scales.

Figueredo, P. H.↗

Sample Results From The Extraction, Scrub, And Strip Test For The Blended NGS Solvent

This report summarizes the results of the extraction, scrub, and strip testing for the September 2013 sampling of the Next Generation Solvent (NGS) Blended solvent from the Modular Caustic Side-Solvent Extraction Unit (MCU) Solvent Hold Tank. MCU is in the process of transitioning from the BOBCalixC6 solvent to the NGS Blend solvent. As part of that transition, MCU has intentionally created a blended solvent to be processed using the Salt Batch program. This sample represents the first sample received from that blended solvent. There were two ESS tests performed where NGS blended solvent performance was assessed using either the Tank 21 material utilized in the Salt Batch 7 analyses or a simulant waste material used in the V-5/V-10 contactor testing. This report tabulates the temperature corrected cesium distribution, or D Cs values, step recovery percentage, and actual temperatures recorded during the experiment. This report also identifies the sample receipt date, preparation method, and analysis performed in the accumulation of the listed values. The calculated extraction D Cs values using the Tank 21H material and simulant are 59.4 and 53.8, respectively. The DCs values for two scrub and three strip processes for the Tank 21 material are 4.58, 2.91, 0.00184, 0.0252, and 0.00575, respectively. The D-values for two scrub and three strip processes for the simulant are 3.47, 2.18, 0.00468, 0.00057, and 0.00572, respectively. These values are similar to previous measurements of Salt Batch 7 feed with lab-prepared blended solvent. These numbers are considered compatible to allow simulant testing to be completed in place of actual waste due to the limited availability of feed material.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Processing and Probability Analysis of Pulsed Terahertz NDE of Corrosion under Shuttle Tile Data

This paper examines data processing and probability analysis of pulsed terahertz NDE scans of corrosion defects under a Shuttle tile. Pulsed terahertz data collected from an aluminum plate with fabricated corrosion defects and covered with a Shuttle tile is presented. The corrosion defects imaged were fabricated by electrochemically etching areas of various diameter and depth in the plate. In this work, the aluminum plate echo signal is located in the terahertz time-of-flight data and a threshold is applied to produce a binary image of sample features. Feature location and area are examined and identified as corrosion through comparison with the known defect layout. The results are tabulated with hit, miss, or false call information for a probability of detection analysis that is used to identify an optimal processing threshold.

Anastasi, Robert F.↗

Iterative Bragg peak removal on X-ray absorption spectra with automatic intensity correction

This study introduces a novel iterative Bragg peak removal with automatic intensity correction (IBR-AIC) methodology for X-ray absorption spectroscopy (XAS), specifically addressing the challenge of Bragg peak interference in the analysis of crystalline materials. The approach integrates experimental adjustments and sophisticated post-processing, including an iterative algorithm for robust calculation of the scaling factor of the absorption coefficients and efficient elimination of the Bragg peaks, a common obstacle in accurately interpreting XAS data, particularly in crystalline samples. The method was thoroughly evaluated on dilute catalysts and thin films, with fluorescence mode and large-angle rotation. The results underscore the technique's effectiveness, adaptability and substantial potential in improving the precision of XAS data analysis. While demonstrating significant promise, the method does have limitations related to signal-to-noise ratio sensitivity and the necessity for meticulous angle selection during experimentation. Overall, IBR-AIC represents a significant advancement in XAS, offering a pragmatic solution to Bragg peak contamination challenges, thereby expanding the applications of XAS in understanding complex materials under diverse experimental conditions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Factors influencing mode choice of adults with travel-limiting disability

