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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Aluminous mare basalts - New data from Apollo 14 coarse fines

Four aluminous mare basalt fragments selected from the Apollo 14 coarse fines collection are described: 14004,34 has an intergranular texture; 14160,103 and 14168,38 are granular; and 14256,10 is a fine-grained metabasalt. Pyroxene compositional trends vary among the fragments: in 14004,34 the trend is from ferroaugite to pyroxferrite; 14160,103 exhibits well-defined iron enrichment trends involving both pigeonite and augite; 14168,38 contains mostly pigeonite with minor augite; and pyroxene compositions in 14256,10 cluster in two distinct populations, high- and low-Ca. The igneous textures (except for 14256,10), the absence of discernible clasts, and low Ni compositions of metal grains lead to the conclusion that the fragments are pieces of pristine aluminous mare basalts. The marked differences in the REE patterns rule out a close genetic relation between any of the four basalts.

Warner, R. D.↗
NASA NTRS1982

Predictions for partial and monolayer coverages of O2 on graphite

Monolayer properties of O2 on graphite are calculated using a pattern recognition, optimization scheme. Equilibrium monolayers are predicted at two different densities with properties in agreement with recent X-ray diffraction, specific heat, and neutron scattering data. Properties of the extremely low density regime are calculated using a model based upon a distribution of two-dimensional O2 clusters. The results are consistent with experimental evidence.

Pan, R. P.↗
NASA NTRS1992

Fractals and cosmological large-scale structure

Observations of galaxy-galaxy and cluster-cluster correlations as well as other large-scale structure can be fit with a 'limited' fractal with dimension D of about 1.2. This is not a 'pure' fractal out to the horizon: the distribution shifts from power law to random behavior at some large scale. If the observed patterns and structures are formed through an aggregation growth process, the fractal dimension D can serve as an interesting constraint on the properties of the stochastic motion responsible for limiting the fractal structure. In particular, it is found that the observed fractal should have grown from two-dimensional sheetlike objects such as pancakes, domain walls, or string wakes. This result is generic and does not depend on the details of the growth process.

Luo, Xiaochun↗
DOE OSTI2020

Josephson behavior in a metal-decorated topological-insulator Bi 0.91 Sb 0.09

We have fabricated W nanoscale clusters on a topological insulator Bi 0.91 Sb 0.09 . The W island arrays effectively induce two-dimensional superconductivity at the surface of Bi 0.91 Sb 0.09 via the superconducting proximity effect. We find that this heterostructure behaves as a dynamic Josephson junction, which shows a Fraunhofer-like pattern of the critical current versus the applied magnetic field. Microwave irradiation experiments reveal the existence of a 4π-periodic supercurrent carried by the topological surface state. Our results open up a route to induce topological superconductivity in a topological insulator.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Dynamics of Magnus-dominated particle clusters, collisions, pinning, and ratchets

Motivated by the recent work in skyrmions and active chiral matter systems, we examine pairs and small clusters of repulsively interacting point particles in the limit where the dynamics is dominated by the Magnus force. We find that particles with the same Magnus force can form stable pairs, triples, and higher ordered clusters or exhibit chaotic motion. For mixtures of particles with opposite Magnus force, particle pairs can combine to form translating dipoles. Under an applied drive, particles with the same Magnus force translate; however, particles with different or opposite Magnus force exhibit a drive-dependent decoupling transition. When the particles interact with a repulsive obstacle, they can form localized orbits with depinning or unwinding transitions under an applied drive. We examine the interaction of these particles with clusters or lines of obstacles and find that the particles can become trapped in orbits that encircle multiple obstacles. Under an ac drive, we observe a series of ratchet effects, including ratchet reversals, for particles interacting with a line of obstacles due to the formation of commensurate orbits. Lastly, in assemblies of particles with mixed Magnus forces of the same sign, we find that the particles with the largest Magnus force become localized in the center of the cluster, while for mixtures with opposite Magnus forces, the motion is dominated by transient local pairs or clusters, where the translating pairs can be regarded as a form of active matter.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Random and Block Sulfonated Polyaramides as Advanced Proton Exchange Membranes

