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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

BD+44°493: Chemo-dynamical Analysis and Constraints on Companion Planetary Masses from WIYN/NEID Spectroscopy

In this work, we present high-resolution (R ~ 100,000), high signal-to-noise ratio (S/N ~ 800) spectroscopic observations for the well-known, bright, extremely metal-poor, carbon-enhanced star BD+44°493. We determined chemical abundances and upper limits for 17 elements from WIYN/NEID data, complemented with 11 abundances redetermined from Subaru and Hubble data, using the new, more accurate, stellar atmospheric parameters calculated in this work. Our analysis suggests that BD+44°493 is a low-mass (0.83 M ⊙ ), old (12.1–13.2 Gyr) second-generation star likely formed from a gas cloud enriched by a single metal-free 20.5 M ⊙ Population III star in the early Universe. With a disk-like orbit, BD+44°493 does not appear to be associated with any major merger event in the early history of the Milky Way. From the precision radial-velocity NEID measurements (median absolute deviation = 16 m s –1 ), we were able to constrain companion planetary masses around BD+44°493 and rule out the presence of planets as small as $m\sin i=2$ M J out to periods of 100 days. This study opens a new avenue of exploration for the intersection between stellar archaeology and exoplanet science using NEID.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Examining the Robustness of Weakened Orographic Influence on Precipitation in Downscaled Climate Projections Over the Western US

Assessing local climate change impacts often requires downscaling coarse global climate model (GCM) output to finer resolution. Two main approaches exist: dynamical downscaling using high-resolution regional climate models, and statistical downscaling based on historical relationships between large-scale and local variables. In a recent analysis of five dynamically downscaled simulations over the western United States, Koszuta et al. (2024, https://doi.org/10.1029/2023gl107298) found that warming weakens orographic influence on winter precipitation, damping increases on windward slopes and amplifying them in rain-shadowed regions. Here we show that this effect is robust across seasons and multiple dynamically downscaled ensembles, and is more pronounced at higher model resolutions. However, it is absent in projections from a widely used statistical model (LOCA2), even when trained on high-resolution future simulations (LOCA2-Hybrid). This highlights a key limitation of many statistical downscaling methods: their preservation of parent GCM trends, which usually fail to capture emergent changes in orographic precipitation patterns.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

WRF-ELM v1.0: a regional climate model to study land–atmosphere interactions over heterogeneous land use regions

Abstract. The Energy Exascale Earth System Model (E3SM) Land Model (ELM) is a state-of-the-art land surface model that simulates the intricate interactions between the terrestrial land surface and other components of the Earth system. Originating from the Community Land Model (CLM) version 4.5, ELM has been under active development, with added new features and functionality, including plant hydraulics, radiation–topography interaction, subsurface multiphase flow, and more explicit land use and management practices. This study integrates ELM v2.1 with the Weather Research and Forecasting (WRF; WRF-ELM) model through a modified Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) framework, enabling affordable high-resolution regional modeling by leveraging ELM's innovative features alongside WRF's diverse atmospheric parameterization options. This framework includes a top-level driver for variable communication between WRF and ELM and Earth System Modeling Framework (ESMF) caps for the WRF atmospheric component and ELM workflow control, encompassing initialization, execution, and finalization. Importantly, this LILAC–ESMF framework demonstrates a more modular approach compared to previous coupling efforts between WRF and land surface models. It maintains the integrity of ELM's source code structure and facilitates the transfer of future developments in ELM to WRF-ELM. To test the ability of the coupled model to capture land–atmosphere interactions over regions with a variety of land uses and land covers, we conducted high-resolution (4 km) WRF-ELM ensemble simulations over the Great Lakes region (GLR) in the summer of 2018 and systematically compared the results against observations, reanalysis data, and WRF-CTSM (WRF coupled with the Community Terrestrial Systems Model). In general, the coupled WRF-ELM model has reasonably captured the spatial distribution of surface state variables and fluxes across the GLR, particularly over the natural vegetation areas. The evaluation results provide a baseline reference for further improvements in ELM in the regional application of high-resolution weather and climate predictions. Our work serves as an example to the model development community for expanding an advanced land surface model's capability to represent fully-coupled land–atmosphere interactions at fine spatial scales. The development and release of WRF-ELM marks a significant advancement for the ELM user community, providing opportunities for fine-scale regional representation, parameter calibration in coupled mode, and examination of new schemes with atmospheric feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

