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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

High-yield growth kinetics and spatial mapping of single-walled carbon nanotube forests at wafer scale

Emerging commercial applications of vertically aligned, single-walled carbon nanotube (SWCNT) “forests” require synthesis that minimizes nanotube diameter while maximizing number density across substrate areas exceeding centimeter scale. To address this need, we synthesized SWCNT forests on full silicon wafers with notable reproducibility and uniformity, and co-optimized growth for small diameters and high densities across large areas to access new territory in this 3D parameter space. We mapped the spatial uniformity of key structural features using Raman microscopy, synchrotron X-ray scattering, and Rutherford backscattering spectrometry. Low C 2 H 2 flux over sub-nm Fe/Mo catalysts produced small-diameter SWCNTs (2.1 nm) at high number densities (2.26 × 10 12 cm -2 ) on wafers up to 6 in. Although removing Mo resulted in larger SWCNT diameters and lower densities (<0.7 × 10 12 cm -2 ), mass conversion rates from C 2 H 2 to SWCNT product were high and remarkably invariant for catalyst compositions and densities (i.e., 47.7% or 1.30 × 10 6 % g-catalyst -1 on 4-in. wafers). These carbon conversion efficiencies far exceed typical benchtop reactors and are on par with the best reported literature values. Our detailed elucidation of correlations among structural characteristics within this resource-efficient process is expected to guide future scale-up efforts of SWCNT forest growth beyond wafer scale.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Electronically driven collapse of the bulk modulus in δ -plutonium

Plutonium metal exhibits an anomalously large softening of its bulk modulus at elevated temperatures that is made all the more extraordinary by the finding that it occurs irrespective of whether the thermal expansion coefficient is positive, negative, or zero—representing an extreme departure from conventional Grüneisen scaling. We show here that the cause of this softening is the compressibility of plutonium’s thermally excited electronic configurations, which has thus far not been considered in thermodynamic models. We show that when compressible electronic configurations are thermally activated, they invariably give rise to a softening of the bulk modulus regardless of the sign of their contribution to the thermal expansion. The electronically driven softening of the bulk modulus is shown to be in good agreement with elastic moduli measurements performed on the gallium-stabilized δ phase of plutonium over a range of temperatures and compositions and is shown to grow rapidly at small concentrations of gallium and at high temperatures, where it becomes extremely sensitive to hydrostatic pressure.

36 MATERIALS SCIENCE↗
NASA NTRS1972

Inner-zone energetic-electron repopulation by radial diffusion.

Quantitative study of the intrusion of natural electrons into the inner radiation zone during and after the geomagnetic storm of Sept. 2, 1966. It is shown that the transport is consistent with a radial-diffusion mechanism in which the first two invariants are conserved. Except for the three-day period of the storm main phase when data were missing, the radial-diffusion coefficient is found to have a value which could be produced by a variation of a large-scale electric field across the magnetosphere having an amplitude of 0.28 mV/m and a period of 1600 sec. Electric fields having approximately these characteristics have been inferred from previous observations of the motion of whistler ducts within the plasmapause. If fields of this amplitude and period exist throughout the magnetosphere, the radial diffusion of all geomagnetically trapped particles except the high-energy inner-zone protons is strongly influenced by electric-field variations. A comprehensive review of previously reported radial-diffusion coefficients shows reasonable agreement for L less than about 3.0, but serious discrepancies among reported values exist for determinations made in the outer zone. These discrepancies cannot be explained by the simple theory of radial diffusion due to variation of large-scale electric or magnetic fields.

