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DOE OSTI2026

Leaf Wax Hydrogen Isotopes Reflect Storm Track Position Over Western North America

Proxy records of past climates have yielded powerful insights into regional hydroclimate dynamics. Novel insights may be gained by reconstructing spatiotemporal changes in precipitation isotopologues in past climate states that cannot be gleaned from individual site‐level studies. In this paper, we ask whether latitudinal gradients in the stable hydrogen isotopic composition of precipitation, as inferred from sedimentary leaf wax biomarkers, reflect aspects of large‐scale climate conditions in western North America (WNA). Modern coretop samples from offshore WNA show that leaf wax hydrogen isotopes broadly track the hydrogen isotopic composition of rainfall between 20 and 40N, but with an offset corresponding to a relatively constant “apparent fractionation” value. Poleward of 40N, the leaf wax signal may be complicated by fluvial transport of leaf waxes from the continental interior. Leaf wax‐inferred precipitation hydrogen isotopes show a shift to more negative values between 30 and 40N. We use modern observational data to show that this latitudinal range marks a major transition between the subtropical arid zone and the location of the midlatitude storm tracks over the northeast Pacific. Nudged water isotope‐enabled models capture the location of the arid to mesic climate transition with fidelity. This modern data set suggests that reconstructions of the latitudinal gradient of precipitation hydrogen isotopes can constrain the sensitivity of the storm tracks to shifts in climatic boundary conditions in past climate states. This approach can yield novel insights into past, present, and future hydroclimate variability in this arid region.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Electron transport barrier and high confinement in configurations with internal islands close to the plasma edge of W7-X

The low magnetic shear in the Wendelstein 7-X (W7-X) stellarator makes it feasible to shape the separatrix by the large islands constituting an island-divertor, and this can be exploited to access various magnetic configurations, including samples of different internal island sizes and locations. To investigate the configuration effects on the plasma confinement, a configuration scan was performed by changing the coil currents to vary the rotational transform between values 5/4 and 5/6 at the plasma boundary with different power levels (2, 4, 6 MW) of electron cyclotron resonance heating (ECRH) at a maximum plasma density of 8 × 10 19 m -2 . neutral beam injection (NBI) heating was also applied during some configurations of the scan to create a density ramp and access high densities beyond the X2 ECRH cutoff. For the magnetic configurations, where the 5/5 and 5/6 island chains were moved closer to separatrix but remaining inside the last closed flux surface, the electron cyclotron emission shows that an electron temperature, T e , pedestal develops already during ECRH heated plasma buildup phase indicating a transport barrier, and the barrier sustains irrespective of changed plasma heating conditions such as NBI in the later part of discharge. The transport barrier is broken by subsequent fast crashes, observed with multiple plasma diagnostics with characteristics such as tokamak edge localized modes, and the corresponding crash amplitude and frequency vary with plasma pressure. The impact of the transport barrier on plasma confinement can be seen through the increased core T e profile, which could be responsible for the overall increase in the stored diamagnetic energy by approximately 10% for these configurations. After the plasma heating is terminated, a backwards transition to a degraded confinement state is also observed. These observations indicate a configuration triggered high confinement mode in low shear W7-X. This work focuses on the occurrence of this transport barrier for different magnetic configurations and its relation to internal magnetic islands.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Can portable glucose and lactate meters be a useful tool in quantifying stress of juvenile Chinook salmon?

