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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Improvement of hot-electron and gamma-ray yields by selecting preplasma thickness for a target irradiated by a short laser pulse

The dependences of the temperature and the number of hot electrons on the size of the plasma corona of a thin foil target irradiated by a short relativistically intense laser pulse are investigated by three-dimensional numerical simulations. For a 30-fs long laser pulse with an energy of 300 mJ we have determined the optimal preplasma size which maximises the yield of forward-accelerated electrons capable of generating gamma-ray photons several MeV in energy. A study is made of gamma-ray generation by such laser-accelerated electrons in the bombardment of a converter target placed behind the laser target; the brightness of this gamma-ray source is shown to range up to 10{sup 15} photons s{sup −1} mrad{sup −2} mm{sup −2} × (0.1 % BW){sup −1}. (paper)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1989

Demonstration of sub-meter GPS orbit determination and 1.5 parts in 10 to the 8th three-dimensional baseline accuracy

Strategies for the estimation of precise GPS orbits and ground baselines, designed to minimize error sources related to the GPS orbit accuracy and the tropospheric delay, are demonstrated. Using GPS data from field experiments conducted in 1985 and 1986, it is shown that, by carefully selecting well-known stations to serve as reference points and by using the GPS data to determine high-accuracy GPS orbits and to solve for wet tropospheric delay fluctuations, the 2000-km baselines in North America can now be estimated with the accuracy better than 1.5 parts in 10 to the 8th. Using these strategies, better than l-m accuracy was achieved for the two best-tracked satellites (of the seven total operational GPS satellites).

Lichten, Stephen M.↗
DOE OSTI2015

New modeling of galactic proton modulation during the minimum of solar cycle 23/24

During the recent prolonged solar minimum of cycle 23/24, the PAMELA detector measured 27-day averaged Galactic proton energy spectra over the energy range that is important for solar modulation. By comparing these spectra to computed spectra from a three-dimensional model that contains all of the important heliospheric modulation processes, the recent minimum can be studied in detail from a modulation perspective. This was done by setting up a realistic heliosphere in the model, and reproducing a representative selection of seven intermittent PAMELA spectra, separated by approximately six months, from 2006 July to 2009 December. Additionally, a new very local interstellar proton spectrum was constructed using measurements below 600 MeV from Voyager 1, taken beyond the heliopause, combined with PAMELA and AMS-02 measurements above 30 GeV at the Earth. As a result of the extreme minimum modulation conditions that governed the recent solar minimum, the highest ever Galactic cosmic ray spectrum at Earth was observed by PAMELA at the end of 2009. It was found that, apart from the self-consistent changes in the heliospheric current sheet and the heliospheric magnetic field over time, additional increases in the mean free paths during this period were required below ∼4 GV in order to reproduce the intensities observed by PAMELA.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A Computational Information Criterion for Particle-Tracking with Sparse or Noisy Data

Traditional probabilistic methods for the simulation of advection-diffusion equations (ADEs) often overlook the entropic contribution of the discretization, e.g., the number of particles, within associated numerical methods. Many times, the gain in accuracy of a highly discretized numerical model is outweighed by its associated computational costs or the noise within the data. Herein, we address the question of how many particles are needed in a simulation to best approximate and estimate parameters in one-dimensional advective-diffusive transport. To do so, we use the well-known Akaike Information Criterion (AIC) and a recently-developed correction called the Computational Information Criterion (COMIC) to guide the model selection process. Random-walk and mass-transfer particle tracking methods are employed to solve the model equations at various levels of discretization. Numerical results demonstrate that the COMIC provides an optimal number of particles that can describe a more efficient model in terms of parameter estimation and model prediction compared to the model selected by the AIC even when the data is sparse or noisy, the sampling volume is not uniform throughout the physical domain, or the error distribution of the data is non-IID Gaussian.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

In situ visualisation of zeolite anisotropic framework flexibility during catalysis

