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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Roman View of Strong Gravitational Lenses

Galaxy–galaxy strong gravitational lenses can constrain dark matter models and the Lambda cold dark matter cosmological paradigm at subgalactic scales. Currently, there is a dearth of images of these rare systems with high signal-to-noise ratio (SNR) and angular resolution. The Nancy Grace Roman Space Telescope (hereafter Roman), scheduled for launch in late 2026, will play a transformative role in strong-lensing science with its planned wide-field surveys. With its remarkable 0.281 square degree field of view and diffraction-limited angular resolution of ~0$^{''}_.$1, Roman is uniquely suited to characterizing dark matter substructure from a robust population of strong lenses. We present a yield simulation of detectable strong lenses in Roman’s planned High Latitude Wide Area Survey (HLWAS). We simulate a population of galaxy–galaxy strong lenses across cosmic time with cold dark matter subhalo populations, select those detectable in the HLWAS, and generate simulated images accounting for realistic Wide Field Instrument detector effects. For a fiducial case of single 146 s exposures, we predict around 160,000 detectable strong lenses in the HLWAS, of which about 500 will have sufficient SNR to be amenable to detailed substructure characterization. We investigate the effect of variation of the point-spread function across Roman’s field of view on detecting individual subhalos and the suppression of the subhalo mass function at low masses. Our simulation products are available to support strong-lens science with Roman, such as training neural networks and validating dark matter substructure analysis pipelines.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Viewing the core of the sun

The sun is a central feature to the human experience. It is found in many familiar idioms like “nothing new under the sun.” It defines our days, makes our planet habitable, and is the ultimate origin of your last meal. Yet how do we understand how it works? Over the last century or so, astronomers have learned a great deal about our sun by observing its outer layers.This has led to significant progress in envisioning the processes that power it, while still leaving the full picture incomplete. Recent exciting measurements of subatomic particles called neutrino shave given us our first detailed view of the dominant nuclear processes inside its core. These observations have provided a detailed view of the phenomena that generate the sun’s energy. But, before I describe these fascinating new measurements, it is perhaps valuable to set the stage.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Human readiness levels and Human Views as tools for user-centered design

The Human Readiness Level (HRL) scale is a simple nine-level scale that brings structure and consistency to the real-world application of user-centered design. It enables multidisciplinary consideration of human-focused elements during the system development process. Use of the standardized set of questions comprising the HRL scale results in a single human readiness number that communicates system readiness for human use. The Human Views (HVs) are part of an architecture framework that provides a repository for human-focused system information that can be used during system development to support the evaluation of HRL levels. Here, this paper illustrates how HRLs and HVs can be used in combination to support user-centered design processes. A real-world example for a U.S. Army software modernization program is described to demonstrate application of HRLs and HVs in the context of user-centered design.

42 ENGINEERING↗
DOE OSTI2024

An in-situ view cell system for investigating swelling behavior of elastomers upon high-pressure hydrogen exposure

The transition to hydrogen as a clean and efficient energy carrier is impeded by challenges in the compatibility of hydrogen with materials used within hydrogen infrastructure. Elastomers, crucial in sealing components, often exhibit premature failures in high-pressure hydrogen environments due to excessive swelling. This study employs an innovative in-situ view cell system to assess the swelling behavior of hydrogenated nitrile butadiene rubber (HNBR) under various hydrogen conditions. The system, designed to withstand pressures up to 96.5 MPa, incorporates Digital Image Correlation (DIC) for strain measurements and volume estimation. Results reveal non-linear volume increases during depressurization, challenging conventional assumptions. Furthermore, investigations into peak hydrogen pressures and pressure-holding scenarios during decompression highlight complex swelling trends. The introduction of a novel computer vision (CV) method enhances precision in volume estimation, overcoming DIC limitations. The study provides insights into mitigating elastomer swelling, crucial for developing robust materials to support future hydrogen-driven energy systems.

