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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Synchrotron radiation from Neptune - Neptune's magnetic field and electron population

On the basis of radio measurements of Neptune at 20 cm, one can infer the presence of about 0.4 mJy synchrotron radiation. By assuming a dipole-like magnetic field, with the energetic electrons confined to the magnetic equator, Neptune's magnetic dipole moment is estimated. Its electron population should be between that in Uranus' and Jupiter's magnetospheres. If the electrons are injected by the solar wind, local acceleration processes in the magnetosphere are required to energize the particles, because adiabatic diffusion alone is not sufficient.

De Pater, Imke↗
NASA NTRS1990

Forecast model applications of retrieved three dimensional liquid water fields

Forecasts are made for tropical storm Emily using heating rates derived from the SSM/I physical retrievals described in chapters 2 and 3. Average values of the latent heating rates from the convective and stratiform cloud simulations, used in the physical retrieval, are obtained for individual 1.1 km thick vertical layers. Then, the layer-mean latent heating rates are regressed against the slant path-integrated liquid and ice precipitation water contents to determine the best fit two parameter regression coefficients for each layer. The regression formulae and retrieved precipitation water contents are utilized to infer the vertical distribution of heating rates for forecast model applications. In the forecast model, diabatic temperature contributions are calculated and used in a diabatic initialization, or in a diabatic initialization combined with a diabatic forcing procedure. Our forecasts show that the time needed to spin-up precipitation processes in tropical storm Emily is greatly accelerated through the application of the data.

Raymond, William H.↗
NASA NTRS2022

X-ray Polarization Detection of Cassiopeia A with IXPE

We report on a ∼5σ detection of polarized 3–6 keV X-ray emission from the supernova remnant Cassiopeia A (Cas A) with the Imaging X-ray Polarimetry Explorer (IXPE). The overall polarization degree of 1.8% ± 0.3% is detected by summing over a large region, assuming circular symmetry for the polarization vectors. The measurements imply an average polarization degree for the synchrotron component of ∼2.5%, and close to 5% for the X-ray synchrotron-dominated forward shock region. These numbers are based on an assessment of the thermal and nonthermal radiation contributions, for which we used a detailed spatial-spectral model based on Chandra X-ray data. A pixel-by-pixel search for polarization provides a few tentative detections from discrete regions at the ∼ 3σ confidence level. Given the number of pixels, the significance is insufficient to claim a detection for individual pixels, but implies considerable turbulence on scales smaller than the angular resolution. Cas A's X-ray continuum emission is dominated by synchrotron radiation from regions within ≲1017 cm of the forward and reverse shocks. We find that (i) the measured polarization angle corresponds to a radially oriented magnetic field, similar to what has been inferred from radio observations; (ii) the X-ray polarization degree is lower than in the radio band (∼5%). Since shock compression should impose a tangential magnetic-field structure, the IXPE results imply that magnetic fields are reoriented within ∼1017 cm of the shock. If the magnetic-field alignment is due to locally enhanced acceleration near quasi-parallel shocks, the preferred X-ray polarization angle suggests a size of 3 × 1016 cm for cells with radial magnetic fields.

Polarimetry↗
DOE OSTI2020

Optimization of DARHT Axis 1 Injector Voltage

The Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility provides flash radiography capabilities using two electron Linear Induction Accelerators (LIA’s). Axis-1 of DARHT produces a 20- MeV, 2-kA, 80-ns-FWHM electron beam. The strict requirements for flash radiography require a detailed understanding of the LIA’s performance, including precision measurements of the injector electron beam energy. The technique for time resolved measurement of the electron beam energy using electron Permanent Magnet Spectrometer (ePMSpec) has been developed. The electron energy then is used to infer the voltage produced by the injector pulsed power. The injector pulsed power of DARHT I consists of a 1.5-MV, glycol-insulated Blumlein that is pulsecharged by a step-up transformer and switched by four, laser-triggered spark gaps. A series of increasing impedance transmission lines are used to transform the output voltage of the Blumlein to a maximum of 3.8MV at the diode. Figure 1a shows a graphic of the Axis-1 prime power tank, Blumlein and downstream transmission lines. The injector pulse power is designed to produce voltage on a velvet cathode located in the vacuum vessel. The specifications of the voltage-pulse flat-top over 60ns is +/-1%. A key element in the high-voltage circuit is the ethylene glycol Blumlein. The outer volume, adjacent to the laser triggered switches of the Blumlein, is a peaking capacitor. This is an independent volume that contains a mixture of ethylene glycol and water to make it an adjustable capacitor of 380 to 750 pF.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Water structure and electric fields at the interface of oil droplets