Blood plasma analyses can provide researchers, aquaculture facilities and fisheries managers with valuable insights into the physiological state and welfare of fish. For example, glucose and lactate are part of the secondary stress response system, and elevated concentrations are indicators of stress. However, analysing blood plasma in the field can be logistically difficult and typically involves sample storage and transport to quantify concentrations in a laboratory setting. Portable glucose and lactate meters offer an alternative to laboratory assays and have shown to be relatively accurate in fish, but these tools have only been validated for a few fish species. The objective of this study was to investigate if portable meters could be reliably used in Chinook salmon (Oncorhynchus tshawytscha). As part of a larger stress response study, juvenile Chinook salmon (157 ± 17 mm fork length [mean ± standard deviation; SD]) were exposed to stress-inducing treatments and sampled for blood. Laboratory reference glucose concentrations (milligrams per deciliter; mg/dl; n = 70) were positively correlated with the Accu-Check Aviva meter (Roche Diagnostics, Indianapolis, IN) measurements (R 2 = 0.79), although glucose values were 1.21 ± 0.21 (mean ± SD) times higher in the laboratory than with the portable meter. Lactate concentrations (milliMolar; mM; n = 52) of the laboratory reference were also positively correlated (R 2 = 0.76) with the Lactate Plus meter (Nova Biomedical, Waltham, MA) and were 2.55 ± 0.50 times higher than portable meter. Our results indicate both meters could be used to measure relative glucose and lactate concentrations in Chinook salmon and provide fisheries professionals with a valuable tool, particularly in remote field settings.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Cosmological constraints from H ii starburst galaxy, quasar angular size, and other measurements

ABSTRACT We compare the constraints from two (2019 and 2021) compilations of H ii starburst galaxy (H iiG) data and test the model independence of quasar (QSO) angular size data using six spatially flat and non-flat cosmological models. We find that the new 2021 compilation of H iiG data generally provides tighter constraints and prefers lower values of cosmological parameters than those from the 2019 H iiG data. QSO data by themselves give relatively model-independent constraints on the characteristic linear size, lm, of the QSOs within the sample. We also use Hubble parameter [H(z)], baryon acoustic oscillation (BAO), Pantheon Type Ia supernova (SN Ia) apparent magnitude (SN-Pantheon), and DES-3 yr binned SN Ia apparent magnitude (SN-DES) measurements to perform joint analyses with H iiG and QSO angular size data, since their constraints are not mutually inconsistent within the six cosmological models we study. A joint analysis of H(z), BAO, SN-Pantheon, SN-DES, QSO, and the newest compilation of H iiG data provides almost model-independent summary estimates of the Hubble constant, $H_0=69.7\pm 1.2\ \rm {km\,s^{-1}\,Mpc^{-1}}$, the non-relativistic matter density parameter, $\Omega _{\rm m_0}=0.293\pm 0.021$, and lm = 10.93 ± 0.25 pc.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Process damping identification using Bayesian learning and time domain simulation

Process damping can provide improved machining productivity by increasing the stability limit at low spindle speeds. However, existing methods for identifying process damping models experimentally require specialized setups and/or multiple cutting tests. While the phenomenon is well known, the modeling challenges limit pre-process parameter selection that leverages the potential increases in material removal rates. This paper proposes a physics-informed Bayesian method that can identify the cutting force and process damping models from a limited set of test cuts without requiring direct measurements of cutting force or vibration. The method uses time domain simulation to incorporate process damping and provide a basis for test selection. Here, new strategies for efficient sampling and dimensionality reduction are applied to lower computation time and minimize the effect of model error. The proposed method is demonstrated and the identified cutting and damping force coefficients are compared to values obtained using machining tests and least-squares fitting.

42 ENGINEERING↗

DOE OSTI2022

Implementation of Sacrificial Support Structures for Hybrid Manufacturing of Thin Walls

Thin-walled features can be difficult to produce with traditional machining methods which often rely on excess stock material for stiffness. This challenge is increased in hybrid manufacturing where the feature is already near net shape before machining. Significant workpiece deflection can result in poor geometric and surface finish tolerances on the finished part. A potential solution to this problem is to implement sacrificial support structures to the as-printed geometry. The supports are then machined away during the finishing portion of the hybrid process. In the present work, several different design parameters for these sacrificial supports were evaluated to determine their impact on the quality of representative thin wall geometry samples. The angle, height, and spacing of triangular support structures were varied for each sample and then machined and examined. The addition of these supports relative to an unsupported configuration provided a deflection reduction of around 0.2 mm. Surface roughness was improved by approximately 1.5 µm. Increasing values of support height were found to correspond to reduced wall deflection. Similarly, decreasing values of support angle and support spacing improved geometric accuracy. Efficiency comparisons showed that increases in print time corresponded to rapidly diminishing gains in geometric accuracy but continued to improve surface roughness. Implications for hybrid finishing of additively manufactured thin-walled structures is briefly discussed.