We present here the experimental and computational characterization of two novel copolyaramide proton exchange membranes (PEMs) with higher conductivity than Nafion at relatively high temperatures, good mechanical properties, high thermal stability, and the capability to operate in low humidity conditions. The random and block copolyaramide PEMs are found to possess different ion exchange capacities (IEC) in addition to subtle structural and morphological differences, which impact the stability and conductivity of the membranes. SAXS patterns indicate the ionomer peak for the dry block copolymer resides at q = 0.1 Å –1 , which increases in amplitude when initially hydrated to 25% relative humidity, but then decrease in amplitude with additional hydration. This pattern is hypothesized to signal the transport of water into the polymer matrix resulting in a reduced degree of phase separation. Coupled to these morphological changes, the enhanced proton transport characteristics and structural/mechanical stability for the block copolymer are hypothesized to be primarily due to the ordered structure of ionic clusters that create connected proton transport pathways while reducing swelling upon hydration. Interestingly, the random copolymer did not possess an ionomer peak at any of the hydration levels investigated, indicating a lack of any significant ionomer structure. The random copolymer also demonstrated higher proton conductivity than the block copolymer, which is opposite to the trend normally seen in polymer membranes. However, it has reduced structural/mechanical stability as compared to the block copolymer. In conclusion, this reduction in stability is due to the random morphology formed by entanglements of polymer chains and the adverse swelling characteristics upon hydration. Therefore, the block copolymer with its enhanced proton conductivity characteristics, as compared to Nafion, and favorable structural/mechanical stability, as compared to the random copolymer, represents a viable alternative to current proton exchange membranes.

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

Size-Dependent Onset of Nitric Acid Dissociation in Cs + ·(HNO 3 )(H 2 O) n =0–11 Clusters at 20 K

We report the water-mediated charge separation of nitric acid upon incorporation into size-selected Cs + ∙(HNO 3 )(H 2 O) n=0-11 clusters at 20 K. Dramatic spectral changes are observed in the range n=7-9 that are traced to the formation of many isomeric structures associated with intermediate transfer of the acidic proton to the water network. This transfer is complete by n=10, which exhibits much simpler vibrational band patterns consistent with those expected for a tri-coordinated hydronium ion (the Eigen motif) along with the NO stretching bands predicted for a hydrated NO 3 – anion that is directly complexed to the Cs + cation. Theoretical analysis of the n=10 spectrum indicates that the dissociated ions adopt a solvent-separated ion-pair configuration such that the Cs + and H 3 O + cations flank the NO 3 – anion in a microhydrated salt bridge. In conclusion, this charge separation motif is evidently assisted by the electrostatic stabilization of the product NO 3 – /H 3 O + ion pair by the proximal metal ion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Planar Defect Layers Template a High-Pressure InBi Polymorph

The short- and long-range order of III–V materials under high pressure has long been the subject of debate, with advancements in structural characterization leading to significant revisions to the accepted structural models. Despite these revisions, previous high-pressure structural assignments in the In–Bi system include the site-disordered β-Sn structure type, a structure type demonstrated to be nonexistent in analogous III–V systems. While X-ray diffraction is consistent with site disordering in InBi at high pressure, cluster expansion calculations indicate that disordering requires temperatures above 3000 K. Here, we propose InBi as a model material for studying unique high-pressure planar defects due to its highly anisotropic stress-dependent properties and structure. Specifically, we identify two sets of planar defects that mimic the diffraction pattern of a site disordered β-Sn structure type and are compatible with the calculated disorder barrier. We derive these defects by symmetry relations over crystallographic transitions. Density functional theory calculations of the proposed defects suggest that these defects are stabilized by diminishing interlayer separations with pressure. Further, we find that one of the proposed defects closely resembles a bulk high-pressure phase of InBi, InBi-ϵ, and we assert that the proposed defects order upon heating, acting as a template for InBi-ϵ growth. The proposed defects and their electronic structure provide a basis for the trend of superconducting critical temperature with increasing pressure. These methods for identifying defects are generalizable to other materials with reports of site disorder at high pressure, prompting a broader search for related high-pressure defects.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Agronomic performance of 27 Populus clones evaluated after two 3–year coppice rotations in Henan, China

