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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

Eliminating chemo-mechanical degradation of lithium solid-state battery cathodes during >4.5 V cycling using amorphous Nb2O5 coatings

Abstract Lithium solid-state batteries offer improved safety and energy density. However, the limited stability of solid electrolytes (SEs), as well as irreversible structural and chemical changes in the cathode active material, can result in inferior electrochemical performance, particularly during high-voltage cycling (>4.3 V vs Li/Li + ). Therefore, new materials and strategies are needed to stabilize the cathode/SE interface and preserve the cathode material structure during high-voltage cycling. Here, we introduce a thin (~5 nm) conformal coating of amorphous Nb 2 O 5 on single-crystal LiNi 0.5 Mn 0.3 Co 0.2 O 2 cathode particles using rotary-bed atomic layer deposition (ALD). Full cells with Li 4 Ti 5 O 12 anodes and Nb 2 O 5 -coated cathodes demonstrate a higher initial Coulombic efficiency of 91.6% ± 0.5% compared to 82.2% ± 0.3% for the uncoated samples, along with improved rate capability (10x higher accessible capacity at 2C rate) and remarkable capacity retention during extended cycling (99.4% after 500 cycles at 4.7 V vs Li/Li + ). These improvements are associated with reduced cell polarization and interfacial impedance for the coated samples. Post-cycling electron microscopy analysis reveals that the Nb 2 O 5 coating remains intact and prevents the formation of spinel and rock-salt phases, which eliminates intra-particle cracking of the single-crystal cathode material. These findings demonstrate a potential pathway towards stable and high-performance solid-state batteries during high-voltage operation.

Science & Technology - Other Topics↗

DOE OSTI2024

The effect of gamma ray irradiation on few layered MoSe2: A material for nuclear and space applications

In recent years, emerging two-dimensional (2D) materials, such as molybdenum diselenide (MoSe2), have been at the center of attention for many researchers. This is due to their unique and fascinating physicochemical properties that make them attractive in space and defense applications that include shielding harsh irradiation environments. In this study, we examined the effects of gamma (γ) rays at various doses on the structural, chemical, and optical properties of MoSe2 layers. After the samples were exposed to intense gamma radiation (from a 60Co source) with various exposure times to vary the total accumulated dosage (up to 100 kGy), Raman and photoluminescence spectroscopies were used to study and probe radiation-induced changes to the samples. When compared to pristine materials, very few changes in optical properties were typically observed, indicating good robustness with little sensitivity, even at relatively high doses of gamma radiation. The imaging using scanning electron microscopy revealed a number of nano-hillocks that were connected to substrate alterations. X-ray photoelectron spectroscopies revealed that Mo’s binding energies remained the same, but Se’s binding energies blueshifted. We associated this shift with the decrease in Se vacancies that occurred after irradiation as a result of Mo atoms creating adatoms next to Se atoms. When compared to pristine materials, very few changes in optical, chemical, and structural properties were typically observed. These findings highlight the inherent resilience of MoSe2 in hostile radioactive conditions, which spurs additional research into their optical, electrical, and structural characteristics as well as exploration for potential space, energy, and defense applications.

Materials Science↗

DOE OSTI2026

The impact of metastability on the high-pressure behavior of cerium

The structures adopted by solids under pressure are often assumed to reflect thermodynamic equilibrium, yet in many materials phase selection is strongly influenced by kinetic pathways and microstructural inheritance. Elemental cerium (Ce) exemplifies this challenge, with decades of conflicting reports describing different high-pressure crystal structures emerging under nominally identical conditions. Here we use neutron diffraction from large ( ~ 60 mm 3 ) sample volumes to follow the structural evolution in ultra-high-purity Ce during controlled pressure-temperature cycling between 85 and 295 K and up to 8 GPa. We find that the crystal structure formed at high pressure depends on the compression pathway: slow compression ( ~ 0.25 GPa hr −1 ) at room temperature favors an orthorhombic phase (α'), whereas slow ( ~ 0.25 GPa hr −1 ) and also moderately faster ( ~ 0.5 GPa hr −1 ) compression at low temperature stabilizes a pure monoclinic phase (α"). The low-temperature phase persists metastably over a wide temperature range but transforms irreversibly upon heating above ~ 280 K, or modest pressure cycling. Remarkably, the lower-pressure γ phase remains trapped far beyond the expected stability field, persisting to the highest pressures studied. These observations show that phase selection in Ce is governed by kinetics and microstructural memory rather than equilibrium thermodynamics or sample morphology alone, establishing path dependence as a defining feature of its high-pressure behavior.

