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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Combining field and remote sensing data to estimate forest canopy damage and recovery following tropical cyclones across tropical regions

Abstract As tropical forests cycle the most water and carbon, it is crucial to understand the short- and long-term effects of intensifying cyclones on these ecosystems. Soil nutrient status has been shown to moderate forest cyclone responses using field litterfall measurements, but litterfall is one of the multiple cyclone impact metrtics, which may or may not be correlated with one another or with site nutrients. We used remotely sensed vegetation indices to quantify immediate damage and two-year recovery for 42 cases across nine tropical forests in Hawaii, Puerto Rico, Mexico, Australia, and Taiwan affected by 12 cyclones between 2004 and 2017. We tested whether changes in leaf area index (LAI) and enhanced vegetation index (EVI) correlated with changes in litterfall observations and how changes varied with total soil phosphorus (P) concentrations across regions. We compared cyclone-induced changes and recovery of LAI and EVI to litterfall observations compiled in a pantropical meta-analysis. We found large variation in changes in LAI and EVI across forests, with the greatest reductions in LAI (−77%) and EVI (−77%) in Mexico (Jalisco) and Puerto Rico, respectively. LAI ( r = −0.52) and EVI ( r = −0.60) changes correlated with those in litterfall across cases. Post-cyclone data showed recovery of LAI by four months, EVI by two months, and litterfall by ten months. We detected larger changes in LAI and EVI in forests with higher soil P, but these relationships were not significant when accounting for cyclone and site as random effects. Principal component analyses indicated a regional clustering of cases related to their contrasting cyclone regimes, with the frequency and intensity of cyclone events negatively correlated. Overall, remote sensing observations complement but do not substitute for ground observations that reveal cyclone damage and post-cyclone recovery in tropical forests, and soil phosphorus moderates some but not all metrics of stability in response to cyclones.

Bloom, Dellena E. (ORCID:0000000205981747)↗
DOE OSTI2022

FGC 1287 and its enigmatic 250 kpc long HI tail in the outskirts of Abell 1367

ABSTRACT We present H i and radio continuum, narrow-band Hα imaging, IFU spectroscopy, and X-ray observations of the FGC 1287 triplet projected ∼1.8 Mpc west of the galaxy cluster Abell 1367. One triplet member, FGC 1287, displays an exceptionally long, 250 kpc H i tail and an unperturbed stellar disc which are the typical signatures of ram pressure stripping (RPS). To generate detectable RPS signatures the presence of an Intracluster medium ICM or intragroup medium IGM with sufficient density to produce RPS at a realistic velocity relative to the ICM or IGM is a prerequisite. However, XMM–Newton observations were not able to detect X-ray emission from the triplet, implying that if a hot ICM/IGM is present, its density, ne, is less than 2.6 × 10−5 cm−3. Higher resolution VLA H i data presented here show FGC 1287’s H i disc is truncated and significantly warped, whereas the H i tail is clumpy. TNG Hα imaging identified three star-forming clumps projected within 20 kpc of FGC 1287’s disc, with VIMOS–IFU data confirming two of these are counterparts to H i clumps in the tail. The triplet’s H i kinematics, together with Hα and radio continuum imaging suggests an interaction may have enhanced star formation in FGC 1287’s disc, but cannot readily account for the origin of the long H i tail. We consider several scenarios which might reconcile RPS with the non-detection of ICM or IGM X-ray emission but none of these unambiguously explains the origin of the long H i tail.