Tomassian, A. D.↗
NASA NTRS2005

Automated Image Registration Using Morphological Region of Interest Feature Extraction

With the recent explosion in the amount of remotely sensed imagery and the corresponding interest in temporal change detection and modeling, image registration has become increasingly important as a necessary first step in the integration of multi-temporal and multi-sensor data for applications such as the analysis of seasonal and annual global climate changes, as well as land use/cover changes. The task of image registration can be divided into two major components: (1) the extraction of control points or features from images; and (2) the search among the extracted features for the matching pairs that represent the same feature in the images to be matched. Manual control feature extraction can be subjective and extremely time consuming, and often results in few usable points. Automated feature extraction is a solution to this problem, where desired target features are invariant, and represent evenly distributed landmarks such as edges, corners and line intersections. In this paper, we develop a novel automated registration approach based on the following steps. First, a mathematical morphology (MM)-based method is used to obtain a scale-orientation morphological profile at each image pixel. Next, a spectral dissimilarity metric such as the spectral information divergence is applied for automated extraction of landmark chips, followed by an initial approximate matching. This initial condition is then refined using a hierarchical robust feature matching (RFM) procedure. Experimental results reveal that the proposed registration technique offers a robust solution in the presence of seasonal changes and other interfering factors. Keywords-Automated image registration, multi-temporal imagery, mathematical morphology, robust feature matching.

Plaza, Antonio↗
NASA NTRS2017

NeMO-Net: The Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 percent error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets. We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

NeMO-Net↗
NASA NTRS2017

NeMO-Net The Neural Multi-Modal Observation Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. Exploiting the fine-scaled features of these datasets, machine learning methods such as MAP, PCA, and SVM can not only accurately classify the living cover and morphology of these reef systems (below 8 error), but are also able to map the spectral space between airborne and satellite imagery, augmenting and improving the classification accuracy of previously low-resolution datasets.We are currently implementing NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive active learning and training software to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. NeMO-Net will be built upon the QGIS platform to ingest UAV, airborne and satellite datasets from various sources and sensor capabilities, and through data-fusion determine the coral reef ecosystem makeup globally at unprecedented spatial and temporal scales. To achieve this, we will exploit virtual data augmentation, the use of semi-supervised learning, and active learning through a tablet platform allowing for users to manually train uncertain or difficult to classify datasets. The project will make use of Pythons extensive libraries for machine learning, as well as extending integration to GPU and High-End Computing Capability (HECC) on the Pleiades supercomputing cluster, located at NASA Ames. The project is being supported by NASAs Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Remote Sensin↗
NASA NTRS2018

NeMO-Net - The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment

In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. By combining spatial and spectral information from varying resolutions, we seek to augment and improve the classification accuracy of previously low-resolution datasets at large temporal scales.NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive learning and training software, currently being developed at NASA Ames, is aimed at assessing the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. The latest iteration uses fully convolutional networks to segment and identify coral imagery taken by UAVs and satellites, including WorldView-2 and Sentinel. We present results taken from the Indian Ocean where classification accuracy has exceeded 91% for 24 geomorphological classes given ample training data. In addition, we utilize deep Laplacian Pyramid Super-Resolution Networks (LapSRN) to reconstruct high resolution information from low resolution imagery, trained from various UAV and satellite datasets. Finally, in the case of insufficient training data, we have developed an interactive online platform that allows users to easily segment and submit their classifications, which has been integrated with the current NeMO-Net workflow. Specifically, we present results from the Fiji islands in which preliminary user data has allowed for the accurate identification of 9 separate classes, despite issues such as cloud shadowing and spectral variation. The project is being supported by NASA's Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.

Neural↗
DOE OSTI2011

On infrared and ultraviolet divergences of cosmological perturbations

We study a consistent infrared and ultraviolet regularization scheme for the cosmological perturbations. The infrared divergences are cured by assuming that the Universe undergoes a transition between a nonsingular preinflationary, radiation-dominated phase and a slow-roll inflationary evolution. The ultraviolet divergences are eliminated via adiabatic subtraction. A consistent regularization of the field fluctuations through this transition is obtained by performing a mode matching for both the gauge invariant Mukhanov variable and its adiabatic expansion. We show that these quantities do not generate ultraviolet divergences other than the standard ones, when evolving through the matching time. We also show how the DeWitt-Schwinger expansion, which can be used to construct the counter-terms regularizing the ultraviolet divergences, ceases to be valid well before horizon exit of the scales of interest. Thus, such counter-terms should not be used beyond the time of the horizon exit and it is unlikely that the observed power spectrum is modified by adiabatic subtraction, as claimed in some literature. On the contrary, the infrared regularization might have an impact on the observed spectrum, and we briefly discuss this possibility.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2012

