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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Nonperturbative resolution of strong coupling singularities in 4D 𝒩 = 1 heterotic M-theory

We investigate the interior of the moduli space of four-dimensional 𝒩 = 1 theories of gravity arising from compactifications of the 𝐸 8 × 𝐸 8 heterotic string on Calabi-Yau threefolds. By studying the threshold corrections to the coupling of the heterotic gauge groups, we infer the existence of a strong coupling singularity for one of the perturbative heterotic gauge groups, which effectively yields an additional finite distance boundary of the classical scalar field space. In heterotic M-theory, this boundary maps to a domain wall solution for which the gauge coupling and the warp factor on one of the Horava-Witten 9-branes diverge, thus highlighting the gravitational origin of the classical strong coupling singularity. The divergence of the warp factor is, however, regulated once nonperturbative effects are taken into account, as we demonstrate by studying the instanton corrections to the 5D BPS domain wall equations. This regularization implies that the classical strong coupling boundary of the scalar field 4D 𝒩 = 1 heterotic M-theory is resolved, indicating that, at the quantum level, the field space can be extended beyond this classical boundary.

Cvetič, Mirjam↗
DOE OSTI2023

SpeckleNN: a unified embedding for real-time speckle pattern classification in X-ray single-particle imaging with limited labeled examples

With X-ray free-electron lasers (XFELs), it is possible to determine the three-dimensional structure of noncrystalline nanoscale particles using X-ray single-particle imaging (SPI) techniques at room temperature. Classifying SPI scattering patterns, or `speckles', to extract single-hits that are needed for real-time vetoing and three-dimensional reconstruction poses a challenge for high-data-rate facilities like the European XFEL and LCLS-II-HE. Here, we introduce SpeckleNN, a unified embedding model for real-time speckle pattern classification with limited labeled examples that can scale linearly with dataset size. Trained with twin neural networks, SpeckleNN maps speckle patterns to a unified embedding vector space, where similarity is measured by Euclidean distance. We highlight its few-shot classification capability on new never-seen samples and its robust performance despite having only tens of labels per classification category even in the presence of substantial missing detector areas. Without the need for excessive manual labeling or even a full detector image, our classification method offers a great solution for real-time high-throughput SPI experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Constraints on Λ CDM extensions from the SPT-3G 2018 $EE$ and $TE$ power spectra

Here, we present constraints on extensions to the Λ CDM cosmological model from measurements of the E-mode polarization autopower spectrum and the temperature-E-mode cross-power spectrum of the cosmic microwave background (CMB) made using 2018 SPT-3G data. The extensions considered vary the primordial helium abundance, the effective number of relativistic degrees of freedom, the sum of neutrino masses, the relativistic energy density and mass of a sterile neutrino, and the mean spatial curvature. We do not find clear evidence for any of these extensions, from either the SPT-3G 2018 dataset alone or in combination with baryon acoustic oscillation and Planck data. None of these model extensions significantly relax the tension between Hubble-constant, H 0 , constraints from the CMB and from distance-ladder measurements using Cepheids and supernovae. The addition of the SPT-3G 2018 data to Planck reduces the square-root of the determinants of the parameter covariance matrices by factors of 1.3–2.0 across these models, signaling a substantial reduction in the allowed parameter volume. We also explore CMB-based constraints on H 0 from combined SPT, Planck, and ACT DR4 datasets. While individual experiments see some indications of different H 0 values between the TT, TE, and EE spectra, the combined H 0 constraints are consistent between the three spectra. For the full combined datasets, we report H 0 = 67.49 ± 0.53 km s -1 Mpc -1 , which is the tightest constraint on H0 from CMB power spectra to date and in 4.1σ tension with the most precise distance-ladder-based measurement of H 0 . The SPT-3G survey is planned to continue through at least 2023, with existing maps of combined 2019 and 2020 data already having ~ 3.5 x lower noise than the maps used in this analysis.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Do chaotic field lines cause fast reconnection in coronal loops?