Elastomer↗
DOE OSTI2020

Multi-View Convolutional Neural Network for Data Spoofing Cyber-Attack Detection in Distribution Synchrophasors

Security of Distribution Synchrophasors Data (DSD) is of paramount importance as the data is used for critical smart grid applications including situational awareness, advanced protection, and dynamic control. Unfortunately, the DSD are attractive targets for malicious attackers aiming to damage grid. Data spoofing is a new class of deceiving attack, where the DSD of one Phasor Measurement Units (PMUs) is tampered by other PMUs thereby spoiling measurement based applications. In order to address this issue, a source authentication based data spoofing attack detection method is proposed using Multi-view Convolutional Neural Network (MCNN). First, common components embedded in raw frequency measurements from DSD are removed by Savitzky-Golay (SG) filter. Second, fast S transform (FST) is utilized to extract representative spatial fingerprints via time frequency analysis. Third, the spatial fingerprint is fed to MCNN, which combines dilated and standard convolutions for automatic feather extraction and source identification. Finally, according to the output of MCNN, spoofing attack detection is performed via threshold criterion. Extensive experiments with actual DSD from multiple locations in FNET/Grideye are conducted to verify the effectiveness of the proposed method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Exploiting voxel-sparsity for bone imaging with sparse-view cone-beam computed tomography

An optimization-based image reconstruction frame work is developed specifically for bone imaging. This framework exploits voxel-sparsity by use of ℓ 1 -norm image regularization and it enables image reconstruction from sparse-view cone-beam computed tomography (CBCT) acquisition. The effectiveness of the voxel-sparsity regularization is enhanced by using a blurred image representation. Ramp-filtering is included in the data discrepancy term and it has the effect of acting as a preconditioner, reducing the necessary number of iterations. The bone image reconstruction framework is demonstrated on CBCT data taken from an equine metacarpal condyle specimen.

Bone imaging↗
DOE OSTI2022

Comparison of Machine Learning and Deep Learning for View Identification from Cardiac Magnetic Resonance Images

Background: Artificial intelligence is increasingly utilized to aid in the interpretation of cardiac magnetic resonance (CMR) studies. One of the first steps is the identification of the imaging plane depicted, which can be achieved by both deep learning (DL) and classical machine learning (ML) techniques without user input. We aimed to compare the accuracy of ML and DL for CMR view classification and to identify potential pitfalls during training and testing of the algorithms. Methods: To train our DL and ML algorithms, we first established datasets by retrospectively selecting 200 CMR cases. The models were trained using two different cohorts (passively and actively curated) and applied data augmentation to enhance training. Once trained, the models were validated on an external dataset, consisting of 20 cases acquired at another center. We then compared accuracy metrics and applied class activation mapping (CAM) to visualize DL model performance. Results: The DL and ML models trained with the passively-curated CMR cohort were 99.1% and 99.3% accurate on the validation set, respectively. However, when tested on the CMR cases with complex anatomy, both models performed poorly. After training and testing our models again on all 200 cases (active cohort), validation on the external dataset resulted in 95% and 90% accuracy, respectively. The CAM analysis depicted heat maps that demonstrated the importance of carefully curating the datasets to be used for training. Conclusions: Both DL and ML models can accurately classify CMR images, but DL outperformed ML when classifying images with complex heart anatomy.

artificial intelligence↗
DOE OSTI2024

Importance of viewing angle: Hotspot effect improves the ability of satellites to track terrestrial photosynthesis

The product of near-infrared reflectance of vegetation and photosynthetic active radiation (NIRvP) is a new tool for monitoring gross primary productivity (GPP) dynamics in terrestrial ecosystems, due to the discovered linear correlation between NIRvP and GPP. While remote sensing-based NIRvP is considerably influenced by sensor geometry, such geometry impacts on the NIRvP-GPP relationship remain underexplored. In this study, we calculate NIRvP using observations from the Deep Space Climate Observatory (DSCOVR) that provide unique hotspot observation geometry in which the sensor viewing angle coincides with the sun direction. We evaluated the linear correlation between NIRvP and GPP in both the common nadir direction and the special hotspot direction. The results indicate that NIRvP in the hotspot direction significantly outperforms that in the nadir direction for tracking GPP variations across different ecosystems from diurnal to daily scales. This conclusion is further supported by data from the MODerate resolution Imaging Spectroradiometer (MODIS) and simulations using the Soil Canopy Observation Photosynthesis Energy (SCOPE) model. Finally, our research highlights the value of using the unconventional hotspot-based sun-tracking satellite observations for a more accurate characterization of GPP dynamics in terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Atomic-Scale View of Redox Induced Changes for Monolayer MoO x on α-TiO 2 (110) with Chemical-State Sensitivity

