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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

In-Situ Process Monitoring Evaluation and Demonstration using Advanced Characterization with Laser Powder Bed Systems

Oak Ridge National Laboratory’s (ORNL) Manufacturing Demonstration Facility (MDF) worked with EOS Group to evaluate the current in-situ sensor capabilities of an EOS M290 Laser Powder Bed Fusion machine. The M290 was fitted with a 1 Mega-Pixel (MP) grayscale visible-light camera and a 5 MP temporally integrated (TI) near-infrared (NIR) camera. One print from stainless steel (SS) 316 and two from Inconel 625 (IN625) were performed where data including in-situ imaging and a machine log file were captured. These data were subsequently analyzed using a Dynamic Multi-Scale Segmentation Convolutional Neural Network (DMSCNN) trained on user defined classes and correlated to as-printed flaws, in the form of porosity, discovered in X-Ray Computed Tomography (XCT). In Phase I, two indications were detected in-situ and spatially correlated to stochastic lack-of-fusion flaws discovered using XCT. In Phase II, using these links from in-situ signatures to XCT flaw populations, a second neural network (NN) was trained to create a Voxelized Property Prediction Model (VPPM) to predict porosity percentages within the part using only features garnered from the in-situ data from two IN625 complex geometries. The VPPM was able to accurately predict porosity values for IN625 parts with an R 2 value of 0.764.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Compound Continental Risk of Multiple Extreme Floods in the United States

Abstract Understanding spatially correlated floods and modeling joint hazard associated with threshold exceedances across multiple locations is crucial for accurate estimation of continental‐scale portfolio risk. This work uses a non‐parametric copula‐based spatial simulator to analyze peak floods across the United States to derive the first‐of‐its‐kind continental portfolio risk estimates at the 10‐ and 100‐year return levels. We find significant interdependence in floods across the nation, revealing the recurring pattern of extreme events affecting the Northeast, Central, West, and Northwest United States in the same year. The stochastic simulator effectively manages high‐dimensional data and offers reliable uncertainty estimates for both spatially dependent floods and the aggregated flood losses at the continental level. El Niño‐Southern Oscillation and Atlantic Multidecadal Oscillation are identified as statistically significant tele‐connectors of aggregate loss. This research aims to advance the understanding of compound continental flood hazard and the potential large‐scale climate teleconnections that lead to such compound floods.

Geology↗
NASA NTRS1995

Remotely sensed image compression based on wavelet transform

In this paper, we present an image compression algorithm that is capable of significantly reducing the vast amount of information contained in multispectral images. The developed algorithm exploits the spectral and spatial correlations found in multispectral images. The scheme encodes the difference between images after contrast/brightness equalization to remove the spectral redundancy, and utilizes a two-dimensional wavelet transform to remove the spatial redundancy. the transformed images are then encoded by Hilbert-curve scanning and run-length-encoding, followed by Huffman coding. We also present the performance of the proposed algorithm with the LANDSAT MultiSpectral Scanner data. The loss of information is evaluated by PSNR (peak signal to noise ratio) and classification capability.

Kim, Seong W.↗
DOE OSTI2023

Delineating the Impact of Transition‐Metal Crossover on Solid‐Electrolyte Interphase Formation with Ion Mass Spectrometry

Abstract Lithium‐metal batteries (LMB) employing cobalt‐free layered‐oxide cathodes are a sustainable path forward to achieving high energy densities, but these cathodes exhibit substantial transition‐metal dissolution during high‐voltage cycling. While transition‐metal crossover is recognized to disrupt solid‐electrolyte interphase (SEI) formation on graphite anodes, experimental evidence is necessary to demonstrate this for lithium‐metal anodes. In this work, advanced high‐resolution 3D chemical analysis is conducted with time‐of‐flight secondary‐ion mass spectrometry (TOF‐SIMS) to establish spatial correlations between the transition metals and electrolyte decomposition products found on cycled lithium‐metal anodes. Insights into the localization of various chemistries linked to crucial processes that define LMB performance, such as lithium deposition, SEI growth, and transition‐metal deposition are deduced from a precise elemental and spatial analysis of the SEI. Heterogenous transition‐metal deposition is found to perpetuate both heterogeneous SEI growth and lithium deposition on lithium‐metal anodes. These correlations are confirmed across various lithium‐metal anodes that are cycled with different cobalt‐free cathodes and electrolytes. An advanced electrolyte that is stable to higher voltages is shown to minimize transition‐metal crossover and its effects on lithium‐metal anodes. Overall, these results highlight the importance of maintaining uniform SEI coverage on lithium‐metal anodes, which is disrupted by transition‐metal crossover during operation at high voltages.