Over the past decade, Boozer has argued that three-dimensional (3D) magnetic reconnection fundamentally differs from two-dimensional reconnection due to the fact that the separation between any pair of neighboring field lines almost always increases exponentially over distance in a 3D magnetic field. According to Boozer, this feature makes 3D field-line mapping chaotic and exponentially sensitive to small non-ideal effects; consequently, 3D reconnection can occur without intense current sheets. We test Boozer's theory via ideal and resistive reduced magnetohydrodynamic simulations of the Boozer–Elder coronal loop model driven by sub-Alfvénic footpoint motions [A. H. Boozer and T. Elder, Phys. Plasmas 28, 062303 (2021)]. In this work, our simulation results significantly differ from their predictions. The ideal simulation shows that Boozer and Elder under-predict the intensity of current density due to missing terms in their reduced model equations. Furthermore, resistive simulations of varying Lundquist numbers show that the maximal current density scales linearly rather than logarithmically with the Lundquist number.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Remote Sensing-Informed Zonation for Understanding Snow, Plant and Soil Moisture Dynamics within a Mountain Ecosystem

In the headwater catchments of the Rocky Mountains, plant productivity and its dynamics are largely dependent upon water availability, which is influenced by changing snowmelt dynamics associated with climate change. Understanding and quantifying the interactions between snow, plants and soil moisture is challenging, since these interactions are highly heterogeneous in mountainous terrain, particularly as they are influenced by microtopography within a hillslope. Recent advances in satellite remote sensing have created an opportunity for monitoring snow and plant dynamics at high spatiotemporal resolutions that can capture microtopographic effects. In this study, we investigate the relationships among topography, snowmelt, soil moisture and plant dynamics in the East River watershed, Crested Butte, Colorado, based on a time series of 3-meter resolution PlanetScope normalized difference vegetation index (NDVI) images. To make use of a large volume of high-resolution time-lapse images (17 images total), we use unsupervised machine learning methods to reduce the dimensionality of the time lapse images by identifying spatial zones that have characteristic NDVI time series. We hypothesize that each zone represents a set of similar snowmelt and plant dynamics that differ from other identified zones and that these zones are associated with key topographic features, plant species and soil moisture. We compare different distance measures (Ward and complete linkage) to understand the effects of their influence on the zonation map. Results show that the identified zones are associated with particular microtopographic features; highly productive zones are associated with low slopes and high topographic wetness index, in contrast with zones of low productivity, which are associated with high slopes and low topographic wetness index. The zones also correspond to particular plant species distributions; higher forb coverage is associated with zones characterized by higher peak productivity combined with rapid senescence in low moisture conditions, while higher sagebrush coverage is associated with low productivity and similar senescence patterns between high and low moisture conditions. In addition, soil moisture probe and sensor data confirm that each zone has a unique soil moisture distribution. This cluster-based analysis can tractably analyze high-resolution time-lapse images to examine plant-soil-snow interactions, guide sampling and sensor placements and identify areas likely vulnerable to ecological change in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Self-Supervised Anomaly Detection via Neural Autoregressive Flows with Active Learning

Many self-supervised methods have been proposed with the target of image anomaly detection. These methods often rely on the paradigm of data augmentation with predefined transformations such as flipping, cropping, and rotations. However, it is not straightforward to apply these techniques for non-image data, such as time series or tabular data, while the performance of the existing deep approaches has been under our expectation on tasks beyond images. In this work, we propose a novel active learning (AL) scheme that relied on neural autoregressive flows (NAF) for self-supervised anomaly detection, specifically on small-scale data. Unlike other generative models such as GANs or VAEs, flow-based models allow to explicitly learn the probability density and thus can assign accurate likelihoods to normal data which makes it usable to detect anomalies. The proposed NAF-AL method is achieved by efficiently generating random samples from latent space and transforming them into feature space along with likelihoods via invertible mapping. The samples with lower likelihoods are selected and further checked by outlier detection using Mahalanobis distance. The augmented samples incorporating with normal samples are used for training a better detector so as to approach decision boundaries. Compared with random transformations, NAF-AL can be interpreted as a likelihood-oriented data augmentation that is more efficient and robust. Extensive experiments show that our approach outperforms existing baselines on multiple time series and tabular datasets, and a real-world application in advanced manufacturing, with significant improvement on anomaly detection accuracy and robustness over the state-of-the-art.