Supported molybdenum oxide (MoO x ) plays an important role in catalytic transformations from alcohol dehydrogenation to transesterification. During these reactions, Mo and oxygen surface species undergo structural and chemical changes. A detailed, chemical-state specific, atomic-scale structural analysis of the catalyst under redox conditions is important for improving catalytic properties. In this study, monolayer of MoO x grown on α-TiO 2 (110) by atomic-layer deposition is analyzed by X-ray standing wave (XSW) excited X-ray photoelectron spectroscopy (XPS). The chemical shifts for Mo 2p 3/2 and O 1s peaks are used to distinguish Mo 6+ from Mo 4+ and surface O from bulk O. Excitation of XPS by XSW allows pin-pointing the location of these surface species relative to the underlying substrate lattice. Finally, measured 3D composite atomic density maps for the oxidized and reduced interfaces compare well with our density functional theory models, and collectively create a unique view of the redoxdriven dynamics for this complex catalytic structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A Molecular View of Methane Activation on Ni(111) through Enhanced Sampling and Machine Learning

A combination of machine learned interatomic potentials (MLIPs) and enhanced sampling simulations is used to investigate the activation of methane on a Ni(111) surface. The work entails the development and iterative refinement of MLIPs, initially trained on a dataset constructed via ab initio molecular dynamics (AIMD) simulations, supplemented by adaptive biasing forces, to enrich the sampling of catalytically relevant configurations. Our results reveal that by incorporating collective variables that capture the behavior of the reactant molecule, as well as additional frames that describe the dynamic response of the catalytic surface, it is possible to enhance considerably the accuracy of predicted energies and forces. By employing enhanced sampling schemes in the refinement of the MLIP, we systematically explore the potential energy surface, leading to a refined MLIP capable of predicting DFT-level energies and forces and replicating key geometric characteristics of the catalytic system. The resulting free energy landscapes at several temperatures provide a detailed view of the thermodynamics and dynamics of methane activation. Specifically, as methane approaches and dissociates on the catalytic surface, the process involves the dynamic interplay of CH 4 and the Ni catalyst that includes both enthalpic and entropic contributions. The progression towards the transition state involves an CH 4 moiety that is increasingly restrained in its ability to rotate or translate, while the stage following the transition state is characterized by a notable rise of the Ni atom that interacts with the cleaved C–H bond. Furthermore, this leads to an increase in the mobility of the adsorbed species, a feature that becomes more pronounced at higher temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Nanoscale View of Engineered Massive Dirac Quasiparticles in Lithographic Superstructures

Massive Dirac fermions are low-energy electronic excitations characterized by a hyperbolic band dispersion. They play a central role in several emerging physical phenomena such as topological phase transitions, anomalous Hall effects, and superconductivity. This work demonstrates that massive Dirac fermions can be controllably induced by lithographically patterning superstructures of nanoscale holes in a graphene device. Their band dispersion is systematically visualized using angle-resolved photoemission spectroscopy with nanoscale spatial resolution. A linear scaling of effective mass with feature sizes is reported, underlining the Dirac nature of the superstructures. In situ electrostatic doping dramatically enhances the effective hole mass and leads to the direct observation of an electronic band gap that results in a peak-to-peak band separation of 0.64 ± 0.03 eV, which is shown via first-principles calculations to be strongly renormalized by carrier-induced screening. The methodology demonstrates band structure engineering guided by directly viewing structurally and electrically tunable massive Dirac quasiparticles in lithographic superstructures at the nanoscale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Surface Terminations of LaAlO 3 Perovskite Nanoparticles as Viewed by Solid-State Nuclear Magnetic Resonance