CHESS 2025: Orthorectified airborne RGB imagery from NEON AOP surveys

This dataset provides Level 1 (L1) and Level 3 (L3) orthorectified Red-Green-Blue (RGB) imagery collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). This high-resolution imagery is a photographic record of red, green, and blue visible light from sunlight reflected off of the Earth’s surface. The data comprise full-color images of the ground surface and are primarily intended to provide context to imaging spectroscopy and light detection and ranging (LiDAR) data. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. RGB images were acquired using the PhaseOne IXM-RS150F high-resolution digital camera onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). The package data include both an L1 product comprising one camera frame per file and an L3 mosaic aligned to the Universal Transverse Mercator (UTM) Zone 13N grid and the World Geodetic System (WGS) 84 projection. Both products are provided in geotif (.tif) format at 0.1 m ground resolution. The bulk of the imagery was collected during the main CHESS field campaign from June 13 to July 15, 2025. Additional images of a portion of the Upper Taylor (UPTA) domain were collected on September 18, 2025, to fill gaps in imagery identified after the main campaign was complete. RGB camera imagery is not radiometrically calibrated, and therefore pixel values should not be exploited for scientific analysis. Pixel values have undergone a manual adjustment to enhance feature identification. The imagery is rigorously geolocated which does allow for reliable geometric information to be retrieved. To generate the orthorectified imagery, the NEON AOP camera captured visible spectrum in red, green, and blue bands. The raw images were then processed using NEON’s camera orthorectification workflow. A boresight calibration flight was made to build a complete camera, distortion, and alignment model. Color balance/white balance and exposure correction were applied to the raw RGB images. The corrected images were orthorectified by ray-tracing image pixels to a lidar-derived digital surface model (DSM) mesh using the refined camera model, outputting orthorectified raster pixels on a regular grid. Flightline-level data were mosaicked by selecting per-pixel contributions from overlapping orthorectified images using line-of-sight (LOS) zenith angle minimization to reduce edge distortions. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2020

Ptychographic X-ray speckle tracking with multi-layer Laue lens systems

The ever-increasing brightness of synchrotron radiation sources demands improved X-ray optics to utilize their capability for imaging and probing biological cells, nano-devices and functional matter on the nanometre scale with chemical sensitivity. Hard X-rays are ideal for high-resolution imaging and spectroscopic applications owing to their short wavelength, high penetrating power and chemical sensitivity. The penetrating power that makes X-rays useful for imaging also makes focusing them technologically challenging. Recent developments in layer deposition techniques have enabled the fabrication of a series of highly focusing X-ray lenses, known as wedged multi-layer Laue lenses. Improvements to the lens design and fabrication technique demand an accurate, robust, in situ and at-wavelength characterization method. To this end, a modified form of the speckle tracking wavefront metrology method has been developed. The ptychographic X-ray speckle tracking method is capable of operating with highly divergent wavefields. A useful by-product of this method is that it also provides high-resolution and aberration-free projection images of extended specimens. Three separate experiments using this method are reported, where the ray path angles have been resolved to within 4 nrad with an imaging resolution of 45 nm (full period). This method does not require a high degree of coherence, making it suitable for laboratory-based X-ray sources. Likewise, it is robust to errors in the registered sample positions, making it suitable for X-ray free-electron laser facilities, where beam-pointing fluctuations can be problematic for wavefront metrology.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A microCT-based platform to quantify drug targeting