36 MATERIALS SCIENCE↗

DOE OSTI2025

SpecDis: Value Added Distance Catalog for 4 Million Stars from DESI Year-1 Data

We present the SpecDis value-added stellar distance catalog accompanying DESI Data Release 1. SpecDis trains a feed-forward neural network (NN) with Gaia parallaxes and gets the distance estimates. To build up an unbiased training sample, we do not apply selections on parallax error or signal-to-noise (S/N) of the stellar spectra, and instead, we incorporate parallax error into the loss function. Moreover, we employ principal component analysis to reduce the noise and dimensionality of stellar spectra. Validated by independent external samples of member stars with precise distances from globular clusters, dwarf galaxies, stellar streams, combined with blue horizontal branch stars, we demonstrate that our distance measurements show no significant bias up to 100 kpc, and are much more precise than Gaia parallax beyond 7 kpc. The median distance uncertainties are 23%, 19%, 11%, and 7% for S/N < 20, 20 ≤ S/N < 60, 60 ≤ S/N < 100, and S/N ≥ 100. Selecting stars with ${\mathrm{log}}\,g\lt 3.8$ and distance uncertainties smaller than 25%, we have more than 74,000 giant candidates within 50 kpc of the Galactic center and 1500 candidates beyond this distance. Additionally, we develop a Gaussian mixture model to identify unresolvable equal-mass binaries by modeling the discrepancy between the NN-predicted and the geometric absolute magnitudes from Gaia parallaxes and identify 120,000 equal-mass binary candidates. Our final catalog provides distances and distance uncertainties for >4 million stars, offering a valuable resource for Galactic astronomy.

astronomy data analysis↗

DOE OSTI2021

Dynamic Properties of FeCrMnNi, a High Entropy Alloy

High entropy alloys (HEAs) represent a new class of materials that potentially possess an ideal combination of high strength and ductility and may be candidate materials that can withstand high amounts of damage before failure, especially under extreme conditions. To this end, a series of shock/spall loading experiments were conducted on an Fe/Cr/Mn/Ni HEA to assess not only its equation of state (EOS) but also its resistance to damage and failure. A single-stage light gas gun was used to conduct a series of flyer plate symmetric impact experiments coupled with recovery of the samples for post-mortem microstructural analysis to obtain fundamental understanding regarding the damage morphology. Our results show that the measured EOS for this alloy was in reasonable agreement with an estimated Hugoniot value. Additionally, the spall strength of these alloys was found to vary between 1.4 and 1.9 GPa within the same plate but was comparable to other iron-based conventional alloys. DOE/NV/03624--1059

36 MATERIALS SCIENCE↗

DOE OSTI2021

Fractionation of Oxygen Isotopes in Uranium Oxides during Peroxide Precipitation and Dry Air Calcination