Selecting superior clones is the first step for commercial short–rotation coppice cultures to provide biomass and bioenergy. Till date, such selection for hybrid Populus clones in middle China is absent. Here we describe the growth, aboveground biomass production and cell wall composition of 27 hybrid poplar clones in Henan, China for two 3–year rotations. Significant variation in these three characteristics over two triennial rotation coppices among the 27 poplar clones was observed. During two 3–year rotation coppices, clones ‘276’, ‘02–17’, and ‘599’ showed relatively higher tree heights and larger basal diameters than those of the other clones. However, the most productive clones were ‘36’ and ‘01–30’. At the end of the second triennial rotation, the aboveground biomass production reached 18 Mg ha–1 year–1. For the cell wall composition analysis, the cellulose contents of clones ‘01–243’ and ‘2001’ were relatively high, while the xylose contents of clones ‘01–30’ and ‘65’ were relatively high. Cluster analysis based on height, basal diameter, biomass, heat value, cellulose content, and survival rate revealed five growth potential classes. Accordingly, clones ‘03–332’, ‘36’, and ‘599’ exhibited high biomass and growth and had the greatest potential to serve as excellent biomass producers in Henan, China. In addition, the expression patterns of 20 key regulatory genes were analyzed, and an integrated coexpression network was constructed. This field trial provides a comprehensive quantification and evaluation of the agronomic performance of 27 poplar clones in Henan, China. The results of this study and the analytical strategies provide an efficient mechanism for selecting clones that will perform well agronomically in local environments. The expression of key genes and the integrated coexpression network provide the molecular mechanisms of poplar biomass performance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

THE CHEMICAL COMPOSITION OF PRAESEPE (M44)

Star clusters have long been used to illuminate both stellar evolution and Galactic evolution. They also hold clues to the chemical and nucleosynthetic processes throughout the history of the Galaxy. We have taken high signal-to-noise (S/N), high-resolution spectra of 11 solar-type stars in the Praesepe open cluster to determine the chemical abundances of 16 elements: Li, C, O, Na, Mg, Al, Si, Ca, Sc, Ti, V, Cr, Fe, Ni, Y, and Ba. We have determined Fe from Fe I and Fe II lines and find [Fe/H] = +0.12 ±0.04. We find that Li decreases with temperature due to increasing Li depletion in cooler stars; it matches the Li-temperature pattern found in the Hyades. The [C/Fe] and [O/Fe] abundances are below solar and lower than the field star samples due to the younger age of Praesepe (0.7 Gyr) than the field stars. The alpha-elements, Mg, Si, Ca, and Ti, have solar ratios with respect to Fe, and are also lower than the field star samples. The Fe-peak elements, Cr and Ni, track Fe and have solar values. The neutron capture element [Y/Fe] is found to be solar, but [Ba/Fe] is enhanced relative to solar and to the field stars. Three Praesepe giants were studied by Carrera and Pancino; they are apparently enhanced in Na, Mg, and Ba relative to the Praesepe dwarfs. The Na enhancement may indicate proton-capture nucleosynthesis in the Ne → Na cycling with dredge-up into the atmospheres of the red giants.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