Zeolites exhibit framework flexibility driving their chemical and catalytic properties. Since the zeolitic pores are extremely small, a slight strain generated in the crystal induces compelling changes in shape, connectivity, accessibility, and the framework chemical properties. These modifications affected the adsorption and desorption of reactants/products and the diffusion within the channels during reaction. Using in situ 3D Bragg coherent X-ray diffraction imaging, we unveil the dynamics of the zeolite structure during catalysis, contraction and/or expansion of its framework also known as zeolite framework flexibility. Here, we imaged three-dimensionally a single faujasite zeolite crystal during the ethanol dehydration reaction revealing anisotropic lattice dynamics simultaneously to guest molecules formation. Understanding zeolite flexibility could permit to tune zeolites properties towards potentially higher adsorption and selectivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Microstructural Analysis of Additively Manufactured 304L Stainless Steel Oxide Dispersion Strengthened Alloy

Selective laser melting (SLM) is one of the additive manufacturing (AM) process that utilizes laser for selectively melting and fusing of a thin layer of powder. This technique allows manufacturing a part directly from computer-aided design (CAD) models by dividing the part into a set of two-dimensional slices, which are built sequentially on top of another. Here, SLM technology enables manufacturing of complex geometries, such as parts with inner cooling channels which could be difficult or time consuming to make by conventional manufacturing processes.

36 MATERIALS SCIENCE↗
DOE OSTI2025

MgO Nanostructures on Au(111) as Catalysts for Low-Temperature Methane Activation and C-C Coupling

The selective conversion of methane (CH4) under mild conditions remains challenging due to strong C-H bonds and catalyst coking. We systematically investigated sub-monolayer MgO nanostructures on Au(111), where two-dimensional (2D) MgO islands with stable Mg-O-Au interfaces catalyze low-temperature CH4 activation and C-C coupling. Upon CH4 exposure at 300 K, surface-bound CHx and C2Hx intermediates formed and persisted post-evacuation, indicating robust CHx-O-Mg linkages. Temperature-programmed studies revealed that C-H activation and C-C coupling intensify with heat: the CHx signal grew continuously while the C2Hx signal reached a plateau at 400-500 K. O 1s and Mg 2p attenuation confirmed adsorption of the hydrocarbons on MgO. Catalytic tests at 500 K yielded C2H6 (70%) and C2H4 (30%) without coking, underscoring MgO's role as an active catalyst. These results offer new design principles for developing coke-resistant and low-temperature methane upgrading catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Temperature-Controlled Rotational Epitaxy of Graphene

When graphene is placed on a crystalline surface, the periodic structures within the layers superimpose and moiré superlattices form. Small lattice rotations between the two materials in contact strongly modify the moiré lattice parameter, upon which many electronic, vibrational, and chemical properties depend. While precise adjustment of the relative orientation in the degree- and sub-degree-range can be achieved via careful deterministic transfer of graphene, we report on the spontaneous reorientation of graphene on a metallic substrate, Ir(111). Here, we find that selecting a substrate temperature between 1530 and 1000 K during the growth of graphene leads to distinct relative rotational angles of 0°, ± 0.6°, ±1.1°, and ±1.7°. When modeling the moiré superlattices as two-dimensional coincidence networks, we can ascribe the observed rotations to favorable low-strain graphene structures. The dissimilar thermal expansion of the substrate and graphene is regarded as an effective compressive biaxial pressure that is more easily accommodated in graphene by small rotations rather than by compression.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Multilayered Ordered Protein Arrays Self-Assembled from a Mixed Population of Virus-like Particles

Biology shows many examples of spatially controlled assembly of cells and biomacromolecules into hierarchically organized structures, to which many of the complex biological functions are attributed. While such biological structures have inspired the design of synthetic materials, it is still a great challenge to control the spatial arrangement of individual building blocks when assembling multiple types of components into bulk materials. Here, in this study, we report self-assembly of multilayered, ordered protein arrays from mixed populations of virus-like particles (VLPs). We systematically tuned the magnitude of the surface charge of the VLPs via mutagenesis to prepare four different types of VLPs for mixing. A mixture of up to four types of VLPs selectively assembled into higher-order structures in the presence of oppositely charged dendrimers during a gradual lowering of the ionic strength of the solution. The assembly resulted in the formation of three-dimensional ordered VLP arrays with up to four distinct layers including a central core, with each layer comprising a single type of VLP. A coarse-grained computational model was developed and simulated using molecular dynamics to probe the formation of the multilayered, core-shell structure. Our findings establish a simple and versatile bottom-up strategy to synthesize multilayered, ordered materials by controlling the spatial arrangement of multiple types of nanoscale building blocks in a one-pot fabrication.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Dissociative double-photoionization of butadiene in the 25-45 eV energy range using 3-D multi-coincidence ion momentum imaging spectrometry