The interaction between uranium and oxygen-containing substrates is nearly ubiquitous within the nuclear fuel cycle. Given the well-known and predictable oxygen stable isotope compositions of atmospheric oxygen and meteoric waters around the world, the use of these isotopes as a potential geolocation or processing signature of uranium compounds has been of interest within the nuclear safeguards community. This study focuses on measuring the oxygen-stable isotope composition of synthetically produced uranium oxides to determine the mechanism and extent of fractionation during materials processing relevant to the nuclear fuel cycle. Here, metastudtite [UO 2 O 2 (H 2 O) 2 ] samples were first produced using water and hydrogen peroxide of a known oxygen isotope composition. This starting material was calcined in dry air at temperatures ranging from 300 °C to 1000 °C for 20 h producing oxides ranging in composition from UO 3 +x (0 ≤ x ≤ 0.5) to U 3 O 8 . In addition, calcinations between 500 and 800 °C were performed at different time intervals to evaluate the rate of isotopic equilibration. The δ 18 O values of water bound to metastudtite were measured by thermogravimetric analysis coupled to isotope ratio infrared spectroscopy (TGA–IRIS). A redesigned fluorination manifold was constructed at the University of Utah and was used to extract the bulk oxygen from precipitated and calcined products using bromine pentafluoride (BrF 5 ). Mineralization water on metastudtite (measured by TGA–IRIS) was closely associated with the aqueous environment of precipitation with a fractionation of +3.5 ± 0.6‰. In contrast, bulk oxygen from metastudtite (measured by fluorination and gas chromatography combined with isotope ratio mass spectrometry) was found to have an inconsistent fractionation with precipitation water. Samples calcined in dry air exhibited a wide range of oxygen isotope compositions which increased from δ 18 O = +1.4 ± 0.9‰ at 300 °C to +17.3 ± 0.9‰ at 1000 °C. This variation in δ 18 O values was a result of oxygen exchange with atmospheric O 2 and was found to be rapid at calcination temperatures greater than 600°C—with equilibration occurring in less than 2 h. These results provide insights into the incorporation and exchange of oxygen isotopes during precipitation and calcination processes comparable to those employed within the nuclear fuel cycle and establish a foundation for future investigations to build upon.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2022

Fracture toughness and crack propagation in LX-17 and PBX 9502 insensitive high explosives

High explosive materials, and in particular insensitive high explosive (IHE) materials, are of significant interest. TATB-based LX-17 and PBX 9502 are two IHE’s and mechanical properties are an important metric of performance. In this work we present, for the first time, a study of fracture as a function of temperature and displacement rate and starter crack length on billet pressed IHE materials using a standard three point bend technique. We demonstrated that the technique can yield consistent results over time by measuring samples from the same lots 4 years later and observed that the fracture toughness of LX-17 and PBX 9502 are similar. We also determined the temperature dependence for different starter crack lengths and found that the fracture toughness generally decreases with larger starter crack sizes and temperatures. For the LX-17, where a wide temperature range of -60 C to 50 C was investigated, the impact of temperature on fracture toughness between -20 C and 23 C was less than expected. For the PBX 9502 we observed the difference in fracture toughness values between -20 C and 23 C did depend on the particular lot, and also there was a tendency of the fracture toughness to scale with the tensile strength. We also investigated the effect of a lower displacement rate and observed that while the impact on the fracture toughness was relatively small, the samples surprisingly did not break (fail) after exceeding the peak load. We took advantage of this to perform x-ray computed tomography (CT) of the samples to image crack propagation in the intact samples. We observed that cracks were generally straight and unaffected by the microstructure in the LX-17, in contrast to the PBX 9502 where the direction of the cracks would frequently change and were likely influenced by the underlying microstructure.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Quantifying replication through repeated analysis of UVM-A, a liquid reference material for cosmogenic 10 Be and 26 Al studies

In this study, in-situ produced cosmogenic nuclide sample preparation and analysis is a complicated, multi-step process with numerous possible sources of error, many of which have not been robustly quantified. Here, we use a liquid reference material (UVM-A) to test whether the analytic precision associated with individual isotopic ratios (n = 96) measured at two Accelerator Mass Spectrometry facilities (Lawrence Livermore National Laboratory and Purdue Rare Isotope Measurement Laboratory) accurately represents the range of values determined for aliquots prepared in a single laboratory over a period of five years. We find that 10 Be/ 9 Be ratios measured at the different accelerator facilities (n = 26 and n = 70) have statistically indistinguishable central tendencies, matching to within 0.1 %. Based on this large dataset, we suggest preliminary consensus values for UVM-A of 1.45 ± 0.06 x 10 -13 for 10 Be/ 9 Be (mean, one standard deviation, n = 96) and 4.47 ± 0.22 x 10 -13 for 26 Al/ 27 Al (mean, one standard deviation, n = 27). For both 10 Be/ 9 Be and 26 Al/ 27 Al, the relative standard deviations of the measured ratios are similar to the reported analytic uncertainties of sample measurement, suggesting that sample preparation introduced little if any additional scatter beyond the uncertainty of isotopic analysis. This dataset demonstrates that robust sample preparation and measurement can generate isotope ratio data reproducible at the level of counting statistics.

