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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 OSTI2026

Strong Lens Discoveries in DESI Legacy Imaging Surveys DR10 with Two Deep Learning Architectures

Abstract We have conducted a search for strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys Data Release 10 (DR10). This paper is the fourth in a series of searches. This is the first catalog of lens candidates covering nearly the entirety of the extragalactic sky south of declination δ ≈ +32 ∘ , all observed by DECam, covering ∼14,000 deg 2 . We impose a z -band magnitude cut of <20 in AB magnitude. We deploy a residual neural network and EfficientNet as an ensemble trained on a compilation of known lensing systems and high-grade candidates as well as nonlenses in the same footprint. The predictions from these two base models are aggregated using a meta-learner. After applying our ensemble to the survey data, we exclude known candidates and systems, and use our own visual inspection portal to rank images in the top 0.01 percentile of all neural network recommendations. We have found 811 lens candidates, five of which are confirmed through Euclid Quick Data Release (Q1). These include 484 new candidates in the Legacy Surveys DR9 footprint, all parts of which have been searched for strong lenses at least once before, either by our group or others. Combining the discoveries from this work with those from the first three papers in this series (335, 1210, and 1512), we have discovered a total of 3868 new candidates in the DESI Legacy Surveys.

Inchausti, Jose Carlos [University of San Francisc↗
DOE OSTI2022

Simultaneous neutron and X-ray tomography for visualization of graphite electrode degradation in fast-charged lithium-ion batteries

Advanced battery characterization using neutron and X-ray-based imaging modalities is crucial to reveal fundamental degradation modes of lithium-ion batteries (LIBs). Taking advantage of the sensitivity of neutrons to some low-Z (Li) and X-rays to high-Z materials (Cu), here we demonstrate the viability of simultaneous neutron and X-ray tomography (NeXT) as a non-destructive imaging platform for ex-situ 3D visualization of graphite electrode degradation following extreme fast charging (XFC). In addition, we underscore the benefits of the simultaneous of NeXT by combining the neutron and X-ray tomography data from the same sample location for material identification and segmentation of one pristine and two XFC-cycled graphite electrodes (9C charge for 450 cycles). Our ex-situ results and methodology development pave the way for the design of NeXT-friendly LIB geometries that will allow operando and/or in-situ 3D visualization of electrode degradation during XFC.

25 ENERGY STORAGE↗
DOE OSTI2021

SDSS-IV MaNGA: the physical origin of off-galaxy H α blobs in the local Universe

ABSTRACT H α blobs are off-galaxy emission-line regions with weak or no optical counterparts. They are mostly visible in H α line, appearing as concentrated blobs. Such unusual objects have been rarely observed and studied, and their physical origin is still unclear. We have identified 13 H α blobs in the public data of MaNGA survey, by visually inspecting both the optical images and the spatially resolved maps of H α line for ∼4600 galaxy systems. Among the 13 H α blobs, 2 were reported in previously MaNGA-based studies and 11 are newly discovered. This sample, though still small in size, is by far the largest sample with both deep imaging and integral field spectroscopy. Therefore, for the first time we are able to perform statistical studies to investigate the physical origin of H α blobs. We examine the physical properties of these H α blobs and their associated galaxies, including their morphology, environments, gas-phase metallicities, kinematics of ionized gas, and ionizing sources. We find that the H α blobs in our sample can be broadly divided into two groups. One is associated with interacting/merging galaxy systems, of which the ionization is dominated by shocks or diffuse ionized gas. It is likely that these H α blobs used to be part of their nearby galaxies, but were stripped away at some point due to tidal interactions. The other group is found in gas-rich systems, appearing as low-metallicity star-forming regions that are visually detached from the main galaxy. These H α blobs could be associated with faint discs, spiral arms, or dwarf galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

InSituNet: Deep Image Synthesis for Parameter Space Exploration of Ensemble Simulations