Zhang, Jiaxin↗
DOE OSTI2024

Chromosome-level genome assemblies and genetic maps reveal heterochiasmy and macrosynteny in endangered Atlantic Acropora

Abstract Background Over their evolutionary history, corals have adapted to sea level rise and increasing ocean temperatures, however, it is unclear how quickly they may respond to rapid change. Genome structure and genetic diversity contained within may highlight their adaptive potential. Results We present chromosome-scale genome assemblies and linkage maps of the critically endangered Atlantic acroporids,Acropora palmataandA. cervicornis. Both assemblies and linkage maps were resolved into 14 chromosomes with their gene content and colinearity. Repeats and chromosome arrangements were largely preserved between the species. The family Acroporidae and the genusAcroporaexhibited many phylogenetically significant gene family expansions. Macrosynteny decreased with phylogenetic distance. Nevertheless, scleractinians shared six of the 21 cnidarian ancestral linkage groups as well as numerous fission and fusion events compared to other distantly related cnidarians. Genetic linkage maps were constructed from oneA. palmatafamily and 16A. cervicornisfamilies using a genotyping array. The consensus maps span 1,013.42 cM and 927.36 cM forA. palmataandA. cervicornis, respectively. Both species exhibited high genome-wide recombination rates (3.04 to 3.53 cM/Mb) and pronounced sex-based differences, known as heterochiasmy, with 2 to 2.5X higher recombination rates estimated in the female maps. Conclusions Together, the chromosome-scale assemblies and genetic maps we present here are the first detailed look at the genomic landscapes of the critically endangered Atlantic acroporids. These data sets revealed that adaptive capacity of Atlantic acroporids is not limited by their recombination rates. The sister species maintain macrosynteny with few genes with high sequence divergence that may act as reproductive barriers between them. In the AtlanticAcropora, hybridization between the two sister species yields an F1 hybrid with limited fertility despite the high levels of macrosynteny and gene colinearity of their genomes. Together, these resources now enable genome-wide association studies and discovery of quantitative trait loci, two tools that can aid in the conservation of these species.

Biotechnology & Applied Microbiology↗
DOE OSTI2023

Quantitative Representativeness and Constituency of the Long-Term Agroecosystem Research Network and Analysis of Complementarity with Existing Ecological Networks

Abstract Studies conducted at sites across ecological research networks usually strive to scale their results to larger areas, trying to reach conclusions that are valid throughout larger enclosing regions. Network representativeness and constituency can show how well conditions at sampling locations represent conditions also found elsewhere and can be used to help scale-up results over larger regions. Multivariate statistical methods have been used to design networks and select sites that optimize regional representation, thereby maximizing the value of datasets and research. However, in networks created from already established sites, an immediate challenge is to understand how well existing sites represent the range of environments in the whole area of interest. We performed an analysis to show how well sites in the USDA Long-Term Agroecosystem Research (LTAR) Network represent all agricultural working lands within the conterminous United States (CONUS). Our analysis of 18 LTAR sites, based on 15 climatic and edaphic characteristics, produced maps of representativeness and constituency. Representativeness of the LTAR sites was quantified through an exhaustive pairwise Euclidean distance calculation in multivariate space, between the locations of experiments within each LTAR site and every 1 km cell across the CONUS. Network representativeness is from the perspective of all CONUS locations, but we also considered the perspective from each LTAR site. For every LTAR site, we identified the region that is best represented by that particular site—its constituency—as the set of 1 km grid locations best represented by the environmental drivers at that particular LTAR site. Representativeness shows how well the combination of characteristics at each CONUS location was represented by the LTAR sites’ environments, while constituency shows which LTAR site was the closest match for each location. LTAR representativeness was good across most of the CONUS. Representativeness for croplands was higher than for grazinglands, probably because croplands have more specific environmental criteria. Constituencies resemble ecoregions but have their environmental conditions “centered” on those at particular existing LTAR sites. Constituency of LTAR sites can be used to prioritize the locations of experimental research at or even within particular sites, or to identify the extents that can likely be included when generalizing knowledge across larger regions of the CONUS. Sites with a large constituency have generalist environments, while those with smaller constituency areas have more specialized environmental combinations. These “specialist” sites are the best representatives for smaller, more unusual areas. The potential of sharing complementary sites from the Long-Term Ecological Research (LTER) Network and the National Ecological Observatory Network (NEON) to boost representativeness was also explored. LTAR network representativeness would benefit from borrowing several NEON sites and the Sevilleta LTER site. Later network additions must include such specialist sites that are targeted to represent unique missing environments. While this analysis exhaustively considered principal environmental characteristics related to production on working lands, we did not consider the focal agronomic systems under study, or their socio-economic context.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Calculation of ion–ion mutual neutralization rate constants using Landau–Zener theory coupled with trajectory simulations for Ar + –Cl − , Br − , I −

