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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Data-driven background model for the CUORE experiment

Here, we present the model we developed to reconstruct the CUORE radioactive background based on the analysis of an experimental exposure of 1038.4 kg yr. The data reconstruction relies on a simultaneous Bayesian fit applied to energy spectra over a broad energy range. The high granularity of the CUORE detector, together with the large exposure and extended stable operations, allow for an in-depth exploration of both spatial and time dependence of backgrounds. We achieve high sensitivity to both bulk and surface activities of the materials of the setup, detecting levels as low as 10 nBq kg −1 and 0.1 nBq cm −2 , respectively. We compare the contamination levels we extract from the background model with prior radio-assay data, which informs future background risk mitigation strategies. The results of this background model play a crucial role in constructing the background budget for the CUPID experiment as it will exploit the same CUORE infrastructure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

FIREFLY: heat load and particle exhaust approximations for rapid evaluation of divertor designs

The divertor in a magnetic confinement fusion reactor is an essential component for power dissipation and particle removal. The FIREFLY package for rapid evaluation of divertor designs is presented as an extension of the FLARE code for field line reconstruction from a flux tube mesh. First, divertor loads are approximated with a simplified heat transport model. Neutralized particles are then sampled from the resulting load distribution, and the EIRENE code is used to track molecules and atoms in a plasma background while accounting for dissociation, charge exchange and ionization. Particles are removed on pumping surfaces in order to estimate the exhaust efficiency for a given divertor geometry. Optimization of the divertor geometry for more efficient particle exhaust is explored by using W7-X as an example, and the sensitivity to model parameters for the plasma background in the proxy calculations is evaluated.

mesh generation, magnetic field lines, scrape-off ↗
NASA NTRS1990

Reconstruction of O3 and N2O fields from ER-2, DC-8, and balloon observations

Measurements of N2O and O3 during the Airborne Arctic Stratospheric Expedition have been composited using the potential vorticity and potential temperature of each measurement as coordinates. For ozone, data sources included the ER-2 and balloon ozonesonde in situ measurements, DC-8 DIAL lidar, and Stratospheric Aerosol and Gas Experiment satellite profiles. For N2O, only ER-2 data were used. These chemical composites have been reconstructed onto average meteorological fields for the mission in a latitude-altitude cross section, yielding a picture of the chemical composition of the polar vortex during this period. Tracers inside the vortex show an apparent descent of about 2 km relative to those outside, resulting in an apparent chemical edge on isentropic and isobaric surfaces.

Schoeberl, Mark R.↗
NASA NTRS2002

Solar Forcing of Regional Climate Change During the Maunder Minimum

We examine the climate response to solar irradiance changes between the late 17th century Maunder Minimum and the late 18th century. Global average temperature changes are small (about 0.3 to 0.4 C) in both a climate model and empirical reconstructions. However, regional temperature changes are quite large. In the model, these occur primarily through a forced shift toward the low index state of the Arctic Oscillation/North Atlantic Oscillation. This leads to colder temperatures over the Northern Hemisphere continents, especially in winter (1 to 2 C), in agreement with historical records and proxy data for surface temperatures.

Shindell, Drew T.↗
NASA NTRS2015

New Insights on Subsurface Imaging of Carbon Nanotubes in Polymer Composites via Scanning Electron Microscopy

Despite many studies of subsurface imaging of carbon nanotube (CNT)-polymer composites via scanning electron microscopy (SEM), significant controversy exists concerning the imaging depth and contrast mechanisms. We studied CNT-polyimide composites and, by threedimensional reconstructions of captured stereo-pair images, determined that the maximum SEM imaging depth was typically hundreds of nanometers. The contrast mechanisms were investigated over a broad range of beam accelerating voltages from 0.3 to 30 kV, and ascribed to modulation by embedded CNTs of the effective secondary electron (SE) emission yield at the polymer surface. This modulation of the SE yield is due to non-uniform surface potential distribution resulting from current flows due to leakage and electron beam induced current. The importance of an external electric field on SEM subsurface imaging was also demonstrated. The insights gained from this study can be generally applied to SEM nondestructive subsurface imaging of conducting nanostructures embedded in dielectric matrices such as graphene-polymer composites, silicon-based single electron transistors, high resolution SEM overlay metrology or e-beam lithography, and have significant implications in nanotechnology.

