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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Quasiparticle Scattering in a Superconductor near a Nematic Critical Point: Resonance Mode and Multiple Attractive Channels

We analyze the scattering rate for 2D fermions interacting via soft nematic fluctuations. The ground state is an s-wave superconductor, but other pairing channels are almost equally attractive. This strongly alters the scattering rate: At energies beyond the pairing gap Δ, it is renormalized by contributions from all pairing channels. At energies of order Δ, it is determined by the competition between scattering into a gapped continuum and dispersing nematic resonance. The outcome is a “peak-peak-dip-hump” spectrum, similar, but not identical, to the “peak-dip-hump” structure in the cuprates.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Signatures of multiple charge excitations in resonant inelastic x-ray scattering spectra of metals

In this work, we study how multiple charge excitations appear in the resonant inelastic x-ray scattering (RIXS) spectra of metals. Typically, the focus is upon single excitations in the problem, the plasmons and electron-hole pairs, while the multiexcitation processes are neglected. However, at small momentum transfer the multiexcitation contributions may dominate the signal and one needs to understand how to interpret the data in such cases. In particular, we demonstrate how to “decode” the total multiexcitation intensity and extract the plasmon dispersion. Furthermore, while our calculations are based on the random phase approximation for jellium, which does not allow us to obtain quantitatively precise results in the entire region of parameters, we expect them to capture semiqualitatively all features expected for charged Fermi-liquid states, including universal and singular properties of the RIXS spectra.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1991

Surface scattering properties estimated from modeling ASAS multiple emission angle reflectance data over the lunar crater volcanic field, Nevada

ASAS multispectral data were acquired over Lunar Lake playa at 12 different lighting and viewing geometries. Atmospheric models and field-based data demonstrate that atmospheric contributions to ASAS data were relatively small and were thus ignored in analyses of surface photometric properties. ASAS data of an artificially roughened playa and cobble-strewn surfaces exhibit trends of increasing reflectance as phase angle decreases. The reflectance of a natural playa surface exhibits Lambertian scattering properties that cannot be replicated with the Hapke (1986) photometric function. The Hapke model does fit the rough and cobble-strewn playa data with single-scattering albedo, asymmetry factor, and roughness terms consistent with known properties of these surfaces. No published photometric model explains the reflectance variations of all three surfaces.

Guinness, Edward A.↗
DOE OSTI2025

Suppression of neutral-pion production in deep-inelastic scattering off nuclei with the CLAS detector

We present the first threefold differential measurement for neutral-pion multiplicity ratios produced in semi-inclusive deep-inelastic electron scattering on carbon, iron, and lead nuclei normalized to deuterium from CLAS at Jefferson Lab. We found that the neutral-pion multiplicity ratio is maximally suppressed for the leading hadrons (energy fraction 𝑧 → 1), suppression varying from 25% in carbon up to 75% in lead. An enhancement of the multiplicity ratio at low 𝑧 and high 𝑝$^2_𝑇$ is observed, suggesting an interconnection between these two variables. This behavior is qualitatively similar to the previous twofold differential measurement of charged pions by the HERMES Collaboration and, recently, by CLAS Collaboration. The largest enhancement was observed at high 𝑝$^2_𝑇$ for heavier nuclei, namely, iron and lead, while the smallest enhancement was observed for the lightest nucleus, carbon. This behavior suggests a competition between partonic multiple scattering, which causes enhancement, and hadronic inelastic scattering, which causes suppression.

color confinement↗
NASA NTRS2021

Interpretation of Spectral LiDAR Backscattering off the Florida Coast

A multispectral backscattering LiDAR (Light detection and range) system (hereafter Oculus) was integrated into a wave glider and used to estimate the scattering order (i.e., single vs multiple collisions), inherent optical properties (IOPs) and characteristics of particulate scatterers (i.e., relative size, composition and motion) on shelf waters of South East Florida. Oculus has a dual-wavelength configuration (473 and 532 nm) and two detection geometries (off- and on-axis). Characteristics of scatterers were investigated based on two complementary LiDAR-derived proxies (the Structural Dissimilarity Index and the spectral slope of LiDAR backscattering). In March 2017, field measurements showed a covariation between direct and diffuse backscattering contributions during morning hours and away from shore. LiDAR attenuation coefficients explained up to 57% of IOPs variability. The analysis of LiDAR-derived proxies suggested higher turbidity and larger particulates near the coast.