A Clustering Graph Generator

In very simple terms a network can be de ned as a collection of points joined together by lines. Thus, networks can be used to represent connections between entities in a wide variety of elds including engi- neering, science, medicine, and sociology. Many large real-world networks share a surprising number of properties, leading to a strong interest in model development research and techniques for building synthetic networks have been developed, that capture these similarities and replicate real-world graphs. Modeling these real-world networks serves two purposes. First, building models that mimic the patterns and prop- erties of real networks helps to understand the implications of these patterns and helps determine which patterns are important. If we develop a generative process to synthesize real networks we can also examine which growth processes are plausible and which are not. Secondly, high-quality, large-scale network data is often not available, because of economic, legal, technological, or other obstacles [7]. Thus, there are many instances where the systems of interest cannot be represented by a single exemplar network. As one example, consider the eld of cybersecurity, where systems require testing across diverse threat scenarios and validation across diverse network structures. In these cases, where there is no single exemplar network, the systems must instead be modeled as a collection of networks in which the variation among them may be just as important as their common features. By developing processes to build synthetic models, so-called graph generators, we can build synthetic networks that capture both the essential features of a system and realistic variability. Then we can use such synthetic graphs to perform tasks such as simulations, analysis, and decision making. We can also use synthetic graphs to performance test graph analysis algorithms, including clustering algorithms and anomaly detection algorithms.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

ON THE BIRTH MASSES OF THE ANCIENT GLOBULAR CLUSTERS

All globular clusters (GCs) studied to date show evidence for internal (star-to-star) variation in their light-element abundances (including Li, C, N, O, F, Na, Mg, Al, and probably He). These variations have been interpreted as evidence for multiple star formation episodes within GCs, with secondary episodes fueled, at least in part, by the ejecta of asymptotic giant branch (AGB) stars from a first generation of stars. A major puzzle emerging from this otherwise plausible scenario is that the fraction of stars associated with the second episode of star formation is observed to be much larger than expected for a standard initial mass function. The present work investigates this tension by modeling the observed anti-correlation between [Na/Fe] and [O/Fe] for 20 Galactic GCs. If the abundance pattern of the retained AGB ejecta does not depend on GC mass at fixed [Fe/H], then a strong correlation is found between the fraction of current GC stellar mass composed of pure AGB ejecta, f{sub p} , and GC mass. This fraction varies from 0.20 at low masses (10{sup 4.5} M{sub Sun }) to 0.45 at high masses (10{sup 6.5} M{sub Sun }). The fraction of mass associated with pure AGB ejecta is directly related to the total mass of the cluster at birth; the ratio between the initial and present mass in stars can therefore be derived. Assuming a star formation efficiency of 50%, the observed Na-O anti-correlations imply that GCs were at least 10-20 times more massive at birth, a conclusion that is in qualitative agreement with previous work. These factors are lower limits because any mass-loss mechanism that removes first- and second-generation stars equally will leave f{sub p} unchanged. The mass dependence of f{sub p} probably arises because lower mass GCs are unable to retain all of the AGB ejecta from the first stellar generation. Recent observations of elemental abundances in intermediate-age Large Magellanic Cloud clusters are re-interpreted and shown to be consistent with this basic scenario. The small scatter in f{sub p} at fixed GC mass argues strongly that the process responsible for the large mass loss is internal to GCs. A satisfactory explanation of these trends is currently lacking.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Graph identification of proteins in tomograms ( GRIP‐Tomo )

Abstract In this study, we present a method of pattern mining based on network theory that enables the identification of protein structures or complexes from synthetic volume densities, without the knowledge of predefined templates or human biases for refinement. We hypothesized that the topological connectivity of protein structures is invariant, and they are distinctive for the purpose of protein identification from distorted data presented in volume densities. Three‐dimensional densities of a protein or a complex from simulated tomographic volumes were transformed into mathematical graphs as observables. We systematically introduced data distortion or defects such as missing fullness of data, the tumbling effect, and the missing wedge effect into the simulated volumes, and varied the distance cutoffs in pixels to capture the varying connectivity between the density cluster centroids in the presence of defects. A similarity score between the graphs from the simulated volumes and the graphs transformed from the physical protein structures in point data was calculated by comparing their network theory order parameters including node degrees, betweenness centrality, and graph densities. By capturing the essential topological features defining the heterogeneous morphologies of a network, we were able to accurately identify proteins and homo‐multimeric complexes from 10 topologically distinctive samples without realistic noise added. Our approach empowers future developments of tomogram processing by providing pattern mining with interpretability, to enable the classification of single‐domain protein native topologies as well as distinct single‐domain proteins from multimeric complexes within noisy volumes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Detecting anomalous packets in network transfers: investigations using PCA, autoencoder and isolation forest in TCP