Ridley, Christopher J. [Oak Ridge National Laborat↗

DOE OSTI2026

Metrology for femtosecond pulsed x-ray heating in diamond anvil cell experiments at the European XFEL: Revisiting the iron phase diagram up to 150 GPa

The development of pulsed intense x-ray sources, such as free electron laser, offers new avenues for high pressure experiments. Here, we study the feasibility and metrology of x-ray heating in diamond anvil cells at the European x-ray free electron laser. This method enables one to volumetrically heat the sample while inhibiting chemical migration and probing the crystallographic structure of the sample throughout the heating with a high repetition rate. We focus our study on iron, whose phase diagram is well established up to 100 GPa, to explore the possibilities and limitations of this technique. We volumetrically heat iron samples at starting pressures ranging from 10 to 138 GPa, using the x-ray beam pulsed at 4.5 MHz in a serial pump-and-probe experimental design. Experimental challenges arise from temperature gradients within the sample, changes in temperature at the 100 ns timescale, the difficulty of direct temperature estimates, the effect of thermal pressure, and the presence of metastable crystallites due to rapid cycles of heating and cooling. Hence, we develop a multi-crystal-like data processing method that allows us to account for sample heterogeneity in probed conditions. We then calibrate our measurements using known physical properties of iron under pressure. Thermal pressure in our experiments increases from 4% of the isochoric prediction at 10 GPa to 23% at 138 GPa, and we show that our data are in agreement with most previous observations of iron in this pressure range. The method can now be implemented at higher pressures and temperatures and on materials with unknown phase diagrams.

Materials science↗

DOE OSTI2026

Dielectric Spectroscopy Cable NDE for Unequal Aging Over Different Lengths

This Pacific Northwest National Laboratory milestone report assesses the effect of unequal aging over different lengths of cable on dielectric spectroscopy (DS) bulk impedance measurements from the cable end. DS measurements can indicate the remaining useful life of cables; however, most benchmark tests are based on accelerated aging of the entire cable. If only a portion of the cable is exposed to a harsh environment (as is frequently the case), the DS measurement will indicate a significantly less-aged cable than if the entire cable were exposed to a uniform environmental stress. The DS measurement is primarily related to the intrinsic insulation material relative permittivity—typically between 1.5 and 3.0. Insulation aging increases permittivity and, correspondingly, the cable’s overall capacitance measured from the cable end. To judge the health of the overall cable system, operators are primarily interested in the condition of the most severely aged section since that is where a failure is most likely to occur. This can be expressed as the dimensionless relative permittivity of the severely aged section divided by the permittivity of a pristine cable. This relative permittivity is an intrinsic material parameter independent of cable length and can serve as a quantitative indication of the insulation condition. If the relative percentages of cable exposed to a harsh and benign environment are known, the DS measurement of the entire cable length, including both pristine and aged sections, can be compensated to predict the relative permittivity (relative to pristine permittivity) of the most severly aged segment. A test was performed on three 50 ft (16 m) cables with 10%, 50%, and 90% of the cable inside a thermal aging oven. Predictably, the aging effect on the DS response was greatest in the 90% sample, followed by the 50% sample, and then the 10% sample. The more interesting result is the ratio of the aged insulation permittivity to the pristine insulation permittivity. Based on prior work, an end-of-life cable has a value of approximately 1.35. If the relative percentages of pristine and severely aged cable lengths are known, and the total cable-length capacitance of the initial pristine cable and the combined pristine plus aged cable are known, the relative aged permittivity (ratio of aged section permittivity / pristine section permittivity) can be estimated. The relative cable lengths exposed to a harsh environment may be known or estimated based on plant layout drawings or cable reflectometry tests that can locate the oven entry and exit points. The compensation was verified using a lumped-parameter model to predict the aged-segment permittivity e2/e1, where e2 is the aged-segment permittivity and e1 is the pristine-segment permittivity. For all three percentages of aged cable lengths, the ratio was quite similar, as would be expected since all cable segments were exposed to the same aging environment. This ratio of aged permittivity to pristine permittivity can be compared to other damage indicating tests, including elongation at break, to assess cable condition.