Introduction: Despite the plethora of research devoted to analyzing the impact of disability on travel behavior, not enough studies have investigated the varying impact of social and environmental factors on the mode choice of people with disabilities that restrict their ability to use transportation modes efficiently. This research gap can be addressed by investigating the factors influencing the mode choice behavior of people with travel-limiting disabilities, which can inform the development of accessible and sustainable transportation systems. Additionally, such studies can provide insights into the social and economic barriers faced by this population group, which can help policymakers to promote social inclusion and equity. Method: This study utilized a Random Parameters Logit model to identify the individual, trip, and environmental factors that influence mode selection among people with travel-limiting disabilities. Here, using the 2017 National Household Travel Survey data for New York State, which included information on respondents with travel-limiting disabilities, the analysis focused on a sample of 8,016 people. In addition, climate data from the National Oceanic and Atmospheric Administration were integrated as additional explanatory variables in the modeling process. Results: The results revealed that people with disabilities may be inclined to travel longer distances walking in the absence of suitable accommodation facilities for other transportation modes. Furthermore, people were less inclined to walk during summer and winter, indicating a need to consider weather conditions as a significant determinant of mode choice. Moreover, low-income people with disabilities were more likely to rely on public transport or walking. Conclusion: Based on this study’s findings, transportation agencies could design infrastructure and plan for future expansions that is more inclusive and accessible, thus catering to the mobility needs of people with travel-limiting disabilities.

99 GENERAL AND MISCELLANEOUS↗

Microstructure characterization of Al–Cr–Fe quasicrystals sintered using spark plasma sintering

In this study, Al–Cr–Fe powders were consolidated using spark plasma sintering at different temperatures (650 °C, 700 °C, 750 °C and 800 °C). The sintered samples were investigated using X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX) and transmission electron microscopy (TEM). The porosity of the pellets is very sensitive to the sintering temperature: it reduces sharply from around 29.3% to around 3.1% when the sintering temperature increases from 650 °C to 700 °C probably due to the softening of quasicrystals at elevated temperatures. Metastable icosahedral Al–Cr–Fe transforms to stable decagonal Al–Cr–Fe in sintering process. Stable icosahedral Al–Cr–Fe forms in the samples sintered at 700 °C, 750 °C and 800 °C. Both stable quasicrystalline phases form through the nucleation and growth process in the sintering process. Selected area electron diffraction (SAED) analysis shows that the icosahedral phase and the decagonal phase formed in the sintering process have a quasilattice constant of about 0.45 nm and 1.2 nm, respectively. - Highlights: • Al–Cr–Fe quasicrystals were sintered using spark plasma sintering. • Metastable icosahedral Al–Cr–Fe transforms to decagonal Al–Cr–Fe during sintering. • Stable icosahedral Al–Cr–Fe forms during sintering at 700 °C to 800 °C. • Strain softening of quasicrystals at high temperature promotes SPS sintering.

36 MATERIALS SCIENCE↗

Free-Energy Landscapes and Surface Dynamics in Methane Activation on Ni(511) via Machine Learning and Enhanced Sampling

Methane activation on stepped Ni(511) surfaces involves the rearrangement of surface atoms as the chemical reaction proceeds. This process is particularly sensitive to temperature. Using machine-learned interatomic potentials (MLIPs) coupled with enhanced sampling techniques, we investigate the activation of methane under realistic operando conditions. Our analysis reveals that methane dissociation occurs predominantly at step-edge nickel atoms. As CH x (where x = 3 or 4) species bind to additional surface nickel atoms, their reduced mobility leads to entropic penalties that suppress certain configurations and transition states. This is reflected in the underlying free energy surfaces, where configurations such as methyl binding to hollow sites and activation routes involving two nickel atoms become unfavorable as temperature increases. At elevated temperatures, methane activation extends from step-edge sites to terrace regions because of reduced free-energy barriers and enhanced surface dynamics. By decomposing the free-energy into enthalpic and entropic contributions, we uncover temperature-dependent shifts in the preferences of methane for the relevant active sites and arrive at a detailed molecular picture of methane activation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Global biogeography of microbial nitrogen-cycling traits in soil