Interfacial water exhibits rich and complex behaviour, playing an important part in chemistry, biology, geology and engineering. However, there is still much debate on the fundamental properties of water at hydrophobic interfaces, such as orientational ordering, the concentration of hydronium and hydroxide, improper hydrogen bonds and the presence of large electric fields. This controversy arises from the challenges in measuring interfacial systems, even with the most advanced experimental techniques and theoretical approaches available. Here we report on an in-solution, interface-selective Raman spectroscopy method using multivariate curve resolution to probe hexadecane-in-water emulsions, aided by a monomer-field theoretical model for Raman spectroscopy. Our results indicate that oil-water emulsion interfaces can exhibit reduced tetrahedral order and weaker hydrogen bonding, along with a substantial population of free hydroxyl groups that experience about 95 cm -1 redshift in their stretching mode compared with planar oil-water interfaces. Given the known electrostatic zeta potential characteristic of oil droplets, we propose the existence of a strong electric field (about 50-90 MV cm -1 ) emanating from the oil phase. This field is inferred indirectly but supported by control experiments and theoretical estimates. These observations are either absent or opposite in the molecular hydrophobic interface formed by small solutes or at planar oil-water interfaces. Instead, water structural disorder and enhanced electric fields emerge as unique features of the mesoscale interface in oil-water emulsions, potentially contributing to the accelerated chemical reactivity observed at hydrophobic-water interfaces.

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

Shell structure in 32P

The nuclear structure of 32P was investigated by detecting multi-γ coincidences along with charged light ions following the bombardment of an 18O target with a 30-MeV 16O beam from the Florida State University accelerator facility using the Clarion2-Trinity array of Clover γ spectrometers and GAGG (Gd-Al-Ga-garnet) scintillators for charged particles. A number of new states up to 12 MeV excitation and spins up to 9+ were observed by their γ decay patterns. Spins and parities were assigned by comparing measured γ angular distributions with polarizations inferred from Compton-scattering asymmetries between the Ge crystals in the Clover spectrometers. The new level scheme of 32P compares well with shell model calculations using the FSU cross-shell interaction and reasonably well with those using the sdpf-m interaction. In particular, structures with higher spin arise from promotion of more nucleons up to the f-p shell.

Allmond, James [ORNL] (ORCID:0000000165338721)↗
DOE OSTI2022

Autodifferentiable Spectrum Model for High-dispersion Characterization of Exoplanets and Brown Dwarfs

We present an autodifferentiable spectral modeling of exoplanets and brown dwarfs. This model enables a fully Bayesian inference of the high-dispersion data to fit the ab initio line-by-line spectral computation to the observed spectrum by combining it with the Hamiltonian Monte Carlo in recent probabilistic programming languages. An open-source code, ExoJAX, developed in this study, was written in Python using the GPU/TPU compatible package for automatic differentiation and accelerated linear algebra, JAX. We validated the model by comparing it with existing opacity calculators and a radiative transfer code and found reasonable agreements for the output. As a demonstration, we analyzed the high-dispersion spectrum of a nearby brown dwarf, Luhman 16 A, and found that a model including water, carbon monoxide, and H 2 /He collision-induced absorption was well fitted to the observed spectrum (R = 10 5 and 2.28-2.30 μm). As a result, we found that T0 = 1295$^{-32}_{+35}$ K at 1 bar and C/O = 0.62 ± 0.03, which is slightly higher than the solar value. This work demonstrates the potential of a full Bayesian analysis of brown dwarfs and exoplanets as observed by high-dispersion spectrographs and also directly imaged exoplanets as observed by high-dispersion coronagraphy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Bubble Chamber Detectors with Light Nuclear Targets: A Snowmass 2021 White Paper

Neutrino cross sections are a critical ingredient in experiments that depend on neutrino scattering to reconstruct event kinematics and infer neutrino characteristics, like NOvA and T2K. An opportunity exists to reduce the 5-10% broad uncertainty on neutrino cross sections by producing more measurements of neutrino scattering from light nuclear targets at the relevant energies. Bubble chambers with light nuclear targets would be ideal for these measurements but the most recent device designed for use with an accelerator neutrino source is at least fifty years old. A new bubble chamber with light nuclear targets could be designed by observing how the technology has progressed for use in dark matter experiments and producing smaller modular devices that use more efficient cooling systems. A smaller modular device could also be designed for deployment to all functioning neutrino beams, but an investigation of the proper operating characteristics is necessary to adapt newer detectors to the structure of contemporary neutrino beams.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2003