Large-scale scientific workflows rely heavily on high-performance file transfers. These transfers require strict quality parameters such as guaranteed bandwidth, no packet loss or data duplication. To have successful file transfers, methods such as predetermined thresholds and statistical analysis need to be done to determine abnormal patterns. Network administrators routinely monitor and analyze network data for diagnosing and alleviating these, making decisions based on their experience. However, as networks grow and become complex, monitoring large data files and quickly processing them, makes it improbable to identify errors and rectify these. Abnormal file transfers have been classified by simply setting alert thresholds, via tools such as PerfSonar and TCP statistics (Tstat). This paper investigates the feasibility of unsupervised feature extraction methods for identifying network anomaly patterns with three unsupervised classification methods—principal component analysis, autoencoder and isolation forest. Here, we collect file transfer statistics from two experiment sets—synthetic iPerf generated traffic and 1000 Genome workflow runs, with synthetically introduced anomalies. Our results show that while PCA and a simple autoencoder finds it difficult to detect clusters, the tree-variant isolation forest is able to identify anomalous packets by breaking down TCP traces into tree classes early.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

METALLICITY GRADIENTS IN THE MILKY WAY DISK AS OBSERVED BY THE SEGUE SURVEY

The observed radial and vertical metallicity distribution of old stars in the Milky Way disk provides a powerful constraint on the chemical enrichment and dynamical history of the disk system. We present the radial metallicity gradient, {Delta}[Fe/H]/{Delta}R, as a function of height above the plane, |Z|, using 7010 main-sequence turnoff stars observed by the Sloan Extension for Galactic Understanding and Exploration survey. The sample consists of mostly old thin and thick disk stars, with a minimal contribution from the stellar halo, in the region 6 kpc < R < 16 kpc, 0.15 kpc < |Z| < 1.5 kpc. The data reveal that the radial metallicity gradient becomes flat at heights |Z| > 1 kpc. The median metallicity at large |Z| is consistent with the metallicities seen in outer disk open clusters, which exhibit a flat radial gradient at [Fe/H] {approx}-0.5. We note that the outer disk clusters are also located at large |Z|; because the flat gradient extends to small R for our sample, there is some ambiguity in whether the observed trends for clusters are due to a change in R or |Z|. We therefore stress the importance of considering both the radial and vertical directions when measuring spatial abundance trends in the disk. The flattening of the gradient at high |Z| also has implications on thick disk formation scenarios, which predict different metallicity patterns in the thick disk. A flat gradient, such as we observe, is predicted by a turbulent disk at high redshift, but may also be consistent with radial migration, as long as mixing is strong. We test our analysis methods using a mock catalog based on the model of Schoenrich and Binney, and we estimate our distance errors to be {approx}25%. We also show that we can properly correct for selection biases by assigning weights to our targets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

CMed: Crowd Analytics for Medical Imaging Data

In this work, we present a visual analytics framework, CMed, for exploring medical image data annotations acquired from crowdsourcing. CMed can be used to visualize, classify, and filter crowdsourced clinical data based on a number of different metrics such as detection rate, logged events, and clustering of the annotations. CMed provides several interactive linked visualization components to analyze the crowd annotation results for a particular video and the associated workers. Additionally, all results of an individual worker can be inspected using multiple linked views in our CMed framework. We allow a crowdsourcing application analyst to observe patterns and gather insights into the crowdsourced medical data, helping him/her design future crowdsourcing applications for optimal output from the workers. We demonstrate the efficacy of our framework with two medical crowdsourcing studies: polyp detection in virtual colonoscopy videos and lung nodule detection in CT thin-slab maximum intensity projection videos. We also provide experts' feedback to show the effectiveness of our framework. Lastly, we share the lessons we learned from our framework with suggestions for integrating our framework into a clinical workflow.

