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At least 883 records · Page 49

Disorder-induced magnetoelastic behaviors of MnTexSbyBi1-x-y alloys

This dataset contains input and output files from density functional theory (DFT) simulations used to study the disorder-induced magnetoelastic behaviors of MnTexSbyBi1-x-y (0 ≤ x + y ≤ 1) alloys and their binary end members MnTe, MnSb, and MnBi. The alloys adopt the hexagonal NiAs-type (nickeline) structure and span ternary (MnTexSb1-x, MnTexBi1-x, MnBixSb1-x), and quaternary compositions across the full MnTe–MnSb–MnBi composition triangle. For each alloy composition, the dataset provides DFT calculations in three magnetic configurations: A-type antiferromagnetic (AFM), C-type AFM, and ferromagnetic (FM). Every magnetic configuration folder contains the fully relaxed crystal structure (CONTCAR), VASP input parameters (INCAR), and the main VASP output file (OUTCAR), from which total electronic energies, Mn magnetic moments, lattice parameters, and percent volume changes between magnetic states are extracted. These data are used to construct compositional phase diagrams, evaluate thermodynamic stability (formability), and map magnetoelastic responses across the alloy space. For A-type AFM and FM configurations, additional data are provided as follows: (i) FORCE_CONSTANTS and thermal_properties.yaml files at the top level of A-type_AFM/ and FM/ folders — present only for compositions marked with an asterisk (*) in Table I of the main text. These are derived from Phonopy finite-displacement calculations on full disordered 128-atom supercells and provide vibrational free energy, entropy (Svib)contribution from explicit disorder calculations. (Table I of the associated main manuscript) (ii) A VCA/ subfolder within A-type_AFM/ and FM/, containing FORCE_CONSTANTS and thermal_properties.yaml from Virtual Crystal Approximation phonon calculations (without spin-orbit coupling). VCA data are available for all compositions and are used to estimate vibrational contributions to the Gibbs free energy across the full composition space. (iii) A SOC/ subfolder containing CONTCAR, INCAR, and OUTCAR from spin-orbit coupling calculations, providing relativistic corrections to electronic energies and lattice parameters (Tables S2–S3 of the SM, and Table I of the main manuscript). (iv) A SOC/VCA/ subfolder containing FORCE_CONSTANTS and thermal_properties.yaml from VCA phonon calculations performed within the SOC framework, combining relativistic and vibrational thermodynamic corrections. The computed properties are used to map the AFM–FM magnetic crossover near MnTe0.75Sb0.25, demonstrate disorder- and spin-induced phonon broadening, identify a semiconductor-to-metal crossover, and quantify the pronounced magnetoelastic volume response near the magnetic phase boundary.

36 MATERIALS SCIENCE↗

Probabilistic flux limiters

The stable numerical integration of shocks in compressible flow simulations relies on the reduction or elimination of Gibbs phenomena (unstable, spurious oscillations). A popular method to virtually eliminate Gibbs oscillations caused by numerical discretization in under-resolved simulations is to use a flux limiter. A wide range of flux limiters have been studied in the literature, with recent interest in their optimization via machine learning methods trained on high-resolution datasets. The common use of flux limiters in numerical codes as plug-and-play blackbox components makes them key targets for design improvement. Even for deterministic dynamical models, numerical uncertainty is introduced via coarse-graining required by insufficient computational power to solve all scales of motion. Conventional flux limiters are deterministic and lack the capacity to address uncertainties, both aleatoric (inherent randomness) and epistemic (modeling uncertainty due to limited knowledge), which arise in coarse-grained numerical simulations. Here, we introduce a conceptually distinct type of flux limiter that is designed to handle the effects of randomness in the model and uncertainty in model parameters. Unlike traditional single-function flux limiters, these new probabilistic flux limiters incorporate multiple flux limiting functions, each applied with a learned probability drawn from high-resolution data to mitigate the effects of uncertainty in numerical simulations. This approach departs from traditional single-function limiters by explicitly modeling and incorporating uncertainty into the shock capturing process. Using the example of Burgers' equation as a testbed, we show that a machine learned, probabilistic flux limiter may be used in a shock capturing code to more accurately capture shock profiles. In particular, we show that our probabilistic flux limiter outperforms standard limiters and can be successively improved upon (up to a point) by expanding the set of probabilistically chosen flux limiting functions.

97 MATHEMATICS AND COMPUTING↗

Algorithms for coordinate reconstruction in position-sensitive virtual Frisch-grid detectors

Arrays of position-sensitive virtual Frisch-grid (VFG) CdZnTe (CZT) detectors provide a cost-effective solution for integrating large-area arrays for gamma-ray imaging and spectroscopy. These detectors employ high-aspect ratio CZT crystals (bars) with thicknesses up to 50 mm and cross-sections of up to 10 × 10 mm 2 . Despite the long drift distances of charge carriers in such crystals, the detectors have demonstrated excellent performance, achieving energy resolutions better than 1 % full width at half maximum (FWHM) at 662 keV and 3D position resolutions finer than 1 mm. The high spatial resolution is a critical feature of these detectors, as it enables correction of response non-uniformities caused by crystal defects, which remain present even in the highest-quality CZT material. Dislocations and dislocation walls are the primary defects responsible for variations in charge carrier losses as they drift from the interaction points toward the charge-collecting electrodes. The mechanism by which these defects affect carrier transport is generally well understood. Dislocations and sub-grain boundaries act as sinks for carrier-trapping centers, primarily impurities and secondary phases such as tellurium inclusions and precipitates. Here, these regions exhibit significantly higher carrier-trapping rates, leading to variations in the μτ-products. Because the locations of these micron-sized regions are fixed within the detector volume, fluctuations in the total collected charge arise from the random distribution of interaction sites. This results in non-uniform detector responses and degradation of energy resolution. However, by measuring the interaction-site locations with sufficient precision, charge-loss variations can be accurately corrected, allowing recovery of nearly intrinsic energy resolution.

