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At least 775 records · Page 43

Calendar Year 2023 Underground Test Area Annual Sampling Letter Report Nevada National Security Site

The calendar year 2023 annual sampling letter report presents Plan implementation and a summary of field activities, sampling methods, well completion diagrams, and analytical laboratory results from sampling of wells associated with the Pahute Mesa CAUs. The CY 2023 letter report also presents data from samples collected from Well ER-EC-11_p3 as part of a sampling investigation. This well was resampled because of anomalously low standard tritium (3H) results from bailer sampling that occurred in July 2021.

54 ENVIRONMENTAL SCIENCES↗

Physical and Hydraulic Properties of RCRA Borehole Samples from the Hanford Site : Final Report, Fiscal Years 2023-2024

Sediment from 44 core samples collected from Resource Conservation and Recovery Act (RCRA) boreholes drilled in the 200 East and 200 West areas of the Hanford Site were characterized for physical and hydraulic properties (Table S.1). Characterization data included gravimetric water contents and matric potentials, grain-size distributions, saturated hydraulic conductivity, water retention characteristics, and unsaturated hydraulic conductivity. These properties provide site-specific data and parameters that can be used in subsurface flow and contaminant transport models to assess the transport and fate of contaminants in the vadose zone and underlying aquifer systems. The analyzed core samples come from specific areas and depth intervals at the Hanford Site that were targeted for sampling to address data gaps identified by site contractors (Khaleel 2020). X-ray computed tomography (XCT) was used to evaluate the general textural characteristics of the samples and to determine which samples to use for further physical and hydraulic property characterization. Subsequent sample selection was determined by consensus after review of the XCT images by Pacific Northwest National Laboratory, Central Plateau Cleanup Company, and INTERA staff.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Quantum-Inspired Bayesian Sampling for Uncertainty Quantification and Machine Learning (Final Technical Report)

With increasing simulation and measurement data, machine learning and artificial intelligence have been widely used in computational decision-making of complex engineering systems. The resulting tools, such as uncertainty quantification solvers, reinforcement learning, and physics-informed machine learning, have achieved great success in critical DOE tasks such as material discovery and design, energy system modeling and control, and numerical weather and climate prediction. A core topic in scientific machine learning and artificial intelligence is Bayesian inference: given an observed data set, people want to estimate the posterior distribution of a (possibly large) number of hidden parameters. Due to the flexibility and weak assumptions, Bayesian sampling has been the mainstream Bayesian inference solvers despite the rapid progress of approximate Bayesian inference. Classical Bayesian sampling methods such as Markov-chain Monte Carlo suffer from a low-acceptance rate due to the random walk nature, therefore state-of-the-art techniques use Hamiltonian Monte Carlo and its variants to efficiently draw posterior samples in a high dimension. The key idea of Hamiltonian Monte Carlo and its variants is to simulate the Hamiltonian dynamics of a classical particle with a fixed mass, and their performance significantly degrades when the posterior distribution is highly spiky or has multiple modes. Leveraging the idea of quantum physics, this project has investigated new theory, algorithms and applications of Bayesian inference (especially Bayesian sampling). The main results include: (1) novel quantum-inspired Bayesian sampling methods that can lead to better accuracy for challenging multi-modal or spiky distributions, (2) more scalable machine learning framework leveraging tensor-compressed Bayesian inference, and (3) Bayesian and sampling approaches for verifying the robustness of continuous and binary neural networks.

97 MATHEMATICS AND COMPUTING↗

Joint Sample Analyses of Nuclear Forensic Materials Provided by the Republic of Kazakhstan: U. S. Laboratory Results

This document serves as an interim report to summarize sample analyses performed by Lawrence Livermore National Laboratory (LLNL) and Los Alamos National Laboratory (LANL) on a series of five nuclear forensics samples provided by the Institute of Nuclear Physics (INP) in the Republic of Kazakhstan. The sample set contains four uranium oxide powders and one low-enriched uranium fuel pellet. The samples were provided as part of a broader collaboration that involved a set of joint sample analyses conducted by INP and the US National Laboratories. The joint analyses are being conducted using well-developed analytical plans. These activities are designed to support the advancement of nuclear forensic science and capacity building in all three institutes in both countries. This report builds upon an earlier preliminary summary of the joint interactions and will be augmented by a final report. The final report will summarize the results and value of all sample analyses performed at the three institutes (INP, LLNL, and LANL). The final report will also provide an intercomparison of the results, analytical methods and best practices employed, as well as outline future collaborative nuclear forensics activities that are being developed in the Kazakhstan region.