Chemistry↗
DOE OSTI2025

Micro-segregation phenomena and related spectroscopic signals in melt-grown β-Ga2O3 single crystals

One of the primary advantages of β-Ga2O3 over incumbent wide bandgap semiconductors is the ability to grow directly from the melt. Melt growth, using Czochralski or similar methods, results in impurities in the crystal which originate from the crucible, such as iridium and other transition metals like chromium. These impurities exhibit optoelectronic signatures useful for their identification and sensitive to the Fermi energy of a given crystal (i.e., signatures vary with the electrical conductivity of the matrix). In this work, we describe how laser Raman systems can be used to map and spatially correlate Cr3+ photoluminescence, electronic-coupled Raman scattering from Ir4+d–d internal transitions, and the Raman line attributed to hydrogenic shallow donors. Laser ablation inductively coupled plasma mass spectrometry directly measured spatially dependent relative metal concentrations and confirmed spectroscopic signals resulting from heterogeneities in impurity concentrations in β-Ga2O3 boules. Mapping of photoluminescence and Raman-related signatures is, thus, demonstrated as an effective and facile method for spatial measurement of chemical heterogeneities in both insulating and conductive melt-grown β-Ga2O3 crystals.

Dutton, Benjamin L. (ORCID:000000031272130X)↗
DOE OSTI2025

CareWELL: Multimodal Region Representation Learning with Spatial Contexts for Urban Health

Rapid urbanization affects living environments by intensifying exposure to air pollution, heat, noise, and urban dynamics, which together contribute to uneven health outcomes across neighborhoods. For instance, cardiovascular, respiratory, and mental health conditions are each influenced by distinct exposures such as air pollution, extreme temperatures, or limited access to green space. These heterogeneous patterns require understanding the characteristics of geographic regions in order to explain why urban health risks vary across urban areas. Recent work in self-supervised region representation learning provides a promising way to model such characteristics from multimodal geospatial data. However, existing methods face two major limitations: (i) they often depend on non-public datasets, limiting reproducibility and applicability, and (ii) their generic pretraining objectives overlook health-relevant determinants, including temporal variability in environmental exposures and inequalities in social conditions. To address these gaps, we propose Context-Aware Region rEpresentation with Weather, Environment, and Location Learning (CareWELL). CareWELL leverages large language models to encode seasonal variability in weather, employs contrastive learning to align geo-coordinate and weather representations, and introduces a context-aware objective that integrates socio-demographic factors while preserving spatial correlations. We evaluate CareWELL by predicting six urban health outcomes in Manhattan, New York City, and demonstrate that CareWELL consistently outperforms state-of-the-art baselines as well as a traditional spatial computing method. These results suggest the importance of context-aware pretraining objectives for learning health-relevant region representations.

Namgung, Min [ORNL]↗
NASA NTRS1978

Inversion of data from diffraction-limited multiwavelength remote sensors. I - Linear case

The remote sensing inverse problem is considered in which the sensor does not necessarily view the same area on the earth at each wavelength, and spatial correlations of the geophysical parameters may be present. Under the conditions of linearity and stationary statistics, the minimum mean-square error solution to the problem of inverting such data is a spatial filter of the Wiener-Kolmogorov class. The resulting remote-sensing system can be characterized by an impulse response matrix in ordinary space or by a transfer matrix in frequency space. A signal-to-noise matrix for the geophysical parameters to be sensed is also defined; this matrix depends on the postulated a priori statistics and on the characteristics of the remote-sensing instrument. The system transfer matrix and the signal-to-noise matrix are simultaneously diagonalizable. The optimum transfer matrix filters out of the estimate vector those eigenparameters for which eigenvalues of the signal-to-noise matrix are less than unity.