We propose InSituNet, a deep learning based surrogate model to support parameter space exploration for ensemble simulations that are visualized in situ. In situ visualization, generating visualizations at simulation time, is becoming prevalent in handling large-scale simulations because of the I/O and storage constraints. However, in situ visualization approaches limit the flexibility of post-hoc exploration because the raw simulation data are no longer available. Although multiple image-based approaches have been proposed to mitigate this limitation, those approaches lack the ability to explore the simulation parameters. Our approach allows flexible exploration of parameter space for large-scale ensemble simulations by taking advantage of the recent advances in deep learning. Specifically, we design InSituNet as a convolutional regression model to learn the mapping from the simulation and visualization parameters to the visualization results. With the trained model, users can generate new images for different simulation parameters under various visualization settings, which enables in-depth analysis of the underlying ensemble simulations. We demonstrate the effectiveness of InSituNet in combustion, cosmology, and ocean simulations through quantitative and qualitative evaluations.

deep learning↗
DOE OSTI2021

Mapping Conductance and Switching Behavior of Graphene Devices In Situ

Graphene is proposed for use in various nanodevice designs, many of which harness emergent quantum properties for device functionality. However, visualization, measurement, and manipulation become nontrivial at nanometer and atomic scales, representing a significant challenge for device fabrication, characterization, and optimization at length scales where quantum effects emerge. Herein, proof of principle results at the crossroads between 2D nanoelectronic devices, e-beam-induced modulation, and imaging with secondary electron e-beam induced currents (SEEBIC) is presented. A device platform compatible with scanning transmission electron microscopy investigations is introduced. Then how the SEEBIC imaging technique can be used to visualize conductance and connectivity in single layer graphene nanodevices, even while supported on a thicker substrate (conditions under which conventional imaging fails) is shown. Finally, it is shown that the SEEBIC imaging technique can detect subtle differences in charge transport through time in nonohmic graphene nanoconstrictions indicating the potential to reveal dynamic electronic processes.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Evolution of tensile and shear cracking in crystalline rocks under compression

Here we performed laboratory-scale unconfined compression experiments on Barre granite specimen with a single pre-existing flaw to study the evolution of tensile and shear cracking that occurs during different stress levels. Moment tensor inversion of acoustic emission (AE) events in combination with the nonelastic strain component obtained through the 2D digital image correlation (DIC) technique are used to track the changes in the source mechanisms of the stress-induced cracks. The mode of deformation computed from the image based strain profiles, enables visual comparison of the nucleation, growth and interaction of the tensile and shear cracks with the microseismic source mechanism observed by moment tensor inversion of the AE events. Comparing the results obtained from the two techniques on the same dataset demonstrates a quantitative correlation between the acoustic and visual observations in terms of the cracking mechanisms obtained at different stages of cracking from crack initiation at the flaw tips to the failure of the rock specimen.

58 GEOSCIENCES↗
DOE OSTI2022

Toward fully automated UED operation using two-stage machine learning model

To demonstrate the feasibility of automating UED operation and diagnosing the machine performance in real time, a two-stage machine learning (ML) model based on self-consistent start-to-end simulations has been implemented. This model will not only provide the machine parameters with adequate precision, toward the full automation of the UED instrument, but also make real-time electron beam information available as single-shot nondestructive diagnostics. Furthermore, based on a deep understanding of the root connection between the electron beam properties and the features of Bragg-diffraction patterns, we have applied the hidden symmetry as model constraints, successfully improving the accuracy of energy spread prediction by a factor of five and making the beam divergence prediction two times faster. The capability enabled by the global optimization via ML provides us with better opportunities for discoveries using near-parallel, bright, and ultrafast electron beams for single-shot imaging. It also enables directly visualizing the dynamics of defects and nanostructured materials, which is impossible using present electron-beam technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Machine Learning Algorithms for Automated NIF Capsule Mandrel Selection