AMUSE-Field I: NUCLEAR X-RAY PROPERTIES OF LOCAL FIELD AND GROUP SPHEROIDS ACROSS THE STELLAR MASS SCALE

We present the first results from AMUSE-Field, a Chandra survey designed to characterize the occurrence and intensity of low-level accretion onto supermassive black holes (SMBHs) at the center of local early-type field galaxies. This is accomplished by means of a Large Program targeting a distance-limited (<30 Mpc) sample of 103 early types spanning a wide range in stellar masses. We acquired new ACIS-S observations for 61 objects down to a limiting (0.3-10 keV) luminosity of 2.5 Multiplication-Sign 10{sup 38} erg s{sup -1}, and we include an additional 42 objects with archival (typically deeper) coverage. A nuclear X-ray source is detected in 52 out of the 103 galaxies. After accounting for potential contamination from low-mass X-ray binaries, we estimate that the fraction of accreting SMBHs within the sample is 45% {+-} 7%, which sets a firm lower limit on the occupation fraction within the field. The measured nuclear X-ray luminosities are invariably highly sub-Eddington, with L{sub X}/L{sub Edd} ratios between {approx}10{sup -4} and 10{sup -8}. As also found in a companion survey targeting Virgo early types, the active fraction increases with increasing host galaxy stellar mass, reflective of 'Eddington incompleteness' within the lower-mass objects. For the Field sample, the average nuclear X-ray luminosity scales with the host stellar mass as M{sup 0.71{+-}0.10}{sub star}, with an intrinsic scatter of 0.73 {+-} 0.09 dex. Qualitatively similar results hold for morphologically homogeneous (type E) or uniform sensitivity (new observations only) subsets. A majority of the AMUSE-Field galaxies (78%) inhabit groups, enabling us to investigate the influence of group richness on nuclear activity. We see no evidence for a positive correlation between nuclear X-ray luminosity, normalized to host properties, and galaxy density. Rather, while the scatter is substantial, it appears that the Eddington-scaled X-ray luminosity of group members may be slightly lower than for isolated galaxies, and that this trend continues to cluster early types.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

Axions and saxions from the primordial supersymmetric plasma and extra radiation signatures

We calculate the rate for thermal production of axions and saxions via scattering of quarks, gluons, squarks, and gluinos in the primordial supersymmetric plasma. Systematic field theoretical methods such as hard thermal loop resummation are applied to obtain a finite result in a gauge-invariant way that is consistent to leading order in the strong gauge coupling. We calculate the thermally produced yield and the decoupling temperature for both axions and saxions. For the generic case in which saxion decays into axions are possible, the emitted axions can constitute extra radiation already prior to big bang nucleosynthesis and well thereafter. We update associated limits imposed by recent studies of the primordial helium-4 abundance and by precision cosmology of the cosmic microwave background and large scale structure. We show that the trend towards extra radiation seen in those studies can be explained by late decays of thermal saxions into axions and that upcoming Planck results will probe supersymmetric axion models with unprecedented sensitivity.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

No-scale ripple inflation revisited

We revisit the no-scale ripple inflation model, where no-scale supergravity is modified by an additional term for the inflaton field in the Kähler potential. This term not only breaks one SU(N,1) symmetry explicitly, but also plays an important role for inflation. We generalize the superpotential in the no-scale ripple inflation model slightly. There exists a discrete Z{sub 2} symmetry/parity in the scalar potential in general, which can be preserved or violated by the non-canonical nomalized inflaton kinetic term. Thus, there are three inflation paths: one parity invariant path, and the left and right paths for parity violating scenario. We show that the inflations along the parity invariant path and right path are consistent with the Planck results. However, the gavitino mass for the parity invariant path is so large that the inflation results will be invalid if we consider the inflaton supersymmetry breaking soft mass term. Thus, only the inflation along the right path gives the correct and consistent results. Notably, the tensor-to-scalar ratio in such case can be large, with a value around 0.05, which may be probed by the future Planck experiment.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Search for contact interactions and large extra dimensions in the dilepton channel using proton–proton collisions at √s = 8 TeV with the ATLAS detector