Zhao, Minhua↗
DOE OSTI2023

Three-dimensional phenotyping of peach tree-crown architecture utilizing terrestrial laser scanning

Tree training systems for temperate fruit have been developed throughout history by pomologists to improve light interception, fruit yield, and fruit quality. These training systems direct crown and branch growth to specific configurations. Quantifying crown architecture could aid the selection of trees that require less pruning or that naturally excel in specific growing/training system conditions. Regarding peaches [Prunus persica (L.) Batsch], access tools such as branching indices have been developed to characterize tree-crown architecture. However, the required branching data (BD) to develop these indices are difficult to collect. Traditionally, BD have been collected manually, but this process is tedious, time-consuming, and prone to human error. These barriers can be circumnavigated by utilizing terrestrial laser scanning (TLS) to obtain a digital twin of the real tree. TLS generates three-dimensional (3D) point clouds of the tree crown, wherein every point contains 3D coordinates (x, y, z). To facilitate the use of these tools for peach, we selected 16 young peach trees scanned in 2021 and 2022. These 16 trees were then modeled and quantified using the open-source software TreeQSM. As a result, “in silico” branching and biometric data for the young peach trees were calculated to demonstrate the capabilities of TLS phenotyping of peach tree-crown architecture. The comparison and analysis of field measurements (in situ) and in silico BD, biometric data, and quantitative structural model branch uncertainty data were utilized to determine the reconstructive model’s reliability as a source substitute for field measurements. Mean average deviation when comparing young tree (YT) height was approx. 5.93%, with crown volume was approx. 13.26% across both 2021 and 2022. All point clouds of the YTs in 2022 showed residuals lower than 12 mm to cylinders fitted to all branches, and mean surface coverage greater than 40% for both the trunk and primary branching orders.

09 BIOMASS FUELS↗
DOE OSTI2021

Measurement of the atmospheric muon rate with the MicroBooNE Liquid Argon TPC

MicroBooNE is a near-surface liquid argon (LAr) time projection chamber (TPC) located at Fermilab. We measure muons originating from cosmic interactions in the atmosphere using both the charge collection and light readout detectors. The data is compared with the cosmic-ray simulation. Agreement is found between the observation, simulation and previous results. Furthermore, the angular resolution of the reconstructed muons inside the TPC is studied in simulation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

The Double-edged Sword of Data-driven Super-Resolution: Adversarial Super-resolution Models

Data-driven super-resolution (SR) methods are often integrated into imaging pipelines as preprocessing steps to improve downstream tasks such as classification and detection. However, these SR models introduce a previously unexplored attack surface into imaging pipelines. In this paper, we present AdvSR, a framework demonstrating that adversarial behavior can be embedded directly into SR model weights during training, requiring no access to inputs at inference time. Unlike prior attacks that perturb inputs or rely on backdoor triggers, AdvSR operates entirely at the model level. By jointly optimizing for reconstruction quality and targeted adversarial outcomes, AdvSR produces models that appear benign under standard image quality metrics while inducing downstream misclassification. We evaluate AdvSR on three SR architectures (SRCNN, EDSR, SwinIR) paired with a YOLOv11 classifier and demonstrate that AdvSR models can achieve high attack success rates with minimal quality degradation. These findings highlight a new model-level threat for imaging pipelines, with implications for how practitioners source and validate models in safety-critical applications.