Small shells, approximately 2 mm in diameter, made from Poly(α-methylstyrene) (PAMS) are used as mandrels in the production of glow discharge polymer capsules located at the center of inertial confinement fusion experiments. The visual inspection process of microscope images of these shell mandrels, including detection of micron-sized defects on the shell surface as well as the handling and sorting, is a very labor-intensive, repetitive, and highly subjective process that stands to benefit greatly from automation. As part of an effort to decrease the number of labor hours spent in capsule handling, inspection, and metrology, the development of robotic systems was presented in a paper by Carlson et al., “Automation in Target Fabrication” [Fusion Sci. Technol., Vol. 70, p. 274 (2016)]. The current work expands the automated image acquisition systems developed previously and adds the use of convolutional neural networks to select capsules best suited for use in the downstream production process. Through the use of these machine learning algorithms, the selection process becomes robust, repeatable, and operator independent. Finally, as an added benefit the system developed as part of this work is able to provide defect statistics on entire shell batches and feed this information upstream to the production team.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Optical properties of Peaked Spectrum radio sources

ABSTRACT In this work, we study the optical properties of compact radio sources selected from the literature in order to determine the impact of the radio-jet in their circumnuclear environment. Our sample includes 58 Compact Steep Spectrum (CSS) and GigaHertz Peaked Spectrum (GPS) and 14 Megahertz-Peaked spectrum (MPS) radio sources located at z ≤ 1. The radio luminosity (LR) of the sample varies between Log LR ∼ 23.2 and 27.7 W Hz−1. We obtained optical spectra for all sources from SDSS-DR12 and performed a stellar population synthesis using the starlight code. We derived stellar masses (M⋆), ages 〈t⋆〉, star formation rates (SFR), metallicities 〈Z⋆〉 and internal reddening AV for all young AGNs of our sample. A visual inspection of the SDSS images was made to assign a morphological class for each source. Our results indicate that the sample is dominated by intermediate to old stellar populations and there is no strong correlation between optical and radio properties of these sources. Also, we found that young AGNs can be hosted by elliptical, spiral and interacting galaxies, confirming recent findings. When comparing the optical properties of CSS/GPS and MPS sources, we do not find any significant difference. Finally, the Mid-Infrared WISE colours analysis suggests that the compact radio sources defined as powerful AGNs are, in general, gas-rich systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Diagnosis of PV Cell Antireflective Coating Degradation Resulting From Hot-Humid High-Voltage Potential Aging

Corrosion of the antireflective coating on a photovoltaic cell ("ARc corrosion") has previously been observed in studies using hot-humid test conditions with external high-voltage (HV) bias. This study primarily focuses on known vulnerable legacy aluminum back surface field cells in mini-modules (MiMos) put through comparative stepped stress tests. Each cell type had MiMos at +1500 V, -1500 V, or unbiased ("Voc") potential, which were sequentially subjected to test conditions of 60 degrees C/60% relative humidity (RH) for 96 h, as in International Electrotechnical Commission Technical Specification 62804-1; 70 degrees C/70% RH for 200 h; and 85 degrees C/85% RH for 200 h. Characterizations at each step included visual camera and electroluminescence (EL) imaging, colorimetry, and current-voltage curve tracing. Final characterizations included: Suns-Voc, spatial mapping of external quantum efficiency, high-resolution photoluminescence, EL, and dark lock-in thermography imaging. Forensics were performed on extracted cores, including scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy, and scanning Auger microscopy (SAM). Forensics were also conducted on MiMos from previous studies that underwent stepped HV aging and separate outdoor aged full-sized modules. ARc corrosion was specifically seen for the glass/encapsulant/cell side of the +1500 V (HV+) stressed MiMos and modules. Appearance, color, and reflectance were the most distinguishing characteristics relative to glass corrosion, gridline corrosion and delamination, and other concurrent degradation modes. SEM/EDS and SAM identified the conversion of silicon nitride to hydrated silica, hydrous silica, or hydrated amorphous silica, which preferentially occurred at the edges and tips of the pyramidal textured cell surface.