Scott, T. C. (ORCID:0000000237464859)↗
DOE OSTI2024

Containers on Switches: A Cluster School Experience

Network switches, such as those from Arista and Mellanox, often have underutilized computational resources in the form of built-in processors and memory. By leveraging these untapped resources, we can optimize functionality and efficiency of computational cluster networks. Our research focuses on deploying containers directly onto these switches to execute various auxiliary tasks ranging from metric logging to system-wide management via post-boot configuration. By doing so, we can significantly enchance the capabilities of the cluster without the need for additional dedicated hardware. Our research involved five distinct scenarios where switch utilization could have a profound impact on HPC Clusters: run cloud-init services via link-local connection; configuring a Telegraf container to export metrics; deploying a caching proxy; creating a reconfigurable IPv6 DHCP/DNS provider for VLAN; and implementing a client detection with Magellan discovery. These scenarios were containerized with podman and docker, and tested both physically on the switch virtually on a QEMU VM both running SONiC OS. Testing and findings indicate that network switches can indeed be used for these scenarios. They offer a wide range of possibilities beyond these applications. They run as expected as containers on the switches, and although there were some minor issues, work-arounds were implemented. Overall, this is a positive result that can be further explored with more scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Discovery of an Ultra-faint Stellar System near the Magellanic Clouds with the DECam Local Volume Exploration Survey

We report the discovery of a new ultra-faint stellar system found near the Magellanic Clouds in the DECam Local Volume Exploration Survey. This new system, DELVE J0155−6815 (DELVE 2), is located at a heliocentric distance of D ⊙ = 71 ± 4 kpc, which places it at a 3D physical separation of 12 ± 3 kpc from the center of the Small Magellanic Cloud and from the center of the Large Magellanic Cloud (LMC). DELVE 2 is identified as a resolved overdensity of old (τ > 13.3 Gyr) and metal-poor ( dex) stars with a projected half-light radius of and an absolute magnitude of . The size and luminosity of DELVE 2 are consistent with both the population of recently discovered ultra-faint globular clusters and the smallest ultra-faint dwarf galaxies. However, its photometrically derived age and metallicity would place it among the oldest and most metal-poor globular clusters in the Magellanic system. In the absence of spectroscopic measurements of the system’s metallicity dispersion and internal kinematics, we are unable to conclusively classify this system at this time. DELVE 2 is detected in Gaia DR2 with a clear proper-motion signal, with multiple blue horizontal-branch stars near the centroid of the system with proper motions consistent with the systemic mean. We measure the system proper motion to be = mas yr−1. We compare the spatial position and proper motion of DELVE 2 with simulations of the accreted satellite population of the LMC and find that it is very likely to be associated with the LMC.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Ensembles of Metastable States Govern Heterogeneous Catalysis on Dynamic Interfaces

Heterogeneous catalysis is at the heart of chemical industry. Being able to tune and design efficient catalysts for processes of interest is of an utmost importance, and for this, the molecular-level understanding of heterogeneous catalysts is the first step, and indeed a prime focus of the modern catalysis research. For a long time, a single most thermodynamically stable structure of the catalytic interface attained in reaction conditions had been envisioned as the reactive phase. However, some catalytic interfaces continue to undergo structural dynamics in the steady state, triggered by high temperatures, pressures, and binding and changing reagents. Among particularly dynamic interfaces are such widely-used catalysts as crystalline and amorphous surfaced supporting (sub-)nano metallic clusters. Recently, it became clear that this dynamic fluxionality causes the supported clusters to populate many distinct structural and stoichiometric states in catalytic conditions. Hence, the catalytic interface should be viewed as an evolving statistical ensemble of many (not one) structures. As such, every member in the ensemble contributes to the properties of the catalyst differently, and in proportion to its probability to be populated. This new notion flips the established paradigm and calls for new theory, modeling approaches, operando measurements, and updated design strategies. The statistical ensemble nature of surface-supported sub-nano cluster catalysts can be exemplified by oxide-supported and adsorbate-covered Pt, Pd, Cu, CuPd clusters, catalytic toward oxidative and non-oxidative dehydrogenation. They have access to a variety of 3D and quasi-2D shapes. The compositions of their thermal ensembles are dependent on the cluster size, leading to size-specific catalytic activities and the famous “every atom counts” phenomenon. The support and adsorbates affect catalyst structures, and state of the reacting species causes the ensemble to change in every reaction intermediate. The most stable member of the ensemble dominates the thermodynamic properties of the corresponding intermediate, whereas the kinetics can be determined by more active but less populated metastable catalyst states, and that suggests that many earlier studies might have overlooked the actual active sites. Both effects depend on the relative time-scales of catalyst restructuring and reaction dynamics. The catalyst may routinely operate off-equilibrium. Ensemble phenomena lead to surprising exceptions from established rules of catalysis, such as scaling relations, and Arrhenius behavior. Catalyst deactivation is also an ensemble property, and its extent of mitigation can be predicted through the new paradigm. These findings were enabled by advances in theory, such as global optimization and subsequent utilization of multiple local minima, and pathways sampling, as well as operando catalyst characterization. The fact that the per-site and per-species resolution is needed for the description and predicting of catalyst properties gives theory the central role in catalysis research, as most experiments provide ensemble-average information and cannot detect the crucial minority species that may be responsible for the catalytic activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The intrinsic reddening of the Magellanic Clouds as traced by background galaxies – III. The Large Magellanic Cloud