Abstract Background Heterotopic ossification (HO) is a frequent and debilitating complication of traumatic musculoskeletal injuries and orthopedic procedures. Prophylactic dosing of botulinum toxin type A (BTxA) holds potential as a novel treatment option if accurately distributed throughout soft-tissue volumes where protection is clinically desired. We developed a high-resolution, microcomputed tomography (microCT)-based imaging strategy to assess drug distribution and validated this platform by quantifying distribution achieved via a prototype delivery system versus a single-bolus injection. Methods We injected an iodine-containing contrast agent (iodixanol 320 mg I/mL) into dissected rabbit musculature followed by microCT imaging and analysis. To contrast the performance of distributed versus bolus injections, a three-dimensional (3D) 64-cm 3 -printed soft-tissue holder was developed. A centered 2-cm 3 volume of interest (VOI) was targeted with a single-bolus injection or an equal volume distributed injection delivered via a 3D-printed prototype. VOI drug coverage was quantified as a percentage of the VOI volume that was < 1.0 mm from the injected fluid. Results The microCT-based approach enabled high-resolution quantification of injection distribution within soft tissue. The distributed dosing prototype provided significantly greater tissue coverage of the targeted VOI (72 ± 3%, mean ± standard deviation) when compared to an equal volume bolus dose (43 ± 5%, p = 0.031) while also enhancing the precision of injection targeting. Conclusions A microCT-based imaging technique precisely quantifies drug distribution within a soft-tissue VOI, providing a path to overcome a barrier for clinical translation of prophylactic inhibition of HO by BTxA. Relevance statement This platform will facilitate rapid optimization of injection parameters for clinical devices used to effectively and safely inhibit the formation of heterotopic ossification. Key points • MicroCT provides high-resolution quantification of soft-tissue drug distribution. • Distributed dosing is required to maximize soft-tissue drug coverage. • Imaging platform will enable rapid screening of 3D-printed drug distribution prototypes. Graphical Abstract

Ausk, Brandon J. (ORCID:0000000335338303)↗
DOE OSTI2021

Distributed Fiber Sensors With High Spatial Resolution in Extreme Radiation Environments in Nuclear Reactor Cores

This paper is a comprehensive experimental report on the neutron radiation effects of distributed optical fiber sensors with enhanced Rayleigh scattering profiles in an in-pile environment. Femtosecond laser direct writing was used to inscribe Type-II modifications in standard telecom fibers and radiation-hardened fibers with fluorine-doped cores. Rayleigh backscattering signals were enhanced for continuous 1.5 m. In-pile lead-out sensors tests were carried out at the MIT Research Reactor for two months, which was operated at a nominal power of 5.7 MW with fast neutron (>0.1 MeV) flux of 1.29 × 1014 n/cm2/s and an in-core temperature of up to 560°C. Using the Optical Frequency Domain Reflectometry technique, the backscattering profiles of fiber sensors were interrogated with a 3-cm spatial resolution to monitor the temperature profile of the reactor. Results show that laser inscribed Type-II modifications in the form of nanogratings are highly stable against extreme temperature and ionizing radiation. Both standard telecom fibers and radiation-hardened fibers with laser-enhanced Rayleigh profiles can continuously perform distributed temperature measurements over the entire duration of the in-pile testing. Temperature coefficients of sensors and spectral shift quality were studied as functions of total radiation fluence. To the best of our knowledge, we present for the first time, the temperature profile of an operating nuclear reactor core with 3-cm spatial resolution, enabled by distributed fiber sensors with laser-enhanced Rayleigh scattering profiles. The high spatial resolution measurements can provide valuable data for the design and validation of digital twin and virtual reality of nuclear energy systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Systematic Evaluation of Atmospheric Forcing, Surface Datasets, and Mesh Effects on Kilometer-Scale Land Surface and River Modeling

Earth system models are advancing toward kilometer-scale resolution to capture local climate impacts and extremes. High-resolution land and river modeling depends on multiple factors, including mesh, surface datasets, and atmospheric forcing, but their relative effects at kilometer scales remain unquantified. We evaluated five Energy Exascale Earth System Model land and river configurations over the Mid-Atlantic region using two mesh (1/8° structured versus variable-resolution unstructured mesh), two surface datasets (default versus newly developed), and three atmospheric forcings (NLDAS2, MSWX, GSWP). Evaluation against satellite, reanalysis, and in situ benchmarks across water, energy, and carbon cycles quantifies how these factors affect model performance. Forcing selection produces the largest bias reductions (12-99% across variables), followed by surface datasets (7-75%) and mesh (up to 21%). Forcing effects vary by variable, with MSWX reducing biases for snow water equivalent, evapotranspiration, albedo, temperature, and gross primary productivity, GSWP for snow cover and runoff, and NLDAS for soil moisture and streamflow. The use of newly developed surface datasets improves gross primary productivity (58% bias reduction) and evapotranspiration but increase soil moisture and albedo biases due to current modeling limitations. Variable-resolution unstructured mesh improves the simulation of small-basin streamflow through better capturing drainage networks, though mesh minimally affects other land variables. These findings provide important guidance for high-resolution modeling development and actionable science.