47 OTHER INSTRUMENTATION↗

Modeling Offshore Wind Farm Performance in Coastal Low-Level Jets Using Coupled Mesoscale-Microscale Large Eddy Simulations

Accurately predicting wind farm reliability under complex offshore atmospheric conditions remains a key challenge, particularly during noncanonical meteorological events such as coastal low-level jets (LLJs). LLJs, characterized by strong nonmonotonic vertical shear and directional veer, depart significantly from the simplified inflow assumptions embedded in conventional design standards, low-fidelity engineering models, and microscale large eddy simulations of the atmospheric boundary layer. In this work, we use the virtual wind farm framework—an exascale, graphics processing unit–accelerated large eddy simulation platform coupled with high-fidelity aeroservoelastic turbine models and advanced mesoscale-microscale coupling via the ExaWind software stack—to investigate turbine responses under realistic LLJ forcing. Simulations are performed over the U.S. North Atlantic offshore domain with the use of meteorological inputs from New York State Energy Research and Development Authority buoy data, focusing on a representative LLJ case impacting the International Energy Agency 15 MW reference turbine. Our results show that LLJs can cause up to 50% power deficits in downstream turbine rows and significantly amplify low-speed shaft and tower loads through nonlinear coupling between complex inflow characteristics and turbine structural dynamics. Two primary mechanisms drive these load amplifications: (1) unique LLJ inflow features—including veer and vertical/lateral shear—and (2) the downstream evolution of the flow under stable thermal stratification, which suppresses turbulence mixing and alters wake recovery. These mechanisms produce streamwise variations in turbine loading not captured by standard hub height–based metrics or existing design load case (DLC) definitions. This study highlights the critical role of rotor-scale flow gradients in driving fatigue and system-level aeroelastic responses, challenging current DLC and control strategies. We advocate the integration of full-flow field, environment-aware wind inputs into load modeling and control algorithms. By leveraging exascale computing to resolve mesoscale-microscale coupling, this work lays the groundwork for next-generation offshore wind turbine design and operation in meteorologically complex marine environments.

17 WIND ENERGY↗

Development Fiber Optic Distributed System for Direct Detection of Subsurface Gases Leakages

Carbon, natural gas, and hydrogen gas storage is an emerging solution to safeguard us against pollution, support goals of negative carbon emission, and protect sources of renewable energy. Properly constructed storage wells provide a virtually impervious barrier to any unintended subsurface transmission. The ability to ensure the long-term integrity of such wells is vital to the success of any storage operation and be successful in the public eyes. Therefore, robust monitoring of any gas migration into the subsurface is highly sought. A fiber-optic distributed chemical sensor (DCS) enables monitoring of long-term well integrity along its depth, ensuring the success of any storage operation and bolsters public acceptance of the safety of the reservoir via leak early detection. The same technique can be applied to gas monitoring in pipeline networks and nuclear stockpile monitoring applications. Fiber based Raman spectroscopy enables DCS, as optical fibers can be deployed in virtually any environment and relay spectroscopic information over long distances back to the user. Hollow core fibers (HCF) make excellent DCSs as the air core of the fiber allows gas from the environment to diffuse into the core, which interacts with the laser signal that is carried in the air core. This work builds upon the previous LDRD project, Fiber Optic System for Direct Detection of Carbon Dioxide Leakage in Carbon Storage Wells (21-FS-003), in which the feasibility of Raman spectroscopy detection of Carbon Dioxide (CO2) in HCF detection was demonstrated. We mitigated the risk of this DCS technology by establishing and completing five objectives. The first objective was to model and optically characterize HCF uptake of CO2, establishing the relationship between HCF length, gas diffusion time, detectable gas concentration, and measured Raman intensity. In objective two, we developed a fiber core drilling recipe to enable additional diffusion ports in the fiber core and established a method for maintaining fiber strength and integrity post drilling. Objective three characterized the drilled fibers against the undrilled fibers, establishing the differences in the gas mechanics and optical properties and provided parameters to iterate the drilling process. In objective four, a fusion splicing technique was developed to join the HCF to conventional single-mode fibers, localizing the gas detection point at the drilled HCF hole, emulating a DCS. Lastly, objective five was the testing of the sensor in Edgar Mines at Colorado School of Mines on a CO2 pipeline with a simulated leak, to showcase the ability to detect CO2 leaks. This capstone result showed CO2 leak detection in < 10 minutes, raising the technology readiness level of HCF segments as deployable DCS.

organic↗

Bioenergy Cropping Reduces the Spatiotemporal Scaling of Soil Bacterial Biodiversity

Widespread bioenergy cropping can transform landscapes, strongly affecting biodiversity. However, the impact of bioenergy cropping on the spatiotemporal scaling of soil biodiversity remains virtually unknown, despite its profound implications for the functioning of the ecological community. Here, we investigated how bioenergy cropping influenced the spatiotemporal scaling of soil bacterial biodiversity in marginal soils (sandy loam and clay loam soils) in Oklahoma, USA. We detected strong, significant species-time-area relationships (STARs) and phylogenetic-time-area relationships (PTARs) in bacterial communities and their lineages, suggesting that STARs and PTARs exist in microbial ecology within the studied system. Also, spatiotemporal scaling rates (the slopes of STAR and PTAR models) varied substantially among bacterial lineages and were positively correlated with their 16S rRNA gene copy numbers, a genomic trait indicative of microbial growth potentials. Strikingly, bioenergy cropping significantly reduced spatiotemporal scaling rates by 6.8%-14.1%, with a more pronounced reduction observed in sandy loam soils, where those rates were significantly lower than in clay loam soils. The heterogeneity of soil phosphorus and carbon resulted in variations in bacterial spatiotemporal scaling rates. Collectively, our findings suggest that bioenergy cropping may alleviate rapid shifts in soil biodiversity across space and time, thereby stabilizing soil biodiversity and supporting its role as part of sustainable land management and climate mitigation strategies.