Microorganisms drive much of the Earth’s nitrogen (N) cycle, but we still lack a global overview of the abundance and composition of the microorganisms carrying out soil N processes. To address this gap, we characterized the biogeography of microbial N traits, defined as eight N-cycling pathways, using publically available soil metagenomes. The relative frequency of N pathways varied consistently across soils, such that the frequencies of the individual N pathways were positively correlated across the soil samples. Habitat type, soil carbon, and soil N largely explained the total N pathway frequency in a sample. In contrast, we could not identify major drivers of the taxonomic composition of the N functional groups. Further, the dominant genera encoding a pathway were generally similar among habitat types. The soil samples also revealed an unexpectedly high frequency of bacteria carrying the pathways required for dissimilatory nitrate reduction to ammonium, a little-studied N process in soil. Finally, phylogenetic analysis showed that some microbial groups seem to be N-cycling specialists or generalists. For instance, taxa within the Deltaproteobacteria encoded all eight N pathways, whereas those within the Cyanobacteria primarily encoded three pathways. Overall, this trait-based approach provides a baseline for investigating the relationship between microbial diversity and N cycling across global soils.

Nelson, Michaeline B.↗

Mass Spectrometry Sample Submission Portal

Each step in the scientific process generates contextual information about the data that is important to consider when performing data integration, developing models of biological process, or training AI models. We will develop a flexible, template-driven tool that will log biological samples, capture metadata about those samples, and track the type(s) of analysis being performed by researchers providing samples for analysis by mass spectrometry.

97 MATHEMATICS AND COMPUTING↗

Costas loop lock detection in the advanced receiver

The advanced receiver currently being developed uses a Costas digital loop to demodulate the subcarrier. Previous analyses of lock detector algorithms for Costas loops have ignored the effects of the inherent correlation between the samples of the phase-error process. Accounting for this correlation is necessary to achieve the desired lock-detection probability for a given false-alarm rate. Both analysis and simulations are used to quantify the effects of phase correlation on lock detection for the square-law and the absolute-value type detectors. Results are obtained which depict the lock-detection probability as a function of loop signal-to-noise ratio for a given false-alarm rate. The mathematical model and computer simulation show that the square-law detector experiences less degradation due to phase jitter than the absolute-value detector and that the degradation in detector signal-to-noise ratio is more pronounced for square-wave than for sine-wave signals.

Mileant, A.↗

Vector formulation for interferogram surface fitting

Interferometry is an optical testing technique that quantifies the optical path difference (OPD) between a reference wave front and a test wave front based on the interference of light. Fringes are formed when the OPD is an integral multiple of the illuminating wavelength. The resultant two-dimensional pattern is called an interferogram. The function of any interferogram analysis program is to extract this OPD and to produce a representation of the test wave front (or surface). This is accomplished through a three-step process of sampling, ordering, and fitting. We develop a generalized linear-algebra vector-notation model of the interferogram sampling and fitting process.

Fischer, David J.↗

Martian Analogue Sample Characterization and Spectral Library Development at the Johnson Space Center

An extensive collection of Martian analogue samples housed at the Johnson Space Center is the focus of ongoing research by the JSC Mars soil genesis group and their collaborators. Because the major element composition of Martian meteorites and in situ analyses of Martian soils and rocks indicate that Mars is predominantly an iron-rich basaltic world, the focus of active sample collection and analysis is basaltic materials and their hydrolytic (both aqueous and hydrothermal) and sulfatetic alteration products. Described below are the scope of the JSC Mars analogue sample collection, the characterization process, and plans to incorporate the data into spectral libraries for the Mars 2003 Mars Exploration Rover (MER) and Mars 2005 Mars Reconnaissance Orbiter (MRO) CRISM missions.