and nuclear chemistry↗

Develop Accurate Techniques for Passive SiC Temperature Monitoring of Miniature Samples for Cross-Cutting Applications

Passive thermometry is critically important because most fuels and materials irradiation experiments are not instrumented, and it is necessary to understand the irradiation temperature to properly interpret any post-irradiation examination data, including evolving properties and/or microstructures. The standard passive thermometry approach uses continuous dilatometry to evaluate changes in the instantaneous coefficient of thermal expansion during post-irradiation thermal annealing. This approach has limitations in terms of sample size (minimum length requirements) and the maximum irradiation temperature that can be accurately determined, which is limited by the reduced swelling (and therefore recovery) following higher temperature irradiation and limitations on the furnaces used with push-rod dilatometers. This work evaluates two new proposed techniques for post-irradiation evaluation of passive SiC temperature monitors: differential scanning calorimetry (DSC) and Raman spectroscopy. DSC is an extremely sensitive technique that can be used for any specimen geometry and is capable of higher temperature operation. Raman spectroscopy is similar in that it is a surface technique capable of examining extremely small samples (submillimeter), can be used with a heated stage up to 1,500°C (planned for future work), and is capable of mapping local irradiation temperatures throughout a sample. Existing SiC samples that were previously irradiated over a wide range of temperatures were cut into multiple pieces to allow for annealing studies using multiple different techniques: dilatometry, DSC, and Raman spectroscopy. This approach mitigates the concern that samples analyzed using one technique may have a slightly different irradiation history than those analyzed using a different technique. Recovery was clearly observed during annealing using both DSC and dilatometry. In some cases, a direct comparison could not be made due to some of the DSC runs accidentally including material from multiple specimens and issues with using an alternative DSC sample holder for the highest temperature annealing studies. Nevertheless, one trend was clear: the DSC runs resulted in higher irradiation temperatures compared to those of the dilatometry runs. Part of this could be attributed to the higher temperature ramp rates used during the DSC runs, which are often preferred to reduce noise in the measurements. By comparison, dilatometry has previously been shown to produce better data at lower ramp rates. Future work should further investigate the ideal ramp rate for both techniques to produce consistent results. Additional work should evaluate the best holder material to use for DSC runs exceeding 1,000°C to provide reliable data while preventing interactions between SiC and the holder.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Develop Accurate Techniques for Passive SiC Temperature Monitoring of Miniature Samples for Cross-Cutting Applications

Passive thermometry is critically important because most fuels and materials irradiation experiments are not instrumented, and it is necessary to understand the irradiation temperature to properly interpret any post-irradiation examination data, including evolving properties and/or microstructures. The standard passive thermometry approach uses continuous dilatometry to evaluate changes in the instantaneous coefficient of thermal expansion during post-irradiation thermal annealing. This approach has limitations in terms of sample size (minimum length requirements) and the maximum irradiation temperature that can be accurately determined, which is limited by the reduced swelling (and therefore recovery) following higher temperature irradiation and limitations on the furnaces used with push-rod dilatometers. This work evaluates two new proposed techniques for post-irradiation evaluation of passive SiC temperature monitors: differential scanning calorimetry (DSC) and Raman spectroscopy. DSC is an extremely sensitive technique that can be used for any specimen geometry and is capable of higher temperature operation. Raman spectroscopy is similar in that it is a surface technique capable of examining extremely small samples (submillimeter), can be used with a heated stage up to 1,500°C (planned for future work), and is capable of mapping local irradiation temperatures throughout a sample. Existing SiC samples that were previously irradiated over a wide range of temperatures were cut into multiple pieces to allow for annealing studies using multiple different techniques: dilatometry, DSC, and Raman spectroscopy. This approach mitigates the concern that samples analyzed using one technique may have a slightly different irradiation history than those analyzed using a different technique. Recovery was clearly observed during annealing using both DSC and dilatometry. In some cases, a direct comparison could not be made due to some of the DSC runs accidentally including material from multiple specimens and issues with using an alternative DSC sample holder for the highest temperature annealing studies. Nevertheless, one trend was clear: the DSC runs resulted in higher irradiation temperatures compared to those of the dilatometry runs. Part of this could be attributed to the higher temperature ramp rates used during the DSC runs, which are often preferred to reduce noise in the measurements. By comparison, dilatometry has previously been shown to produce better data at lower ramp rates. Future work should further investigate the ideal ramp rate for both techniques to produce consistent results. Additional work should evaluate the best holder material to use for DSC runs exceeding 1,000°C to provide reliable data while preventing interactions between SiC and the holder.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