Sullivan, Haley [ORNL] (ORCID:0000000274069217)↗
NASA NTRS2021

Coral Oxygen Isotopic Records Capture the 2015/2016 El Niño Event in the Central Equatorial Pacific

Coral oxygen isotopes (δ^(18)O) from the central equatorial Pacific provide monthly resolved records of El Niño-Southern Oscillation activity over past centuries to millennia. However, calibration studies using in situ data to assess the relative contributions of warming and freshening to coral δ^(18)O records are exceedingly rare. Furthermore, the fidelity of coral δ^(18)O records under the most severe thermal stress events is difficult to assess. Here, we present six coral δ^(18)O records and in situ temperature, salinity, and seawater δ^(18)O data from Kiritimati Island (2°N, 157°W) spanning the very strong 2015/16 El Niño event. Local sea surface temperature (SST) anomalies of +2.4 ± 0.4°C and seawater δ^(18)O anomalies of −0.19 ± 0.02‰ contribute to the observed coral δ^(18)O anomalies of −0.58 ± 0.05‰, consistent with a ∼70% contribution from SST and ∼30% from seawater δ^(18)O. Our results demonstrate that Kiritimati coral δ^(18)O records can provide reliable reconstructions even during the largest class of El Niño events.

Oxygen isotope anomalies↗
DOE OSTI2025

Sharp front tracking with geometric interface reconstruction

Here, this paper presents a novel sharp front-tracking method designed to address limitations in classical front-tracking approaches, specifically their reliance on smooth interpolation kernels and extended stencils for coupling the front and fluid mesh. In contrast, the proposed method employs exclusively sharp, localized interpolation and spreading kernels, restricting the coupling to the interfacial fluid cells–those containing the interface/front. This localized coupling is achieved by integrating a divergence-preserving velocity interpolation method with a piecewise parabolic interface calculation (PPIC) and a polyhedron intersection algorithm to compute the indicator function and local interface curvature. Surface tension is computed using the Continuum Surface Force (CSF) method, maintaining consistency with the sharp representation. Additionally, we propose an efficient local roughness smoothing implementation to account for surface mesh undulations, which is easily applicable to any triangulated surface mesh. Building on our previous work, the primary innovation of this study lies in the localization of the coupling for both the indicator function and surface tension calculations. By reducing the interface thickness on the fluid mesh to a single cell, as opposed to the 4–5 cell spans typical in classical methods, the proposed sharp front-tracking method achieves a highly localized and accurate representation of the interface. This sharper representation mitigates parasitic currents and improves force balancing, making it particularly suitable for scenarios where the interface plays a critical role, such as microfluidics, fluid-fluid interactions, and fluid-structure interactions. The proposed method is comprehensively validated and tested on canonical interfacial flow problems, including stationary and translating Laplace equilibria, oscillating droplets, and rising bubbles. The presented results demonstrate that the sharp front-tracking method significantly outperforms the classical approach in terms of accuracy, stability, and computational efficiency. Notably, parasitic currents are reduced by approximately two orders of magnitude and stable results are obtained for parameter ranges where classical front tracking fails to converge.

42 ENGINEERING↗
DOE OSTI2025

Multiscale Characterization of Additive Manufacturing Components with Computed Tomography, 3D X-ray Microscopy, and Deep Learning