bacterial diversity↗

EPCAPE-PT-LANL Measurements: Wideband Integrated Bioaerosol Sensor

Coastal cities offer a unique environment for studying aerosol-cloud interactions and the effects of urban emissions on cloud properties. As part of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), the Partitioning Thrust by Los Alamos National Laboratory (EPCAPE-PT-LANL) was conducted. Our campaign focused on measuring the optical and chemical properties of aerosols and their interactions within marine stratocumulus clouds in La Jolla, California. EPCAPE-PT-LANL enhances the primary goals of EPCAPE through innovative observations of vapor-phase transitions between aerosols and cloud droplets, the impact of black carbon on aerosol-cloud dynamics, and the effects of cloud processing on aerosol optical properties. Instrument: Wideband Integrated Bioaerosol Sensor (Droplet Measurements Technology) Data Notes: The WIBS is an online single-particle measurement that detects FBAPs (within a size range of 0.5 - 30 microns in diameter) based on the excitation and emission wavelengths of the individual particles. Using two xenon lamps, the WIBS excites FBAPs at 280 nm and 370 nm. Their emission is detected across two wavebands of 310-400 nm and 420-650 nm. We classified the FBAPs into seven different categories (A, B, C, AB, BC, AC, and ABC) using the classification scheme in Perring et. al. (2015) [1]. Averaged number concentration of FBAPs (total and by category) and particles that non-fluorescent bioaerosols particles (NFBAPs). In separate files, we also present one-minute-averaged size distributions and the asymmetry factor (AF, a surrogate for shape) of all FBAPs and NFBAPs. The logarithmic bin width of the size bins are the same as the average bin width of the AOS's optical particle counter (OPC, Grimm) for the range of sizes in which they overlap (26 bins from 0.5 - 30 microns). AF of the particles ranges from 0-100 and is divided into five bins with a linear spacing at increments of 20. The smallest AF bin represents more spherical particles while the largest bin represents more rod-shaped particles. [1] Perring, A. E., et al. (2015), Airborne observations of regional variation in fluorescent aerosol across the United States, J. Geophys. Res. Atmos., 120, 1153–1170, doi:10.1002/2014JD022495. Abstract and description of the campaign can be found here : https://www.arm.gov/research/campaigns/amf2023epcape-pt-lanl. Files data_10min_WIBS_AFDist.csv Header: - FBAP_AFDist[/cm3]_Bin_1 to Bin_5: Concentration of fluorescent bioaerosol particles in the each of 5 AF bins, measured in particles per cubic centimeter. Each bin represents a specific range of particle AF, capturing the shapes of FBAPs detected during the measurement. - NFBAP_AFDist[/cm3]_Bin_1 to Bin_5: Concentration of non-fluorescent bioaerosol particles in the each of 5 AF bins, measured in particles per cubic centimeter. Each bin represents a specific range of particle AF, capturing the shapes of NFBAPs detected during the measurement. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active (true) or inactive (false) during the measurement. AF Bins: • Bin 1: 0 – 20 [unitless] • Bin 2: 21 – 40 [unitless] • Bin 3: 41 – 60 [unitless] • Bin 4: 61 – 80 [unitless] • Bin 5: 81 – 100 [unitless] Files data_10min_WIBS_Conc.csv Header: - NumberConcentrationA[/cm3]: Number concentration of bioaerosol particles detected by fluorescence channel A, measured in particles per cubic centimeter. - NumberConcentrationB[/cm3]: Number concentration of bioaerosol particles detected by fluorescence channel B, measured in particles per cubic centimeter. - NumberConcentrationC[/cm3]: Number concentration of bioaerosol particles detected by fluorescence channel C, measured in particles per cubic centimeter. - NumberConcentrationAB[/cm3]: Combined number concentration of bioaerosol particles detected by both fluorescence channels A and B, measured in particles per cubic centimeter. - NumberConcentrationBC[/cm3]: Combined number concentration of bioaerosol particles detected by both fluorescence channels B and C, measured in particles per cubic centimeter. - NumberConcentrationAC[/cm3]: Combined number concentration of bioaerosol particles detected by both fluorescence channels A and C, measured in particles per cubic centimeter. - NumberConcentrationABC[/cm3]: Combined number concentration of bioaerosol particles detected by all three fluorescence channels A, B, and C, measured in particles per cubic centimeter. - NumberConcentrationNFBAP[/cm3]: Number concentration of non-fluorescent bioaerosol particles, measured in particles per cubic centimeter. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active (true) or inactive (false) during the measurement. Files data_10min_WIBS_SizeDist.csv Header: - FBAP_SizeDist[/cm3]_Bin_1 to FBAP_SizeDist[/cm3]_Bin_26: Number concentrations of FBAP in each of 26 size bins, measured in particles per cubic centimeter. Each bin represents a specific range of particle sizes, capturing the size distribution of FBAPs detected during the measurement. - NFBAP_SizeDist[/cm3]_Bin_1 to NFBAP_SizeDist[/cm3]_Bin_26: Number concentrations of NFBAP in each of 26 size bins, measured in particles per cubic centimeter. Similar to FBAP, each bin covers a specific range of particle sizes, detailing the size distribution of NFBAPs detected. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active (true) or inactive (false) during the measurement. Size Bins: • Bin 1: 0.48 to 0.57 μm • Bin 2: 0.57 to 0.67 μm • Bin 3: 0.67 to 0.79 μm • Bin 4: 0.79 to 0.93 μm • Bin 5: 0.93 to 1.1 μm • Bin 6: 1.1 to 1.29 μm • Bin 7: 1.29 to 1.52 μm • Bin 8: 1.52 to 1.8 μm • Bin 9: 1.8 to 2.11 μm • Bin 10: 2.11 to 2.5 μm • Bin 11: 2.5 to 2.94 μm • Bin 12: 2.94 to 3.46 μm • Bin 13: 3.46 to 4.08 μm • Bin 14: 4.08 to 4.81 μm • Bin 15: 4.81 to 5.67 μm • Bin 16: 5.67 to 6.68 μm • Bin 17: 6.68 to 7.88 μm • Bin 18: 7.88 to 9.29 μm • Bin 19: 9.29 to 10.96 μm • Bin 20: 10.96 to 12.92 μm • Bin 21: 12.92 to 15.23 μm • Bin 22: 15.23 to 17.96 μm • Bin 23: 17.96 to 21.17 μm • Bin 24: 21.17 to 24.96 μm • Bin 25: 24.96 to 29.43 μm • Bin 26: 29.43 to 34.70 μm