Dissociative double-photoionization of butadiene in the 25-45 eV energy range has been studied with tunable synchrotron radiation using full three-dimensional ion momentum imaging. Using ab initio calculations, the electronic states of the molecular dication below 33 eV are identified. The results of the measurement and calculation show that double ionization from π orbitals selectively triggers twisting about the terminal or central C–C bonds. We show that this conformational rearrangement depends upon the dication electronic state, which effectively acts as a gateway for the dissociation reaction pathway. For photon energies above 33 eV, three-body dissociation channels where neutral H-atom evaporation precedes C–C charge-separation in the dication species appear in the correlation map. The fragment angular distributions support a model where the dication species is initially aligned with the molecular backbone parallel to the polarization vector of the light, indicating a high probability for double-ionization to the “gateway states” for molecules with this orientation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Unveiling the spatial distribution of molecular coherences at conical intersections by covariance X-ray diffraction signals

Significance Monitoring the real-space motion of the electrons directly involved in ultrafast molecular dynamics is a challenging goal, hindered by the strong contributions of the remaining inactive electrons. Molecular quantum coherences can provide a direct window into elementary electronic dynamics, but they could not be separately imaged so far. Here, we demonstrate a time- and frequency-resolved X-ray diffraction technique, which can employ existing stochastic X-ray pulses to separately image the coherence contributions. The technique can selectively follow the relevant electrons involved in the ultrafast dynamics and identify the confined molecular regions covered by their motion. It enables readily feasible measurements and can be straightforwardly extended to full three-dimensional imaging via X-ray and electron diffraction.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2026

Edge Reconstruction in a Quantum Spin Hall Insulator

We study interaction-driven edge reconstruction in a quantum spin Hall insulator described by the Bernevig-Hughes-Zhang model with Kanamori-Hubbard interactions using the real-space density matrix renormalization group method in both the grand-canonical and canonical ensembles. For a two-dimensional cylinder with a smooth edge, we identify discrete particle-number transitions that lead to a spin-polarized edge state stabilized by an emergent ferromagnetic exchange interaction. The reconstruction is orbital-selective, occurring predominantly in the 𝑠-orbital channel. Our results reveal a microscopic mechanism for emergent fluctuating moments at the edge that could compromise the topological protection of helical edge states by time-reversal symmetry.

Soni, Rahul [ORNL] (ORCID:0000000317714299)↗
DOE OSTI2015

Diffuse magnetic neutron scattering in the highly frustrated double perovskite Ba 2 YRuO 6

Here we investigated diffuse magnetic scattering in the highly frustrated double perovskite Ba 2 YRuO 6 using polarized neutrons. Consistent with previous reports, the material shows two apparent transitions at 47 and 36 K to an eventual type I face-centered-cubic magnetic ground state. The (100) magnetic reflection shows different behavior from the five other observed reflections upon heating from 1.8 K, with the former broadening well beyond the resolution limit near 36 K. Closer examination of the latter group reveals a small, but clear, increase in peak widths between 36 and 47 K, indicating that this regime is dominated by short-range spin correlations. Diffuse magnetic scattering persists above 47 K near the position of (100) to at least 200 K, consistent with strong frustration. Reverse Monte Carlo (RMC) modeling of the diffuse scattering from 45 to 200 K finds that the spin-spin correlations between nearest and next-nearest neighbors are antiferromagnetic and ferromagnetic, respectively, at temperatures near the upper ordering temperature, but both become antiferromagnetic and of similar magnitude above 100 K. The significance of this unusual crossover is discussed in light of the super-superexchange interactions between nearest and next-nearest neighbors in this material and the demands of type I order. The dimensionality of the correlations is addressed by reconstructing the scattering in the (hk0) plane using the RMC spin configurations. This indicates that one-dimensional spin correlations dominate at temperatures close to the first transition. In addition, a comparison between mean-field calculations and (hk0) scattering implies that further neighbor couplings play a significant role in the selection of the ground state. Finally, the results and interpretation are compared with those recently published for monoclinic Sr 2 YRuO 6 , and similarities and differences are emphasized.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Wildfire Mapping in Interior Alaska Using Deep Neural Networks on Imbalanced Datasets

