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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Atomically Revealing Bulk Point Defect Dynamics in Hydrogen‐Driven γ‐Fe 2 O 3 → Fe 3 O 4 → FeO Transformation

Understanding how point defects in the bulk govern redox transformations is essential for advancing hydrogen-based metal production and designing high-performance oxide materials. This study reveals the atomic-scale mechanisms driving hydrogen-induced reduction of γ-Fe 2 O 3 to Fe 3 O 4 , focusing on how bulk vacancy dynamics dictate structural evolution and reaction kinetics. A key finding is the pronounced contrast in defect behavior between the two oxides: in γ-Fe 2 O 3 , intrinsic Fe vacancies promote oxygen vacancy clustering, destabilizing the local lattice and driving nanopore formation. In contrast, Fe 3 O 4 exhibits a higher oxygen vacancy formation energy and lacks intrinsic Fe vacancies, suppressing vacancy aggregation and maintaining a dense, pore-free structure. This divergence governs distinct reduction pathways—γ-Fe 2 O 3 undergoes an interface-reaction-limited transformation confined to the γ-Fe 2 O 3 /Fe 3 O 4 boundary, while Fe 3 O 4 supports a uniform increase in oxygen vacancy concentration, enabling bulk-phase reduction to lower-oxide FeO. Integrated in situ electron microscopy and density functional theory modeling uncover a vacancy-mediated mechanism, where synergistic cation-anion vacancy dynamics steer microstructure evolution and phase progression. These insights highlight the critical role of vacancy dynamics in controlling oxide reactivity and offer a pathway toward vacancy engineering to enhance reduction kinetics in hydrogen metallurgy and to tailor porosity, reactivity, and structural resilience in oxide-based catalysts and energy materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Understanding drivers of oil and gas well integrity issues in the greater wattenberg area of Colorado

Well integrity is critically important to maintain to minimize the environmental impacts of oil and gas development and other subsurface energy operations. The Wattenberg Field of Colorado—a top producing field with >40,000 wells—has one of the most robust publicly reported well integrity programs in the country. Here, in this study, we analyzed annular pressure and annular-fluid geochemical test results collected from Wattenberg wells through the end of 2019 to characterize the frequency and spatial variability of integrity issues in the field and understand their drivers. Estimated frequencies of integrity issues among tested wells were 8.2-17.1% between 1955 and 2019 and 6.1-11.4% in 2019 alone. The frequency of integrity issues was nearly four times greater in wells located above the Longmont Wrench Fault Zone. Potential drivers of integrity issues were identified using ensemble decision tree models trained with a broad set of relevant information. Models show that well integrity issues are spatially clustered on regional and sub-regional scales and suggest the relatively high frequency of integrity issues observed is likely attributed to geologic factors. These findings are valuable for regulatory agencies and operators seeking to inform well integrity monitoring, plugging, and emissions reduction efforts and design future subsurface energy projects.

03 NATURAL GAS↗
DOE OSTI2022

The Illumination of Thunderclouds by Lightning: 2. The Effect of GLM Instrument Threshold on Detection and Clustering

Abstract Lightning is measured from space using optical instruments that detect transient changes in the illumination of the cloud top. How much of the flash (if any) is recorded by the instrument depends on the instrument detection threshold. NOAA's Geostationary Lightning Mapper (GLM) employs a dynamic threshold that varies across the imaging array and changes over time. This causes flashes in certain regions and at night to be recorded in greater detail than other flashes, and threshold inconsistencies will impose biases on all levels of GLM data products. In this study, we quantify the impact of the varying GLM threshold on event/group/flash detection, flash clustering, and gridded product generation by imposing artificial thresholds on the event data taken from a thunderstorm with a low instrument threshold (∼0.7 fJ). We find that even modest increases in threshold severely impact event (60% loss by 2 fJ, 90% loss by 10 fJ) and group (25% loss by 2 fJ, 81% loss by 10 fJ) detection by suppressing faint illumination of the cloud top from weak sources and scattering. Flash detection is impacted less by threshold increases (4% loss by 2 fJ), but reductions are still significant at higher thresholds (35% loss by 10 fJ, or 44% if single‐group flashes are removed). Undetected pulses cause individual flashes to be split and severely impact the construction of gridded products. All of these factors complicate the interpretation of GLM data, particularly when trended over time under a changing threshold.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The critical role of soil moisture in compound hazards