ABSTRACT We present a map of the total intrinsic reddening across ≃ 90 deg2 of the Large Magellanic Cloud (LMC) derived using optical (ugriz) and near-infrared (IR; YJKs) spectral energy distributions (SEDs) of background galaxies. The reddening map is created from a sample of 222 752 early-type galaxies based on the lephareχ2 minimization SED-fitting routine. We find excellent agreement between the regions of enhanced intrinsic reddening across the central (4 × 4 deg2) region of the LMC and the morphology of the low-level pervasive dust emission as traced by far-IR emission. In addition, we are able to distinguish smaller, isolated enhancements that are coincident with known star-forming regions and the clustering of young stars observed in morphology maps. The level of reddening associated with the molecular ridge south of 30 Doradus is, however, smaller than in the literature reddening maps. The reduced number of galaxies detected in this region, due to high extinction and crowding, may bias our results towards lower reddening values. Our map is consistent with maps derived from red clump stars and from the analysis of the star formation history across the LMC. This study represents one of the first large-scale categorizations of extragalactic sources behind the LMC and as such we provide the lephare outputs for our full sample of ∼ 2.5 million sources.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

IMG/VR v4: an expanded database of uncultivated virus genomes within a framework of extensive functional, taxonomic, and ecological metadata

Viruses are widely recognized as critical members of all microbiomes. Metagenomics enables large-scale exploration of the global virosphere, progressively revealing the extensive genomic diversity of viruses on Earth and highlighting the myriad of ways by which viruses impact biological processes. IMG/VR provides access to the largest collection of viral sequences obtained from (meta)genomes, along with functional annotation and rich metadata. A web interface enables users to efficiently browse and search viruses based on genome features and/or sequence similarity. Here, for this work, we present the fourth version of IMG/VR, composed of >15 million virus genomes and genome fragments, a ≈6-fold increase in size compared to the previous version. These clustered into 8.7 million viral operational taxonomic units, including 231 408 with at least one high-quality representative. Viral sequences in IMG/VR are now systematically identified from genomes, metagenomes, and metatranscriptomes using a new detection approach (geNomad), and IMG standard annotation are complemented with genome quality estimation using CheckV, taxonomic classification reflecting the latest taxonomic standards, and microbial host taxonomy prediction. IMG/VR v4 is available at https://img.jgi.doe.gov/vr, and the underlying data are available to download at https://genome.jgi.doe.gov/portal/IMG_VR.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

MeerKAT view of the dancing ghosts – peculiar galaxy pair PKS 2130−538 in Abell 3785