Rosenkranz, P. W.↗
DOE OSTI2024

Characterizing the multisectoral impacts of future global hydrologic variability

There is significant uncertainty in how global water supply will evolve in the future, due to uncertain climate, socioeconomic, and land use change drivers and variability of hydrologic processes. It is critical to characterize the potential impacts of uncertainty in future water supply given its importance for food and energy production. In this work, we introduce a framework that integrates stochastic hydrology and human-environmental systems to characterize uncertainty in future water supply and its multisector impacts. We develop a global stochastic watershed model and demonstrate that this model can generate a large ensemble of realizations of basin-scale runoff with global coverage that preserves the mean, variance, and spatial correlation of a historical benchmark. We couple this model with a well-known human-environmental systems model to explore the impacts of runoff variability on the water and agricultural sectors across spatial scales. We find that the impacts of future hydrologic variability vary across sectors and regions. Impacts are felt most strongly in the water and agricultural sectors for basins that are expected to have unsustainable water use in the future, such as the Indus River basin. For this basin, we find that the variability in future irrigation water withdrawals and irrigated cropland increase over time due to uncertainty in renewable water supply. We also use the Indus basin to show how our stochastic ensemble can be leveraged to explore the global multisector consequences of local extreme runoff conditions. This work introduces a novel technique to explore the propagation of future hydrologic variability across human and natural systems and spatial scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Wide-field probing of silica laser-induced damage precursors by photoluminescence photochemical quenching

Here, we describe a wide-field approach to probe transient changes in photoluminescence (PL) of defects on silica surfaces. This technique allows simultaneous capture of spatially resolved PL with spontaneous quenching behavior. We attribute the quenching of PL intensity to photochemical reactions of surface defects and/or subsurface fractures with ambient molecules. Such quenching curves can be accurately reproduced by our theoretical model using two quenchable defect populations with different reaction rates. The fitting parameters of our model are spatially correlated to fractures in silica where point defects and mechanical stresses are known to be present, potentially indicating regions prone to laser-induced damage growth. We believe that our approach allows rapid spatial resolved identification of damage prone morphology, providing a new pathway to fast, non-destructive predictions of laser-induced damage growth.

47 OTHER INSTRUMENTATION↗
NASA NTRS1975

Combined magnetic and gravity analysis

Efforts are made to identify methods of decreasing magnetic interpretation ambiguity by combined gravity and magnetic analysis, to evaluate these techniques in a preliminary manner, to consider the geologic and geophysical implications of correlation, and to recommend a course of action to evaluate methods of correlating gravity and magnetic anomalies. The major thrust of the study was a search and review of the literature. The literature of geophysics, geology, geography, and statistics was searched for articles dealing with spatial correlation of independent variables. An annotated bibliography referencing the Germane articles and books is presented. The methods of combined gravity and magnetic analysis techniques are identified and reviewed. A more comprehensive evaluation of two types of techniques is presented. Internal correspondence of anomaly amplitudes is examined and a combined analysis is done utilizing Poisson's theorem. The geologic and geophysical implications of gravity and magnetic correlation based on both theoretical and empirical relationships are discussed.

Hinze, W. J.↗
NASA NTRS1992

Structure, rotation, and the peculiar velocity cD galaxy in Abell 2107

The radial velocities of 75 galaxies in the field of Abell 2107 were measured within the framework of a program to study the kinematics of cD clusters of galaxies. Sixty-eight of these galaxies are cluster members. The mean observed velocity of A2107 is 12335 +/- 86 km/s, and the velocity dispersion is 672 +67/-52 km/s. The cD galaxy has a peculiar velocity of 270 km/s with respect to the cluster mean. The distribution of velocities is well fitted by a Gaussian, but the velocities are spatially correlated. Simple two-body subcluster models for A2107 are investigated; they are found to be consistent with the observed data and to account for the peculiar velocity of the cD galaxy. Alternatively, the spatial distribution of the velocities is also consistent with rotation of the single cluster at the 98-percent confidence level.