ARENA Test Bed↗

DOE OSTI2026

A Tutorial on Bayesian analysis of linear shock compression data

Gas gun and other shock compression experiments often produce shock wave velocity measurements that are linearly associated with particle velocity. Traditionally, this empirical relationship is quantified with a single Hugoniot curve that is estimated using least squares regression. However, for downstream modeling and simulation tasks, it is often more useful to have multiple Hugoniot curves in the pressure–volume plane that are consistent with the data. We employ Bayesian uncertainty quantification methods as a framework for propagating measurement uncertainty through to model parameters and predictions. Specifically, this Tutorial shows how to sample multiple Hugoniot curves in the pressure–volume plane that are consistent with the shock wave-particle velocity measurements in a two-step Bayesian approach. First, we obtain an analytical expression for the posterior distribution of the linear model parameters using Bayesian linear regression. Second, we propagate samples from the posterior distribution through the Rankine–Hugoniot equations to yield Hugoniot curves in the pressure–volume plane. The procedure is demonstrated with publicly available data on argon, copper, and nickel, and compared against bootstrapping and linear regression. The Bayesian procedure is shown to be interpretable, computationally inexpensive, and less sensitive than an alternative bootstrapping approach to the removal of the point in the copper dataset that has the largest particle velocity. As a Tutorial on Bayesian methodology for the shock compression community, we provide several derivations and explanations that make this paper self-contained, and make all code and data available at github.com/llnl/BALSCD.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Growth of deuterium supersaturated surface layer with increasing ion flux and fluence in plasma-exposed tungsten

Deuterium supersaturated surface layer (DSSL) in tungsten, a few nm thick layer exhibiting extremely high deuterium content (> 5%), has been studied as a function of deuterium plasma ion flux and fluence. Tungsten samples were exposed at 400 K and deuterium ion energy of ∼ 60 eV. The deuterium ion flux spanned over an order of magnitude, being 7.3 × 10 20 , 4.2 × 10 21 , and 3.8 × 10 22 D/m 2 . The fluence ranged from 3.4 × 1024 to 3.4 × 1025 D/m2. The samples and their deuterium content were analyzed by nuclear reaction analysis (NRA), scanning transmission electron microscopy (STEM), and thermal desorption spectroscopy (TDS). The largest thickness of DSSL was found to be around 10.5 nm and was observed in the case of the highest exposure flux and fluence, whereas the layer was only about 3.8 nm thick in the case of the lowest value of the two parameters. The thickness of the DSSL was found to monotonically increase with both deuterium flux and fluence. Finally, similar to the thickness, the estimated D concentration seems to follow the same trend, increasing from the lowest value of around 3 at.% to the highest value of around 5 at.%.

Deuterium↗

DOE OSTI2024

The first high-redshift cavity power measurements of cool-core galaxy clusters with the International LOFAR Telescope

Radio-mode feedback associated with the active galactic nuclei (AGNs) at the cores of galaxy clusters injects a large amount of energy into the intracluster medium (ICM), offsetting radiative losses through X-ray emission. This mechanism prevents the ICM from rapidly cooling down and fueling extreme starburst activity as it accretes onto the central galaxies, and it is therefore a key ingredient in the evolution of galaxy clusters. However, the influence and mode of feedback at high redshifts (z ∼ 1) remains largely unknown. Low-frequency sub-arcsecond-resolution radio observations taken with the International LOFAR Telescope have demonstrated their ability to assist X-ray observations with constraining the energy output from the AGNs (or “cavity power”) in galaxy clusters, thereby enabling research at higher redshifts than before. In this pilot project, we tested this hybrid method on a high-redshift (0.6 < z < 1.3) sample of 13 galaxy clusters for the first time with the aim of verifying the performance of this method at these redshifts and providing the first estimates of the cavity power associated with the central AGN for a sample of distant clusters. We were able to detect clear radio lobes in three out of 13 galaxy clusters at redshifts of 0.7 < z < 0.9, and we used these detections in combination with ICM pressures surrounding the radio lobes obtained from standard profiles to calculate the corresponding cavity powers of the AGNs. Combining our results with the literature, the current data appear to suggest that the average cavity power peaked at a redshift ofz ∼ 0.4 and slowly decreases toward higher redshifts. However, we require more and tighter constraints on the cavity volume and a better understanding of our observational systematics to confirm any deviation of the cavity power trend from a constant level.

