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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Shock propagation in aerogel and TPP foams for inertial fusion energy target design

Achieving practical inertial fusion energy (IFE) requires the development of target designs with well-characterized microstructure and compression response. We measured shock dynamics in low-density (17.5–500 mg/cm 3 ) aerogel and two-photon polymerization (TPP) foams using x-ray phase contrast imaging (XPCI) methods and the Velocity Interferometer System for Any Reflector. By analyzing shock front evolution, we examined how target type and density influence shock propagation and energy dissipation. Talbot-XPCI shows that aerogels support a smooth, bowed shock front due to their homogeneous nanometer-scale pore network. In contrast, TPP foams exhibit irregular, stepwise propagation driven by interactions with their periodic micrometer-scale lattice. Shock velocity follows a power-law relation: aerogels deviate from classical ρ −1/2 scaling due to pore-collapse dissipation, while TPP foams follow the trend with larger uncertainties from density variations. Comparisons with xRAGE simulations reveal systematic underestimation of shock speeds. These results provide the first experimental constraints on shock propagation in TPP foams over a wide density range and highlight the influence of internal structure on anisotropic shock behavior. Our findings support improved benchmarking of EOS and hydrodynamic models and inform the design of foam architectures that promote implosion symmetry in IFE capsules.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Bayesian Gaussian process inference for neutron spin echo measurement

Neutron spin echo (NSE) spectroscopy provides unique access to microscopic dynamics, but its application is often constrained by low neutron flux, long acquisition times, and significant noise. Here, we present a Bayesian inference approach based on Gaussian process regression (GPR) to reconstruct high-quality spin echo signals from sparse and noisy data by exploiting correlations in reciprocal space. Benchmarks on synthetic datasets and validation with experimental NSE measurements of dendrimers show that GPR suppresses noise, interpolates missing intensity values, and accommodates irregular observations. The method improves accuracy, shortens acquisition times, and enables high-throughput and real-time studies. Beyond NSE, the framework is broadly applicable to other low signal-to-noise ratio scattering techniques, thereby extending the scope of neutron spectroscopy.

Tung, Chi-Huan [Oak Ridge National Laboratory (ORN↗
DOE OSTI2026

A stress-based fracture model for reacting metal ejecta

The evolution of reacting metal ejecta continues to be a topic of interest at the forefront of metals in reactive and extreme environments. Ejecta are small particles formed when the surface of a metal undergoes Richtmyer–Meshkov instability from a strong shock. Experiments have shown that in the case where ejecta are in ambient conditions that induce a reaction, the ejecta behave irregularly. The ejecta temperature rises and then plateaus, and the acceleration profile shows unexpected jumps. These variations are assumed to be related to the exothermic heat release and particle mass loss caused by the reaction. To explain this phenomenon, efforts to model this in simulations have increased. While current models can capture many of these physical processes, they currently assign a constant reaction shell thickness with little physical reasoning. This work remedies this problem by assigning a dynamic physically informed shell thickness to the reacting particles, using solid analysis. The shell thickness of the particles impacts the rate of change of reacted mass in the system, as well as the rate at which the particles react. The model is based on a simple stress–strain relationship and gives a dynamic assignment for when the reacting particle should begin to fracture. We compare our model to the previous computational and simulation data to analyze the effects of different model parameters.

42 ENGINEERING↗
DOE OSTI2020

The early-stage growth and reversibility of Li electrodeposition in Br-rich electrolytes

Significance Spatial variations in chemical composition and transport properties of the material phases (interphases) formed on reactive metals in liquid electrolytes are thought to be responsible for the propensity of metal battery electrodes to electrodeposit in irregular, nonplanar morphologies. Equilibrium theoretical calculations using joint density functional analysis in vacuum and generic liquid media indicate that in-plane transport at such interphases is enhanced substantially if LiX (X = Br > Cl > F) species predominate. This study employs optical visualization experiments and nucleation theory to experimentally investigate nucleation and early-stage growth dynamics of metallic lithium in electrolytes enriched with LiBr. It is shown that the Li-Br–rich interphases formed profoundly alter the morphology of Li electrodeposits by enhancing Li-ion surface diffusion.