Three-Dimensional MHD Modeling of The Solar Corona and Solar Wind: Comparison with The Wang-Sheeley Model

We present simulation results from a tilted-dipole steady-state MHD model of the solar corona and solar wind and compare the output from our model with the Wang-Sheeley model which relates the divergence rate of magnetic flux tubes near the Sun (inferred from solar magnetograms) to the solar wind speed observed near Earth and at Ulysses. The boundary conditions in our model specified at the coronal base and our simulation region extends out to 10 AU. We assumed that a flux of Alfven waves with amplitude of 35 km per second emanates from the Sun and provides additional heating and acceleration for the coronal outflow in the open field regions. The waves are treated in the WKB approximation. The incorporation of wave acceleration allows us to reproduce the fast wind measurements obtained by Ulysses, while preserving reasonable agreement with plasma densities typically found at the coronal base. We find that our simulation results agree well with Wang and Sheeley's empirical model.

Usmanov, A. V.↗
NASA NTRS2017

The Refined Shock Velocity of the X-Ray Filaments in the RCW 86 Northeast Rim

A precise measurement of shock velocities is crucial for constraining the mechanism and efficiency of cosmic-ray (CR) acceleration at supernova remnant (SNR) shock fronts. The northeastern rim of the SNR RCW 86 is thought to be a particularly efficient CR acceleration site, owing to the recent result in which an extremely high shock velocity of 6000 km s1 was claimed. Here, we revisit the same SNR rim with the Chandra X-ray Observatory, 11 years after the first observation. This longer baseline than previously available allows us to determine a more accurate proper motion of the nonthermal X-ray filament, revealing a much lower velocity of 3000 340 km s1 (and even slower at a brighter region). Although the value has dropped to one-half of that from the previous X-ray measurement, it is still higher than the mean velocity of the H filaments in this region (1200 km s1). This discrepancy implies that the filaments bright in nonthermal X-rays and H emission trace different velocity components, and thus a CR pressure constrained by combining the X-ray kinematics and the H spectroscopy can easily be overestimated. We also measure the proper motion of the thermal X-ray filament immediately to the south of the nonthermal one. The inferred velocity (720 360 km s1) is significantly lower than that of the nonthermal filament, suggesting the presence of denser ambient material, possibly a wall formed by a wind from the progenitor, which has drastically slowed down the shock.

acceleration of particles - ISM: individuals objec↗
DOE OSTI2025

Analog Systems for Edge Optimization

Over the past decade, analog computing has the subject of substantial research interest providing a path toward improved computational efficiency in the post-Dennard era. Analog matrix vector multiplication (MVM) accelerators provide a popular approach given the ubiquity of MVM operations in numerous applications. However, historically analog computing systems can struggle with applications requiring high precision due to the inherent susceptibility of these systems to analog non-idealities. Therefore, prior work on analog systems has focused either on applications known to be tolerant of limited precision (e.g., neural network inference), or using expensive techniques to emulate high-precision using many analog MVM operations. In this work, we propose an alternative approach. Motivated by recent advances in inexact nonlinear solvers and optimizers, we explore the potential of co-designing optimization algorithms which can take full advantage of the fundamentally inexact analog MVM operations. To enable these co-designed algorithms we also develop a general mathematical theory of the precision and energy efficiency of analog operations, and a new system architecture for tightly-coupled analog and digital computation. Finally, we examine the applicability of analog computing to a wider class of symmetric positive definite systems and find potential in using analog operations as a sparse approximate inverse preconditioner. With these core innovations, this project provides a path toward effectively implementing optimization algorithms on power-constrained autonomous and semi-autonomous systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2008

STEREO/SECCHI Stereoscopic Observations Constraining the Initiation of Polar Coronal Jets

We report on the first stereoscopic observations of polar coronal jets made by the EUVI/SECCHI imagers on board the twin STEREO spacecraft. The significantly separated viewpoints (approximately 11 degrees ) allowed us to infer the 3D dynamics and morphology of a well-defined EUV coronal jet for the first time. Triangulations of the jet's location in simultaneous image pairs led to the true 3D position and thereby its kinematics. Initially the jet ascends slowly at approximately equal to 10-20 kilometers per second and then, after an apparent 'jump' takes place, it accelerates impulsively to velocities exceeding 300 kilometers per second with accelerations exceeding the solar gravity. Helical structure is the most important geometrical feature of the jet which shows evidence of untwisting. The jet structure appears strikingly different from each of the two STEREO viewpoints: face-on in the one viewpoint and edge-on in the other. This provides conclusive evidence that the observed helical structure is real and is not resulting from possible projection effects of single viewpoint observations. The clear demonstration of twisted structure in polar jets compares favorably with synthetic images from a recent MHD simulation of jets invoking magnetic untwisting as their driving mechanism. Therefore, the latter can be considered as a viable mechanism for the initiation of polar jets.