14 SOLAR ENERGY↗
DOE OSTI2025

Diagnosis of PV Cell Antireflective Coating Degradation Resulting from Hot-Humid, High Voltage Potential Aging

Corrosion of the antireflective coating on a photovoltaic cell ("ARc corrosion") has previously been observed in studies using hot-humid test conditions with external high-voltage (HV) bias. This study primarily focuses on known vulnerable, legacy aluminum back surface field (Al-BSF) cells in mini-modules (MiMos) put through comparative stepped stress tests. Each cell type had MiMos at +1500 V, -1500 V, or unbiased ("Voc") potential, which were sequentially subjected to test conditions of 60deg C/60% relative humidity (RH) for 96 h, as in International Electrotechnical Commission (IEC) Technical Specification 62804-1; 70 deg C/70% RH for 200 h; and 85 deg C/85% RH for 200 h. Characterizations at each step included visual camera and electroluminescence (EL) imaging, colorimetry, and current-voltage (I-V) curve tracing. Final characterizations included: Suns-Voc; spatial mapping of external quantum efficiency (EQE); high-resolution photoluminescence (PL), EL, and dark lock-in thermography (DLIT) imaging. Forensics were performed on extracted cores, including scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), and scanning Auger microscopy (SAM). Forensics were also conducted on MiMos from previous studies that underwent stepped HV aging and separate outdoor aged full-sized modules. ARc corrosion was specifically seen for the glass/encapsulant/cell side of the +1500V (HV+) stressed MiMos and modules. Appearance, color, and reflectance were the most distinguishing characteristics relative to glass corrosion, gridline-corrosion and -delamination as well as other concurrent degradation modes. SEM/EDS and SAM identified conversion of silicon nitride to hydrated silica, hydrous silica, or hydrated amorphous silica, which preferentially occurred at the edges and tips of the pyramidal textured cell surface.

14 SOLAR ENERGY↗
DOE OSTI2026

High Contrast Pattern Projection To Enable Background Oriented Schlieren Based Air Leak Detection Through Any Interior Or Exterior Building Surface

Air leakage in buildings wastes an estimated 4 quads of energy per year in the United States. Finding and sealing leakage sites is critical in existing buildings. Previous work has shown that background oriented Schlieren (BOS) imaging can be used to visualize air leakage but requires the leak to exit through a high contrast surface like a brick wall. To remedy this, different techniques of projecting various high contrast patterns on low contrast building surfaces like interior gypsum walls or vinyl siding were investigated. For each technique, the background quality was measured and compared to an ideal printed random dot background. The background quality metrics were correlated with the measured visualization metrics to understand which metrics are most important for maximizing air leak visualization performance. In this work, leakage visualization performance is presented for these various projected backgrounds with an aim to expand the building surfaces suitable for the BOS leak detector.

Jatana, Gurneesh [ORNL] (ORCID:0000000288903225)↗
DOE OSTI2021

Accurate in vivo tumor detection using plasmonic-enhanced shifted-excitation Raman difference spectroscopy (SERDS)

For the majority of cancer patients, surgery is the primary method of treatment. In these cases, accurately removing the entire tumor without harming surrounding tissue is critical; however, due to the lack of intraoperative imaging techniques, surgeons rely on visual and physical inspection to identify tumors. Surface-enhanced Raman scattering (SERS) is emerging as a non-invasive optical alternative for intraoperative tumor identification, with high accuracy and stability. However, Raman detection requires dark rooms to work, which is not consistent with surgical settings. Methods: Herein, we used SERS nanoprobes combined with shifted-excitation Raman difference spectroscopy (SERDS) detection, to accurately detect tumors in xenograft murine model. Results: We demonstrate for the first time the use of SERDS for in vivo tumor detection in a murine model under ambient light conditions. We compare traditional Raman detection with SERDS, showing that our method can improve sensitivity and accuracy for this task. Conclusion: Our results show that this method can be used to improve the accuracy and robustness of in vivo Raman/SERS biomedical application, aiding the process of clinical translation of these technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Foundation Models for Zero-Shot Segmentation of Scientific Images without AI-Ready Data