In this computational study, we self-consistently calculate the rate constants of mutual neutralization reactions by incorporating the electron transfer probability, using Landau–Zener state transition theory with inputs derived from ab initio quantum chemistry calculations, into classical trajectory simulations. Electronic structure calculations are done using correlation consistent basis sets with multi-reference configuration interaction to map all the molecular electronic states below the ion-dissociation limit as a function of the distance between the reacting species. Our electronic structure calculations have been significantly improved from our previous work through improved selection of molecular electronic configurations maintaining a fine grid of 1a 0 over a wide range of bond lengths and accurate treatment of spin–orbit couplings. Non-adiabatic coupling matrix elements are calculated with the three-point central difference method near each avoided crossing to estimate the exact crossing point R x and coupling parameter H if , which are inputs to the multi-channel Landau–Zener theory to calculate the electron transition probability. Our approach is applied to estimate the mutual neutralization rate constants for the following ion pairs: Ar + –Cl − , Ar + –Br − , Ar + –I − at ∼133 Pa. Furthermore, our predictions are compared against the experimental data reported. It is seen that the improvement in the electronic structure calculation results in excellent agreement between the simulation results and the available experimental data to within a factor of ∼2 or ∼±50%.

Complete-active space self-consistent field↗
DOE OSTI2023

GRB 221009A: Discovery of an Exceptionally Rare Nearby and Energetic Gamma-Ray Burst

We report the discovery of the unusually bright long-duration gamma-ray burst (GRB), GRB 221009A, as observed by the Neil Gehrels Swift Observatory (Swift), Monitor of All-sky X-ray Image, and Neutron Star Interior Composition Explorer Mission. This energetic GRB was located relatively nearby (z = 0.151), allowing for sustained observations of the afterglow. The large X-ray luminosity and low Galactic latitude (b = 4$^°_.$3) make GRB 221009A a powerful probe of dust in the Milky Way. Using echo tomography, we map the line-of-sight dust distribution and find evidence for significant column densities at large distances (≳10 kpc). We present analysis of the light curves and spectra at X-ray and UV–optical wavelengths, and find that the X-ray afterglow of GRB 221009A is more than an order of magnitude brighter at T 0 + 4.5 ks than that from any previous GRB observed by Swift. In its rest frame, GRB 221009A is at the high end of the afterglow luminosity distribution, but not uniquely so. In a simulation of randomly generated bursts, only 1 in 10 4 long GRBs were as energetic as GRB 221009A; such a large E γ,iso implies a narrow jet structure, but the afterglow light curve is inconsistent with simple top-hat jet models. Using the sample of Swift GRBs with redshifts, we estimate that GRBs as energetic and nearby as GRB 221009A occur at a rate of ≲1 per 1000 yr—making this a truly remarkable opportunity unlikely to be repeated in our lifetime.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Remote vibration sensing through opaque media using permanent magnets

A method of sensing vibrations or displacements remotely is provided. Magnets are attached to vibrating objects or the vibrating objects themselves are magnetic. A number of magnetic sensors are placed a specified distance from the magnets. Vibrational displacement of the vibrating objects is determined according to a model that maps changes in magnetic field to vibrations or spatial displacements.