58 GEOSCIENCES↗

DOE OSTI2025

Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection

Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection Description This dataset contains input and output data for the manuscript Mongird, K. et al. (under review) titled "Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection". Input data corresponds to gridded spatial siting attributes that are necessary to conduct a random forest machine learning analysis of siting feature importance. Output data includes SHAP feature analysis outputs, and classification report values. For data on power plant siting results referred to in the manuscript, please refer to the CERF: IM3 Projected Western US Power Plant Locations data download page. The downloadable data includes values for eight different future scenarios for the Western US. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States (see, https://tgw-data.msdlive.org/). These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 Technical Information The dataset includes two sets of data files: (1) CERF gridded siting parameters and (2) Feature analysis outputs and classification reports. All downloadable data is in csv file format. Files with x/y coordinate information use the Albers Equal Area Conic projection (ESRI:102003). 1. CERF Gridded Siting Parameters This directory provides a balanced sample of gridded CERF siting parameters data for eight different scenarios for the Western US through 2055, seven different technologies, and eight timesteps. This data serves as input to the feature analysis. It contains the following parameters. region_name - name of region (i.e., state) sited - binary value representing whether the grid cell received a siting of that technology type (1=True) rcp - binary value representing scenario resource concentration pathway (0 = RCP4.5, 1 = RCP8.5) ssp - binary value representing scenario shared socioeconomic pathway (0 = SSP3, 1 = SSP5) climate - binary value representing cooler (0) or hotter (1) GCM forcing tech_name - generation technology name sited_year - year that values correspond to transmission_cost - cost of transmission interconnection pipeline_cost - cost of natural gas pipeline interconnection interconnection_cost - total interconnection cost (sum of transmission cost and gas pipeline cost) lmp - associated locational marginal value ($/MWh) associated with the grid cell, timestep, scenario, and technology xcoord - x-coordinate of location ycoord - y-coordinate of location 2a. Feature Analysis Output The dataset includes the feature analysis shap output for locational marginal price and interconnection cost. It contains the following parameters. technology - generator technology name scenario - name of scenario feature - name of feature, either locational_marginal_price or interconnection_cost value - the mean of absolute value of SHAP values for given feature 2b. Feature Analysis Classification Report This download includes the classification report associated with each random forest model. The dataset contains the following parameters. technology - generation technology name scenario - name of scenario test - one of precision (the proportion of predicted positives that are actually correct), recall (the proportion of actual positives that were correctly identified), f1-score (the harmonic mean of precision and recall) 0.0 - value of test for classification of 0 (grid cell not chosen for siting) 1.0 - value of test for classification of 1 (grid cell chosen for siting) accuracy - accuracy of model (i.e., fraction of all predictions that were right) macro avg - Simple average of test values for all classes weighted avg - Weighted average of test values for all classes, weighted based on Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗

DOE OSTI2025

Oxygen stable isotopes in the nuclear fuel cycle: Assessment of the potential for determining the fabrication and provenance history of anhydrous and hydrous uranium oxides

Determining the origin and history of interdicted nuclear materials is a central challenge in nuclear forensics. The oxygen stable isotope composition of uranium oxide compounds has emerged as a promising forensic signature, attracting increasing attention since the early 2000s. This review examines analytical techniques for measuring oxygen isotope compositions in uranium oxides and evaluates how the nuclear fuel production cycle introduces or modifies these isotopic signatures. The potential for forensic geolocation is explored through workflows that calibrate the relationship between environmental water oxygen isotopes and those found in uranium oxides. Key strengths and limitations of this approach are assessed, including gaps in knowledge related to isotope fractionation during specific stages of the fuel cycle, and processing facility water inputs. The importance of proper sample handling and storage under inert atmospheres, as well as a deeper understanding of both intra-sample oxygen isotope heterogeneity, and hydrous uranium oxide phase formation, is highlighted for improving the reliability of forensic interpretations. In conclusion, the development of uranium oxide standards with well-characterized δ 18 O values and international collaboration toward consensus on their use are identified as essential steps for advancing the field.