Additive manufacturing (AM) facilitates the creation of complex-geometry parts, driving advancements in lightweight aerospace components, high-efficiency engine cooling channels, and customized medical implants. However, ensuring the quality and reliability of AM parts remains challenging due to internal defects, surface irregularities, porosity, and residual trapped powder, which are often inaccessible to traditional inspection methods. Recent developments in X-ray computed tomography (XCT) and 3D X-ray microscopy (XRM), particularly systems equipped with resolution-at-a-distance (RaaD™) capabilities, enable high-resolution, non-destructive evaluation of AM components across multiple scales, from sub-micrometer to macroscopic levels. This paper explores modern XCT and XRM techniques for multiscale characterization of AM parts, focusing on their ability to detect and analyze defects such as porosity, cracks, inclusions, and surface roughness, while offering insights into defect formation mechanisms, material properties, and process-induced variations. The integration of deep learning (DL) frameworks, including Simurgh, DeepRecon, and DeepScout, enhances XCT/XRM workflows by reducing scan times, improving resolution recovery, and enabling accurate defect detection even with limited projection data. These DL-based methods overcome limitations of traditional reconstruction techniques, enabling faster, more reliable characterization of dense materials like Inconel 718 and novel alloys such as AlCe. Applications include process parameter optimization, high-throughput quality control, and multistage AM process evaluation, with DL-enhanced workflows accelerating analysis times from weeks to days. Correlative imaging approaches further validate XCT and XRM data against scanning electron microscopy (SEM) images of physically sectioned samples, confirming the accuracy of DL-based reconstructions and enabling comprehensive defect analysis. While challenges remain in generalizing DL models to diverse materials and imaging conditions, improvements in resolution, noise reduction, and defect detection highlight the transformative potential of these methods. This multiscale and correlative approach enables precise identification and correlation of microstructural features with the overall performance of AM components. By integrating advanced XCT, XRM, and DL techniques, this paper demonstrates a significant leap forward in AM characterization, offering valuable insights into the relationships between processing parameters, microstructure, and part performance, and driving innovations that enhance the quality and reliability of AM products for demanding industrial applications.

Additive manufacturing↗
DOE OSTI2022

Building interface bonding and shield for stable Li-rich Mn-based oxide cathode

Implementation of Li-rich Mn-based oxide cathode with high-energy-density has been restrained by capacity/voltage degradation that results from irreversible lattice oxygen loss and structure rearrangements. To resolve these challenges, in this work, Li 1.2 Mn 0.54 Ni 0.13 Co 0.13 O 2 encapsulated by amorphous Co x B (CB-LRM) is rationally designed via autocatalytic plating for highly reversible cationic/anionic hybrid cathode material. Band coherency is ingeniously evoked by interface-reconstruction between bulk structure and amorphous coating layer, which lower the energy of O $2p$ states. Furthermore, this is associated with strengthened orbital hybridization of O $2p$-Mn $3d$ and increased formation energy of oxygen vacancy, which mitigates the lattice oxygen loss considerably. Additionally, interface shielding effects that protect electrode against electrolyte corrosion and the reduction of surface oxygen are also present with fully coverage of amorphous Co x B coating layer. As a result, the as-designed CBLRM cathode exhibits excellent cycle stability after 100 loops with only 0.154% per cycle capacity fade and improved voltage degradation. Given this, this work provides a potential avenue for rational design of lattice oxygen-based electrode materials with high-energy-density.

25 ENERGY STORAGE↗
DOE OSTI2014

Ultrasonic multi-skip tomography for pipe inspection

The inspection of wall loss corrosion is difficult at pipe supports due to limited accessibility. The recently developed ultrasonic Multi-Skip screening technique is suitable for this problem. The method employs ultrasonic transducers in a pitch-catch geometry positioned on opposite sides of the pipe support. Shear waves are transmitted in the axial direction within the pipe wall, reflecting multiple times between the inner and outer surfaces before reaching the receivers. Along this path, the signals accumulate information on the integral wall thickness (e.g., via variations in travel time). The method is very sensitive in detecting the presence of wall loss, but it is difficult to quantify both the extent and depth of the loss. Multi-skip tomography has been developed to reconstruct the wall thickness profile along the axial direction of the pipe. The method uses model-based full wave field inversion; this consists of a forward model for predicting the measured wave field and an iterative process that compares the predicted and measured wave fields and minimizes the differences with respect to the model parameters (i.e., the wall thickness profile). Experimental results are very encouraging. Various defects (slot and flat bottom hole) are reconstructed using the tomographic inversion. The general shape and width are well recovered. The current sizing accuracy is in the order of 1 mm.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Investigation of Nanoparticle Degradation in Hydrogen Fuel Cell Systems through Automated Electron Microscopy