Land and River modeling↗
DOE OSTI2020

Direct Optical Patterning of Quantum Dot Light-Emitting Diodes via In Situ Ligand Exchange

Precise patterning of quantum dot (QD) layers is an important prerequisite for fabricating QD light-emitting diode (QLED) displays and other optoelectronic devices. However, conventional patterning methods cannot simultaneously meet the stringent requirements of resolution, throughput, and uniformity of the pattern profile while maintaining a high photoluminescence quantum yield (PLQY) of the patterned QD layers. Here, a specially designed nanocrystal ink is introduced, "photopatternable emissive nanocrystals" (PENs), which satisfies these requirements. Photoacid generators in the PEN inks allow photoresist-free, high-resolution optical patterning of QDs through photochemical reactions and in situ ligand exchange in QD films. Various fluorescence and electroluminescence patterns with a feature size down to approximate to 1.5 mu m are demonstrated using red, green, and blue PEN inks. The patterned QD films maintain approximate to 75% of original PLQY and the electroluminescence characteristics of the patterned QLEDs are comparable to thopse of non-patterned control devices. The patterning mechanism is elucidated by in-depth investigation of the photochemical transformations of the photoacid generators and changes in the optical properties of the QDs at each patterning step. This advanced patterning method provides a new way for additive manufacturing of integrated optoelectronic devices using colloidal QDs.

Cho, Himchan↗
DOE OSTI2021

Super-Resolution Photothermal Patterning in Conductive Polymers Enabled by Thermally Activated Solubility

Doping induced solubility control (DISC) patterning is a recently developed technique which uses the change in polymer solubility upon doping, along with an optical dedoping process, to achieve high resolution optical patterning. DISC patterning is remarkable because the process resolution exceeds the linear Abbe’s diffraction limit, however, no mechanism has been proposed to explain such high resolution. Here, we use diffraction to spatially modulate the light intensity and determine the dissolution rate, revealing a superlinear dependence on light intensity, which yields features that are sharper than the profile of the writing photomask. This rate law is independent of wavelength, indicating that patterning resolution is not dominated by an optical dedoping reaction, as was previously proposed. Instead we show here that the optical patterning mechanism is primarily controlled by the thermal profile generated by the laser. To quantify this effect, the thermal profile and dissolution rate are modeled using a finite-element model and compared against patterned line cross sections as a function of wavelength, laser intensity, and dwell time. Our model reveals that although the laser-generated thermal profile is broadened considerably beyond the lasers resolution, the highly temperature dependent dissolution rate results in selective dissolution near the peak of the thermal profile. Therefore, the key factor in achieving super-resolution patterning is a strongly temperature dependent dissolution rate|a common feature of many polymers. In addition to suggesting several routes to improved resolution, our model also demonstrates that doping is not required for optical patterning of conjugated polymers, as was previously believed. Instead, we demonstrate that superlinear resolution optical patterning is attainable in any conjugated polymer simply by tuning the solvent quality during patterning, thus extending the applicability of our method to a wide class of materials. Here, we demonstrate the generality of photothermal patterning by writing sub-400 nm features into undoped Pff-BT4T-2OD.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Material Characterization of Grade 91 Steel Welds using, Micro-resolution Ultrasonic Imaging System