Wildfires are the dominant disturbance impacting many regions in Alaska and is expected to intensify due to climate change. Accurate tracking and quantification of wildfires are important for climate modeling and ecological studies in this region. Remote sensing platforms (e.g., MODIS, Landsat) are an important tool for mapping wildfires in Alaska at varying spatial and temporal scales. Deep neural networks (DNN) have shown superior performance in many classification problems such as high-dimensional remote sensing data. Detection of wildfires is an imbalanced classification problem where one class contains a much smaller or larger sample size and DNNs performance can decline. We take a known weight-selection strategy during DNN training and apply them to MODIS variables (e.g., NDVI, surface reflectance) for a binary classification (i.e., wildfire or no-wildfire) across Alaska during the 2004 wildfire year, which is one of the largest on record. The method splits the input training data into sets, one for training the DNN to update weights and the other that splits into a validation set that is equally balanced between the wildfire and no-wildfire class. The performance is monitored on the validation set to select the weights based on the best validation-loss score. This approach was applied to two sampled datasets, such as where the no-wildfire class can significantly outweigh the wildfire class. The normal DNN training strategy was unable to map wildfires for the highly imbalanced dataset, however, the weight-selection strategy was able to map wildfires very accurately (0.96 recall score for 78,702 wildfire pixels (500×500 m)).

Langford, Zach↗
DOE OSTI2020

Parallel Lattice Subpaving Map (plsm)

Custom spatial subdivision of N-dimensional lattice region in GPU memory. An extension of the method of a hyper-octree is used to allow for arbitrary subdivision ratios in each dimension. In addition, the decision to refine (or select) a given sub-region is based on a user-provided callback, allowing for arbitrary refinement domains to be expressed either geometrically or programmatically.

Fackler, Philip↗
DOE OSTI2020

Dynamic Importance Sampling

Dynamic Importance (DynIm) Sampling is a new approach for importance sampling in high-dimensional space. DynIm has two key characteristics. (1) Importance sampling: The notion of importance of candidate samples is used to guide the sampling, where importance is defined based on the (dis)similarity from previously selected samples (via Euclidean distance metric). (2) Dynamic sampling: The sampling can be performed dynamically, as new candidates are generated and new samples must be selected. DynIm was developed as part of a machine learning based coupling of scales in large multiscale simulations and can be used for a variety of applications.

Bhatia, Harsh↗
NASA NTRS1980

Estimation of effective hydrologic properties of soils from observations of vegetation density

An existing one-dimensional model of the annual water balance is reviewed. Slight improvements are made in the method of calculating the bare soil component of evaporation, and in the way surface retention is handled. A natural selection hypothesis, which specifies the equilibrium vegetation density for a given, water limited, climate-soil system, is verified through comparisons with observed data and is employed in the annual water balance of watersheds in Clinton, Ma., and Santa Paula, Ca., to estimate effective areal average soil properties. Comparison of CDF's of annual basin yield derived using these soil properties with observed CDF's provides excellent verification of the soil-selection procedure. This method of parameterization of the land surface should be useful with present global circulation models, enabling them to account for both the non-linearity in the relationship between soil moisture flux and soil moisture concentration, and the variability of soil properties from place to place over the Earth's surface.

Tellers, T. E.↗
NASA NTRS1985

Numerical solution of strong radiation gasdynamic interactions in a hydrogen-seedant mixture

Theoretical and experimental results are provided for the absorption of laser energy by a gas flow. A two-dimensional numerical model described the temperature field, fluid dynamics, variable absorptivity and gas dynamics. The model was tested using a hydrogen-seedant mixture injected with 10.6 micron laser radiation. The laser mix was selected to allow reduced temperature gradients and energy source terms. It was found possible, by varying parameters such as the laser power and flash pressure, to precisely position the peak absorptance region in higher speed flows. More refined models are being tested to achieve accurate absorptance predictions in flows below Mach 0.0001.

Merkle, C. L.↗