ABSTRACT We present MeerKAT L-band (886–1682 MHz) observations of the extended radio structure of the peculiar galaxy pair PKS 2130−538 known as the ‘Dancing Ghosts’. The complex of bending and possibly interacting jets and lobes originate from two active galactic nuclei hosts in the Abell 3785 galaxy cluster, one of which is the brightest cluster galaxy. The radio properties of the PKS 2130−538 – flux density, spectral index, and polarization – are typical for large, bent-tail galaxies. We also investigate a number of thin extended low surface brightness filaments originating from the lobes. South-east from the Dancing Ghosts, we detect a region of low surface brightness emission that has no clear origin. While it could originate from the Abell 3785 radio halo, we investigate the possibility that it is associated with the two PKS 2130−538 hosts. We find no evidence of interaction between the two PKS 2130−538 hosts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Online Voltage Event Detection Using Synchrophasor Data with Structured Sparsity-Inducing Norms

This paper develops an accurate and computationally efficient data-driven framework to detect voltage events from PMU data streams. It develops an innovative Proximal Bilateral Random Projection (PBRP) algorithm to quickly decompose the PMU data matrix into a low-rank matrix, a row-sparse event-pattern matrix and a noise matrix. Here, the row-sparse pattern matrix significantly distinguishes events from normal behavior. These matrices are then fed into a clustering algorithm to separate voltage events from normal operating conditions. Large-scale numerical study results on real-world PMU data show that the proposed algorithm is computationally more efficient and achieves higher F scores than state-of-the-art benchmarks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Photoionization energetics and dissociation pathways of hydroperoxyethyl formate produced in the reaction of CH 3 CHOO + formic acid

The bimolecular reaction of Criegee intermediates, zwitterionic carbonyl oxide species produced in alkene ozonolysis, with organic acids leads to formation of functional hydroperoxides implicated in the generation of atmospheric aerosols. This theoretical study using high-level explicitly correlated coupled-cluster theory examines the low energy conformers of hydroperoxyethyl formate [HOOCH(CH 3 )OCHO, HPEF] formed in the bimolecular reaction of CH 3 CHOO, a simple alkyl-substituted Criegee intermediate, with formic acid, and the detection of HPEF via photoionization. Here, the vertical and adiabatic ionization energies of HPEF are computed, along with the pathways for dissociative ionization that produce HO 2 or OCHO fragments with daughter ions.

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

High-significance detection of correlation between the unresolved gamma-ray background and the large-scale cosmic structure

Our understanding of the γ-ray sky has improved dramatically in the past decade, however, the unresolved γ-ray background (UGRB) still has a potential wealth of information about the faintest γ-ray sources pervading the Universe. Statistical cross-correlations with tracers of cosmic structure can indirectly identify the populations that most characterize the γ-ray background. In this study, we analyze the angular correlation between the γ-ray background and the matter distribution in the Universe as traced by gravitational lensing, leveraging more than a decade of observations from the Fermi-Large Area Telescope (LAT) and 3 years of data from the Dark Energy Survey (DES). We detect a correlation at signal-to-noise ratio of 8.9. Most of the statistical significance comes from large scales, demonstrating, for the first time, that a substantial portion of the UGRB aligns with the mass clustering of the Universe as traced by weak lensing. Blazars provide a plausible explanation for this signal, especially if those contributing to the correlation reside in halos of large mass (∼ 10 14 M ⊙ ) and account for approximately 30–40% of the UGRB above 10 GeV. Additionally, we observe a preference for a curved γ-ray energy spectrum, with a log-parabolic shape being favored over a power-law. We also discuss the possibility of modifications to the blazar model and the inclusion of additional γ-ray sources, such as star-forming galaxies, misalinged active galactic nuclei, or particle dark matter.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Short-period Variability in the Globular Cluster NGC 419 and the SMC Field