Astronomy & Astrophysics↗

DOE OSTI2026

Compositional Homogeneity in Rapidly Solidified 316L stainless steel produced by laser powder-bed fusion processing

The segregation of alloying elements in rapidly solidified 316L stainless steel produced using additive manufacturing technologies is widely reported throughout literature. The microstructure of thin walls manufactured from 316L stainless steel using laser powder bed fusion are examined for the presence of alloy segregation, i.e. the rejection of solutes to grain boundaries. Metallographic methods including mechanical polishing and chemical etching are used to prepare samples for microanalysis m

Jankowski, Alan F. [Sandia National Laboratories (↗

DOE OSTI2026

How efficiently can AI recognize Wireless Devices?

This poster presents a hardware benchmarking methodology for a 3-layer CNN waveform classifier deployed using ONNX Runtime on an NVIDIA Jetson AGX Orin. The dataset consist of 9 signal types, -30 to +30 dB SNR with 5dB increments. Benchmarking on the Jetson AGX Orin gave an accuracy of 91.9% and GPU throughput of 107,120 predictions/sec (23× faster than CPU). The Jetson GPU reached approximately 27M samples/sec with stable performance but fell below the 40 MHz rate needed for real-time radio feeds. Sustained testing of 5 minutes confirmed stable performance with no memory leaks, establishing a reproducible benchmarking baseline for future edge-deployment optimization.

99 - GENERAL AND MISCELLANEOUS↗

DOE OSTI2025

Multi-contrast machine learning improves schistosomiasis diagnostic performance

Schistosomiasis currently affects over 250 million people and remains a public health burden despite ongoing global control efforts. Conventional microscopy is a practical tool for diagnosis and screening ofSchistosoma haematobium, but identification of eggs requires a skilled microscopist. Here we present a machine learning (ML)-based strategy for automated detection ofS. haematobiumthat combines two imaging contrasts, brightfield (BF) and darkfield (DF), to improve diagnostic performance. We collected BF and DF images of urine samples, many of them containingS. haematobiumeggs, during two different field studies in Côte d’Ivoire using a mobile phone-based microscope, the SchistoScope. We then trained separate egg-detection ML models and compared the patient-level performance of BF and DF models alone to combinations of BF and DF models, using annotations from trained microscopists as the gold standard. We found that models trained on DF images, and almost all BF and DF combinations, performed significantly better than models trained on BF images only. When models were trained on images from the first field study (n = 349 patients, 748 images of each contrast), patient-level classification performance on patient images from the second study (n = 375 patients, 752 images of each contrast) met the WHO Diagnostic Target Product Profile (TPP) sensitivity and specificity for the monitoring and evaluation use case (sensitivity for all models and combinations was >75% when evaluated at a confidence score threshold that resulted in specificity >96.5%). When we used images from both field studies for the training set, performance of the models was improved. Overall, this work shows that the use of DF and BF increases the performance of ML models on images from devices with low-cost optics, while retaining the portability, power, and time-to-results of the WHO’s diagnostic TPP. DF requires no additional sample preparation and does not increase the complexity of the imaging system. It thus offers a practical means to improve performance of automated diagnostics forS. haematobiumas well as other microscopy-based diagnostics.

Infectious Diseases↗

DOE OSTI2025

First in operando transient grating spectroscopy measurements on tungsten during high flux plasma operation in PISCES-RF

This work details the construction and first in operando transient grating spectroscopy measurements conducted on PISCES-RF during plasma operation. A preliminary study on a tungsten sample with varied plasma species (Ar and D 2 ), ion flux (4 × 10 21 to 6 × 10 22 ion/m 2 /s), ion energy (5 to 80 eV), and surface temperature (20 to 200 °C) is presented. Prior to plasma exposure, the thermal diffusivity and surface acoustic wave (SAW) speed, (6.9 ± 0.2) × 10 −5 m 2 /s and (2.66 ± 0.02) km/s, were measured in situ with a thermal grating period of 12.5 μm. During Ar plasma exposure, these two quantities vary according to the sample surface temperature. At low flux and varied ion energy, D 2 plasma exposure also results in thermal diffusivity and SAW speed varying with surface temperature alone. At high flux, D 2 plasma exposure results in no convincing change to the thermal diffusivity, but the SAW speed is reduced. After returning to 20 °C, post plasma exposures, the thermal diffusivity and SAW speed almost recover to the initial value prior to exposure.