Patsourakos, S.↗
DOE OSTI2021

High-energy emission from a magnetar giant flare in the Sculptor galaxy

Magnetars are the most highly magnetized neutron stars in the cosmos (with magnetic field 10 13 –10 15 G). Giant flares from magnetars are rare, short-duration (about 0.1 s) bursts of hard X-rays and soft γ rays. Owing to the limited sensitivity and energy coverage of previous telescopes, no magnetar giant flare has been detected at gigaelectronvolt (GeV) energies. Here, we report the discovery of GeV emission from a magnetar giant flare on 15 April 2020 (refs. 3,4 and A. J. Castro-Tirado et al., manuscript in preparation). The Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope detected GeV γ rays from 19 s until 284 s after the initial detection of a signal in the megaelectronvolt (MeV) band. Our analysis shows that these γ rays are spatially associated with the nearby (3.5 megaparsecs) Sculptor galaxy and are unlikely to originate from a cosmological γ-ray burst. Thus, we infer that the γ rays originated with the magnetar giant flare in Sculptor. Furthermore, we suggest that the GeV signal is generated by an ultra-relativistic outflow that first radiates the prompt MeV-band photons, and then deposits its energy far from the stellar magnetosphere. After a propagation delay, the outflow interacts with environmental gas and produces shock waves that accelerate electrons to very high energies; these electrons then emit GeV γ rays as optically thin synchrotron radiation. This observation implies that a relativistic outflow is associated with the magnetar giant flare, and suggests the possibility that magnetars can power some short γ-ray bursts.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1976

Dynamics of the Jovian magnetosphere and energetic particle radiation

Inferences are drawn from Jovian magnetosphere data acquired in the flybys of Pioneer 10 and Pioneer 11. Data on the outer magnetosphere and the inner core, and on observed 10-hr variations in particle intensity, are summarized, with attention given to the immense size and complexity of the magnetosphere and the behavior of trapped charged particles. The data support the maintenance and acceleration of charged particles trapped in Jupiter's magnetic field by inward diffusion in violation of the third adiabatic invariant. Prodigious quantities of high-energy particles are found to escape from Jupiter into interplanetary space, and MHD waves in the circumjovian plasma are considered. Whether the 10-hr variations are spatial or temporal in origin is weighed in favor of the latter. Production and loss mechanisms for the particles, and the nature of the Jovian magnetosphere itself, are noted among questions remaining obscure.

Simpson, J. A.↗
DOE OSTI2023

Adaptive learning-driven high-throughput synthesis of oxygen reduction reaction Fe–N–C electrocatalysts

Reducing human reliance on inefficient energy systems and fossil fuels has become more urgent due to the consequences of global climate change. However, traditional trial-and-error approaches have hampered our ability to accelerate the discovery and implementation of functional materials for efficient energy conversion devices, such as polymer electrolyte fuel cells (PEFCs). To address this, we develop an adaptive learning framework that integrates machine learning and state-of-the-art capabilities in high-throughput synthesis to achieve expedited optimization of iron-nitrogen-carbon PEFC oxygen reduction reaction (ORR) electrocatalysts. We use statistical inference, uncertainty quantification, and global optimization to build a computational design-of-experiment tool that identifies the optimum compositions to be investigated next to reduce the demands placed on experimental materials discovery. We benchmark the ability of the proposed strategy to discover optimum catalyst synthesis conditions in a six-dimensional search space when starting with a thirty-six-sample database. By following the adaptive learning strategy, we synthesize fourteen new catalysts from approximately ten billion unique compositions and discover four catalysts that outperform all original samples. The best machine learning-optimized catalyst is 33% more active than the highest-performing one in the initial database, showing an ORR activity seven times larger than those typically reported for the same class of materials.