Oegerle, William R.↗
NASA NTRS1999

Collective Interaction in a Linear Array of Supersonic Rectangular Jets: A Linear Spatial Instability Study

A linear spatial instability model for multiple spatially periodic supersonic rectangular jets is solved using Floquet-Bloch theory. It is assumed that in the region of interest a coherent wave can propagate. For the case studied large spatial growth rates are found. This work is motivated by an increase in mixing found in experimental measurements of spatially periodic supersonic rectangular jets with phase-locked screech and edge tone feedback locked subsonic jets. The results obtained in this paper suggests that phase-locked screech or edge tones may produce correlated spatially periodic jet flow downstream of the nozzles which creates a large span wise multi-nozzle region where a coherent wave can propagate. The large spatial growth rates for eddies obtained by model calculation herein are related to the increased mixing since eddies are the primary mechanism that transfer energy from the mean flow to the large turbulent structures. Calculations of spacial growth rates will be presented for a set of relative Mach numbers and spacings for which experimental measurements have been made. Calculations of spatial growth rates are presented for relative Mach numbers from 1.25 to 1.75 with ratios of nozzle spacing to nozzle width ratios from s/w(sub N) = 4 to s/w(sub N) = 13.7. The model may be of significant scientific and engineering value in the quest to understand and construct supersonic mixer-ejector nozzles which provide increased mixing and reduced noise.

Miles, Jeffrey Hilton↗
DOE OSTI2023

Annihilation-gamma-based diagnostic techniques for magnetically confined electron–positron pair plasma

Efforts are underway to magnetically confine electron–positron pair plasmas to study their unique behaviour, which is characterized by significant changes in plasma time and length scales, supported waves and unstable modes. However, use of conventional plasma diagnostics presents challenges with these low-density and annihilating matter–antimatter plasmas. To address this problem, we propose to develop techniques based on the distinct emission provided by annihilation. This emission exhibits two spatial correlations: the distance attenuation of isotropic sources and the back-to-back propagation of momentum-preserving 2 $\gamma$ annihilation. We present the results of our analysis of the $\gamma$ emission rate and the spatial profile of the annihilation in a magnetized pair plasma from direct pair collisions, from the formation and decay of positronium as well as from transport processes. In order to demonstrate the effectiveness of annihilation-based techniques, we tested them on annular $\gamma$ emission profiles produced by a $\beta ^+$ radioisotope on a rotating turntable. Direct and positronium-mediated annihilation result in overlapping volumetric $\gamma$ sources, and the 2 $\gamma$ emission from these volumetric sources can be tomographically reconstructed from coincident counts in multiple detectors. Transport processes result in localized annihilation where field lines intersect walls, limiters or internal magnets. These localized sources can be identified by the fractional $\gamma$ counts on spatially distributed detectors.

Physics↗
DOE OSTI2026

Near-field-driven radiative thermal dynamics in aperiodic photonic nanostructures

Harnessing structural correlations in near-field plasmonic and polaritonic systems hold untapped potential for controlling light–matter interactions at the nanoscale. By tuning these correlations, one can reshape mode localization, coupling, and spectral distribution which are properties central to manipulating energy transport and field enhancement in nanophotonic platforms. We exploit Vogel spirals, an aperiodic geometry where a single parameter dictates spatial correlations, to show how correlation strength reshapes the modal spectrum and transient dynamics of near-field coupling. As a proof of concept, we demonstrate that aperiodic configurations outperform both uncorrelated (random) and periodic arrays in controlling near-field radiative heat-transfer dynamics. These results establish deterministic aperiodic order as a powerful platform for tailoring correlated electromagnetic responses in next-generation nanophotonic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Correlative piezoresponse and micro-Raman imaging of CuInP 2 S 6 –In 4/3 P 2 S 6 flakes unravels phase-specific phononic fingerprint via unsupervised learning

Characterizing the novel properties of layered van der Waals materials is key for their application in functional devices. A better understanding of this type of material requires correlative imaging of diverse nanoscale material properties. Within this class of materials, CuInP 2 S 6 (CIPS) has received a significant degree of interest due to its ionically mediated room temperature ferroelectricity. Moreover, it is possible to form stable self-assembled heterostructures of ferroelectric CuInP 2 S 6 (CIPS) and non-ferroelectric (i.e., lacking Cu) In 4/3 P 2 S 6 (IPS) phases, by controlling the targeted composition and kinetics of synthesis. In this work, we present a correlative nanometric imaging study of the phononic modes and piezoelectricity of the phase-separated thin heteroepitaxial CIPS/IPS flakes. Here, we show that it is possible to isolate the different phononic modes of the two phases by spatially correlating them with their distinct ferroelectric behavior. The coupling of our experimental data with unsupervised learning statistical methods enables unraveling specific Raman peaks that are characteristic of each chemical phase (CIPS and IPS) present in the composite sample, discarding the less significant ones.