Delta Scuti (δ Sct) stars have been extensively studied in our Galaxy but far less in extragalactic systems. Here we study the population of δ Sct variables in NGC 419, an intermediate-age globular cluster of the Small Magellanic Cloud (SMC), using g, r, and i Gemini-S/Gemini Multi-Object Spectrograph (GMOS) time-series observations. Our goal is to study the role of such variables in the cluster extended main-sequence turnoff (MSTO). We report the discovery of 54 δ Sct stars and three eclipsing binaries in the NGC 419 field. We find only a handful of the δ Sct stars at the MSTO of NGC 419, while the majority are fainter, indicating that the cluster is younger (≲1.2 Gyr) than previously thought. Considering their radial distribution, we identify only six δ Sct stars as probable members of NGC 419, while the 48 remaining are likely δ Sct stars of the SMC field. Cluster δ Sct stars appear close to the red edge of the MSTO, supporting the idea that the extended MSTO has its origin in an age spread. The 48 field δ Sct stars represent the largest detection of δ Sct stars made in the SMC. The period distribution of these newly detected δ Sct stars (0.04 day ≲ P ≲ 0.15 day) is similar to that detected in other systems. The amplitude distribution (0.05 mag ≲ Δr ≲ 0.60 mag) is likely biased because of the lack of low-amplitude stars. We finally use the δ Sct stars to calculate distances using different period–luminosity relations. The average distance moduli obtained are 18.76 ± 0.14 mag for NGC 419 and 18.86 ± 0.11 mag for the SMC field, which agree with previous measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

The ecological assembly of bacterial communities in Antarctic wetlands varies across levels of phylogenetic resolution

Summary As functional traits are conserved at different phylogenetic depths, the ability to detect community assembly processes can be conditional on the phylogenetic resolution; yet most previous work quantifying their influence has focused on a single level of phylogenetic resolution. Here, we have studied the ecological assembly of bacterial communities from an Antarctic wetland complex, applying null models across different levels of phylogenetic resolution (i.e. clustering ASVs into OTUs with decreasing sequence identity thresholds). We found that the relative influence of the community assembly processes varies with phylogenetic resolution. More specifically, selection processes seem to impose stronger influence at finer (100% sequence similarity ASV) than at coarser (99%–97% sequence similarity OTUs) resolution. We identified environmental features related with the ecological processes and propose a conceptual model for the bacterial community assembly in this Antarctic ecosystem. Briefly, eco‐evolutionary processes appear to be leading to different but very closely related ASVs in lotic, lentic and terrestrial environments. In all, this study shows that assessing community assembly processes at different phylogenetic resolutions is key to improve our understanding of microbial ecology. More importantly, a failure to detect selection processes at coarser phylogenetic resolution does not imply the absence of such processes at finer resolutions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Metal-insulator transition and magnetism of SU(3) fermions in the square lattice

We study the SU(3) symmetric Fermi-Hubbard model (FHM) in the square lattice at 1/3-filling using numerically exact determinant quantum Monte Carlo and numerical linked-cluster expansion techniques. We present the different regimes of the model in the T–U plane, which are characterized by local and short-range correlations, and capture signatures of the metal-insulator transition and magnetic crossovers. These signatures are detected as the temperature scales characterizing the rise of the compressibility, and an interaction-dependent change in the sign of the diagonal spin-spin correlation function. The analysis of the compressibility estimates the location of the metal-insulator quantum critical point at U c /t ~ 6, and provides a temperature scale for observing Mott physics at finite T. Furthermore, from the analysis of the spin-spin correlation function we observe that for U/t ≳ 6 and T ~ J = 4⁢t 2 /U there is a development of a short-range two-sublattice (2SL) antiferromagnetic structure, as well as an emerging three-sublattice (3SL) antiferromagnetic structure as the temperature is lowered below T/J ≲ 0.57. This crossover from 2SL to 3SL magnetic ordering agrees with Heisenberg limit predictions, and has observable effects on the density of on-site pairs. Finally, we describe how the features of the regimes in the T–U plane can be explored with alkaline-earth-like atoms in optical lattices with currently achieved experimental techniques and temperatures. Furthermore, the results discussed in this paper provide a starting point for the exploration of the SU(3) FHM upon doping.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Cluster-Graph Fingerprinting: A Framework for Quantitative Analysis of Machine-Learned Interatomic Model Training and Simulation Data

Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these models can lead to difficult-to-detect errors that can compromise prediction accuracy. To address this challenge, we introduce a novel fingerprinting approach based on the Chebyshev Interaction Model for Efficient Simulation (ChIMES) ML-IAM graph-based descriptor. Our strategy enables efficient and statistically rigorous analysis of system configurations used in ML-IAM training and those generated by their application, e.g., in molecular dynamics simulations. We demonstrate that these fingerprints can effectively assess novelty of a configuration relative to an existing data set and determine dissimilarity among individual configurations, which are two key tasks in workflows for active learning-based ML-IAM training, data set curation, and on-the-fly uncertainty quantification.