Grade 91 (9Cr-1Mo-V) steel is a common structural material for fossil-fuel fired and nuclear power plants because of its creep strength and oxidation resistance at high temperatures. In this research, we studied the feasibility of correlating the high-resolution images obtained from the immersion ultrasonic imaging technique to microstructure regions in Grade 91 steel plate weldments. The high-resolution ultrasonic images presented in this paper were generated using a 20-MHz focused transducer as the transmitter, and a laser vibrometer as the receiver in the through transmission configuration to produce longitudinal and shear waves. This nondestructive evaluation (NDE) method was used to identify the Fusion Zone (FZ), Heat-Affected Zone (HAZ), and Base Metal (BM) regions of Grade 91 cold metal transfer (CMT) and flux core arc welds (FCAW). The ultrasonic imaging results were analyzed using beam propagation amplitudes and homogeneity, which in turn were used to relate the different microstructure regions of the FCAW and CMT welded samples. With this study, we were able to identify highly susceptible microstructures in the weld that could potentially promote creep type failures.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2021

Quantifying the Solar Energy Resource for Puerto Rico

After Hurricane Maria, multiple U.S. Department of Energy laboratories studied the state of the electric grid in Puerto Rico and analyzed grid resilience and grid integration of renewable energy. As part of the work done at the National Renewable Energy Laboratory, researchers created new solar resource data, conducted a technical potential and supply curve analysis, and studied the interannual variability of the solar resource. A new methodology was developed to downscale solar resource data from the National Solar Radiation Data Base (NSRDB) from a 4-km x 4-km spatial and 30-minute temporal resolution to a 2 km x 2 km and 5-minute resolution. This methodology primarily used simple physical principles to develop high-resolution cloud properties which were then used to compute solar radiation. The high-resolution datasets were validated against ground measurements and the error metrics were found to be similar to the original lower resolution dataset. Using 20 years of downscaled data from the NSRDB multi-year capacity factors for photovoltaics (PV) were developed for both single-axis tracking and fixed latitude-tilt configurations. Use of the multi-year data provides the ability to understand variability in capacity factors due to variability in weather over a long period of time. For Puerto Rico the coastal regions were found to have significant higher capacity factors than inland. Using land-use and terrain information a technical potential analysis was conducted for Puerto Rico. This analysis restricted single PV plant development to a maximum of 100 MW nameplate capacity. The nameplate capacity for each municipality were then determined. Based on our assumptions, 56 of the 78 total municipalities of Puerto Rico contain some level of solar capacity. Most of the interior municipalities did not have any capacity because of the geographic exclusions used in this study. The lowest capacity for a PV plant observed in a municipality was 10 MW. The maximum capacity within a county was 2,000 MW. Further a supply curve analysis was conducted by taking the results of the technical potential and quantifying system and transmission costs. The levelized cost of energy (LCOE) was calculated for each theoretical PV plant site, and the levelized cost of transmission was added to the LCOE to produce a total cost estimate for each site. The results of the supply curve analysis allow for a relative comparison of the cost for integrating new PV capacity into the grid. This analysis indicates that cheaper total LCOE sites tend to be larger in capacity. The total capacity in this study was found to be far beyond the maximum peak load for the island. However, this study does not consider the economic and market potential for development. The cumulative capacity presented in this study assumes that the best locations are developed first and ignores the complex decision paths for new power plant development. Therefore, this analysis can only be treated as illustrative. Finally this study investigates the impact of inter-annual variability of resource using a variety of metrices including probability of exceedance and variation in capacity factor and LCOE. This study demonstrates that the capacity factor or LCOE could vary by over 10% year to year. This clearly indicates the risks involved in using any particular year of data and clearly points to the use of multi-year data to reduce some of the risks related to variability in weather.