Proton exchange membrane fuel cells (PEMFC) are promising devices for the deployment of hydrogen-powered heavy-duty vehicles, providing a higher efficiency for similar driving range and fueling time than the existing ones. However, PEMFCs still encounter durability challenges mainly due to catalyst degradation in the cathode. Mitigating these performance losses requires a better understanding of the degradation mechanisms under heavy-duty accelerated stress tests (ASTs) [1]. Scanning transmission electron microscopy (STEM) combined with energy dispersive X-ray spectroscopy (EDS) are key tools for the analysis of Pt and PtCo nanoparticle size, spatial distribution and composition [2]. Electron tomography is also used to determine the rate and type of degradation of catalyst nanoparticles as a function of their position on the carbon support. In this work, automated data acquisition software, paired with a custom Python code, have been used to study the effect of different accelerated stress tests (ASTs) on nanoparticle coarsening [2]. Figure 1 shows high-angle annular dark-field (HAADF)-STEM images and EDS maps comparing the cathodes of membrane electrode assemblies (MEAs) following an electrocatalyst AST performed under H2/N2 with that of the heavy-duty AST performed under H2/air. We will discuss how AST conditions affect considerably the spatial distribution of the nanoparticles across the electrode between the membrane and microporous layer. Although the median particle size increased more in the MEA aged under the heavy-duty AST, as determined using a high-throughput image analysis, the quantitative EDS measurements demonstrate that the electrocatalyst AST resulted in more Pt and Co dissolution from the cathode, which is another important indicator of electrocatalyst degradation. We will further present the impact of the relative humidity (% RH) on the degradation mechanisms demonstrated using the same approach. Electron tomography has been used to distinguish the Pt nanoparticles residing on the carbon support surface (exterior) from those within the pore structure (interior) in order to determine the relative stability of interior and exterior nanoparticles. As shown in Figure 2, we will compare the Pt catalyst particle size at the beginning of test (BOT) and end of test (EOT), and discuss the importance of automating the electron tomography workflow, i.e. acquisition, reconstruction, and visualization, to increase sampling and determine the standard deviation of these measurement. The outlook for utilizing low-dose cryo-tomography for limiting damage to the catalyst, support, and especially proton-conducting ionomer will also be discussed [3].

Amichi, Lynda↗
DOE OSTI2019

Predicting near-term variability in ocean carbon uptake

Abstract. Interannual variations in air–sea fluxes of carbon dioxide ( CO 2 ) impact the global carbon cycle and climate system, and previous studies suggest that these variations may be predictable in the near term (from a year to a decade in advance). Here, we quantify and understand the sources of near-term predictability and predictive skill in air–sea CO 2 flux on global and regional scales by analyzing output from a novel set of retrospective decadal forecasts of an Earth system model. These forecasts exhibit the potential to predict year-to-year variations in the globally integrated air–sea CO 2 flux several years in advance, as indicated by the high correlation of the forecasts with a model reconstruction of past CO 2 flux evolution. This potential predictability exceeds that obtained solely from foreknowledge of variations in external forcing or a simple persistence forecast, with the longest-lasting forecast enhancement in the subantarctic Southern Ocean and the northern North Atlantic. Potential predictability in CO 2 flux variations is largely driven by predictability in the surface ocean partial pressure of CO 2 , which itself is a function of predictability in surface ocean dissolved inorganic carbon and alkalinity. The potential predictability, however, is not realized as predictive skill, as indicated by the moderate to low correlation of the forecasts with an observationally based CO 2 flux product. Nevertheless, our results suggest that year-to-year variations in ocean carbon uptake have the potential to be predicted well in advance and establish a precedent for forecasting air–sea CO 2 flux in the near future.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Evidence for Present Day Volcanism on Venus: A Case Study of Idunn Mons