54 ENVIRONMENTAL SCIENCES↗

Virtual Reality for Shoot/No-Shoot Decision Training in Law Enforcement: A Literature Review and Research Agenda

Virtual reality (VR) can materially improve “shoot / no-shoot” (SNS) training by giving officers realistic, repeatable practice making high-stakes decisions under pressure. Traditional tools—live-fire ranges and video simulators—build basics, but they cannot adapt to each officer in real time or fully mirror the complexity of the field. VR closes that gap by creating immersive scenarios that are safer, more flexible, easier to scale across units, and able to capture objective performance data. SNS decisions are not just about marksmanship; they rely on perception, judgment, memory, and the ability to hold fire when a threat is uncertain. Effective training therefore needs realism, decision complexity, and branching outcomes that reflect the true consequences of choices. These elements strengthen recognition of hostile intent while reducing false positives and building the self-control required in ambiguous situations. VR brings specific advantages: dynamic environments, full-body interaction, and the ability to measure performance with precision—enabling targeted feedback and better transfer of learning to the street. At the same time, responsible deployment must address scenario quality (credible environments and behaviors), lawful decision models, and user wellbeing (appropriate stress levels, comfort, and safety). Sandia’s VIPER Lab is positioned to lead this work. The team combines human-performance science, AI/ML, and VR/AR development with a deep equipment bench (e.g., omnidirectional treadmill, eye-tracking, haptics, multiple HMDs). This ecosystem supports building and validating next-generation SNS training that is immersive, measurable, and trustworthy. Bottom line: Investment in VR-enabled SNS training that blends evidence-based design with careful validation and legal safeguards is expected to pay off in safer, more consistent decision-making and improved community trust, delivered through training that is practical to deploy at scale.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

First Measurement of Near-Threshold and Subthreshold 𝐽/𝜓 Photoproduction off Nuclei

We report on the first measurement of J/ψ photoproduction from nuclei in the photon energy range of 7 to 10.8 GeV, extending above and below the photoproduction threshold in the free proton of ∼ 8.2 GeV. The experiment used a tagged photon beam incident on deuterium, helium, and carbon, and the GlueX detector at Jefferson Lab to measure the semi-inclusive A(γ, e + e − p) reaction with a dilepton invariant mass M(e + e − ) ∼ m J/ψ = 3.1 GeV. The incoherent J/ψ photoproduction cross sections in the measured nuclei are extracted as a function of the incident photon energy, momentum transfer, and proton reconstructed missing light-cone momentum fraction. Comparisons with theoretical predictions assuming a dipole form factor allow extracting a gluonic radius for bound protons of p $\sqrt4⟨r^2⟩$ = 0.85 ± 0.14 fm. The data also suggest an excess of the measured cross section for sub-threshold production and for interactions with high missing light-cone momentum fraction protons. The measured enhancement can be explained by modified gluon structure for high-virtuality bound-protons.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