Nanocrystal surfaces generally undergo reconstructions that differentiate them from the bulk structures, often in nontrivial ways. Understanding these terminations is critical across diverse fields, from heterogeneous catalysis to the formation of topological states and the synthesis of semiconductor nanomaterials. Determining surface structures is currently an interdisciplinary task, most often involving high-resolution electron microscopy and surface electron diffraction. These methods, however, do not provide a global view of the ensemble of structures present in a sample. Here, we show how surface-sensitive solid-state nuclear magnetic resonance (SSNMR) spectroscopy methods can bridge this gap. In this context, we investigated the surface structure of lanthanum aluminate (LaAlO 3 ) perovskite nanoparticles. Four distinct surface terminations have previously been observed for this material, but their relative abundances were unknown. Using an array of double- and triple-resonance SSNMR methods probing the relative proximities of surface 1 H, 27 Al, 17 O, and 139 La nuclei, we conclude the surface to be majority terminated (80%) by AlO x with substantial (20%) LaO x terminated regions.

Materials↗
DOE OSTI2022

Epidural anesthesia needle guidance by forward-view endoscopic optical coherence tomography and deep learning

Epidural anesthesia requires injection of anesthetic into the epidural space in the spine. Accurate placement of the epidural needle is a major challenge. To address this, we developed a forward-view endoscopic optical coherence tomography (OCT) system for real-time imaging of the tissue in front of the needle tip during the puncture. We tested this OCT system in porcine backbones and developed a set of deep learning models to automatically process the imaging data for needle localization. A series of binary classification models were developed to recognize the five layers of the backbone, including fat, interspinous ligament, ligamentum flavum, epidural space, and spinal cord. The classification models provided an average classification accuracy of 96.65%. During puncture, it is important to maintain a safe distance between the needle tip and the dura mater. Regression models were developed to estimate that distance based on the OCT imaging data. Based on the Inception architecture, our models achieved a mean absolute percentage error of 3.05% ± 0.55%. Overall, our results validated the technical feasibility of using this novel imaging strategy to automatically recognize different tissue structures and measure the distances ahead of the needle tip during the epidural needle placement.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

View factor estimation of hot spot velocities in inertial confinement fusion implosions at the National Ignition Facility

nertial confinement fusion (ICF) experiments at the National Ignition Facility (NIF) suffer from asymmetries in thex-ray drive that degrade capsule performance compared to expectations for a symmetric one-dimensional implosion.Mode 1, or pole-to-pole, drive asymmetry can reduce confinement and implosion efficiency, driving a bulk motion ofthe hot spot that is detectable with neutron diagnostics. Understanding and removing sources of mode 1 asymmetry inICF implosions is important for improving performance, and the three-dimensional nature of the problem makes high-resolution radiation-hydrodynamic modeling extremely computationally expensive. This work describes a reducedorder view factor model that calculates the drive asymmetry induced by beam-to-beam variations in laser delivery andhohlraum diagnostic windows along the equator. Capsule response is estimated by coupling to a Green’s function thatrelates final hot spot velocity to the applied time-varying mode 1 asymmetry. The model makes several predictionsabout the impact of mode 1 drivers such as laser delivery and target misalignment, and achieves good agreementin both magnitude and vector direction for several shots in three families of high-performance platforms. However,notable discrepancies suggest other potential sources of mode 1 asymmetry not captured by the model are also at play