Mazumdar, Yi Chen↗
DOE OSTI2025

CHARGE-MAP: An integrated framework to study the multicriteria EV charging infrastructure expansion problem

The widespread adoption of electric vehicles (EVs) in recent years has necessitated the development of effective charging infrastructures. However, charging infrastructure expansion is a multifaceted problem that requires careful consideration of the existing infrastructure, spatiotemporal distribution of charging demands, power-grid capacity, and budget constraints. Here, to approach this complex problem, we present CHARGE-MAP, a data-driven simulation-optimization framework, focused on ensuring meaningful charging experience for individual EV owners. CHARGE-MAP integrates three modules: an agent-based simulation module that estimates spatiotemporal distribution of charging demands by modeling EV adopter mobility and charging behavior; an optimization module that determines optimal new charging station/charger locations and capacities, while minimizing expected detour distances and wait-times with a limited number of new stations; and a power module that determines how to connect the stations to the power grid while maintaining its stability. Using the state of Virginia (consisting of 95 counties and 38 independent cities) as a case study, our results show that CHARGE-MAP can meet the demand of ~198,600 predicted EVs with 1,305 new public charging stations and 2,164 new chargers. It reduces average detour distances for charging by 66% and wait-times at stations by 72% compared to the existing infrastructure. Furthermore, transformer capacity requirement analysis reveals that only 1.8% of residential transformers require upgrades, while over 80% of commercial charging locations can be supported with modest transformer infrastructure (25 to 50 kVA). This indicates that targeted investments can facilitate cost-effective EV integration. Consequently, CHARGE-MAP provides policymakers and urban planners with crucial data-driven insights for effective EV charging infrastructure expansion. Sign up for PNAS alerts.

charging infrastructure↗
DOE OSTI2023

Distant Echoes of the Milky Way’s Last Major Merger

The majority of the Milky Way’s stellar halo consists of debris from our galaxy’s last major merger, the Gaia-Sausage-Enceladus (GSE). In the past few years, stars from the GSE have been kinematically and chemically studied in the inner 30 kpc of our galaxy. However, simulations predict that accreted debris could lie at greater distances, forming substructures in the outer halo. Here we derive metallicities and distances using Gaia DR3 XP spectra for an all-sky sample of luminous red giant stars, and map the outer halo with kinematics and metallicities out to 100 kpc. We obtain follow-up spectra of stars in two strong overdensities—including the previously identified outer Virgo Overdensity—and find them to be relatively metal rich and on predominantly retrograde orbits, matching predictions from simulations of the GSE merger. We argue that these are apocentric shells of GSE debris, forming 60–90 kpc counterparts to the 15–20 kpc shells that are known to dominate the inner stellar halo. Extending our search across the sky with literature radial velocities, we find evidence for a coherent stream of retrograde stars encircling the Milky Way from 50 to 100 kpc, in the same plane as the Sagittarius Stream but moving in the opposite direction. These are the first discoveries of distant and structured imprints from the GSE merger, cementing the picture of an inclined and retrograde collision that built up our galaxy’s stellar halo.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Geometrically frustrated interactions drive structural complexity in amorphous calcium carbonate