25 ENERGY STORAGE↗
DOE OSTI2024

Hot Hydrogen Testing of W-Coated UN Kernels in a Mo30W Matrix

Ceramic uranium mononitride (UN) is being considered as a reactor fuel for nuclear thermal propulsion. To avoid or reduce the dissociation of UN at the high temperatures needed, embedding it in a metallic matrix (cermet) has been proposed. To assess the viability of this concept, hot hydrogen testing of tungsten-coated UN kernels embedded in a Mo-30 wt% W (Mo30W) alloy matrix has been performed at temperatures from 1800°C to 2300°C. Both the isolated kernels and kernels consolidated by spark plasma sintering in the Mo30W matrix were tested. In addition to direct observations and mass loss measurements, the samples were analyzed by X-ray diffraction (XRD) and scanning electron microscopy (SEM)/energy dispersive X-ray spectroscopy (EDS) after each run. The decomposition of UN started at 1800°C despite the coating and matrix, and increased at 2000°C. Uranium seeped through the tungsten grain boundaries of the coating at all temperatures. The consolidated sample expanded irregularly at 2000°C through the formation of voids, and SEM/EDS analysis showed uranium-containing veins in the matrix consisting of U 2 Mo according to the XRD data. The observed pore generation at 2000°C was explained by the formation of water vapor from residual oxides and diffused hydrogen. At 2200°C and above, both the kernels and the consolidated samples melted through the formation of uranium or low–melting point uranium-molybdenum alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Comparative Evaluation of Spectral Methods for Robust Reactor Noise Estimation

Reactor noise analysis provides a noninvasive means to determine neutron kinetic parameters from stochastic fluctuations in detector signals. However, standard cross-power spectral density (CPSD) analyses can be sensitive to numerical processing choices, which may introduce processing-dependent systematic shifts in estimates of the prompt neutron decay constant (α) and limit reproducibility. This study uses a hybrid multitaper–Welch spectral estimator to analyze subcritical noise measurements from a fast-spectrum critical assembly. The decay constant α was extracted using three frequency-domain methods: the CPSD, the magnitude-squared coherence (MSC), and the generalized magnitude-squared coherence (GMSC). These coherence-based estimators normalize detector auto-spectral structure and are expected to reduce the sensitivity of fitted α values to processing parameters. A Sobol global sensitivity analysis identified which numerical inputs most strongly influence the fitted values of α. All estimators produced a linear dependence of α on inverse count rate, with delayed-critical extrapolations near 1.7 × 10 4 s −1 , in agreement within 8% of MCNP6.3 KOPTS benchmark calculations. Sensitivity results show that while the CPSD depends on both time-bin width and taper selection, the MSC and GMSC are dominated by time-bin width alone, indicating reduced parameter coupling and greater robustness to processing variability. These findings demonstrate the feasibility and practical value of coherence-based spectral estimators for extracting α from reactor noise and support their broader application to multi-detector and irregular datasets in subcritical system characterization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Parametric Finite Element Analysis of Naturally Corroded Steel Specimens Using 3D Surface Laser Scans

Corrosion is considered a uniform thickness reduction design guideline of the maritime industry. However, additionally, the corroded and irregular morphology of the surface affects the steel's load-bearing capacity and its impact on the strength and elongation behaviour of the steel is not yet fully understood. These effects on the local behaviour of steel structures under tensile loading were investigated with tensile tests on naturally corroded steel specimens and nonlinear finite element simulations including the corroded surface morphology with a uniform surface idealation. The models also include the deformed specimen shape. The developed approach led to highly accurate parametric finite element models predicting the ultimate tensile strength and longitudinal position of fracture. The results show that all included aspects are essential for accurate simulations, while solely the maximum available surface resolution was not as decisive.

corrosion↗
DOE OSTI2021

Random Matrix Theory in Cd isotopes

Random matrix theory (RMT) is used to provide a measure of the chaoticity (q) of calculated results for the spectra for various Cd isotopes. Here, the goal is to gain a better understanding of the internal dynamics in play; namely, whether it tracks with regular or irregular (chaotic) behavior as determined through an RMT analyses of calculated spectra. The basis-state configurations used to determine the spectra includes all positive, negative, natural (J π = 1 – , 2 + , ...), and unnatural parity configurations (J π = 0 – , 1 + , 2 – , ...), unless suppressed for comparative purposes. The results show that when intruder-state configurations are in play, regular behavior emerges, but when not in play, chaotic behavior seems to dominate the dynamics.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Hard x-ray methods for studying the structure of amorphous thin films and bulk glassy oxides