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

A large field-of-view high-resolution hard x-ray microscope using polymer optics

Here, we present an effective approach using a matched pair of polymer-based condenser-objective lenses to build a compact full-field X-ray microscope with a high spatial resolution. A unique condenser comprising arrays of high-aspect-ratio prisms with equilateral cross-section is used for uniformly illuminating samples over a large field of view (FoV) from all angles, which match the acceptance of an objective made of interdigitated orthogonal rows of one-dimensional lenses. State-of-the-art Talbot grating interferometry used to characterize these lenses for the first time revealed excellent focusing properties and minimal wave-front distortions. Using a specific lens-pair designed for 20 keV X-rays, short-exposure times, and image registration with a cross-correlation technique, we circumvent vibrational instabilities to obtain distortion-free images with a uniform resolution of 240 nm (smallest resolvable line pair) over a large FoV, 80 × 80 µm 2 in extent. The results were contrasted with those collected under illumination using commercial two-dimensional parabolic lenses with a smaller FoV. This approach implemented on a diffractometer would enable diffraction-contrast or dark-field microscopy for fast observations of ‘mesoscopic’ phenomena in real space complementing reciprocal-space studies using diffraction on the same instrument.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Expanding the momentum field of view in angle-resolved photoemission systems with hemispherical analyzers

In photoelectron spectroscopy, the measured electron momentum range is intrinsically related to the excitation photon energy. Low photon energies <10 eV are commonly encountered in laser-based photoemission and lead to a momentum range that is smaller than the Brillouin zones of most materials. This can become a limiting factor when studying condensed matter with laser-based photoemission. An additional restriction is introduced by widely used hemispherical analyzers that record only electrons photoemitted in a solid angle set by the aperture size at the analyzer entrance. Here, we present an upgrade to increase the effective solid angle that is measured with a hemispherical analyzer. We achieve this by accelerating the photoelectrons toward the analyzer with an electric field that is generated by a bias voltage on the sample. Our experimental geometry is comparable to a parallel plate capacitor, and therefore, we approximate the electric field to be uniform along the photoelectron trajectory. With this assumption, we developed an analytic, parameter-free model that relates the measured angles to the electron momenta in the solid and verify its validity by comparing with experimental results on the charge density wave material TbTe3. By providing a larger field of view in momentum space, our approach using a bias potential considerably expands the flexibility of laser-based photoemission setups.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Achieving high spatial resolution in a large field-of-view using lensless x-ray imaging

X-ray ptychography, a powerful scanning lensless imaging technique, has become attractive for nondestructively imaging internal structures at nanoscale. Stage positioning overhead in conventional step-scan ptychography is one of the limiting factors on the imaging throughput. In this work, we demonstrate the use of advanced fly scan ptychography to achieve high-resolution ptychograms of modern integrated circuits on a large field-of-view at millimeter scale. By completely removing stage overheads between scan points, the imaging time for millimeter-size sample can be significantly reduced. Furthermore, we implement the orthogonal probe relaxation technique to overcome the variation of illumination across the large scan area as well as local vibrations. The capability of x-ray ptychography shown here is broadly applicable for various studies, which requires both high spatial resolution and large scan area.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Design and simulation of multilayer coatings for a multi-channel Wolter-like x-ray imager with large field of view and high resolution

X-ray diagnostics are key instruments for understanding the physics behind inertial confinement fusion experiments. We report on the multilayer design optimization for the Toroidal X-ray Imager (TXI), a hard x-rays microscope instrument designed by Commissariat à l’énergie atomique (CEA) and Laboratoire Charles Fabry (LCF) to be installed on the National Ignition Facility. TXI includes six channels designed for three different energy bands centered on 8.7, 13, and 17.5 keV. Each channel is made up of two toroidal mirrors arranged in a Wolter-like configuration. The required field of view is 800 × 400 µm2, and the resolution should be better than 5 µm. In addition, we seek to estimate the spatial distribution of the temperature, which requires no spectral overlap of the different energy bands and a good spectral homogeneity of the image produced. The development of the multilayer coatings was performed in a two-step method. First, the coatings were optimized to obtain proper energy bands. Then, an x-ray tracing code was used to calculate the integrated optical response of each channel and adjust the response of the mirror to fulfill the requirements. To fulfill all the specifications, we propose an original design using a combination of two aperiodic coatings, one with a narrow bandwidth and the other one with a larger bandwidth.

hard x-rays↗