14 SOLAR ENERGY↗
DOE OSTI2026

Using 2.5D super-resolution to improve flaw detection in metal additive manufacturing parts

Industrial X-ray computed tomography (XCT) enables non-destructive inspection of additively manufactured (AM) parts, but high-resolution scanning requires long acquisition times and significant computational resources, limiting throughput in production environments. Super-resolution techniques can recover high-resolution information from low-resolution scans, but existing methods face a trade-off between 2D approaches that ignore inter-slice information and 3D methods that are computationally prohibitive for practical deployment. To address this trade-off, we propose a 2.5D deep learning-based super-resolution approach that uses seven neighbouring low-resolution slices to super-resolve the centre slice. This work evaluates the method on real XCT scans of steel AM parts, comparing reconstruction quality and flaw detection performance of 2D, 2.5D, and 3D ESRGAN-based super-resolution methods. Results demonstrate that 2.5D super-resolution significantly improves detection of small, process-induced flaws (e.g. porosity) compared to 2D methods, while avoiding the prohibitive computational burden of full 3D approaches. These findings provide initial evidence of 2.5D super-resolution as a practical, deployable solution for improving flaw detection in high-throughput industrial XCT inspection.

X-ray CT↗
DOE OSTI2020

Advanced High-Performance Computational Modeling of the Seismic Response of High-Hazard and/or Nuclear Facilities and Critical Infrastructure at the NNSS

New methods for predicting the amplitude and variability of ground shaking from earthquakes (and explosions) are needed for seismic hazard analysis for buildings, nuclear power plants, and critical infrastructure at the NNSS. We are comparing existing 1-D and new 3-D geophysical methods for estimating the shear-wave velocity structure in the upper 30 meters of the ground surface (Vs30), which plays a major role in ground motion amplification and seismic response of buildings. We evaluate the performance of these methodologies at the U1a Complex at the NNSS and develop simple 1-D and high-resolution 3-D Vs30 models. We then emplace these high-resolution models into a background seismic velocity model. We will collaborate with Lawrence Livermore National Laboratory (LLNL) to conduct numerical modeling of the ground shaking at the NNSS using their high-performance computing technology and state-of-the-art ground motion simulation methodology. The primary work that was completed in FY 2019 was to acquire the seismic systems and familiarize staff at the NNSS with their use. We also worked on developing a collection plan with the Device Assembly Facility (DAF) at the NNSS, but due to time constraints and other ongoing projects at the DAF, we had to use U1a as a backup. We were able to coordinate the seismic survey, and we will complete the collection of seismic data in FY 2020. Additionally, during FY 2019, we completed the geologic framework model (GFM) for the U1a Complex and modeled the Yucca fault. LLNL worked with us through FY 2019 to prepare the data files for their modeling software and tested the software for reliability. In FY 2020 we will develop the end-to-end capability so that any facility could easily be modeled and the expected shaking from a local earthquake understood. The work in FY 2020 will include building fault models from the GFM and finalizing the velocity model analysis. The final simulations will be run for multiple rupture models, and final assessments will demonstrate the seismic hazard at the U1a Complex.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Interior soft x-ray tomography with sparse global sampling

To investigate the feasibility of interior imaging reconstruction in soft X-ray tomography for higher-resolution cellular imaging, including whole-cell imaging, we develop an alignment and reconstruction algorithm that combines a small number of sparse whole-cell images with a high-resolution local interior scan. Based on numerical simulations, we demonstrate that combined reconstructions mitigate the depth-of-field limitation in high-resolution scans, enable radiation dose optimization, and yield quantitative X-ray absorption values with sparse sampling. We further validate our numerical approach using experimental data from two different cell types and show that the combined reconstruction reliably provides high spatial resolution within an interior region of interest of a whole cell. The resulting sparse reconstruction framework offers robust, faithful visualization of cellular organelles in soft X-ray tomography. This mesoscale imaging strategy allows one to ‘scout’ and zoom into selected subcellular volumes of interest, enabling increased spatial resolution without sacrificing larger-volume imaging and providing information on the relative positions of all organelles within a cell.

3D imaging↗
DOE OSTI2021

Diverse Super-Resolution (diversity_SR) [SWR-21-60]

Deep learning tools for enhancing the spatial resolution of wind data. The software is developed in Python using the TensorFlow deep learning package. Models for diversity super-resolution is provided. Included in the package are pretrained models with example code/data to perform the super-resolution as well as tools of training models for different enhancement- or data-types. The super-resolution is an inherently ill-conditioned problem, with multiple high-resolution fields plausibly mapping to the same coarse field. Considitional GANs provide a framework for generating a distribution of high-resolution realizations from a given low-resolution input. Stochastic estimation is used to inform the network of the expected degree and location of sub-grid diversity. The package includes a pretrained network to generate distributions of 10x-enhanced fields of wind data.