GROWdb US River Systems - Samples

GROW Overview We developed the Genome Resolved Open Watersheds database (GROWdb), which aims to increase genomic sampling and understanding of global river microbiomes. An emphasis of GROWdb is to create a publicly available and ever-expanding microbial genome database that is focused on rivers while being interoperable with databases from other ecosystems. GROWdb is based on a network-of-networks approach to move beyond a small collection of well-studied rivers, towards a spatially distributed, global network of systematic observations. GROWdb represents the first microbial, river-focused resource parsed at various scales from genes to MAGs to community level including expression and potential based measurements that will be of interest to microbiologists, ecologists, geochemists, hydrologists, and modelers. Dataset Acknowledgement GROWdb contains data from various research campaigns, please acknowledge the following data generators, as appropriate: WHONDRS derived genomes or samples - include this statement in your acknowledgements: “This study used data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) under the River Corridor Science Focus Area (SFA) at the Pacific Northwest National Laboratory (PNNL) that was generated at the U.S. Department of Energy (DOE) Joint Genome Institute User Facility. PNNL is operated by Battelle Memorial Institute for the U.S. DOE under Contract No. DE-AC05-76RL01830. The SFA is supported by the U.S. DOE, Office of Biological and Environmental Research (BER), Environmental System Science (ESS) Program.” Total Samples loaded onto this Narrative: 178 Note: Not all GROW samples may be loaded into KBase Data Availability The data underlying GROWdb are accessible across various platforms to ensure all levels of data structure are widely available. First, all reads and MAGs are publicly hosted on National Center for Biotechnology (NCBI) under Bioproject PRJNA946291. Second, all data related data presented here including MAG annotations, extended data tables, phylogenetic tree files, antibiotic resistance gene database files, and MAG abundance tables are available in Zenodo (link). Beyond the flat database files listed above, our aim for GROWdb was to maximize data use by making the data available in searchable and interactive platforms including the National Microbiome Data Collaborative (NMDC) data portal, the Department of Energy’s Systems Biology Knowledgebase (KBase), and a GROW specific user interface released here, GROWdb Explorer. Each platform provides different ways to interact with GROWdb: NMDC GROWdb formed a pilot project for the NMDC. Specifically, individual GROWdb datasets (metagenomes, metatranscriptomes, etc) are easily accessible and searchable through the NMDC data portal, where they are systematically connected to each other and to a rich suite of sample information and standard analysis results, following Findable, Accessible, Interoperable, and Reusable (FAIR) data practices. KBase GROWdb is publicly available within KBase, including samples (this Narrative), MAGs, and corresponding genome scale metabolic models. Access within KBase allows for immediate access and reuse of data, including comparison to private data using KBase’s 500+ analysis tools. Other linked narratives in KBase: GROW Metagenome Assembled Genomes (MAGs) GROW Metabolic Models GROWdb Explorer GROWdb data is also explorable through a graphical user interface built through the Colorado State University Geospatial Centroid (https://geocentroid.shinyapps.io/GROWdatabase/), allowing users to search and graph microbial and spatial data simultaneously. In summary, this microbial genome resource represents the first publicly available genome collection from rivers and offers data that can be leveraged across microbiome studies. GROWdb is an expanding repository to incorporate and unify global river multi-omic data for the future.