AGR 5/6/7 Data Qualification Report for ATR Cycles 162B through 168A

This report provides the qualification status of experimental data for the Advanced Gas Reactor (AGR) 5/6/7 fuel irradiation. AGR-5/6/7 was conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) in support of development and qualification of tri-structural isotropic (TRISO) low-enriched fuel for use in high temperature gas-cooled reactors. The objectives of the AGR-5/6/7 experiments are to: (i) irradiate reference-design fuel particles to support fuel qualification, (ii) establish operating margins for the fuel beyond normal operating conditions, and (iii) provide irradiated-fuel performance data and irradiated-fuel samples for post-irradiation examination (PIE) and safety testing. The test train contains five separate capsules that were independently controlled and monitored. Each capsule contains multiple 12.51-mm-long compacts filled with low enriched uranium carbide/oxide (UCO) TRISO fuel particles. The primary objective of the AGR-5/6 test (Capsules 1, 2, 4, and 5) is to verify successful performance of the reference-design fuel under normal operating conditions. The AGR-7 test (Capsule 3) was designed to explore fuel performance at higher temperatures to demonstrate the capability of the fuel to withstand conditions beyond normal operating conditions in support of plant design and licensing. AGR 5/6/7 will also provide irradiated-fuel performance data on fission-gas release from failed particles during irradiation. The AGR-5/6/7 capsules were irradiated in the ATR northeast flux trap location. The experiment began on February 16, 2018 and ended on July 22, 2020, spanning nine ATR cycles over two and a half years. Thus, the AGR-5/6/7 fuel compacts were irradiated for a total of 360.9 effective full power days. The AGR 5/6/7 experiment was able to remain in the reactor core during all three Powered Axial Locator Mechanism (PALM) cycles (163A, 165A, and 167A) without overheating its fuel compacts. This report includes irradiation monitoring data from nine ATR Cycles: 162B, 163A, 164A, 164B, 165A, 166A, 166B, 167A, and 168A, as stored in the Nuclear Data Management and Analysis System (NDMAS). During irradiation, data records consisted of instantaneous measurements recorded every minute and provided by text files automatically every 2 hours. The AGR 5/6/7 data streams addressed in this report include thermocouple (TC) temperatures, sweep gas data (flow rates [capsule inlet, outlet, and downstream at detector], pressure, and moisture content), and Fission Product Monitoring System (FPMS) data (release rates and release to birth rate ratios [R/Bs]) for each of the five capsules. A total of 94,989,908 TC temperature and sweep gas data records were received and processed by NDMAS for AGR 5/6/7 irradiation. Of these records, 41,593,387 (or 43.7% of the total) met data collection and accuracy requirements and are labeled as Qualified. A total of 57,746,693 TC temperature readings were captured from 54 installed TCs. Among them, 10,034,676 TC temperature records (only 17.4%) were Qualified and 47,701,371 TC temperatures (or 82.6%) are Failed due to 48 TC failures (63.5%) and due to missing values (19.1%). To assess performance of the operational TCs, analysis of daily correlations between TCs found no evidence of virtual junction failure for any TCs. Analyses on control charts of TC temperature differences revealed trending in TC readings for TC2, 4, 5, and 13 in Capsule 3, but there is no conclusive indication of TC drift failure that caused those trends. Therefore, TC control charts are not used to disqualify TC data, but only for users’ consideration. For sweep gas flow rates, a total of 31,519,747 gas flow records (84.4%) are Qualified for use for AGR-5/6/7 experiment; 5,723,468 gas flow records (15.4%) are Failed due mostly to missing values; and 74,641 high sweep gas flow rates (0.2 %) are Trend. A large number of Failed missing TC temperature and gas flow values were caused by an error in the data output script that outputted a ‘NULL’ value when values were unchanged. This problem was fixed during the outage of Cycle 166B, which led to a substantially decreased number of missing values during the last three cycles. Nonetheless, a large amount of non-missing data remained because of the high data acquisition frequency (1-minute) and still provided sufficient data to effectively monitor the experiment as designed. For FPMS data, NDMAS received and processed fission product release and R/B data for nine ATR cycles, when ATR core reached full power during AGR 5/6/7 irradiation. These data consist of 110,388 release rate records and 110,388 R/B records for the twelve radionuclides (Kr 85m, Kr 87, Kr 88, Kr 89, Kr 90, Xe 131m, Xe 133, Xe 135, Xe 135m, Xe 137, Xe 138, and Xe 139) for each of the five capsules. Equivalent numbers of uncertainty records associated the release rates and R/B values were provided. To date, qualification status of the FPMS data stored in the NDMAS dat

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Towards a Deeper Fundamental Understanding of (Al,Sc)N Ferroelectric Nitrides

Density functional theory (DFT) calculations, within the virtual crystal alloy approximation, are performed, along with the development of a Landau-type model employing a symmetry-allowed analytical expression of the internal energy and having parameters determined from first principles, to investigate properties and energetics of Al1-xScxN ferroelectric nitrides in their hexagonal forms. These DFT computations and this model predict the existence of two different types of minima, namely, the fourfold-coordinated wurtzite (WZ) polar structure and a five-fold coordinated paraelectric hexagonal phase (denoted as H5), for any Sc composition up to 40%. The H5 minimum progressively becomes the lowest-energy state within hexagonal symmetry as the Sc concentration increases from 0 to 0.4. Furthermore, the model points to several key findings. Examples include the crucial role of the coupling between polarization and strains to create the WZ minimum, in addition to polar and elastic energies, and that the origin of the H5 state overcoming the WZ phase as the global minimum within hexagonal symmetry when increasing the Sc composition mostly lies in the compositional dependency of only two parameters-one linked to the polarization and another one being purely elastic in nature. Other examples are that forcing Al1-xScxN systems to have no or a weak change in lattice parameters when heating them allows us to reproduce their finite-temperature polar properties well and that a value of the axial ratio close to that of the ideal WZ structure implies a large polarization at low temperatures but not necessarily at high temperatures because of the ordered-disordered character of the temperature-induced formation of the WZ state. Such findings should allow for a better fundamental understanding of (Al,Sc)N ferroelectric nitrides, which may be used to design efficient devices having, e.g., low operating voltages.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NewLife Nuclear - An Environmentally and Economically Minded Solution for Fusion Energy Waste Handling

Energy demand is rising as a result of innovative and increasingly more energy intensive processes coming to fruition, particularly through the recent interest in the development of AI data centers as well as manufacturing with the push towards increasing domestic manufacturing interest. Fusion energy can provide virtually limitless energy to support this increase in energy demand. Fusion energy concepts, largely classified as magnetic fusion energy (MFE) and inertial fusion energy (IFE) are being pursued, each having unique challenges to overcome before the successful deployment of electricity to the grid. Achieving fusion ignition on the National Ignition Facility, first in December 2022, and eight times since, has demonstrated the scientific viability of the IFE approach. Meanwhile, MFE test stands continue to improve confinement times, making meaningful strides in progressing towards experimental scientific viability. In each of these approaches, an emphasis is placed on generating more power out of the system than what is required to power the system. An under-researched area applicable to both IFE and MFE is handling activated waste coming out of fusion energy systems, both in the course of normal daily operations, as well as in intermittent periods as structural materials may need to be replaced. In the context of an IFE plant system, commonly discussed plant designs suggest targets are ignited within a chamber at a rate of up to one million targets per day. Between each shot, the chamber housing the ignition event will clear a portion of the chamber – resulting in a mixture of vaporized target gas, target debris, and other materials being expelled from the chamber [source]. Additionally, IFE system concepts typically discuss the modularization of plant designs, which are expected to be replaced periodically as the components degrade over time. This would result in the irradiated chamber structure materials, likely metals and alloys, needing to be removed and safely stored. In MFE plant systems, while targets are not ignited at a repetition rate with the frequent chamber clearing as is expected in IFE plant systems, it is anticipated that portions of the confinement area interfacing with the hot plasma will need to be replaced periodically. In each system, without additional investment and research into alternative processing and recycling methods, the result is storing irradiated materials, and other elements in a safe containment area until they are no longer activated. – resulting in significant waste both economic and environmental.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Dielectron production in central Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02TeV