Morris, Richard V.↗

TPSAS-NF1676L-32493-DND

The Committee on Earth Observation Satellites (CEOS) System Engineering Office (SEO) has supported the Open Data Cube (ODC) initiative to provide a data architecture solution that has value to its global users and increases the impact of EO satellite data. ODC is an open-source platform for processing satellite data. We have developed software products and tools around the core ODC that would help users perform machine learning on EO satellite data. The recent United Nations (UN) Sustainable Development Agenda provides a shared blueprint for peace and prosperity for people and for the planet, considering our current situation and helping to create a plan. The core of this agenda is a set of seventeen Sustainable Development Goals (SDGs), which represent an urgent call for action by all countries - both developed and developing - in a global partnership. The CEOS SEO team has recently developed and released a set of innovative Jupyter notebooks addressing UN SDGs 6.6.1 (spatial extents of water-related ecosystems), 11.3.1 (ratio of land consumption rate to population growth rate), and 15.3.1 (proportion of land that is degraded over total land area). These notebooks empower users by providing features that will assist with streamlining analysis ready data retrieval, processing, and visualization. We have recently incorporated several machine learning techniques in these notebooks. In this paper, we present the lessons learned from our experience on classifying land using supervised and unsupervised machine learning techniques using ODC framework for UN SDGs. We identify the current limitations of ODC to seamlessly support machine learning techniques. We propose features that would help machine learning, specifically within the ODC framework. We propose a thematic indexing/loading of data for both unsupervised learning as well as data annotation/labeling pipeline. Currently, ODC supports machine learning by separating data-management from the analysis process. It works as a mechanism to load cubes of data. ODC does not natively support features that are vital in machine learning such as validation splits, fair/balanced sampling, establishing load size constraints, etc. We believe that our proposed features will empower users by providing features that bring machine learning techniques closed to ODC. Enhancements to ODC to better accommodate machine learning techniques can assist in fulfilling UN SDGs such as 6.3.2, 6.4.2, 6.6.1, 11.3.1, 14.1.1, 15.1.1, 15.3.1, and 15.4.2.

Syed R Rizvi↗

ftmsRanalysis: An R package for exploratory data analysis and interactive visualization of FT-MS data

The high-resolution and mass accuracy of Fourier transform mass spectrometry (FT-MS) has made it an increasingly popular technique for discerning the composition of soil, plant and aquatic samples containing complex mixtures of proteins, carbohydrates, lipids, lignins, hydrocarbons, phytochemicals and other compounds. Thus, there is a growing demand for informatics tools to analyze FT-MS data that will aid investigators seeking to understand the availability of carbon compounds to biotic and abiotic oxidation and to compare fundamental chemical properties of complex samples across groups. We present ftmsRanalysis, an R package which provides an extensive collection of data formatting and processing, filtering, visualization, and sample and group comparison functionalities. The package provides a suite of plotting methods and enables expedient, flexible and interactive visualization of complex datasets through functions which link to a powerful and interactive visualization user interface, Trelliscope. Example analysis using FT-MS data from a soil microbiology study demonstrates the core functionality of the package and highlights the capabilities for producing interactive visualizations.

97 MATHEMATICS AND COMPUTING↗

Thermal Flux Maximization from a DD Neutron Generator

The University of Sharjah recently acquired a model DD-109.4M neutron generator from Adelphi Technology. The generator is moderated and has three neutron ports which are capable of providing fast and thermal neutrons. The neutron ports are plugged with polyethylene layers of different thickness in order to control the neutron flux at different regions in the port. Neutron Activation Analysis (NAA) is an important analysis technique to determine the amounts of isotopes in a sample at different concentrations. For many isotopes the ability to precisely determine their concentrations is enhanced by utilizing thermal neutrons in the activation process; where the capture cross section is greatest. It is thus important to subject the sample to the maximum thermal flux in order to minimize the time required to activate the sample and consequently extend the lifetime of the neutron generator. A detailed MCNP model of the neutron generator has been developed for the purpose of determining the moderator thickness required to maximize the thermal neutron flux in the neutron port. The maximization of the neutron flux must therefore take into account both the forward and backscattered neutrons reaching the sample. Also provided in this work is a mapping of the thermal flux at different moderator thicknesses in order to study the variation of the flux over the area of the sample. The developed model will be used as the basis for optimizing experiments and predicting their results. A study was performed to determine the moderator thickness needed to maximize the thermal neutron flux that can be obtained from a DD neutron generator. This has a significant role in the efficient utilization of the neutron generator. The maximum thermal neutron flux was found at approximately a 3.2 cm moderator thickness. The thermal neutron flux is resulting from both the directly moderated neutrons and the backscattered neutrons from the surrounding polyethylene. The results obtained in this work will be verified experimentally by irradiating samples at different moderator thickness and performing a neutron activation analysis for these samples. (authors)

07 ISOTOPE AND RADIATION SOURCES↗