Research is conducted for non-resonant new phenomena in dielectron and dimuon final states, originating from either contact interactions or large extra spatial dimensions. The LHC 2012 proton–proton collision dataset recorded by the ATLAS detector is used, corresponding to 20 fb –1 at √s = 8 TeV. The dilepton invariant mass spectrum is a discriminating variable in both searches, with the contact interaction search additionally utilizing the dilepton forward-backward asymmetry. No significant deviations from the Standard Model expectation are observed. Lower limits are set on the ℓℓqq contact interaction scale Λ between 15.4 TeV and 26.3 TeV, at the 95% credibility level. For large extra spatial dimensions, lower limits are set on the string scale MS between 3.2 TeV to 5.0 TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1990

Laboratory and theoretical models of planetary-scale instabilities and waves

Meteorologists and planetary astronomers interested in large-scale planetary and solar circulations recognize the importance of rotation and stratification in determining the character of these flows. In the past it has been impossible to accurately model the effects of sphericity on these motions in the laboratory because of the invariant relationship between the uni-directional terrestrial gravity and the rotation axis of an experiment. Researchers studied motions of rotating convecting liquids in spherical shells using electrohydrodynamic polarization forces to generate radial gravity, and hence centrally directed buoyancy forces, in the laboratory. The Geophysical Fluid Flow Cell (GFFC) experiments performed on Spacelab 3 in 1985 were analyzed. Recent efforts at interpretation led to numerical models of rotating convection with an aim to understand the possible generation of zonal banding on Jupiter and the fate of banana cells in rapidly rotating convection as the heating is made strongly supercritical. In addition, efforts to pose baroclinic wave experiments for future space missions using a modified version of the 1985 instrument led to theoretical and numerical models of baroclinic instability. Rather surprising properties were discovered, which may be useful in generating rational (rather than artificially truncated) models for nonlinear baroclinic instability and baroclinic chaos.

Hart, John E.↗
DOE OSTI2013

H→γγ as a Triangle Anomaly: Possible Implications for the Hierarchy Problem

The Standard Model calculation of H→γγ has the curious feature of being finite but regulator-dependent. While dimensional regularization yields a result which respects the electromagnetic Ward identities, additional terms which violate gauge invariance arise if the calculation is done setting d = 4. This discrepancy between the d=4 – ϵ and d = 4 results is recognized as a true ambiguity which must be resolved using physics input; as dimensional regularization respects gauge invariance, the d = 4 – ϵ calculation is accepted as the correct SM result. However, here we point out another possibility; working in analogy with the gauge chiral anomaly, we note that it is possible that the individual diagrams do violate the electromagnetic Ward identities, but that the gauge-invariance-violating terms cancel when all contributions to H→γγ, both from the SM and from new physics, are included. We thus examine the consequences of the hypothesis that the d = 4 calculation is valid, but that such a cancellation occurs. We work in general renormalizable gauge, thus avoiding issues with momentum routing ambiguities. We point out that the gauge-invariance-violating terms in d = 4 arise not just for the diagram containing a SM $W^{\pm}$ boson, but also for general fermion and scalar loops, and relate these terms to a lack of shift invariance in Higgs tadpole diagrams. We then derive the analogue of "anomaly cancellation conditions", and find consequences for solutions to the hierarchy problem. In particular, we find that supersymmetry obeys these conditions, even if it is softly broken at an arbitrarily high scale.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2011