LiDAR↗
NASA NTRS1991

Surface scattering properties estimated from modeling airborne multiple emission angle reflectance data

Here, researchers apply the Hapke function to airborne bidirectional reflectance data collected over three terrestrial surfaces. The objectives of the study were to test the range of natural surfaces that the Hapke model fits and to evaluate model parameters in terms of known surface properties. The data used are multispectral and multiple emission angle data collected during the Geologic Remote Sensing Field Experiment (GRSFE) over a mud-cracked playa, an artificially roughened playa, and a basalt cobble strewn playa at Lunar Lake Playa in Nevada. Airborne remote sensing data and associated field measurements were acquired at the same time. The airborne data were acquired by the Advanced Solid State Array Spectroradiometer (ASAS) instrument, a 29-spectral band imaging system. ASAS reflectance data for a cobble-strewn surface and an artificially rough playa surface on Lunar Lake Playa can be explained with the Hanke model. The cobble and rough playa sites are distinguishable by a single scattering albedo, which is controlled by material composition; by the roughness parameter, which appears to be controlled by the surface texture and particle size; and the symmetry factor of the single particle phase function, which is controlled by particle size and shape. A smooth playa surface consisting of compacted, fine-grained particles has reflectance variations that are also distinct from either the cobble site or rough playa site. The smooth playa appears to behave more like a Lambertian surface that cannot be modeled with the Hapke function.

Guinness, Edward A.↗
NASA NTRS2011

Effective Albedo of Vegetated Terrain at L-Band

This paper derives an explicit expression for an effective albedo of vegetated terrain from the zero- and multiple- order radiative transfer (RT) model comparison. The formulation establishes a direct physical link between the effective vegetation parameterization and the theoretical description of absorption and scattering within the canopy. The paper will present an evaluation of the derived albedo for corn canopies with data taken during an experiment at Alabama A&M Winfield A. Thomas Agricultural Research Station near Huntsville, Alabama in June, 1998. The test site consisted of two 50-m x 60-m plots - one with a bare surface and the other with grass cover - and four 30-m x 50-m plots of corn at different planting densities. One corn field was planted at a full density of 9.5 plants/sq m while the others were planted at 1/3, 1/2 and 2/3 of the full density. The fields were observed with a truck-mounted L-band radiometer at incident angle of 15 degree for the period of two weeks. Soil moisture (SM) changed daily due to irrigation and natural rainfall. Variations in gravimetric SM from 18 % to 34 % were seen during this period. Ground truth data, including careful characterization of the corn size and orientation statistics, and its dielectric, was also collected and used to simulate the effective albedo for the vegetation. The single-scattering albedo is defined as the fractional power scattered from individual vegetation constituents with respect to canopy extinction. It represents single-scattering properties of vegetation elements only, and is independent of ground properties. The values of the albedo get higher when there is dense vegetation (i.e. forest, mature corn, etc.) with scatterers, such as branches and trunks (or stalks in the case of corn), which are large with respect to the wavelength. This large albedo leads to a reduction in brightness temperature in the zero-order RT solution (known as tau-omega model). Higher-order multiple-scattering RT solutions are required for proper representation of scattering within vegetation. In this paper, an expression for an effective albedo for the whole canopy including the ground is derived for use in the zero-order RT model-based SM retrieval. This effective albedo takes into account of all the processes taking place within the canopy, including multiple-scattering. This new formulation will be presented and its importance for microwave SM retrieval will be evaluated for corn canopies in conjunction with the detailed ground truth data obtained during the experiment at Alabama in 1998. Emphasis will be placed on examining how the radiometer response to SM is modified by the corn canopy scattering under different field conditions. A semi-empirical parameterization of the effective albedo will be investigated through analysis of SM and vegetation water content effects on the effective albedo.

Kurum, Mehmet↗
DOE OSTI2019

(U) Analytic One-Group S 2 Slab Problem with Isotropic Scattering and Fission Applied to Neutron Multiplicity Sensitivity

A one-group isotropic S 2 transport problem in a homogeneous slab is solved analytically and used to derive an analytic expression for the Feynman Y for this special case. Analytic derivatives of the Feynman Y are then taken with respect to an arbitrary input parameter. The analytic solution is used to verify the results of the new Feynman Y sensitivity capability that Alex Clark (NC State/XCP-3) has integrated into the neutron sensitivity code SENSMG. SENSMG’s Feynman Y capability relies on the multigroup discrete-ordinates code PARTISN and the methodology developed by Mattingly to compute the Feynman Y deterministically, and the Feynman Y sensitivity capability relies on work by O’Brien et al., extended by Clark.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2013

A high-order integral solver for scalar problems of diffraction by screens and apertures in three-dimensional space