Attribution↗

DOE OSTI2021

Potassium isotopic fractionation in a humid and an arid soil–plant system in Hawai‘i

Plants play a critical role in the cycling of potassium (K) and the fractionation of its isotopes. However, little is known about K stable isotopic compositions in natural soil–plant systems and possible fractionation during intra-plant transport and root-soil uptake of K. Herein this study focuses on K isotopic fractionation within a humid and an arid soil–plant system sampled on the windward and leeward sides of Kohala Mountain, Hawai‘i. We determined the K isotopic compositions of < 2-mm bulk soil, soil saturation extraction, and selected plant tissues by multi-collector inductively coupled plasma mass spectrometry and X-ray absorption spectroscopy. We studied soils and individual tissue samples such as roots, stems, barks, shoots (a sum of stems and fresh leaves), leaves (fresh and dead), seeds, and flowers of trees and grasses. The results demonstrated that: (i) tissue δ 41 K values ranged from –1.06 ± 0.06 to 1.15 ± 0.09‰; (ii) within the same plant, stems (barks), dead leaves, and reproductive tissues (flowers and seeds) were isotopically lighter compared to fresh leaves, and to a lesser extent, roots; (iii) δ 41 K values of the humid soil (-0.54 ± 0.07 to –0.49 ± 0.06‰) were lower than those of the arid soil (-0.24 ± 0.07 to –0.14 ± 0.06‰); and (iv) soil bioavailable pool δ 41 K (saturation extracts) ranged from –0.63 ± 0.08 to 0.34 ± 0.08‰ and 0.48 ± 0.08 to 0.54 ± 0.10‰ in the humid and arid soils, respectively. From synchrotron-based analysis of K atoms, we identified two major K-bearing phases co-existing as ionic K + and K-pectate association of different fractions. Based on K isotopic and synchrotron data, we conclude that two dominant processes are responsible for plant-mediated K isotopic fractionation, including (1) K redistribution during intra-plant circulation and (2) uptake at the root-soil interface. For intra-plant circulation of K, there is a high affinity of isotopically lighter K to organic complexes as K-pectate, and K-pectate is particularly enriched in roots and fresh leaves. For K uptake at root-soil interface, isotopically lighter K is preferentially taken by roots from soil bioavailable pools following a low-affinity (passive) transport path. Soil K budget in two sites reflects strong source mixing effects with limited plant imprints. This work provides exploratory data on the biogeochemical fractionation of K isotopes in the soil–plant system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

High-resolution modeling of indoor radon exposure with uncertainty quantification in Utah

Indoor radon accounts for 37% of population-level exposure to ionizing radiation in the United States. However, radon metrics are typically reported at coarse spatial scales, potentially obscuring meaningful local variation. We developed a high-resolution modeling framework to estimate indoor radon concentrations across Utah while explicitly quantifying predictive uncertainty. A total of 19,497 residential radon measurements collected between 2006 and 2017 were combined with environmental and housing characteristics and analyzed using a geospatial neural network that accommodates spatial dependence and nonlinear associations. Predictions were generated on a uniform hexagonal grid at 0.73 km2 resolution (H3 level 8). Out-of-sample predictions aggregated to the H3 level 8 grid showed good agreement with observed concentrations (Pearson r=0.64), while household-level predictions exhibited more moderate agreement (r=0.45). The model produced well-calibrated uncertainty estimates, with 24.1% of held-out observations exceeding the predicted 75th-percentile threshold. Maps of predicted radon concentrations and the probability of exceeding the U.S. EPA action level of 148 Bq/m3 (4 pCi/L) revealed substantial fine-scale spatial heterogeneity that was not apparent in conventional coarse-resolution summaries, with greater local variability observed in densely monitored urban counties than in sparsely sampled regions. High-resolution radon models that explicitly quantify uncertainty provide a useful framework for characterizing the spatial distribution of indoor radon and identifying areas of elevated exceedance risk. These findings highlight the value of fine-scale monitoring data and uncertainty-aware modeling approaches for radon exposure assessment, environmental risk characterization, and radon-related health research.