High-energy photon diffraction minimizes many of the corrections associated with laboratory x-ray diffractometers, and enables structure factor measurements to be made over a wide range of momentum transfers. The method edges us closer toward an ideal experiment, in which coordination numbers can be extracted without knowledge of the sample density. Three case studies are presented that demonstrate new hard x-ray methods for studying the structure of glassy and amorphous materials. First, the methodology and analysis of high-energy grazing incidence on thin films is discussed for the case of amorphous In 2 O 3 . Additionally, the connectivity of irregular InO 6 polyhedra are shown to exist in face-, edge- and corner-shared configurations in the approximate ratio of 1:2:3. Secondly, the technique of high-energy small and wide angle scattering has been carried out on laser heated and aerodynamically levitated samples of silica-rich barium silicate (20BaO:80SiO 2 ), from the single phase melt at 1500 C-o to the phase separated glass at room temperature. Based on Ba-O coordination numbers of 6 to 7, it is argued that the although the potential of Ba is ionic, it is weak enough to cause the liquid-liquid immiscibility to become metastable. Lastly, high-energy small and wide angle scattering has also been applied to high water content (up to 12 wt.%) samples of hydrous SiO 2 glass quenched from 1500 C-o at 4 GPa. An increase of Si 1 O 2 correlations at 4.3 angstrom is found to be consistent with an increase in the population of three-membered SiO 4 rings at the expense of larger rings.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Blue phosphorene reactivity on the Au(111) surface

Abstract The synthesis of blue phosphorene by molecular beam epitaxy (MBE) has recently come under the spotlight due to its potential applications in electronic and optoelectronic devices. However, this synthesis remains a significant challenge. The surface reactivity between the P atoms and the Au atoms should be considered for the P/Au(111) system. In the MBE process, the temperature of the substrate is a key parameter for the growth of blue phosphorene. During the initial growth stage, irregularly shaped Phosphorus clusters grow on top of Au(111) surface at room temperature. When the substrate temperature is increased, these clusters transform into a phosphorene-like structure with a honeycomb lattice. An atom exchange reaction is observed between the P and first layer Au atoms under thermal activation at higher temperature, where the P atoms replace Au atoms to form a blue phosphorene structure within the top Au layer and at the step edges.

Materials Science↗
DOE OSTI2022

Energetic particle loss mechanisms in reactor-scale equilibria close to quasisymmetry

Abstract Collisionless physics primarily determines the transport of fusion-born alpha particles in 3D equilibria. Several transport mechanisms have been implicated in stellarator configurations, including stochastic diffusion due to class transitions, ripple trapping, and banana drift-convective orbits. Given the guiding center dynamics in a set of six quasihelical and quasiaxisymmetric equilibria, we perform a classification of trapping states and transport mechanisms. In addition to banana drift convection and ripple transport, we observe substantial non-conservation of the parallel adiabatic invariant which can cause losses through diffusive banana tip motion. Furthermore, many lost trajectories undergo transitions between trapping classes on longer time scales, either with periodic or irregular behavior. We discuss possible optimization strategies for each of the relevant transport mechanisms. We perform a comparison between fast ion losses and metrics for the prevalence of mechanisms such as banana-drift convection (Velasco et al 2021 Nucl. Fusion 61 116059), transitioning orbits, and wide orbit widths. Quasihelical configurations are found to have natural protection against ripple-trapping and diffusive banana tip motion leading to a reduction in prompt losses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Turbulence-reduced high-performance scenarios in Wendelstein 7-X

In the Wendelstein 7-X (W7-X) stellarator, turbulence is the dominant transport mechanism in most discharges. This leads to a 'clamping' of ion temperature over a wide range of heating power, predominantly flat density profiles where hollow profiles driven by neoclassical thermo-diffusion would be expected and by rapid impurity transport in injection experiments. Significantly reduced turbulent transport is observed in the presence of strong core density gradients found transiently after core pellet injection and irregularly after boronisation or boron pellet injection. Density peaking is also achieved in a controlled manner in purely neutral beam heated discharges where particle transport analysis reveals an abrupt reduction in the main-ion particle flux leading to significant density profile peaking not explained by the NBI particle source alone. The plasmas exhibit a heat diffusivity of around $\chi = 0.25 \pm 0.1\,\mathrm{m}^2\ \mathrm{s}^{-1}$ at mid radius, a factor of around 4 lower than ECRH dominated discharges. Despite the improved confinement, the achieved ion temperature is limited by broader heat deposition and the lower power-per-particle given the higher density. This is overcome with limited reintroduction of ECRH power, where the low heat diffusivity diffusivity is maintained, the density rise supressed and ion temperatures above the clamping limit are achieved. The applicability of these plasmas for a high performance scenario on transport relevant time scales is assessed, including initial predictions for planned heating upgrades of W7-X, based on a range of assumptions about particle transport.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Characterizing core and edge turbulence regimes with fluctuation imaging diagnostics in Wendelstein 7-X