We present a novel methodology for the numerical solution of problems of diffraction by infinitely thin screens in three-dimensional space. Our approach relies on new integral formulations as well as associated high-order quadrature rules. The new integral formulations involve weighted versions of the classical integral operators related to the thin-screen Dirichlet and Neumann problems as well as a generalization to the open-surface problem of the classical Calderón formulae. The high-order quadrature rules we introduce for these operators, in turn, resolve the multiple Green function and edge singularities (which occur at arbitrarily close distances from each other, and which include weakly singular as well as hypersingular kernels) and thus give rise to super-algebraically fast convergence as the discretization sizes are increased. When used in conjunction with Krylov-subspace linear algebra solvers such as GMRES, the resulting solvers produce results of high accuracy in small numbers of iterations for low and high frequencies alike. We demonstrate our methodology with a variety of numerical results for screen and aperture problems at high frequencies—including simulation of classical experiments such as the diffraction by a circular disc (featuring in particular the famous Poisson spot), evaluation of interference fringes resulting from diffraction across two nearby circular apertures, as well as solution of problems of scattering by more complex geometries consisting of multiple scatterers and cavities.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2011

Towards Simulating a Realistic Planetary Seismic Wavefield: The Contribution of the Megaregolith and Low-Velocity Waveguides

Lunar seismograms are distinctly different from their terrestrial counterparts. The Apollo lunar seismometers recorded moonquakes without distinct P- or S-wave arrivals; instead waves arrive as a diffuse coda that decays over several hours making the identification of body waves difficult. The unusual character of the lunar seismic wavefield is generally tied to properties of the megaregolith: it consists of highly fractured and broken crustal rock, the result of extensive bombardment of the Moon. The megaregolith extends several kilometers into the lunar crust, possibly into the mantle in some regions, and is covered by a thin coating of fine-scale dust. These materials possess very low seismic velocities that strongly scatter the seismic wavefield at high frequencies. Directly modeling the effects of the megaregolith to simulate an accurate lunar seismic wavefield is a challenging computational problem, owing to the inherent 3-D nature of the problem and the high frequencies (greater than 1 Hz) required. Here we focus on modeling the long duration code, studying the effects of the low velocities found in the megaregolith. We produce synthetic seismograms using 1-D slowness integration methodologies, GEMINI and reflectivity, and a 3-D Cartesian finite difference code, Wave Propagation Program, to study the effect of thin layers of low velocity on the surface of a planet. These codes allow us generate seismograms with dominant frequencies of approximately 1 Hz. For background lunar seismic structure we explore several models, including the recent model of Weber et al., Science, 2011. We also investigate variations in megaregolithic thickness, velocity, attenuation, and seismogram frequency content. Our results are compared to the Apollo seismic dataset, using both a cross correlation technique and integrated envelope approach to investigate coda decay. We find our new high frequency results strongly support the hypothesis that the long duration of the lunar seismic codes is generated by the presence of the low velocity megaregolith, and that the diffuse arrivals are a combination of scattered energy and multiple reverberations within this layer. The 3-D modeling indicates the extreme surface topography of the Moon adds only a small contribution to scattering effects, though local geology may play a larger role. We also study the effects of the megaregolith on core reflected and converted phases and other body waves. Our analysis indicates detection of core interacting arrivals with a polarization filter technique is robust and lends the possibility of detecting other body waves from the Moon.

Schmerr, Nicholas C.↗
NASA NTRS2010

Overview of the Graphical User Interface for the GERMcode (GCR Event-Based Risk Model)

The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERMcode calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERMcode also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERMcode for application to thick target experiments. The GERMcode provides scientists participating in NSRL experiments with the data needed for the interpretation of their experiments, including the ability to model the beam line, the shielding of samples and sample holders, and the estimates of basic physical and biological outputs of the designed experiments. We present an overview of the GERMcode GUI, as well as providing training applications.

Kim, Myung-Hee Y.↗
NASA NTRS2010

Overview of the Graphical User Interface for the GERM Code (GCR Event-Based Risk Model

The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERM code calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERM code also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERM code accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERM code for application to thick target experiments. The GERM code provides scientists participating in NSRL experiments with the data needed for the interpretation of their experiments, including the ability to model the beam line, the shielding of samples and sample holders, and the estimates of basic physical and biological outputs of the designed experiments. We present an overview of the GERM code GUI, as well as providing training applications.