Wu, Yunhan [ORNL] (ORCID:0000000178842994)↗

DOE OSTI2024

A Review of Online Monitoring within Used Nuclear Fuel Recycling Processes

The processing of used nuclear fuels and related materials is often complex and variable. The ability to quickly optimize conditions to the material being processed can aid in increasing efficiency and safety, but requires very quick determination of the conditions present in the feedstock, the process, and the product. Furthermore, accurate quantification of materials such as enriched uranium and plutonium aids in maintaining material accountancy and avoiding nuclear proliferation risks. Traditional analytical methods require process samples to be collected and analyzed in a laboratory, which often takes days to weeks. Online monitoring is suitable for collecting this information nearly instantaneously, enabling much faster optimization of the process or detection of material diversion. Online monitoring is also beneficial as it is typically based on robust and nondestructive analytical methods, so no material is removed as samples. This review examines online monitoring relevant to used nuclear fuel processing for the determination of both chemical and physical parameters. The chemical parameters include quantities such as concentration, isotopic composition, and speciation. These values are often well suited to spectroscopic or spectrometric measurements as they are fast, nondestructive, and easily implemented in an online manner. Physical quantities are often more varied and include temperature, pressure, tank fill levels, and others. Due to the specificity of these quantities, specialized instrumentation is often used. However, this instrumentation is often amendable to online monitoring.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Exploration of structure-activity relationships for the SARS-CoV-2 macrodomain from shape-based fragment linking and active learning

The macrodomain of severe acute respiratory syndrome coronavirus 2 nonstructural protein 3 is required for viral pathogenesis and is an emerging antiviral target. We previously performed an x-ray crystallography–based fragment screen and found submicromolar inhibitors by fragment linking. However, these compounds had poor membrane permeability and liabilities that complicated optimization. Here, we developed a shape-based virtual screening pipeline—FrankenROCS. We screened the Enamine high-throughput collection of 2.1 million compounds, selecting 39 compounds for testing, with the most potent binding with a 130 μM median inhibitory concentration (IC 50 ). We then paired FrankenROCS with an active learning algorithm (Thompson sampling) to efficiently search the Enamine REAL database of 22 billion molecules, testing 32 compounds with the most potent binding with a 220 μM IC 50 . Further optimization led to analogs with IC 50 values better than 10 μM. This lead series has improved membrane permeability and is poised for optimization. FrankenROCS is a scalable method for fragment linking to exploit synthesis-on-demand libraries.

Science & Technology - Other Topics↗

DOE OSTI2024

Learning Only on Boundaries: A Physics-Informed Neural Operator for Solving Parametric Partial Differential Equations in Complex Geometries

Recently, deep learning surrogates and neural operators have shown promise in solving partial differential equations (PDEs). However, they often require a large amount of training data and are limited to bounded domains. In this work, we present a novel physics-informed neural operator method to solve parameterized boundary value problems without labeled data. By reformulating the PDEs into boundary integral equations (BIEs), we can train the operator network solely on the boundary of the domain. This approach reduces the number of required sample points from $O(N^d)$ to $O(N^{d-1}$), where $d$ is the domain’s dimension, leading to a significant acceleration of the training process. Additionally, our method can handle unbounded problems, which are unattainable for existing physics-informed neural networks (PINNs) and neural operators. Finally, our numerical experiments show the effectiveness of parameterized complex geometries and unbounded problems.

97 MATHEMATICS AND COMPUTING↗