97 MATHEMATICS AND COMPUTING↗
NASA NTRSDate not supplied

Springtime SEA Air Is Consistently Both Smoky and Humid, but This Relationship (and Its Radiative Effects) Varies Spatially and Seasonally

The atmosphere over the southeast Atlantic Ocean (SEA) sees a consistent springtime biomass burning (BB) smoke from widespread agricultural fires on the African continent. This smoke layer is initially lofted high in a continental mixed layer (~5-6km) and is then transported westward in the free troposphere, where it overlies and ultimately mixes into the SEA stratocumulus-topped oceanic boundary layer. Coincident with this smoke is an elevated humidity signal which is present from the time a given airmass is over the continental source region. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) was a NASA Earth Venture Suborbital mission with the goal of measuring aerosol, cloud, and atmospheric properties over this region during three deployments in September 2016, August 2017, and October 2018. A previous study discussed the spatial characteristics of the water vapor-BB plume observations in the September 2016 flight data and their degree of agreement with several atmospheric reanalyses and models. In the present work, we first discuss atmospheric chemistry, structure, and aerosol results from all three ORACLES deployments to place these results in a broader seasonal context. Despite the differing locations and season of each deployment, we show that there continues to be good agreement between the airborne ORACLES dataset and large-scale reanalyses, specifically the ECMWF ERA5 and CAMS reanalyses. Other reanalyses (specifically NASA's MERRA-2) preserved the observed correlation between meteorology and biomass burning conditions, but, as was seen for 2016, was frequently displaced spatially relative to the observations. The CAMS reanalysis performs better with water vapor than with CO. Results comparing CAMS column AOD to the field measurements show slight overestimates, consistent with previous analysis, but the good relationship observed between AOD and inlet-based aerosol extinction demonstrates this metric's utility to broader studies. The good ERA5/CAMS/ORACLES agreement allows us to next examine the multi-year seasonal patterns and trends beyond the three ORACLES deployment periods. Looking at seven years of reanalysis data for the BB season, we find distinct variations between each month/deployment in terms of vertical smoke distribution and correlation to atmospheric specific humidity, due to changing conditions through the BB season. Using k-means clustering of these climatological reanalysis, we identify six canonical atmospheric profile types of varying total atmospheric humidity and vertical structure and describe their changing incidence spatially and throughout the season, and six analogous profile types for carbon monoxide, allowing us to characterize the atmospheric structure of both vapor and BB over time throughout the SEA region. This classification will allow for a more complete analysis of the broader radiative and dynamical effects of humid aerosols overlying stratocumulus clouds.

Kristina Marie Myers Pistone↗
DOE OSTI2024

Influence of Carbon-Nitride Dot-Emitting Species and Evolution on Fluorescence-Based Sensing and Differentiation

Carbon dots have attracted widespread interest for sensing applications based on their low cost, ease of synthesis, and robust optical properties. We investigate structure–function evolution on multiemitter fluorescence patterns for model carbon-nitride dots (CNDs) and their implications on trace-level sensing. Hydrothermally synthesized CNDs with different reaction times were used to determine how specific functionalities and their corresponding fluorescence signatures respond upon the addition of trace-level analytes. Archetype explosives molecules were chosen as a testbed due to similarities in substituent groups or inductive properties (i.e., electron withdrawing), and solution-based assays were performed using ratiometric fluorescence excitation–emission mapping (EEM). Analyte-specific quenching and enhancement responses were observed in EEM landscapes that varied with the CND reaction time. We then used self-organizing map models to examine EEM feature clustering with specific analytes. Finally, the results reveal that interactions between carbon-nitride frameworks and molecular-like species dictate response characteristics that may be harnessed to tailor sensor development for specific applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