The first measurement of the 𝑒 + ⁢𝑒 − pair production at midrapidity and low invariant mass in central Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV at the Large Hadron Collider is presented. The yield of 𝑒 + ⁢𝑒 − pairs is compared with a cocktail of expected hadronic decay contributions in the invariant mass (𝑚𝑒⁢𝑒) and pair transverse momentum (𝑝 T,𝑒⁢𝑒 ) ranges 𝑚 𝑒⁢𝑒 < 3.5 GeV/𝑐 2 and 𝑝 T,𝑒⁢𝑒 < 8 GeV/𝑐. For 0.18 < 𝑚 𝑒⁢𝑒 < 0.5 GeV/𝑐 2 the ratio of data to the cocktail of hadronic contributions amounts to 1.40 ± 0.11⁢(stat.) ± 0.23 ⁢(syst.) ± 0.16⁢ (cocktail) and 1.42 ± 0.11⁢ (stat.) ± 0.23 (syst.)$^{+0.24}_{−0.29}$ ⁢(cocktail), including or not including medium effects in the estimation of the heavy-flavor background, respectively. It is consistent with predictions from two different models for an additional contribution of thermal 𝑒+⁢𝑒− pairs from the hadronic and partonic phases. In the intermediate-mass range (1.2 < 𝑚 𝑒⁢𝑒 < 2.6 GeV/𝑐 2 ), the pair transverse impact parameter of the 𝑒 + ⁢𝑒 − pairs (DCA𝑒⁢𝑒, where “DCA” denotes “distance of closest approach”) is used for the first time in Pb-Pb collisions to separate displaced dielectrons from heavy-flavor hadron decays from a possible (thermal) contribution produced at the interaction point. The data are consistent with a suppression of 𝑒 + ⁢𝑒 − pairs from $𝑐\bar{𝑐}$ and an additional prompt component. Finally, the first direct-photon measurement in the 10% most central Pb-Pb collisions at $\sqrt{s_{NN}}$ = 5.02 TeV is reported via the study of virtual direct photons in the transverse momentum range 1 < 𝑝 T < 5 GeV/𝑐. A model including prompt photons, as well as photons from the preequilibrium and fluid-dynamic phases, can reproduce the result, while being at the upper edge of the data uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

EPCAPE-PT-LANL Measurements: Single Particle Soot Photometer

Coastal cities offer a unique environment for studying aerosol-cloud interactions and the effects of urban emissions on cloud properties. As part of the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE), the Partitioning Thrust by Los Alamos National Laboratory (EPCAPE-PT-LANL) was conducted. Our campaign focused on measuring the optical and chemical properties of aerosols and their interactions within marine stratocumulus clouds in La Jolla, California. EPCAPE-PT-LANL enhances the primary goals of EPCAPE through innovative observations of vapor-phase transitions between aerosols and cloud droplets, the impact of black carbon on aerosol-cloud dynamics, and the effects of cloud processing on aerosol optical properties. Instrument: Single Particle Soot Photometer (Droplet Measurements Technology) Data Notes: Contact us if you want additional data products from this instrument. Reported data is the black carbon (rBC) number and mass concentration with diagnostic flags. The SP2 measures incandescence from particles that is induced with a 1064 Nd-YAG laser. Particles that absorb the laser energy and then emit radiation is assumed to contain black carbon. The amount of intensity of radiation is related to the mass of absorbing material in the particle. Here, we calibrate the incandescence intensity to size selected Regal Black (Cabot) nebulized from solution. Data provided for the EPCAPE campaign used the combined broadband high-gain + low-gain channels (BHBL). Each channel has a lower threshold of detection equivalent to 2-s of the respective channel noise. Thresholding has been applied to select between the high-gain and low-gain channels. The detection limit is 80-540 nm (Deq) or 0.36- 55 fg. It is assumed that rBC is the only aerosol type that is in significant concentration in the sampled atmosphere that absorbs the laser energy. Particle data are integrated over 10 second windows to calculate a rBC number and mass concentration. QC/QA: • Diagnostic flags that impacted measured concentration: - Sample, Sheath, and Purge Flow Rates: Despite observing fluctuations in all flows, the rBC detection and mass quantification are generally observed to be stable, although large changes in sample flow rate did impact detection efficiency. A flag was implemented for sample flow deviations >12 cm3/min from the set point averaged over 30 seconds - Laser Power: Detection efficiency decreases with laser power and deviations in laser power also affect mass quantification. Flag for laser power is set for deviations in laser current from the set value >5 mA. - Primary Detector Threshold: Primary thresholding is the signal value which determines whether a “particle” is recorded. Thresholding errors occur when the threshold value is too HIGH and real particles are ignored. • Several periods without data: - 16-18 Nov: Ultra Zero Air generator failure, flows deviated significantly from set points. rBC # conc recovered but questionable. - 20-21 Nov: Offline for calibrations for several hours each day. - 25-27 Nov: Data is missing. - 30 Nov: Power outage 3 Dec: SP2 hard-drive full. - 3 Dec: Power Outage Header: - BHBL_NumbConc[#/cc]: Refers to the number concentration of refractory black carbon (rBC) measured from combined broadband high-gain and low-gain channels, expressed in particles per cubic centimeter. - BHBL_BCMass_Conc[ug/m3]: Refers to the mass concentration of refractory black carbon (rBC) measured from combined broadband high-gain and low-gain channels, expressed in micrograms per cubic meter. - NoData_Flag[bool]: A boolean flag that indicates whether no data was recorded during a measurement. - NoBC_Flag[bool]: A boolean flag indicating whether no black carbon particles were recorded during the measurement. - Laser_Flag[bool]: A boolean flag indicating deviations in laser current during the measurement. - SampleFlow_Flag[bool]: A boolean flag indicating deviations from the set sample flow rate during the measurement. - PrimThresh_Flag[bool]: A boolean flag indicating deviations from the set primary threshold during the measurement, potentially ignoring real particles. - Manual_Flag[bool]: A boolean flag indicating manual intervention or adjustments during the measurement. - CVI_Flag[bool]: A boolean flag indicating whether the Counterflow Virtual Impactor (CVI) was active or inactive during the measurement.