Soil moisture regulates the exchange of energy, water, and carbon across land–vegetation–atmosphere interfaces. Extremes in soil moisture can amplify natural hazards through interactions with diverse Earth system processes. Despite its mechanistic importance, soil moisture remains underrepresented in hazard research and predictive frameworks. Here, in this study, we review our current understanding of the role of soil moisture in the evolution and onset of diverse compound hazards by synthesizing the latest findings from observational and modelling studies. We highlight key soil moisture mechanisms, including atmospheric feedbacks that amplify drought–heatwave–wildfire events, precipitation couplings that promote clustered storms, and threshold responses that drive vegetation die-offs, trigger landslides, and induce flooding. Persistent challenges in observational data, model representation and operational implementation have limited the integration of soil moisture into hazard early-warning systems. Addressing these gaps through advances in observations, data assimilation, and physics-based and data-driven modelling will enhance hazard prediction and preparedness in a rapidly changing world.

Li, Chuxuan [University of California, Los Angeles↗
DOE OSTI2023

Repartitioned Brillouin-Wigner perturbation theory with a size-consistent second-order correlation energy

Second-order Møller-Plesset perturbation theory (MP2) often breaks down catastrophically in small-gap systems, leaving much to be desired in its performance for myriad chemical applications such as noncovalent interactions, thermochemistry, and dative bonding in transition metal complexes. This divergence problem has reignited interest in Brillouin-Wigner perturbation theory (BWPT), which is regular at all orders but lacks size consistency and extensivity, severely limiting its application to chemistry. In this work, we propose an alternative partitioning of the Hamiltonian that leads to a regular BWPT perturbation series that, through the second order, is size-extensive, size-consistent (provided its Hartree–Fock reference is also), and orbital invariant. Here, our second-order size-consistent Brillouin-Wigner (BW-s2) approach can describe the exact dissociation limit of H 2 in a minimal basis set, regardless of the spin polarization of the reference orbitals. More broadly, we find that BW-s2 offers improvements relative to MP2 for covalent bond breaking, noncovalent interaction energies, and metal/organic reaction energies, although rivaling coupled-cluster with single and double substitutions for thermochemical properties.

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

AbacusHOD : a highly efficient extended multitracer HOD framework and its application to BOSS and eBOSS data

ABSTRACT We introduce the AbacusHOD model and present two applications of AbacusHOD and the AbacusSummit simulations to observations. AbacusHOD is a Halo Occupation Distribution (HOD) framework written in Python that is particle-based, multitracer, highly generalized, and highly efficient. It is designed specifically with multitracer/cosmology analyses for next-generation large-scale structure surveys in mind, and takes advantage of the volume and precision offered by the new state-of-the-art AbacusSummit cosmological simulations. The model is also highly customizable and should be broadly applicable to any upcoming surveys and a diverse range of cosmological analyses. In this paper, we demonstrate the capabilities of the AbacusHOD framework through two example applications. The first example demonstrates the high efficiency and the large HOD extension feature set through an analysis of full-shape redshift-space clustering of BOSS galaxies at intermediate to small scales ($\lt 30\, h^{-1}$ Mpc), assessing the necessity of introducing secondary galaxy biases (assembly bias). We find strong evidence for using halo environment instead of concentration to trace secondary galaxy bias, a result which also leads to a moderate reduction in the ‘lensing is low’ tension. The second example demonstrates the multitracer capabilities of the AbacusHOD package through an analysis of the extended Baryon Oscillation Spectroscopic Survey cross-correlation measurements between three different galaxy tracers: luminous red galaxies, emission-line galaxies, and quasi-stellar objects. We expect the AbacusHOD framework, in combination with the AbacusSummit simulation suite, to play an important role in a simulation-based analysis of the upcoming Dark Energy Spectroscopic Instrument data sets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The role of the turbulence driving mode for the initial mass function

Turbulence is a critical ingredient for star formation, yet its role for the initial mass function (IMF) is not fully understood. Here we perform magnetohydrodynamical (MHD) simulations of star cluster formation including gravity, turbulence, magnetic fields, stellar heating, and outflow feedback to study the influence of the mode of turbulence driving on IMF. We find that simulations that employ purely compressive turbulence driving (COMP) produce a higher fraction of low-mass stars as compared to simulations that use purely solenoidal driving (SOL). The characteristic (median) mass of the sink particle (protostellar) distribution for COMP is shifted to lower masses by a factor of ∼1.5 compared to SOL. Our simulation IMFs capture the important features of the observed IMF form. We find that turbulence-regulated theories of the IMF match our simulation IMFs reasonably well in the high-mass and low-mass range, but underestimate the number of very low-mass stars, which form towards the later stages of our simulations and stop accreting due to dynamical interactions. Our simulations show that for both COMP and SOL, the multiplicity fraction is an increasing function of the primary mass, although the multiplicity fraction in COMP is higher than that of SOL for any primary mass range. We find that binary mass ratio distribution is independent of the turbulence driving mode. The average specific angular momentum of the sink particles in SOL is a factor of 2 higher than that for COMP. Overall, we conclude that the turbulence driving mode plays a significant role in shaping the IMF.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1979