Idunn Mons in Imdr Regio on Venus is perhaps one of the best studied volcanoes on Venus in part due to having both radar and night-time emissivity data of the region [1-3]. Smrekar et al. [1] first presented night-time emissivity data of Idunn Mons from the VIRTIS instrument on Venus Express, which showed that some lava flows have high emissivity consistent with unweathered basalt. Smrekar et al. [1], based on known weathering rates at that time, suggested that the lava flows were less than 2.5 million years old and possible as young as 250,000 years old. However, recent experimental work has shown that basaltic rocks and associated minerals in contact with the Venusian caustic atmosphere would react quickly to produce rinds of alteration materials coating the surface and obscure emissivity signatures of igneous minerals within a few to ~10,000 years [4-9]. These new experimentally derived weathering and oxidation rates were used to suggest that lava flows at Idunn Mons with unweathered signatures are quite young and Idunn Mons may be volcanically active today [4, 8]. Independent geologic mapping and related stratigraphic reconstruction over the study area is consistent with the experimental results [2, 10]. Considering all the available evidence, we have taken a comprehensive approach combining these recent experimental results with previous orbital night-time emissivity, as well as atmospheric measurements, to constrain the evolution of Idunn Mons [3,10]. Our results suggest that Idunn Mons is both volcanically and tectonically active today, and that volcanism and tectonic activity are likely related [11]. Venus being volcanically active has been suggested at other volcanic centers, as well [e.g. 12-17]. Therefore, we use Idunn Mons specifically as a case study of a potentially active volcano that may be detectable by the upcoming fleet of missions that will be arriving at Venus in the next decade.

Justin Filiberto↗
DOE OSTI2020

Detecting an underground tunnel by applying joint traveltime and waveform inversion

Underground tunnel and void detection is a challenging geophysical problem, and many methods have been proposed. Seismic techniques are promising because of the large seismic velocity contrasts between the air-filled void and the surrounding sediment and concrete. We apply a joint seismic traveltime and waveform inversion method to image a buried tunnel with concrete walls and a void space inside. The joint inversion images the top of the concrete tunnel as a high-velocity anomaly and the void space as a low-velocity anomaly. The location of the velocity anomalies predicted by the method agrees with the known location of the tunnel. As a comparison, the stand-alone full waveform inversion is also applied to the data. The first-arrival traveltime tomography shows weak nonlinearity but fails to image the hidden low-velocity layer. Full waveform inversion is able to image complex near-surface structures, but fitting waveforms may not honor the traveltime fit, especially when the data contain noise. Synthetic and real data tests show that the joint inversion method retains the advantages of both traveltime inversion and full waveform inversion and overcomes their respective drawbacks at the same time. The field example shows the joint inversion provides a better reconstruction of the high-velocity feature representing the top of the concrete wall in terms of its magnitude and location.

58 GEOSCIENCES↗
DOE OSTI2015

Super-resolution of fluorescence-free plasmonic nanoparticles using enhanced dark-field illumination based on wavelength-modulation

Super-resolution imaging of fluorescence-free plasmonic nanoparticles (NPs) was achieved using enhanced dark-field (EDF) illumination based on wavelength-modulation. Indistinguishable adjacent EDF images of 103-nm gold nanoparticles (GNPs), 40-nm gold nanorods (GNRs), and 80-nm silver nanoparticles (SNPs) were modulated at their wavelengths of specific localized surface plasmon scattering. The coordinates (x, y) of each NP were resolved by fitting their point spread functions with a two-dimensional Gaussian. The measured localization precisions of GNPs, GNRs, and SNPs were 2.5 nm, 5.0 nm, and 2.9 nm, respectively. From the resolved coordinates of NPs and the corresponding localization precisions, super-resolution images were reconstructed. Depending on the spontaneous polarization of GNR scattering, the orientation angle of GNRs in two-dimensions was resolved and provided more elaborate localization information. This novel fluorescence-free super-resolution method was applied to live HeLa cells to resolve NPs and provided remarkable subdiffraction limit images.

77 NANOSCIENCE AND NANOTECHNOLOGY↗