Glaws, Andrew↗
DOE OSTI2022

Experimental X-ray Charge-Density Studies–A Suitable Probe for Superconductivity? A Case Study on MgB 2

Case studies of 1T-TiSe 2 and YBa 2 Cu 3 O 7-δ have demonstrated that X-ray diffraction (XRD) studies can be used to trace even subtle structural phase transitions which are inherently connected with the onset of superconductivity in these benchmark systems. However, the utility of XRD in the investigation of superconductors like MgB 2 lacking an additional symmetry-breaking structural phase transition is not immediately evident. Nevertheless, high-resolution powder XRD experiments on MgB 2 in combination with maximum entropy method analyses hinted at differences between the electron density distributions at room temperature and 15 K, that is, below the T c of approx. 39 K. The high-resolution single-crystal XRD experiments in combination with multipolar refinements presented here can reproduce these results but show that the observed temperature-dependent density changes are almost entirely due to a decrease of atomic displacement parameters as a natural consequence of a reduced thermal vibration amplitude with decreasing temperature. Our investigations also shed new light on the presence or absence of magnesium vacancies in MgB 2 samples–a defect type claimed to control the superconducting properties of the compound. Here, we propose that previous reports on the tendency of MgB 2 to form non-stoichiometric Mg 1–x B 2 phases (1 – x ~ 0.95) during high-temperature (HT) synthesis might result from the interpretation of XRD data of insufficient resolution and/or usage of inflexible refinement models. Indeed, advanced refinements based on an Extended Hansen–Coppens multipolar model and high-resolution X-ray data, which consider explicitly the contraction of core and valence shells of the magnesium cations, do not provide any significant evidence for the formation of non-stoichiometric Mg 1–x B 2 phases during HT synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

GPS-Based Gamma Survey for Characterizing and Decommissioning NORM Sites - 20389

Gamma survey techniques are an especially powerful decommissioning tool at naturally occurring radioactive material (NORM) sites due to both the low cost to obtain data over a large spatial scale and the abundance of gamma emitters in the uranium and thorium decay series. Gamma surveys are executed by coupling a detector - most often a sodium iodide crystal - to a global positioning system (GPS), then reporting a location and gross gamma reading coincidentally to a data logger. Systems may be carried by workers or mounted to a car, all-terrain vehicle, or unmanned aerial system (UAS). The resulting data set provides a high-resolution but low precision map of the gamma radiation field over the area surveyed. Frequently this map is also correlated to soil concentrations of NORM radionuclides (most often, Ra-226) and/or exposure rate. Gamma survey parameters such as movement speed, transect spacing, and data logging frequency define the spatial resolution of the resulting surface, and can be optimized depending on the desired survey sensitivity. This paper examines gamma survey as a tool for decommissioning NORM sites and provides an overview of current gamma survey technology designed to improve the efficiency and effectiveness of the decommissioning process. Topics to be discussed in the paper include: - An overview of gamma survey systems, and the utility of different delivery vehicles depending on desired cost, desired spatial resolution, and site topography. - The influence of physical detector characteristics on detection sensitivity and survey planning. - The tradeoff between high-resolution and large spatial extent, but inherently uncertain data, and low-resolution, low spatial extent, but highly certain data, as well as the specific utility of each of these types of data during NORM facility decommissioning. - Confounding variables that may limit the utility of gamma survey at some sites (e.g., radon gas and spatial heterogeneity / hot spots), and methods to plan for and control these conditions. Results show that the confounding variables, such as radon and data output can greatly influence the overall data quality associated with the decommissioning process. In addition, the use of real-time and aerial survey platforms provides a method for ensuring proper spatial extent of the data. When applied thoughtfully, gamma survey is a powerful tool for detecting NORM radionuclides in the environment and a cost-effective technique for identifying areas requiring remediation. However, entities performing or using gamma survey as a decommissioning tool must be aware of both its advantages and its limitations before basing remediation or regulatory action on gamma survey results. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