Effect of grazing flow on the acoustic impedance of Helmholtz resonators consisting of single and clustered orifices

A semiempirical fluid mechanical model is derived for the acoustic behavior of thin-walled single orifice Helmholtz resonators in a grazing flow environment. The incident and cavity sound fields are connected in terms of an orifice discharge coefficient whose values are determined experimentally using the two-microphone method. Measurements show that at high grazing flow speeds, acoustical resistance is almost linearly proportional to the grazing flow speed and almost independent of incident sound pressure. The corresponding values of reactance are much smaller and tend towards zero. For thicker-walled orifice plates, resistance and reactance were observed to be less sensitive to grazing flow as the ratio of plate thickness to orifice diameter increased. Loud tones were observed to radiate from a single orifice Helmholtz resonator due to interaction between the grazing flow shear layer and the resonator cavity. Measurements showed that the tones radiated at a Strouhal number equal to 0.26. The effects of grazing flow on the impedance of Helmholtz resonators consisting of clusters of orifices was also studied. In general, both resistance and reaction were found to be virtually independent of orifice relative spacing and number. These findings are valid with and without grazing flow.

Hersch, A. S.↗
NASA NTRS1984

The Skylab lunar multispectral scanner data

Skylab S-192 multispectral scanner data, in 12 bands covering wavelengths from 0.41 to 2.3 microns, have been investigated to identify and classify geologic units of the lunar surface. Seventeen spectral cluster classes have been identified, seven in the highlands, seven in the maria, and three of which occur in both or in border regions. This finding may be roughly indicative of the relative heterogeneity of these regions. It implies that there is as much heterogeneity in the highlands as in the maria. This work extends the spectral and aerial coverage of similar studies of the lunar surface and provides useful data for comparison for most of the lunar near side.

Seeger, C. R.↗
NASA NTRS1994

Non-gaussian statistics of pencil beam surveys

We study the effect of the non-Gaussian clustering of galaxies on the statistics of pencil beam surveys. We derive the probability from the power spectrum peaks by means of Edgeworth expansion and find that the higher order moments of the galaxy distribution play a dominant role. The probability of obtaining the 128 Mpc/h periodicity found in pencil beam surveys is raised by more than one order of magnitude, up to 1%. Further data are needed to decide if non-Gaussian distribution alone is sufficient to explain the 128 Mpc/h periodicity, or if extra large-scale power is necessary.

Amendola, Luca↗
NASA NTRS2019

Discovery of Activities via Statistical Clustering of Fixation Patterns

Human behavior often consists of a series of distinct activities, each characterized by a unique pattern of interaction with the visual environment. This is true even in a restricted domain, such as a pilot flying an airplane; in this case, activities with distinct visual signatures might be things like communicating, navigating, monitoring, etc. We propose a novel analysis method for gaze-tracking data, to perform blind discovery of these hypothetical activities. We compare, not individual fixations, but groups of fixations aggregated over a fixed time interval (Tau). We assume that the environment has been divided into a finite set of discrete areas-of-interest (AOIs). For a given time interval, we compute the proportion of time spent fixating each AOI, resulting in an N-dimensional vector, where N is the number of AOIs. These proportions can be converted to integer counts by multiplying by Tau divided by the average fixation duration, a parameter that we fix at 283 milliseconds. We compare different intervals by computing the chi-squared statistic. The p-value associated with the statistic is the likelihood of observing the data under the hypothesis that the data in the two intervals were generated by a single process with a single set of probabilities governing the fixation of each AOI. We cluster the intervals, first by merging adjacent intervals that are sufficiently similar, optionally shifting the boundary between non-merged intervals to maximize the difference. Then we compare and cluster non-adjacent intervals. The method is evaluated using synthetic data generated by a hand-crafted set of activities. While the method generally finds more activities than put into the simulation, we have obtained agreement as high as 80 percent between the inferred activity labels and ground truth.