Amorphous calcium carbonate is an important precursor for biomineralization in marine organisms. Key outstanding problems include understanding the structure of amorphous calcium carbonate and rationalizing its metastability as an amorphous phase. Here we report high-quality atomistic models of amorphous calcium carbonate generated using state-of-the-art interatomic potentials to help guide fits to X-ray total scattering data. Exploiting a recently developed inversion approach, we extract from these models the effective Ca∙∙∙Ca interaction potential governing the structure. This potential contains minima at two competing distances, corresponding to the two different ways that carbonate ions bridge Ca 2+ -ion pairs. We reveal an unexpected mapping to the Lennard-Jones–Gauss model normally studied in the context of computational soft matter. The empirical model parameters for amorphous calcium carbonate take values known to promote structural complexity. We thus show that both the complex structure and its resilience to crystallization are actually encoded in the geometrically frustrated effective interactions between Ca 2+ ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Calcite Twinning in Mollusk Shells and Carrara Marble

Mollusk shells protect the animals that form and inhabit them. They are composites of minerals and organics, with diverse mesostructures, including nacre, prismatic calcite, crossed-lamellar aragonite, and foliated calcite. Twins, that is, crystals mirror symmetric with respect to their coherent interface, occurring as formation or deformation twins, are observed in all mollusk shell mesostructures but never within calcite prisms. Here, nanotwins and microwins within single calcite prisms are observed in different shells. Using Polarization-dependent Imaging Contrast (PIC) mapping with 20–60 nm resolution, twins are observed to be 0.2–3 µm thick layers of differently oriented and colored crystals with respect to the main prism crystal. Multiple twins are interspersed with the prism crystal, parallel to one another, and similarly oriented. When comparing images of calcite prisms and twins obtained by PIC mapping and by Electron Back-Scattered Diffraction (EBSD), the images correspond precisely. All twins are e-twin types, with 127° angular distance between c-axes. E-twins are the most common deformation twins in geologic calcite, as also observed here in Carrara marble. Location of all twins near the outer surface of all shells and e-twin type both suggest that twins within calcite prisms in mollusk shells result from deformation twinning.

36 MATERIALS SCIENCE↗
DOE OSTI2022

CHANG-ES XXV: H i imaging of nearby edge-on galaxies – Data Release 4

ABSTRACT We present the ${\rm H}\, {\small I}$ distribution of galaxies from the Continuum Haloes in Nearby Galaxies – an EVLA Survey (CHANG-ES). Though the observational mode was not optimized for detecting ${\rm H}\, {\small I}$, we successfully produce ${\rm H}\, {\small I}$ cubes for 19 galaxies. The moment-0 maps from this work are available on CHANG-ES data release website (i.e. https://www.queensu.ca/changes). Our sample is dominated by star-forming, ${\rm H}\, {\small I}$-rich galaxies at distances from 6.27 to 34.1 Mpc. ${\rm H}\, {\small I}$ interferometric images on two of these galaxies (NGC 5792 and UGC 10288) are presented here for the first time, while 12 of our remaining sample galaxies now have better ${\rm H}\, {\small I}$ spatial resolutions and/or sensitivities of intensity maps than those in existing publications. We characterize the average scale heights of the ${\rm H}\, {\small I}$ distributions for a subset of most inclined galaxies (inclination > 80 deg), and compare them to the radio continuum intensity scale heights, which have been derived in a similar way. The two types of scale heights are well correlated, with similar dependence on disc radial extension and star formation rate surface density but different dependence on mass surface density. This result indicates that the vertical distribution of the two components may be governed by similar fundamental physics but with subtle differences.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Searching for three-nucleon short-range correlations

Electron scattering measurements from high-momentum nucleons in nuclei at SLAC and Jefferson Lab (JLab) have shown that these nucleons are generally associated with two-nucleon short-range correlations (2N-SRCs). These SRCs are formed when two nucleons in the nucleus interact at short distance via the strong tensor attraction or repulsive core of the NN potential. A series of measurements at JLab have mapped out the A dependence and isospin dependence of 2N-SRCs, and have begun to map out their momentum structure. However, we do not yet know if 3N-SRCs, similar high-momentum configurations of three nucleons, play an important role in nuclei. Here, we summarize here previous attempts to isolate 3N-SRCs, go over the limitations of these previous attempts, and discuss the present and near-term prospects for searching for 3N-SRCs, mapping out their A dependence in nuclei, and constraining their isospin and momentum structure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