59 BASIC BIOLOGICAL SCIENCES↗

Genomic-based biosurveillance for avian influenza: whole genome sequencing from wild mallards sampled during autumn migration in 2022–2023 reveals a high co-infection rate on migration stopover site in Georgia

The Caucasus region, including Georgia, is an important intersection for migratory waterbirds, offering potential for avian influenza virus (AIV) transmission between populations from different geographic areas. In 2022 and 2023, wild ducks were sampled during autumn migration events in Georgia to study the genetic relationships and molecular characteristics of influenza strains. Sequencing and phylogenetic analysis were used to compare the sampled strains to reference sequences from Africa, Asia, and Europe, allowing assessment of genetic relationships and virus transmission between migratory birds. Protein language modeling identified potential co-infections. Of 225 duck samples, 128 tested positive for the influenza M gene. 55 influenza-positive samples underwent whole-genome sequencing, revealing significant diversity. Analysis of the hemagglutinin (HA) segment showed notable differences among subtypes. Most samples were H6N1 and H6N6, but co-infections with combinations like H6H3, N8N1, N6H9, N2N6, and H9H6/N1N2 were also identified. These findings demonstrate the high variability of influenza viruses in migratory waterbirds in Georgia, including a notable rate of co-infections. Some samples exhibited uncommon genetic characteristics compared to other strains from the same year, suggesting Georgia’s role as a mixing vessel for influenza viruses. This facilitates reassortment during co-infections and contributes to the genetic diversity observed across flyways.

59 BASIC BIOLOGICAL SCIENCES↗

Crystal Chemistry and Structural Variations for Zircon Samples from Various Localities

This study investigates the variations of structural parameters and chemistry of a partially metamict and seven detrital zircon samples from different localities using single-crystal X-ray diffraction, synchrotron high-resolution powder X-ray diffraction, and electron-probe micro-analysis techniques. The unit-cell parameters for the eight zircon samples vary linearly with increasing unit-cell volume, V. A zircon sample from the Canadian Arctic Islands has the smallest unit-cell parameters, bond distances, ideal stoichiometric composition, unaffected by α-radiation damage, and is chemically pure. A zircon sample from Jemaa, Nigeria has the largest unit-cell parameters because of the effect of α-radiation doses received over a long time (2384 Ma). All the samples show good correlations between Zr and Si apfu (atom per formula unit) versus unit-cell volume, V. The α-radiation doses in the samples are lower than ~3.5 × 1015 α-decay events/mg. Substitutions of other cations at the Zr and Si sites control the variations of the structural parameters. Relatively large unit-cell parameters and bond distances occur because the Zr site accommodates other cations that have larger ionic radii than the Zr atom. Geological age increases the radiation doses in zircon and it is related to V.

58 GEOSCIENCES↗

Transmission electron microscopy of ion irradiated ODS MA956 samples

Oxide dispersion strengthened (ODS) alloys are promising candidate materials for the next generation advanced nuclear reactors due to their superior irradiation resistance and mechanical properties. To better understand the effect of irradiation on MA956, it is essential to study higher dose (50-100 dpa) samples, so that the general trend of microstructural evolution and the resulting radiation-hardening can be deduced. Currently, ion irradiations are considered the only way to achieve doses beyond ~50 dpa in a practical time frame relevant to alloy and welding development programs. This dataset contains TEM characterization results of ODS MA956 samples that were ion irradiated under different conditions: Sample #5 (1.25 dpa at 190℃); Sample #9 (50 dpa at 190℃); Sample #15 (1.25dpa under 320℃); and Sample 17 (25 dpa at 320℃). TEM characterization focused on the irradiation induced defects (dislocation lines and loops) using the on-zone axis bright field STEM technique. These data were collected using a FEI Tecnai G2 F30 S/TEM at Microscopy and Characterization Suite (MaCS) at Center for Advanced Energy Studies (CAES), Idaho Falls, ID. This project (ion irradiation and TEM studies) was supported by the U.S. Department of Energy, Office of Nuclear Energy under DOE Idaho Operations Office Contract DE-AC07-05ID14517 as part of Nuclear Science User Facilities award #18-14784 (PI: Ramprashad Prabhakaran, PNNL).