54 ENVIRONMENTAL SCIENCES↗

DASSH-F: Subchannel Based Thermal Analysis

The DASSH thermal analysis code is designed to rapidly allow a reactor design engineer to obtain flow rates requirements that satisfy peak temperature constraints in the domain. The advantage of using DASSH over a hand calculation is that it has a more rigorous treatment of the pin power distribution and coolant heat transfer within an assembly and between assemblies. The advantage of using DASSH over a conventional 3D subchannel code or a computational fluid dynamics code (CFD) is that it can obtain the desired solution in a matter of minutes in serial with minor computer memory needs. The DASSH methodology for pin lattice models is virtually identical to SUPERENERGY-2 with additional functionalities taken from follow on work to SUPERENERGY-2 done at ANL in the 1980s. DASSH today is an integral component of the Argonne Fast Reactor analysis suite for reactor design work. DASSH obtains the power distribution from a coupled neutron-gamma heating calculation in GAMSOR (including DIF3D) at each time point of a companion fuel cycle analysis calculation with REBUS. The domain in DASSH assumes a hexagonal grid typical for fast reactors with much of the geometry information taken from the DIF3D model. DASSH assumes the assemblies that are loaded into each grid position are ducted to control the coolant flow. The user can alternatively provide their own geometry and power profile instead of inheriting it from DIF3D. Considerable detail is given on the subchannel formulation of DASSH in this document. Much of the formulation and design of the code builds upon research done by previous authors with little new investigation. Thus the decisions made in developing the subchannel model used in DASSH have their origins over 50 years ago. Much of the heat transfer methodology in DASSH is built upon correlations for both the coolant mixing and heat transfer coefficients for pins and ducts. DASSH is thus not a rigorous treatment of a given problem, but a rapid assessment of the temperature field that has known limitations with respect to an experimental measurement or CFD calculation. The DASSH input and output are detailed along with usage of the software. The DASSH output provides tables of evaluated material properties and key coolant and pin temperature results. DASSH can create Python scripts that generate domain summary pictures. DASSH can also generate assembly temperature maps and VTK output files which allow the DASSH solution to be visualized. As the primary purpose of the DASSH software is to compute the coolant and fuel pin temperature distribution for a given model of a reactor, much of the output focus is giving the user quick summary tables needed to assess the performance of a given orifice flow specification. The present version of DASSH has a crude orifice search capability and a sufficient orifice flow search capability. The flow search tries to meet user specified constraints for 1) peak 2-sigma clad temperature, 2) peak coolant temperature, and 3) desired bulk outlet temperature. This document serves as the manual for the Fortran based DASSH software that was developed to replace the Python version of DASSH developed as part of the VTR program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DASSH-F: Subchannel Based Thermal Analysis

The DASSH thermal analysis code is designed to rapidly allow a reactor design engineer to obtain flow rates requirements that satisfy peak temperature constraints in the domain. The advantage of using DASSH over a hand calculation is that it has a more rigorous treatment of the pin power distribution and coolant heat transfer within an assembly and between assemblies. The advantage of using DASSH over a conventional 3D subchannel code or a computational fluid dynamics code (CFD) is that it can obtain the desired solution in a matter of minutes in serial with minor computer memory needs. The DASSH methodology is virtually identical to SUPERENERGY-2 with additional functionalities taken from follow on work to SUPERENERGY-2 done at ANL in the 1980s. DASSH today is an integral component of the Argonne Fast Reactor analysis suite for reactor design work. DASSH obtains the power distribution from a coupled neutron-gamma heating calculation in GAMSOR (including DIF3D) at each time point of a companion fuel cycle analysis calculation with REBUS. The domain in DASSH assumes a hexagonal grid typical for fast reactors with much of the geometry information taken from the DIF3D model. DASSH assumes the assemblies that are loaded into each grid position are ducted to control the coolant flow. Considerable detail is given on the subchannel formulation of DASSH in this document. Much of the formulation and design of the code builds upon research done by previous authors with little new investigation. Thus the decisions made in developing the subchannel model used in DASSH have their origins over 50 years ago. Much of the heat transfer methodology in DASSH is built upon correlations for both the coolant mixing and heat transfer coefficients for pins and ducts. DASSH is thus not a rigorous treatment of a given problem, but a rapid assessment of the temperature field that has known limitations with respect to an experimental measurement or CFD calculation. The DASSH input and output are detailed along with usage of the software. The DASSH output provides tables of evaluated material properties and key coolant and pin temperature results. DASSH can create Python scripts that generate domain summary pictures. DASSH can also generate assembly temperature maps and VTK output files which allow the DASSH solution to be visualized. As the primary purpose of the DASSH software is to compute the coolant and fuel pin temperature distribution for a given model of a reactor, much of the output focus is giving the user quick summary tables needed to assess the performance of a given orifice flow specification. The present version of DASSH has a crude orifice search capability and an efficient orifice flow search capability. The flow search tries to meet user specified constraints for 1) peak 2-sigma clad midwall temperature, 2) peak coolant temperature, and 3) desired bulk outlet temperature. There are many development shortcomings in DASSH detailed in this document, but this version is functional for modern analysis needs. This document serves as the manual for the Fortran based DASSH software that was developed to replace the Python version of DASSH developed as part of the VTR program.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Three pairs of fungal Trametes strains isolated from distinct geographic origins show conserved genomic features and adaptive response to plant biomass