Eye Movements↗
DOE OSTI2024

Shared Use Travel Behavior for Improving Rural Mobility: Insights from Greene County, Pennsylvania

Rural communities are considered disadvantaged communities as they suffer from a lack of transport options. Thus, rural regionsprovide less accessibility for commuters to reach their destination as opposed to urban regions. However, the issues of transport disadvantageand shared use mobility in rural areas within the United States (US) have not been well investigated. Furthermore, transport disadvantagediffers between communities and regions across the globe; thus, there is a need to study the behavioral choices of rural commuters within theUS context. This study contributes by analyzing the behavioral choices of rural communities within the US through a case study site ofWaynesburg, Pennsylvania, for adopting a shared use shuttle service. K-means clusters showed that trips from the survey data were a goodrepresentation of real trips from Ecolane. Furthermore, random parameter-based binary logit models were calibrated using data collected fromstudents, faculty, and residents in Waynesburg, Greene County, to study the behavioral choices of commuters. The findings for the faculty andstudents group revealed that prior experience with shared services increases the likelihood of using a shared shuttle. An important personalcharacteristic of inconvenience showed a higher propensity toward using existing modes as opposed to a shared shuttle. Such commutersvalue personal vehicles as more convenient as they have childcare responsibilities and varying schedules for work that require them to moveback and forth across locations, thus making a shared shuttle less attractive for them. The socioeconomic factors of age and gender show ahigher propensity for using shared shuttles. Furthermore, the findings from this study could be helpful for agencies in improving rural mobility andconsidering such shared mobility services for rural communities

42 ENGINEERING↗
DOE OSTI2021

Astrometric Membership Tests for the Zinn–Newell–Gibson UV-bright Stars in Galactic Globular Clusters

In 1972, Zinn, Newell, & Gibson (ZNG) published a list of 156 candidate UV-bright stars they had found in 27 Galactic globular clusters (GCs), based on photographs in the U and V bands. UV-bright stars lie above the horizontal branch (HB) and blueward of the asymptotic giant branch (AGB) and red giant branch in the clusters’ color–magnitude diagrams. They are in rapid evolutionary phases—if they are members and not unrelated bright foreground stars. The ZNG list has inspired numerous follow-up studies, aimed at understanding late stages of stellar evolution. However, the ZNG candidates were presented only in finding charts, and celestial coordinates were not given. Using my own collection of CCD frames in u and V, I have identified all of the ZNG objects, and have assembled their coordinates, parallaxes, and proper motions from the recent Gaia Early Data Release 3 (EDR3). Based on the Gaia astrometry, I have determined which objects are probable cluster members (45% of the sample). For the members, using photometry from EDR3, I have assigned the stars to various evolutionary stages, including luminous post-AGB stars, and stars above the HB. I point out several ZNG stars of special interest that have still, to my knowledge, never been studied in detail. This study is an adjunct to a forthcoming survey of the Galactic GCs in the uBVI photometric system, designed for detection of low-gravity stars with large Balmer discontinuities.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Statistical Association between the Candidate Repeating FRB 20200320A and a Galaxy Group

Abstract We present results from angular cross correlations between select samples of CHIME/FRB repeaters and galaxies in three photometric galaxy surveys, which have shown correlations with the first CHIME/FRB catalog containing repeating and nonrepeating sources: Wide-field Infrared Survey Explorer (WISE) × SCOS, DESI-BGS, and DESI-LRG. We find a statistically significant correlation (p-value <0.001, after accounting for look-elsewhere factors) between a sample of repeaters with an extragalactic dispersion measure (DM) > 395 pc cm −3 and WISE × SCOS galaxies with redshiftz> 0.275. We demonstrate that the correlation arises surprisingly because of a statistical association between FRB 20200320A (extragalactic DM ≈ 550 pc cm −3 ) and a galaxy group in the same dark matter halo at redshiftz≈ 0.32. We estimate that the host halo, along with an intervening halo at redshiftz≈ 0.12, accounts for at least ∼30% of the extragalactic DM. Our results strongly motivate incorporating galaxy group and cluster catalogs into direct host association pipelines for FRBs with ≲ 1 ′ localization precision, effectively utilizing the two-point information to constrain FRB properties such as their redshift and DM distributions. In addition, we find marginal evidence for a negative correlation at 99.4% confidence limit between a sample of repeating FRBs with baseband data (median extragalactic DM = 354 pc cm −3 ) and DESI-LRG galaxies with redshift 0.3 ≤z< 0.45, suggesting that the repeaters might be more prone than apparent nonrepeaters to propagation effects in FRB–galaxy correlations due to intervening free electrons over angular scales ∼0.°5.