Prabhakaran, Ramprashad↗

Tools for uranium characterization in carbonate samples: case studies of natural U–Pb geochronology reference materials

Laser ablation U–Pb analyses of carbonate (LAcarb) samples has greatly expanded the potential for U–Pb dating to a variety of carbonate-producing settings. Carbonates that were previously considered impossible to date using isotope dilution methods may preserve radiogenic domains that can be dated using spatially resolved laser ablation geochronology techniques. Work is ongoing to identify reference materials and to consider best practices for LAcarb. In this study we apply standard and emerging characterization tool sets on three natural samples with the dual goal of enhancing the study of carbonates and establishing a new set of well-characterized natural reference materials for LAcarb studies. We start with the existing carbonate reference material WC-1 from the Permian Reef Complex of Texas, building on the published description to offer a deeper look at U and associated trace elements. We consider a tufa sample from the Miocene Barstow Formation of the Mojave Block, California, as a possible secondary calcite reference material due to its well-behaved U–Pb systematics. There are currently no natural dolomite standards. We present an unusual dolomite sample with very well-behaved U–Pb systematics from the Miocene of the Turkana Basin of Kenya as a possible dolomite reference material for LAcarb dating. In addition to using X-ray fluorescence (XRF) mapping and spectroscopy to better understand U in these natural samples, we have analyzed multiple aliquots of each of them for 87 Sr/ 86 Sr by thermal ionization mass spectrometry (TIMS). The Sr isotope compositions are analytically homogeneous within petrographically homogeneous regions of all three samples, and thus these materials could be used as Sr isotope standards as well. While not part of the current contribution, this combination could streamline simultaneous LA analyses of 87 Sr/ 86 Sr and U–Pb geochronology.

36 MATERIALS SCIENCE↗

MicroBooNE BNB Inclusive Overlay Sample (With Wire Info)

MicroBooNE samples are provided for collaborative development in two different formats: HDF5, targeting the broadest audience, and artroot, targeting users that are familiar with the software infrastructure of Fermilab neutrino experiments and more in general of HEP experiments. The HDF5 files are stored on Zenodo, together with a list of artroot files accessible with xrootd.This sample includes simulated interactions of neutrinos from the Booster Neutrino Beam (BNB), overlaid on top of cosmic ray data. The sample is inclusive, i.e. it includes all types of neutrinos and interactions, with relative abundance matching our nominal flux and cross section models. Interactions are simulated in in the whole cryostat volume.The HDF5 files in this sample include the information at the wire waveform level (after deconvolution and finding of regions of interest). As this information significantly increases the file size, this sample contains about 17% of the events of the corresponding sample without wire information.More documentation, including detailed description of content, recipes, and example usage, at https://github.com/uboone/OpenSamples.Suggested text for acknowledgment is the following:We acknowledge the MicroBooNE Collaboration for making publicly available the data sets [data set DOIs] employed in this work. These data sets consist of simulated neutrino interactions from the Booster Neutrino Beamline overlaid on top of cosmic data collected with the MicroBooNE detector [2017 JINST 12 P02017].In addition, we request that software products resulting from the usage of the datasets are also made publicly available.

Abratenko, Polina↗

MicroBooNE BNB Electron Neutrino Overlay Sample (With Wire Info)

MicroBooNE samples are provided for collaborative development in two different formats: HDF5, targeting the broadest audience, and artroot, targeting users that are familiar with the software infrastructure of Fermilab neutrino experiments and more in general of HEP experiments. The HDF5 files are stored on Zenodo, together with a list of artroot files accessible with xrootd.This sample includes simulated interactions of neutrinos from the Booster Neutrino Beam (BNB), overlaid on top of cosmic ray data. The sample is restricted to charged-current electron neutrino interactions within the argon active volume of the time projection chamber.The HDF5 files in this sample include the information at the wire waveform level (after deconvolution and finding of regions of interest). As this information significantly increases the file size, this sample contains about 20% of the events of the corresponding sample without wire information.More documentation, including detailed description of content, recipes, and example usage, at https://github.com/uboone/OpenSamples.Suggested text for acknowledgment is the following:We acknowledge the MicroBooNE Collaboration for making publicly available the data sets [data set DOIs] employed in this work. These data sets consist of simulated neutrino interactions from the Booster Neutrino Beamline overlaid on top of cosmic data collected with the MicroBooNE detector [2017 JINST 12 P02017].In addition, we request that software products resulting from the usage of the datasets are also made publicly available.