A generic model for transport in turbulent shear flows

Turbulence regulation by large-scale shear flows is crucial for a predictive modeling of transport in plasma. In this paper the suppression of turbulent transport by large-scale flows is studied numerically by measuring the turbulent diffusion D{sub t} and scalar amplitude <n{sup '2}> of decaying passive scalar fields n{sup '} advected by various turbulent flows. Both uniform flows and shear flows are shown to suppress turbulence causing the quenching in transport and turbulence amplitude. The uniform flows U{sub 0}={Lambda}y with the advection rate {Lambda} in the case of a finite correlated forcing with {tau}{sub F}=1 gives rise to the advection/sweeping effect which suppresses D{sub t}, <u{sup '2}> and <n{sup '2}> as {proportional_to}{Lambda}{sup -2} for {Lambda}>>{tau}{sub F}{sup -1}. In contrast, no influence of the uniform flow is found in the case of a short correlated forcing {tau}{sub F}{yields}0 due to Galilean invariance. For the shear flow U{sub 0}={Omega}sinxy ({Omega}= constant shearing rate) with the appropriate choice of the forcing ({tau}{sub F}{yields}0) the nature of transport suppression is shown to crucially depend on the properties of the turbulence. Specifically, for prescribed turbulence with a short correlation time {tau}{sub c}={tau}{sub F}<<{Omega}{sup -1}, the turbulence statistics scale as D{sub t{proportional_to}{Omega}}{sup -0.02}, <n{sup '2}>{proportional_to}{Omega}{sup -0.62} and cross-phase cos{theta}{proportional_to}{Omega}{sup 0.29}. For consistently evolved turbulence with a finite correlation time {tau}{sub c{>=}{Omega}}{sup -1}, turbulence statistics are suppressed more strongly as D{sub t{proportional_to}{Omega}}{sup -1.75}, <n{sup '2}>{proportional_to}{Omega}{sup -2.41}, <u'{sub x}2>{proportional_to}{Omega}{sup -0.65} and <{omega}{sup '2}>{proportional_to}{Omega}{sup -0.50}. A novel renormalization scheme is then introduced to rescale our results into the regime within which the kinetic energy and enstrophy are unchanged by shear flow. This allows our numerical results to closely match previous analytical predictions [E. Kim, Mod. Phys. Lett. B 18, 1 (2004)] and to understand different experimental scalings observed in laboratory plasmas. Furthermore, D{sub t} is found to be related to <n{sup '2}> by <n{sup '2}>{proportional_to}D{sub t}/D{sub {Omega}}, where D{sub {Omega}}{proportional_to}{Omega}{sup (2/3)} is the shear accelerated diffusion of n{sup '} with an interesting scaling cos{theta}{proportional_to}{radical}(D{sub t}D{sub {Omega}}).

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Quantum Critical Higgs: from AdS 5 to colliders

We examine distinctive signatures of Quantum Critical Higgs models at the LHC and future higher energy colliders. In these models the Higgs boson is part of a conformal sector that is softly broken at a threshold scale, and generically the scaling dimension of the Higgs is larger than in the Standard Model. In particular we examine the gg → H → ZZ, gg → H → γγ, and gg → Z → H Z channels to see how the cross sections deviate from the Standard Model in the high invariant mass region. In order to perform the calculations we use 5D duals of Quantum Critical Higgs models using the AdS/CFT correspondence, with a soft wall to break the conformal symmetry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Many-Body Potential for Simulating Self-Assembly of Polymer-Grafted Nanoparticles in a Polymer Matrix

Many-body interactions between polymer-grafted nanoparticles (NPs) play a key role in promoting their assembly into low-dimensional structures within polymer melts, even when the particles are spherical and isotropically grafted. However, capturing such interactions in simulations of NP assembly is very challenging because explicit modeling of the polymer grafts and melt chains is highly computationally expensive, even using coarse-grained models. Here, we develop a many-body potential for describing the effective interactions between spherical polymer-grafted NPs in a polymer matrix through a machine-learning approach. The approach involves using permutationally invariant polynomials to fit two- and three-body interactions derived from the potential of mean force calculations. The potential developed here reduces the computational cost by several orders of magnitude, thereby, allowing us to explore assembly behavior over large length and time scales. We show that the potential not only reproduces previously known assembled phases such as 1D strings and 2D hexagonal sheets, which generally cannot be achieved using isotropic two-body potentials, but can also help discover interesting phases such as networks, clusters, and gels. We demonstrate how each of these assembly morphologies intrinsically arises from a competition between two- and three-body interactions. Our approach for deriving many-body effective potentials can be readily extended to other colloidal systems, enabling researchers to make accurate predictions of their behavior and dissect the role of individual interaction energy terms of the overall potential in the observed behavior.

36 MATERIALS SCIENCE↗