36 MATERIALS SCIENCE↗
DOE OSTI2022

PDBspheres: a method for finding 3D similarities in local regions in proteins

Abstract We present a structure-based method for finding and evaluating structural similarities in protein regions relevant to ligand binding. PDBspheres comprises an exhaustive library of protein structure regions (‘spheres’) adjacent to complexed ligands derived from the Protein Data Bank (PDB), along with methods to find and evaluate structural matches between a protein of interest and spheres in the library. PDBspheres uses the LGA (Local–Global Alignment) structure alignment algorithm as the main engine for detecting structural similarities between the protein of interest and template spheres from the library, which currently contains >2 million spheres. To assess confidence in structural matches, an all-atom-based similarity metric takes side chain placement into account. Here, we describe the PDBspheres method, demonstrate its ability to detect and characterize binding sites in protein structures, show how PDBspheres—a strictly structure-based method—performs on a curated dataset of 2528 ligand-bound and ligand-free crystal structures, and use PDBspheres to cluster pockets and assess structural similarities among protein binding sites of 4876 structures in the ‘refined set’ of the PDBbind 2019 dataset.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Grass xylan structural variation suggests functional specialization and distinctive interaction with cellulose and lignin

SUMMARY Xylan is the most abundant non‐cellulosic polysaccharide in grass cell walls, and it has important structural roles. The name glucuronoarabinoxylan (GAX) is used to describe this variable hemicellulose. It has a linear backbone of β‐1,4‐xylose (Xyl) residues that may be substituted with α‐1,2‐linked (4‐ O ‐methyl)‐glucuronic acid (GlcA), α‐1,3‐linked arabinofuranose (Ara f ), and sometimes acetylation at the O ‐2 and/or O ‐3 positions. The role of these substitutions remains unclear, although there is increasing evidence that they affect the way xylan interacts with other cell wall components, particularly cellulose and lignin. Here, we used substitution‐dependent endo‐xylanase enzymes to investigate the variability of xylan substitution in grass culm cell walls. We show that there are at least three different types of xylan: (i) an arabinoxylan with evenly distributed Ara f substitutions without GlcA (AXe); (ii) a glucuronoarabinoxylan with clustered GlcA modifications (GAXc); and (iii) a highly substituted glucuronoarabinoxylan (hsGAX). Immunolocalization of AXe and GAXc in Brachypodium distachyon culms revealed that these xylan types are not restricted to a few cell types but are instead widely detected in Brachypodium cell walls. We hypothesize that there are functionally specialized xylan types within the grass cell wall. The even substitutions of AXe may permit folding and binding on the surface of cellulose fibrils, whereas the more complex substitutions of the other xylans may support a role in the matrix and interaction with other cell wall components.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Multi defect detection and analysis of electron microscopy images with deep learning

Electron microscopy is widely used to explore defects in crystal structures, but human detecting of defects is often time-consuming, error-prone, and unreliable, and is not scalable to large numbers of images or real-time analysis. In this work, we discuss the application of machine learning approaches to find the location and geometry of different defect clusters in irradiated steels. We show that a deep learning based Faster R-CNN analysis system has a performance comparable to human analysis with relatively small training data sets. Furthermore, this study proves the promising ability to apply deep learning to assist the development of automated microscopy data analysis even when multiple features are present and paves the way for fast, scalable, and reliable analysis systems for massive amounts of modern electron microscopy data.

36 MATERIALS SCIENCE↗