36 MATERIALS SCIENCE↗
NASA NTRS2016

Structure and Composition of the Distant Lunar Exosphere: Constraints from ARTEMIS Observations of Ion Acceleration in Time-Varying Fields

By analyzing the trajectories of ionized constituents of the lunar exosphere in time-varying electromagnetic fields, we can place constraints on the composition, structure, and dynamics of the lunar exosphere. Heavy ions travel slower than light ions in the same fields, so by observing the lag between field rotations and the response of ions from the lunar exosphere, we can place constraints on the composition of the ions. Acceleration, Reconnection, Turbulence, and Electrodynamics of Moon's Interaction with the Sun (ARTEMIS) provides an ideal platform to utilize such an analysis, since its two-probe vantage allows precise timing of the propagation of field discontinuities in the solar wind, and its sensitive plasma instruments can detect the ion response. We demonstrate the utility of this technique by using fully time-dependent charged particle tracing to analyze several minutes of ion observations taken by the two ARTEMIS probes ~3000-5000 km above the dusk terminator on 25 January 2014. The observations from this time period allow us to reach several interesting conclusions. The ion production at altitudes of a few hundred kilometers above the sunlit surface of the Moon has an unexpectedly significant contribution from species with masses of 40 amu or greater. The inferred distribution of the neutral source population has a large scale height, suggesting that micrometeorite impact vaporization and/or sputtering play an important role in the production of neutrals from the surface. Our observations also suggest an asymmetry in ion production, consistent with either a compositional variation in neutral vapor production or a local reduction in solar wind sputtering in magnetic regions of the surface.

Moon↗
DOE OSTI2025

Basic Research Needs for Inverse Methods for Complex Systems under Uncertainty

Inverse problems, which aim to infer unknown properties of a system using experimental and observational data, are central to addressing many of the U.S. Department of Energy’s (DOE) most critical scientific and engineering challenges. Accurate, computationally efficient, and data-efficient solutions to inverse problems are essential for advancing DOE mission-critical science drivers, including analyzing data from large-scale experimental facilities, optimizing fusion reactor performance, accelerating materials discovery, enhancing geophysical imaging, improving wildfire predictions, and enabling autonomous systems and digital twins. However, these problems are becoming increasingly complex, often involving nonlinear, highdimensional, and interconnected systems and models that span multiple physics and scales, while relying on data with varying quantity, quality, and information content. Compounding these challenges is the uncertainty inherent in DOE-relevant systems, where errors in inputs, noise in data, incompleteness of data, and discrepancies between models and reality constrain the accuracy and precision of solutions. At the same time, the convergence of recent scientific computing trends—scientific machine learning, artificial intelligence, and computing advances such as exascale computing—is creating unprecedented opportunities for tackling these challenges. The cross-cutting nature of inverse problems, combined with their growing complexity and rapidly evolving data and algorithmic demands, strongly motivates the formulation of a prioritized research agenda to maximize their capabilities and impact. In response to this need, DOE’s Advanced Scientific Computing Research (ASCR) program in the Office of Science convened the Workshop on Basic Research Needs for Inverse Problems for Complex Systems Under Uncertainty in June 2025. This workshop brought together experts across disciplines to identify grand challenges and major opportunities in the field. Through collaborative discussions, the workshop defined transformative research directions aimed at addressing the mathematical, statistical, and computational challenges posed by inverse problems under uncertainty. As a result of these efforts, four priority research directions (PRDs) were identified to guide future research and development in this area. These PRDs, summarized below, represent a roadmap for advancing the foundational science and mathematics of inverse problems, enabling robust, scalable, and uncertainty-aware solutions that are critical for DOE applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Bridging Cloud and Edge Computing at NREL Using CONNECT: Cloud Optimized Networking for Next-Gen Edge Computing Technologies [Slides]

CONNECT is an innovative on-premise hardware and software solution that integrates edge and cloud computing infrastructure at NREL. Built on the AWS Greengrass middleware and leveraging the MQTT protocol, CONNECT enables real-time data streaming from IoT devices and gateways to both cloud and local services, empowering researchers to rapidly capture, analyze, and act upon edge-generated data while leveraging cloud capabilities. The platform addresses research infrastructure challenges by providing a pre-approved platform which is already configured with the correct networking and cybersecurity baselines thus eliminating procurement delays and enabling on-demand availability. CONNECT's hybrid architecture efficiently manages burstable workloads, allowing research teams to dynamically scale computational capacity, handle peak data loads, and reduce operational bottlenecks. Advanced capabilities include built-in GPU support for executing machine learning models which enables low-latency inference at the edge from models trained in the cloud. This architecture supports real-time analytics and filtering, providing a mechanism to allow only transmitting and processing high-value data. Cloud-based configuration management permits engineers to manage on-premise systems remotely, optimizing operational efficiency. By bridging edge and cloud computing, CONNECT provides NREL researchers with a flexible, scalable platform that accelerates scientific discovery while maintaining robust security and performance standards.

97 MATHEMATICS AND COMPUTING↗