Kim, Myung-Hee↗
DOE OSTI2020

Interactive Visual Study of Multiple Attributes Learning Model of X-Ray Scattering Images

Existing interactive visualization tools for deep learning are mostly applied to the training, debugging, and refinement of neural network models working on natural images. However, visual analytics tools are lacking for the specific application of x-ray image classification with multiple structural attributes. In this paper, we present an interactive system for domain scientists to visually study the multiple attributes learning models applied to x-ray scattering images. It allows domain scientists to interactively explore this important type of scientific images in embedded spaces that are defined on the model prediction output, the actual labels, and the discovered feature space of neural networks. Users are allowed to flexibly select instance images, their clusters, and compare them regarding the specified visual representation of attributes. The exploration is guided by the manifestation of model performance related to mutual relationships among attributes, which often affect the learning accuracy and effectiveness. The system thus supports domain scientists to improve the training dataset and model, find questionable attributes labels, and identify outlier images or spurious data clusters. Case studies and scientists feedback demonstrate its functionalities and usefulness.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Scattering from phase-separated vesicles. I. An analytical form factor for multiple static domains

This is the first in a series of studies considering elastic scattering from laterally heterogeneous lipid vesicles containing multiple domains. Unique among biophysical tools, small-angle neutron scattering can in principle give detailed information about the size, shape and spatial arrangement of domains. A general theory for scattering from laterally heterogeneous vesicles is presented, and the analytical form factor for static domains with arbitrary spatial configuration is derived, including a simplification for uniformly sized round domains. The validity of the model, including series truncation effects, is assessed by comparison with simulated data obtained from a Monte Carlo method. Several aspects of the analytical solution for scattering intensity are discussed in the context of small-angle neutron scattering data, including the effect of varying domain size and number, as well as solvent contrast. Finally, the analysis indicates that effects of domain formation are most pronounced when the vesicle's average scattering length density matches that of the surrounding solvent.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Neutrino Dipole Moments and Radiative Signatures from Partial Compositeness

We investigate composite neutrino models where heavy neutrinos emerge as bound states from a near-conformal strongly coupled sector. Standard Model neutrinos mix with these composite singlets via an inverse seesaw mechanism, where the anomalous scaling dimensions of the composite-sector operators naturally suppress light neutrino masses to sub-eV scales. Matching the conformal dynamics onto low-energy theory yields enhanced electromagnetic transition dipole operators with couplings $d_{μN} \sim 10^{-6}$-$10^{-8}\,\mathrm{GeV}^{-1}$, parametrically larger than the loop-level predictions of minimal Dirac or Majorana models. We carry out a dedicated event-level simulation of the production-and-decay chain $νX \to \mathcal{U} X \to νγX$ and compute the resulting event rates at MiniBooNE and MINERvA within the model, accounting for the composite production cross section and decay kinematics in detail. We further present predictions for the photon energy, angular, and multiplicity distributions. For the benchmark scenarios accessible at these experiments the radiative signal is predominantly single-photon; the composite structure additionally permits fragmentation of the up-scattered state into multiple heavy neutrinos, each decaying as $N\toνγ$, with multi-photon final states emerging for lighter compositeness scales or higher beam energies as a qualitatively new probe of the composite dynamics.

Assi, Benoît [Cincinnati U.; Fermilab] (ORCID:0000↗
DOE OSTI2025

Quantifying dispersity in size and shape of nanoparticles from small-angle scattering data using machine learning based CREASE

Here, we use machine learning (ML) enhanced computational reverse engineering analysis of scattering experiments (CREASE) to interpret small-angle X-ray scattering (SAXS) data obtained from a system of nanoparticles without a priori knowledge of their exact shapes (e.g. spheres or ellipsoids), sizes (0.5–50 nm) and distributions. The SAXS measurements yielded three categories of scattering profiles exhibiting 'strong', 'weak' and 'no' features. Diminishing features (e.g. broadening or disappearing peaks) in scattering profiles have always been attributed to the presence of significant dispersity in the system. Such featureless SAXS data are not suitable for traditional analysis using analytical models. If one were to fit a relevant analytical model (e.g. the lmfit analytical model for polydisperse spheres) to these 'weak' and 'no' SAXS profiles from our nanoparticle systems, one would obtain non-unique interpretations of the data. Relying on electron microscopy to identify the distributions of nanoparticle shapes and sizes is also unfeasible, especially in high-throughput synthesis and characterization loops. In such situations, to identify the distributions of particle sizes and shapes that could be present in the sample, one must rely on methods like ML-CREASE to interpret the data quickly and output all relevant interpretations about the structure present in the system. The ML-CREASE optimization loop takes the experimental scattering profile as input and outputs multiple candidate solutions whose computed scattering profiles match the SAXS profile input. The ML-CREASE method outputs distributions of relevant structural features, such as the volume fraction of the nanoparticles in the system and the mean and standard deviation of the particle size and aspect ratio, assuming a type of distribution (e.g. normal, log-normal) for size and aspect ratio. We find that, for the SAXS profiles analyzed here, accounting for the shape dispersity along with size dispersity of the nanoparticles using ML-CREASE improved the match between the computed scattering profiles and input experimental profiles.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