Two density fluctuation imaging systems, phase contrast imaging (PCI) and gas puff imaging (GPI) measure spatially resolved density fluctuations with high time resolution throughout the core plasma (PCI) and in the scrape-off layer (GPI) of the Wendelstein 7-X (W7-X) stellarator. Both systems combined give a comprehensive overview of overall fluctuation levels, spectral properties such as their distribution in frequency and wavenumber space as well as their spatial distribution. These tools are used to assess changes in density turbulence in three representative discharges that transition into stable divertor detachment by different strategies (impurity seeding, density ramping and power starvation). Several general trends are identified when the radiated power fraction is systematically increased: In the plasma edge, the line emission observed by GPI shifts radially inward with a drop in electron temperature, and normalized intensity fluctuation profiles follow this inward shift. Skewness and kurtosis of these edge fluctuations are reduced, indicating a reduction of large intermittent transport events, and poloidal phase velocities decrease in magnitude. These observations are consistent with a reduced power input into the plasma edge and a general reduction of turbulent activity. Core density fluctuation levels remain nearly constant in the impurity seeding scenario, indicating that detachment does not significantly impact turbulence there. However, a strong reduction in the dominant outboard fluctuation phase velocity is observed that deviates from the previous interpretation of neoclassical radial electric field changes, showing that the core plasma is not completely unaffected. In the density ramp and power starvation scenarios, undesirable and irregular large-scale events arise clearly in both diagnostic systems as the radiative fraction is increased. Impurity seeding therefore seems to be a promising strategy on W7-X to achieve detachment without significantly altering core turbulence, especially when targeting a specific operating point in core density and heating power.

Wendelstein 7-X↗
DOE OSTI2021

An adaptive masking method for beam halo measurement by a digital micro mirror device

We report that in high intensity particle beams, irregularities in cathode emission, scattering effects, dark current and space charge forces can lead to a common phenomenon termed beam halo with associated emittance growth, beam loss and overall beam quality degradation. It is of fundamental interest and practical importance to precisely monitor such beam halo, which could offer valuable insights into the experimental strategy for the suppression of this undesired feature. A Digital Micro mirror Device (DMD) is a computer-controlled micro-electrical-mechanical system that contains a compact array of physically independent reflective mirrors. Using a standard DMD, we come up with an adaptive masking method for halo measurement, which demonstrates superior robustness and efficiency comparing to the conventional approaches as confirmed by simulation and experimental results. Our development includes an integrated package of hardware, software and a graphic user interface (GUI) that is robust and portable and can be applied as a beam halo diagnostic for electron guns or radiating charged particle beams in general.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Graph Neural Networks for low-energy event classification & reconstruction in IceCube

IceCube, a cubic-kilometer array of optical sensors built to detect atmospheric and astrophysical neutrinos between 1 GeV and 1 PeV, is deployed 1.45 km to 2.45 km below the surface of the ice sheet at the South Pole. The classification and reconstruction of events from the in-ice detectors play a central role in the analysis of data from IceCube. Reconstructing and classifying events is a challenge due to the irregular detector geometry, inhomogeneous scattering and absorption of light in the ice and, below 100 GeV, the relatively low number of signal photons produced per event. To address this challenge, it is possible to represent IceCube events as point cloud graphs and use a Graph Neural Network (GNN) as the classification and reconstruction method. The GNN is capable of distinguishing neutrino events from cosmic-ray backgrounds, classifying different neutrino event types, and reconstructing the deposited energy, direction and interaction vertex. Based on simulation, we provide a comparison in the 1 GeV–100 GeV energy range to the current state-of-the-art maximum likelihood techniques used in current IceCube analyses, including the effects of known systematic uncertainties. For neutrino event classification, the GNN increases the signal efficiency by 18% at a fixed background rate, compared to current IceCube methods. Alternatively, the GNN offers a reduction of the background (i.e. false positive) rate by over a factor 8 (to below half a percent) at a fixed signal efficiency. For the reconstruction of energy, direction, and interaction vertex, the resolution improves by an average of 13%–20% compared to current maximum likelihood techniques in the energy range of 1 GeV–30 GeV. The GNN, when run on a GPU, is capable of processing IceCube events at a rate nearly double of the median IceCube trigger rate of 2.7 kHz, which opens the possibility of using low energy neutrinos in online searches for transient events.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Vascular dysfunction in hemorrhagic viral fevers: opportunities for organotypic modeling