The genomes of white-rot fungi hold extended repertoires of enzymes active on virtually all the chemical bonds that intertwine lignocellulose polymers, and several Trametes species have been identified as powerful tools for biorefinery or bioremediation. However, only few studies have addressed the intra-species polymorphism one would expect from fungal strains collected in contrasted environments. We compared the genome sequence of pairs of strains collected in different geographic areas, for each of three fungal species. Using an updated list of the predicted functions for fungal ligno- and cellulolytic enzymes (CAZymes), we observed a high conservation of the gene repertoires among the six strains. We compared the adaptative response of the fungi grown on crystalline cellulose, wheat straw, aspen or pine sawdust by transcriptomics and secretomics. The gene regulation profiles were determined by the species and the substrates, rather than the strain. The secretomes did not show marked differences in the sets of secreted CAZymes after 3 day-growth on the substrates. We identified five transcription factor genes and two sesquiterpenoid synthesis genes induced during growth on lignocellulose. Wider studies using larger sets of strains will be necessary to evaluate the genericity of our findings, and to assess the phenotype diversity one could expect from geographic diversity as compared to taxonomic diversity in Trametes fungi.

Drula, E. [French National Research Institute for ↗

HDG-1 Experiment Irradiation Monitoring Data Qualification Final Report

SUMMARY The U.S. Department of Energy (DOE) Advanced Reactor Technologies (ART) Graphite Research and Development (GRD) Program is conducting a series of six experiments to quantify the effects of irradiation on nuclear-grade graphite. This report documents the qualification of irradiation monitoring data for the fifth experiment, High Dose Graphite-1 (HDG-1). Qualified monitoring data are required by the ART program to support the design and licensing of the first high-temperature reactor (HTR) nuclear plant. Data are classified as Qualified if they meet the usage requirements described in the experiment planning and quality assurance (QA) documents, Failed if they do not meet those requirements and provide no usable information, or Trend if they do not fully meet all requirements but still provide useful information subject to an assessment of how any deficiencies may affect a particular use of the data. HDG-1 irradiation began with Advanced Test Reactor (ATR) Cycle 168B on August 24, 2020, and concluded after Cycle 173C on January 27, 2025. The HDG-1 capsule was removed from the reactor core twice—during core internal change (CIC) Cycle 170A and powered axial locator mechanism (PALM) Cycle 172A—to prevent overheating of the graphite specimens during high-power PALM cycles. The capsule was therefore irradiated during a total of seven normal ATR cycles: 168B, 169A, 171A, 171B, 173A, 173B, and 173C. Irradiation monitoring data evaluated in this report include thermocouple (TC) temperature, gas flow rate, gas moisture, gas pressure, specimen load, and graphite stack displacement. Temperature. A total of 14,508,065 TC temperature records were captured. Of these, 13,901,785 (95.8%) are Qualified and 606,280 (4.2%) are Failed. The principal source of failed temperature data was the instrument failure of TC-9 (Zone 2) on June 24, 2024, and TC-10 (Zone 1) on July 5, 2024, near the end of Cycle 173A, which resulted in 595,554 Failed readings. An additional 379 missing values and 10,347 slightly negative values from TC-13 during ATR outages are also Failed. Neither TC-9 nor TC-10 was used as a temperature-control TC, and their failures did not compromise capsule condition monitoring. Correlation analysis of all 13 TCs found no evidence of virtual junction formation. Control chart analysis revealed clear downward drift of approximately 80°C for TC-6 (Zone 3) relative to other stable TCs, and possible downward drift of approximately 60°C for TC-13 relative to the Zone 5 control TC (TC-1), though TC-13 remained consistent with the Zone 2 control TC (TC-12). Gas flow. A total of 20,088,090 gas flow rate records were captured. Of these, 19,941,463 (99.3%) are Qualified and 146,627 (0.7%) are Failed due to missing values. All argon, helium, and total gas flow data were within expected ranges throughout the irradiation. Gas moisture. A total of 1,116,005 outlet gas moisture values were captured. Of these, 1,101,421 (98.7%) are Qualified and 14,584 (1.3%) are Failed, comprising 14,556 out-of-range values and 28 missing values. The out-of-range moisture values exceeded 22,000 ppmv for approximately 1 week at the beginning of Cycle 173A, when accumulated moisture evaporated after the capsule was retrieved from water storage during PALM Cycle 172A and reinserted into the east flux trap. Moisture levels returned to below 25 ppmv for the remaining three cycles, and the transient high-moisture event did not affect the integrity of specimen irradiation. Gas pressure. A total of 7,812,035 gas pressure values were captured. Of these, 6,642,048 (85.0%) are Qualified and 1,169,987 (15.0%) outlet pressure values are Failed, comprising 718,537 zero outlet pressure values due to sensor failure from Cycle 168B through Cycle 171B, 54,550 missing values, and 396,900 too-low outlet pressure values, ranging from 1.1 to 1.6 psia after sensor replacement during Cycle 173A. Load. A total of 6,696,030 load values were captured. Of these, 6,694,580 (99.98%) are Qualified and 1,450 (0.02%) are Failed due to missing values. Applied loads to the six specimen stacks were stable throughout the irradiation. Stack displacement. A total of 6,696,030 displacement values were captured. Of these, 5,713,297 (85.32%) are Qualified and 3,781 (0.06%) are Failed due to missing values. Stack displacement increased consistently throughout the irradiation, reaching approximately 3.08 in. for Channels 5 and 6 by the end of irradiation. 978,952 (14.62%) substantially elevated displacements observed for Channel 6 beginning in Cycle 171A and for Channel 5 beginning in Cycle 173A are assigned Trend status. Raising pressure. A total of 1,115,999 raising pressure values were captured. Of these, 1,115,430 (99.95%) are Qualified and 569 (0.05%) are Failed due to missing values. Ram pressure. A total of 6,696,030 ram pressure values were captured. Of these, 6,692,249 (99.95%) are Qualified and 3,484 (0.05%) are Failed due to missing values. Stack raising was perf

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