Surface acoustic wave SAW↗

DOE OSTI2026

Emergence of low-energy spin waves in superconducting electron-doped cuprates

In order to fully utilize the technological potential of unconventional superconductors, an enhanced understanding of the superconducting mechanism is necessary. In the best performing superconductors, the cuprates, superconductivity is intimately linked with magnetism, although the details of this coupling remain elusive. Here, we address this gap by studying the electron-doped cuprate Nd 1.85 Ce 0.15 CuO 4−δ that has an antiferromagnetic ground state when synthesized and only becomes superconducting after a reductive annealing process. Using neutron spectroscopy, we show that the as-grown crystal exhibits a large spin pseudogap in the magnetic fluctuation spectrum. Annealing removes defects introduced by the commonly employed synthesis method and significantly reduces the spin pseudogap. While the spin pseudogap in the annealed sample likely arises from superconductivity, in the as-grown sample it results from the absence of long-wavelength spin waves. These results reveal a direct connection between defects, magnetism, and superconductivity, offering new insight into the mechanisms underlying high-temperature superconductivity and guiding the design of improved superconducting materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2026

Structured illumination for surface-resolved grazing-incidence X-ray scattering

Grazing-incidence (GI) scattering techniques are widely used to characterize thin films, offering high surface sensitivity and insight into morphology and structure. However, these approaches typically provide statistical averaged information due to elongated footprint or limited spatial resolution due to beam size. Here we introduce a method that combines structured illumination with GI X-ray scattering and leverages our computational imaging approach to resolve local structural details. We demonstrate that our method captures local features of an organic semiconductor thin film without the need for sample rotation as in tomography. The method expands GI techniques from statistical averaging to high-resolution imaging, thereby providing the capability for detailed analysis of local material properties, such as domain shape, orientation and polymorphism, which are critical for advancing material design towards more efficient and tailored materials.

Gursoy, Doga↗

DOE OSTI2026

Constraining primordial non-Gaussianity from DESI DR1 quasars and Planck PR4 CMB lensing

We present the first measurement of local-type primordial non-Gaussianity from the cross-correlation between 1.2 million spectroscopically confirmed quasars from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI) and the Planck PR4 CMB lensing reconstructions. The analysis is performed in three tomographic redshift bins covering 0.8 < z < 3.5, covering a sky fraction of ∼20%. We adopt a catalog-based pseudo-C ℓ estimator and apply linear imaging weights validated on noiseless mocks. Compared to previous analyses using photometric quasar samples, our results benefit from the high purity of the DESI spectroscopic sample, the reduced noise of PR4 lensing, and the absence of excess large-scale power in the spectroscopic quasar auto-correlation. Fitting simultaneously for the non-Gaussianity parameter f NL and the linear bias amplitude in each redshift bin, we obtain f NL = 2 +28 -34 for a response parameter p = 1.6, and f NL = 6 +20 -24 for p = 1.0. These results improve the constraints on f NL by ∼35% compared to the previous analysis based on the Legacy Imaging Survey DR9. Additionally, we derive an optimal weighting scheme to maximize the constraining power. In this case, and assuming p = 1.6, we obtain f NL = 19 +25 -31 . Our results demonstrate the statistical power of DESI quasars for probing inflationary physics, and highlight the promise of future DESI data releases.

cosmological parameters from CMBR↗

DOE OSTI2023

Surface analysis insight note: Illustrating the effect of adventitious contamination on Pt photoemission peak intensities

Adventitious carbon contaminations are not only omnipresent and used for charge referencing of XPS spectra but also can alter the apparent presence of the element peaks that span over the large spectral window of binding energies. This Insight note describes the effect of an adventitious contamination layer on Pt and presents, in brief, the approach whereby the component spectra are derived for ion beam cleaned Pt samples that can then utilize linear mathematics to peak fit said spectra thus quantifying the amount of each component including that assigned to the contamination itself of Pt metal.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2026

Impact of Crystalline Phases on Low-Activity Waste Glass Durability: Insights from PCT and VHT

During vitrification of nuclear wastes, slow cooling along the container centerline promotes crystalline phase formation, which can alter residual glass composition and reduce chemical durability. This study investigates the effects of crystalline phases on the chemical durability of low-activity waste (LAW) borosilicate glasses using the product consistency test (PCT) and vapor hydration test (VHT) on container centerline cooled (CCC) samples. A preliminary model (R2 = 0.88) was developed to predict CCC PCT responses based on glass composition, PCT data from quenched glasses, and measured crystal fractions. Using the latest LAW glass dataset, the feasibility of predictive modeling is evaluated, limitations in current data and methods are identified, and challenges for improving model accuracy are discussed to guide future data collection and model development.

borosilicate glass↗