The hemorrhagic fever viruses (HFVs) cause severe or fatal infections in humans. Named after their common symptom hemorrhage, these viruses induce significant vascular dysfunction by affecting endothelial cells, altering immunity, and disrupting the clotting system. Despite advances in treatments, such as cytokine blocking therapies, disease modifying treatment for this class of pathogen remains elusive. Improved understanding of the pathogenesis of these infections could provide new avenues to treatment. While animal models and traditional 2D cell cultures have contributed insight into the mechanisms by which these pathogens affect the vasculature, these models fall short in replicating in vivo human vascular dynamics. The emergence of microphysiological systems (MPSs) offers promising avenues for modeling these complex interactions. These MPS or ‘organ-on-chip’ models present opportunities to better mimic human vascular responses and thus aid in treatment development. In this review, we explore the impact of HFV on the vasculature by causing endothelial dysfunction, blood clotting irregularities, and immune dysregulation. We highlight how existing MPS have elucidated features of HFV pathogenesis as well as discuss existing knowledge gaps and the challenges in modeling these interactions using MPS. Understanding the intricate mechanisms of vascular dysfunction caused by HFV is crucial in developing therapies not only for these infections, but also for other vasculotropic conditions like sepsis.

42 ENGINEERING↗
DOE OSTI2021

The theoretical study on intermittency and propagation of geodesic acoustic mode in L-mode discharge near tokamak edge

Abstract Through a systematically developed theory, we demonstrate that the motion of Instanton identified in Zhang et al (2017 Phys. Plasmas 24 122304) is highly correlated to the intermittent excitation and propagation of geodesic acoustic mode (GAM) that is observed in tokamaks. While many numerical simulations have observed the phenomena, it is the first theory that reveals the physical mechanism behind GAM intermittent excitation and propagation. The preceding work is based on the micro-turbulence associated with toroidal ion temperature gradient mode, and slab-based phenomenological model of zonal flow. When full toroidal effect is introduced into the system, two branches of zonal flow emerge: the torus-modified low frequency zonal flow (TLFZF), and GAM, necessitating a unified exploration of GAM and TLFZF. Indeed, we observe that the transition from the Caviton to Instanton is triggered by a rapid zero-crossing of radial group velocity of drift wave and is found to be strongly correlated with the GAM onset. Many features peculiar to intermittent GAMs, observed in real machines, are thus identified in the numerical experiment. The results will be displayed in figures and in a movie; first for single central rational surface, and then with coupled multiple central rational surfaces. The periodic bursting first shown disappears as being replaced by irregular one, more similar to the intermittent characteristics observed in GAM experiments.

Physics↗
DOE OSTI2021

Graph convolutional networks applied to unstructured flow field data

Abstract Many scientific and engineering processes produce spatially unstructured data. However, most data-driven models require a feature matrix that enforces both a set number and order of features for each sample. They thus cannot be easily constructed for an unstructured dataset. Therefore, a graph based data-driven model to perform inference on fields defined on an unstructured mesh, using a graph convolutional neural network (GCNN) is presented. The ability of the method to predict global properties from spatially irregular measurements with high accuracy is demonstrated by predicting the drag force associated with laminar flow around airfoils from scattered velocity measurements. The network can infer from field samples at different resolutions, and is invariant to the order in which the measurements within each sample are presented. The GCNN method, using inductive convolutional layers and adaptive pooling, is able to predict this quantity with a validation R 2 above 0.98, and a Normalized Mean Squared Error below 0.01, without relying on spatial structure.

Ogoke, Francis (ORCID:0000000224327783)↗