Abratenko, Polina↗

TRAC Time Tags of individual particle samples collected for microscopy analysis at RMBL [AMF2] from June 2023 to August 2023

The dataset presents the time tags of individual particle samples collected on microscopy substrates during the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign in Gothic, CO. A Time Resolved Aerosol Collector was deployed at the Rocky Mountain Biological Laboratory, 200 m north of AMF2 to collect ambient particles. The instrument inlet was placed 5 m above ground level. Particles are deposited on 400 mesh copper carbon-B film TEM grids (Ted Pella 01814-F). Samples are sealed and currently stored at Purdue University. A subset of the samples can be shared. Please contact dataset authors for more information. The dataset reports the sample start times in UTC and MST along with the sample ID, used to guide its location and retrieval from the storage plate. TRAC sampling started on June 17, 2023, and ended on July 31, 2023.

54 ENVIRONMENTAL SCIENCES↗

Chemical features of the Luna 16 regolith sample.

The Luna 16 regolith sample differs from Apollo 11, 12 and 14 regolith and basalt samples by having smaller negative Eu and Sr anomalies and nearly chondritic Eu/Sm and Eu/Sr ratios although the overall REE, Ba, Sr and U concentrations are 25 to 45 times chondrites. Major element data, in particular FeO vs Al2O3, show that the Luna 16 regolith sample is composed of materials that follow a quantitatively different Fe/Al variation than do Apollo 11, 12, 14 and 15 samples. The small Eu and Sr anomalies and the displaced Fe/Al variation are two chemical features unique to the Luna 16 regolith sample. The Luna 16 regolith sample can contain little if any of the rock types abundant at Apollo sites, thus indicating that the unique chemical features are typical of local or nearby materials and indicate a separate petrogenetic province for major component rock types of the Luna 16 regolith.

Hubbard, N. J.↗

Sampling functions for geophysics

A set of spherical sampling functions is defined such that they are related to spherical-harmonic functions in the same way that the sampling functions of information theory are related to sine and cosine functions. An orderly distribution of (N + 1) squared sampling points on a sphere is given, for which the (N + 1) squared spherical sampling functions span the same linear manifold as do the spherical-harmonic functions through degree N. The transformations between the spherical sampling functions and the spherical-harmonic functions are given by recurrence relations. The spherical sampling functions of two arguments are extended to three arguments and to nonspherical reference surfaces. Typical applications of this formalism to geophysical topics are sketched.

Giacaglia, G. E. O.↗

Nuclear magnetic resonance properties of lunar samples.

Nuclear magnetic resonance spectra of Na-23, Al-27, and P-31 in fines samples 10084,60 and 14163,168 and in crystalline rock samples 12021,55 and 14321,166, have been recorded over a range of frequencies up to 20 MHz. A shift in the field at which maximum absorption occurs for all of the spectra relative to the field at which maximum absorption occurs for terrestrial analogues is attributed to a sample-dependent magnetic field at the Na, Al, and P sites opposing the laboratory field. The magnitude of these fields internal to the samples is sample dependent and varies from 5 to 10 G. These fields do not correlate with the iron content of the samples. However, the presence of single-domain particles of iron distributed throughout the plagioclase fraction that contains the principal fraction of Na and Al is inferred from electron magnetic resonance spectra shapes.

Kline, D.↗

Dielectric properties of Apollo 14 lunar samples.

Laboratory characterization of dielectric properties of lunar samples 14301,41, 14310,75, 14318,30 and 14321,163 is made. Our measurements of dielectric constants and losses were made over a range of frequency from 100 Hz to 10 MHz and temperature from 77 to 473 K by two-terminal capacitance substitution methods. The dielectric behavior of these samples is generally similar to other lunar samples from Apollo 11 and Apollo 12 sites when these samples are free from absorbed moisture. As did sample 12002,58, sample 14310,75 showed a distinctive dispersion that may be associated with the presence of water, and different values of the activation energy for conduction as the temperature was varied. The activation energies range from about 0.03 to 0.5 eV.

Chung, D. H.↗