Zero-shot and prompt-based models have excelled at visual reasoning tasks by leveraging large-scale natural image corpora, but they often fail on sparse and domain-specific scientific image data. We introduce Zenesis, a no-code interactive computer vision platform designed to reduce data readiness bottlenecks in scientific imaging workflows. Zenesis integrates lightweight multimodal adaptation for zero-shot inference on raw scientific data, human-in-the-loop refinement, and heuristic-based temporal enhancement. We validate our approach on Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) datasets of catalyst-loaded membranes. Zenesis outperforms baselines, achieving an average accuracy of 0.947, Intersection over Union (IoU) of 0.858, and Dice score of 0.923 on amorphous catalyst samples; and 0.987 accuracy, 0.857 IoU, and 0.923 Dice on crystalline samples. These results represent a significant performance gain over conventional methods such as Otsu thresholding and standalone models like the Segment Anything Model (SAM). Zenesis enables effective image segmentation in domains where annotated datasets are limited, offering a scalable solution for scientific discovery.

Mukherjee, Shubhabrata↗
DOE OSTI2025

Atomic-scale imaging of frequency-dependent phonon anisotropy

Directly visualizing vibrational anisotropy in individual phonon modes is essential for understanding a wide range of intriguing optical, thermal and elastic phenomena in materials. Although conventional optical and diffraction techniques have been used to estimate vibrational anisotropies, they fall short in achieving the spatial and energy resolution necessary to provide detailed information. Here, we introduce a new form of momentum-selective electron energy-loss spectroscopy, which enables the element-resolved imaging of frequency- and symmetry-dependent vibrational anisotropies with atomic resolution. Vibrational anisotropies manifest in different norms of orthogonal atomic displacements, known as thermal ellipsoids. Using the centrosymmetric strontium titanate as a model system, we observed two distinct types of oxygen vibrations with contrasting anisotropies: oblate thermal ellipsoids below 60 meV and prolate ones above 60 meV. In non-centrosymmetric barium titanate, our approach can detect subtle distortions of the oxygen octahedra by observing the unexpected modulation of q-selective signals between apical and equatorial oxygen sites near 55 meV, which originates from reduced crystal symmetry and may also be linked to ferroelectric polarization. These observations are quantitatively supported by theoretical modelling, which demonstrates the reliability of our approach. The measured frequency-dependent vibrational anisotropies shed new light on the dielectric and thermal behaviours governed by acoustic and optical phonons. Furthermore, the ability to visualize phonon eigenvectors at specific crystallographic sites with unprecedented spatial and energy resolution opens new avenues for exploring dielectric, optical, thermal and superconducting properties.

Ferroelectrics and multiferroics↗
DOE OSTI2021

Automatic information extraction from neutron radiography imaging to estimate axial fuel expansion in $\mathrm{EBR-II}$

Approximately 130,000 metal fuel pins were irradiated in the Experimental Breeder Reactor II (EBR-II) during its 30 years of operation to develop and characterize existing and prospective fuels. For many of the metal fuel irradiation experiments, neutron radiography imaging was performed to characterize fuel behavior, like fuel swelling. However, due to the lack of technology or resources, many of the images have not been processed or were processed manually through visual examination. This paper represents first-attempt to develop an image processing algorithm capable of automatically extracting information regarding the degree of fuel swelling from neutron radiography imaging. The algorithm was applied to 120 images of three different metallic fuel pin compositions—U-10Zr, U-8Pu-10Zr, and U-19Pu-10Zr. The algorithm performs operations of image intensity adjustment, image binarization, region finding, and labeling to extract information about fuel swelling. The average growth for U-10Zr was found to be 8.49% with 95% Confidence Interval (CI) [8.33 –8.66%], for U-8Pu-10Zr — 7.50% with 95% CI [7.23 – 7.78%], and for U-19Pu-10Zr — 3.15%, with 95% CI [2.40 – 3.91%]. The results obtained by applying this automatic image processing algorithm are consistent with previously reported studies of the same types of fuels. The automatic image processing algorithm will be expanded to include thousands of available neutron radiography images and different types of fuels to investigate empirical dependencies of fuel swelling, which can be subsequently applied to advanced fuel modeling. Results from this study can later be compared to BISON simulations to further benchmark modeling efforts and develop assessment cases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