Astronomy & Astrophysics↗
NASA NTRS1994

Classification of asteroid spectra using a neural network

The 52-color asteroid survey (Bell et al., 1988) together with the 8-color asteroid survey (Zellner et al., 1985) provide a data set of asteroid spectra spanning 0.3-2.5 micrometers. An artificial neural network clusters these asteroid spectra based on their similarity to each other. We have also trained the neural network with a categorization learning output layer in a supervised mode to associate the established clusters with taxonomic classes. Results of our classification agree with Tholen's classification based on the 8-color data alone. When extending the spectral range using the 52-color survey data, we find that some modification of the Tholen classes is indicated to produce a cleaner, self-consistent set of taxonomic classes. After supervised training using our modified classes, the network correctly classifies both the training examples, and additional spectra into the correct class with an average of 90% accuracy. Our classification supports the separation of the K class from the S class, as suggested by Bell et al. (1987), based on the near-infrared spectrum. We define two end-member subclasses which seem to have compositional significance within the S class: the So class, which is olivine-rich and red, and the Sp class, which is pyroxene-rich and less red. The remaining S-class asteroids have intermediate compositions of both olivine and pyroxene and moderately red continua. The network clustering suggests some additional structure within the E-, M-, and P-class asteroids, even in the absence of albedo information, which is the only discriminant between these in the Tholen classification. New relationships are seen between the C class and related G, B, and F classes. However, in both cases, the number of spectra is too small to interpret or determine the significance of these separations.

Howell, E. S.↗
DOE OSTI2025

Manipulating the Assembly and Architecture of Fibrillar Silk

Silk is a unique and exceptionally strong biological material. However, no synthetic method has yet come close to replicating the properties of natural silk. This shortfall is attributed to an insufficient understanding of both silk nanofibril structure and the mechanism of formation. Here in situ atomic force microscopy (AFM) and photo-induced force microscopy (PiFM) is utilized to investigate the formation process and define the basic structural paradigm of individual silk nanofibrils. By visualizing the multistage process of silk nanofibril formation, the importance of conformational transformations along the assembly pathway is revealed. Unfolded silk structures initially accumulate into amorphous clusters, which then evolve into crystal nuclei via conformational transformation into β-crystallites. Nanofibril elongation then occurs through the attachment of silk molecules at a single end of the nanofibril tip; this is facilitated through the formation of a new amorphous cluster that then repeats the aforementioned conformational transformation. However, enzymatic digestion of the amorphous regions leads to direct, rapid elongation of β-crystalline fibers. These findings imply that the energy landscape is characterized by shallow minima associated with intermediate states, which can be eliminated by introducing β-crystallites, and motivate research into the directed modification of the silk assembly pathway to select for features beneficial to specific applications.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Evaluation of Density-Functional Tight-Binding Methods for Simulation of Protic Molecular Ion Pairs

In this work, we benchmark the accuracy of the density-functional tight-binding (DFTB) method, namely the long-range corrected second-order (LC-DFTB2) and third-order (DFTB3) models, for predicting energetics of imidazolium-based ionic liquid (IL) ion pairs. We compare the DFTB models against popular density functionals such as LC-ωPBE and B3LYP, using ab initio domain-based local pair-natural orbital coupled cluster (DLPNO-CC) energies as reference. Calculations were carried out in the gas phase, as well as in aqueous solution using implicit solvent methods. We find that the LC-DFTB2 model shows excellent performance in the gas phase and agrees well with reference energies in implicit solvent, often outperforming DFTB3 predictions for complexation energetics. Our study identifies a range of opportunities for use of the LC-DFTB method and quantifies its sensitivity to protonation states and the types of chemical interactions between ion pairs.

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

Atomic-scale electronic inhomogeneity in single-layer iron chalcogenide alloys revealed by machine learning of STM/S data

Chemical pressure from the isovalent substitution of Se by a larger Te atom in the epitaxial film of iron chalcogenide FeSe can effectively tune its superconducting, topological, and magnetic properties. However, such substitution during epitaxial growth inherently leads to defects and structural inhomogeneity, making the determination of alloy composition and atomic sites for the substitutional Te atoms challenging. Here, we utilize machine learning to distinguish between Se and Te atoms in scanning tunneling microscopy images of single-layer FeSe1−xTex on SrTiO3(001) substrates. Defect locations are first identified by analyzing spatial-dependent dI/dV tunneling spectra using the K-means clustering method. After excluding the defect regions, the remaining dI/dV spectra are further analyzed using the singular value decomposition method to determine the Se/Te ratio. Our findings demonstrate an effective and reliable approach for determining alloy composition and atomic-scale electronic inhomogeneity in superconducting single-layer iron chalcogenide films.

Materials Science↗