correlative microscopy↗
DOE OSTI2026

Measuring pH Changes Inside a Bipolar Membrane Junction

Here, the local pH environment within bipolar membrane (BPM) junctions is complex and not well understood, yet it is important to control for advancing the performance of BPM-based electrochemical systems. We report a voltammetric strategy using an ultrathin Ni mesh pH probe to spatially resolve pH changes in the BPM junction during model BPM electrolyzer operation. Under reverse bias, we observe depletion of OH – at the anion-exchange layer (AEL) interface, with a degree diminishing with increasing distance from the AEL. These gradients correlate with current-dependent water dissociation (WD) and are modulated by the electric field and the surface charge state of the catalyst. By correlating spatial pH profiles with the surface-charging behavior of WD catalysts, we explore a mechanism of catalyst-mediated H + and OH – transfer facilitated by hydrogen-bonding networks. These findings highlight the role of local chemistry and electrostatics in BPM performance and offer new methods to probe and engineer catalytic junctions in electrochemical energy devices.

Hou, Shujin [University of California, Berkeley, C↗
DOE OSTI2026

A Nonergodic Ground-Motion Model for the San Francisco Bay Area for Small-Magnitude Earthquakes

ABSTRACT Recently, generative models have become a computationally efficient alternative to physics-based numerical simulations of ground motions. Neural networks can learn from existing ground-motion data to generate unobserved ground-motion data at new source and site locations. A key challenge with generative models is ensuring that predicted ground motions remain within a physically realistic range. For this purpose, we developed an empirical, nonergodic ground-motion model (GMM) for small-magnitude earthquakes in the San Francisco Bay area based on about 5000 recordings per component for Mw ≤ 4 earthquakes. The nonergodic GMM predicts spatially varying median source, site, and path effects for both the Fourier amplitude spectrum (FAS) and the Fourier phase derivative (a proxy for duration), as well as the corresponding epistemic uncertainty for each term. For FAS, our model shows above-average source and site effects in the western part of the region and below-average effects in the eastern part, with regional effects exhibiting larger spatial correlation lengths with increasing frequency. For duration, the source term is negligible for small-magnitude earthquakes, and the site term leads to site-specific variations up to 5 s. Path effects for FAS and duration depend on the source–site pair and are extrapolated spatially using recent methods for path-effect modeling. The aleatory variability of the within-site within-path residuals is similar to the variability found in previous studies for other regions. The nonergodic model provides two key contributions: first, median adjustment terms that are transferable to larger magnitude earthquakes, further reducing aleatory variability in probabilistic seismic hazard analysis; second, region-specific criteria for validating machine learning-based ground-motion generators to evaluate whether synthetic ground motions exhibit physically realistic source, site, and path effects.

Lacour, Maxime↗
DOE OSTI2021

A Kinematic Perspective on the Formation Process of the Stellar Groups in the Rosette Nebula

Stellar kinematics is a powerful tool for understanding the formation process of stellar associations. Here, we present a kinematic study of the young stellar population in the Rosette nebula using recent Gaia data and high-resolution spectra. We first isolate member candidates using the published mid-infrared photometric data and the list of X-ray sources. A total of 403 stars with similar parallaxes and proper motions are finally selected as members. The spatial distribution of the members shows that this star-forming region is highly substructured. The young open cluster NGC 2244 in the center of the nebula has a pattern of radial expansion and rotation. We discuss its implication on the cluster formation, e.g., monolithic cold collapse or hierarchical assembly. On the other hand, we also investigate three groups located around the border of the H ii bubble. The western group seems to be spatially correlated with the adjacent gas structure, but their kinematics is not associated with that of the gas. The southern group does not show any systematic motion relative to NGC 2244. These two groups might be spontaneously formed in filaments of a turbulent cloud. The eastern group is spatially and kinematically associated with the gas pillar receding away from NGC 2244. This group might be formed by feedback from massive stars in NGC 2244. Our results suggest that the stellar population in the Rosette Nebula may form through three different processes: the expansion of stellar clusters, hierarchical star formation in turbulent clouds, and feedback-driven star formation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