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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Assessing residential PM 2.5 concentrations and infiltration factors with high spatiotemporal resolution using crowdsourced sensors

Building conditions, outdoor climate, and human behavior influence residential concentrations of fine particulate matter (PM 2.5 ). To study PM 2.5 spatiotemporal variability in residences, we acquired paired indoor and outdoor PM 2.5 measurements at 3,977 residences across the United States totaling >10,000 monitor-years of time-resolved data (10-min resolution) from the PurpleAir network. Time-series analysis and statistical modeling apportioned residential PM 2.5 concentrations to outdoor sources (median residential contribution = 52% of total, coefficient of variation = 69%), episodic indoor emission events such as cooking (28%, CV = 210%) and persistent indoor sources (20%, CV = 112%). Residences in the temperate marine climate zone experienced higher infiltration factors, consistent with expectations for more time with open windows in milder climates. Likewise, for all climate zones, infiltration factors were highest in summer and lowest in winter, decreasing by approximately half in most climate zones. Large outdoor–indoor temperature differences were associated with lower infiltration factors, suggesting particle losses from active filtration occurred during heating and cooling. Absolute contributions from both outdoor and indoor sources increased during wildfire events. Infiltration factors decreased during periods of high outdoor PM 2.5 , such as during wildfires, reducing potential exposures from outdoor-origin particles but increasing potential exposures to indoor-origin particles. Time-of-day analysis reveals that episodic emission events are most frequent during mealtimes as well as on holidays (Thanksgiving and Christmas), indicating that cooking-related activities are a strong episodic emission source of indoor PM 2.5 in monitored residences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Spatiotemporally resolved measurements of electric field around a piezoelectric transformer using electric-field induced second harmonic (E-FISH) generation

When a piezoelectric transformer (PT) is actuated at its second harmonic frequency by a low input voltage, the generated electric field at the distal end can be sufficient to breakdown the surrounding gas, making them attractive power sources for non-equilibrium plasma generation. Understanding the potential and electric fields produced in the surrounding medium by the PT is important for effectively designing and using PT plasma devices. In this work, the spatiotemporally resolved characteristics of the electric field generated by a PT operating in open air have been investigated using the femtosecond electric field-induced second harmonic generation (E-FISH) method. Here, electric field components were determined by simultaneously conducting E-FISH measurements with the incident laser polarized in two orthogonal directions relative to the PT crystal. Results of this work demonstrate the spatial distribution of electric field around the PT’s output distal end and how it evolves as a function of time. Notably, the strongest electric field appears on the face of the PT’s distal surface, near the top and bottom edges and decreases by approximately 70% over 3 mm. The time delay between the PT’s input voltage and measured electric field indicates that there is an about 0.45 phase difference between the PT’s input voltage and output signal.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Effects of spatiotemporal plasma power distribution on the modeling of ignition kernel evolution in quiescent and turbulent methane/air mixtures

Abstract The present work improves a phenomenological plasma-assisted combustion model by integrating the spatiotemporal distribution of plasma power density, thereby considering the evolution of plasma streamers in the modeling, and subsequently, better predicting the ignition kernel evolution. The improved phenomenological model is validated against experiments representing the plasma discharge and post-discharge ignition kernel evolution. Specifically, the new model demonstrates a more accurate prediction of ultrafast gas heating and O 2 dissociation during the plasma discharge, compared to the original model. In addition, the new model is found to closely match the experimental pressure wave and heated channel profiles post-discharge without the need for tuning the energy deposition (unlike the original model), highlighting its accuracy of post-discharge ignition kernel dynamics. The improved phenomenological model is then employed to investigate ignition kernel evolution for a stoichiometric methane-air discharge across various discharge gap configurations. Simulations reveal a non-uniform temperature and streamer distribution progressing from the electrode tips toward the center, contrasting uniform cylindrical discharges previously described in the original model. Streamer propagation is observed to be faster for larger gaps when maintained at the same average electric field for different discharge gaps. The tendency of smaller gaps to produce detached toroidal ignition kernels is observed, while larger gaps promote cylindrical and attached ignition kernels. Interactions between successive ignition kernels from consecutive discharges varied significantly, with the smallest gap (1 mm) promoting the quenching of the preceding ignition kernel due to the initial kernel–kernel separation. The intermediate gap (2 mm) promotes detached kernel growth. In contrast, in the largest gap (4 mm), kernels consistently combine and expand attached to electrodes. The impact of homogeneous isotropic turbulence is also explored, showing the persistence of ignition kernels early on but eventually quenching due to enhanced radical and heat losses with pronounced turbulence intensity.

Johnson, Praise Noah↗
DOE OSTI2025

Planar laser-induced fluorescence system for spatiotemporal ion velocity distribution function measurements

In this work, we present a planar laser-induced fluorescence (PLIF) system for measuring two-dimensional (2D), spatiotemporally resolved ion velocity distribution functions (IVDFs). A continuous-wave tunable diode laser produces a laser sheet that irradiates the plasma, and the resulting fluorescence is captured by an intensified CCD (ICCD) camera. Fluorescence images recorded at varying laser wavelengths are converted into 2D IVDFs using the Doppler shift principle. The developed diagnostic is implemented in an electron beam generated E × B plasma with a bulk plasma density of $\sim\!\!{10^{10}}{\text{c}}{{\text{m}}^{ - 3}}$ . The developed diagnostic is validated against a conventional single-point LIF method using photomultiplier tube-based detection, while significantly reducing the total measurement time by the number of spatial positions measured. The time-resolving capability of this diagnostic is tested by oscillating the plasma between two nominal operating modes with different density profiles and triggering the ICCD camera by the externally driven plasma oscillation. The measured 2D IVDF maps reveal several signatures of ion dynamics in this plasma source, including radially outflowing ions across the electric field and anomalous ion heating at the periphery, consistent with recent kinetic simulations and theoretical studies. A possible correlation between these ion kinetic features and rotating spoke structures is discussed.

E×B plasma↗
DOE OSTI2026

Spatiotemporal structure of edge harmonic oscillation and its role in ELM-free QH-mode at KSTAR

In Quiescent H-mode (QH-mode), edge-localized modes (ELMs) are naturally replaced by a low-n edge harmonic oscillation (EHO), yet the self-regulating transport mechanism driven by the EHO remains insufficiently understood. Using high-spatiotemporal-resolution imaging diagnostics on KSTAR—electron cyclotron emission imaging and broadband electron cyclotron emission—we resolve the eigenmode structure of the EHO and elucidate its regulatory role in edge transport. The EHO is localized within the pedestal near the maximum pressure gradient, propagates in the ion-diamagnetic direction, and its radial envelope expands with increasing shear, suggesting that rotational shear is closely associated with the structural evolution of the EHO. Information-theoretic Transfer Entropy analysis identifies a distinct ‘dual-stabilization’ regulatory interaction pattern: the EHO is associated with enhanced outward energy transport to limit the pressure gradient, while the background shear flow is associated with preferential regulatory influence on the EHO saturation amplitude and energy flux. These results demonstrate that the QH-mode pedestal is sustained by a shear-associated regulation mechanism, where the coupling between rotational shear and mode structure appears closely linked to the sustained ELM-free state.

ECEI↗
DOE OSTI2024

Physics-inspired spatiotemporal-graph AI ensemble for the detection of higher order wave mode signals of spinning binary black hole mergers

We present a new class of AI models for the detection of quasi-circular, spinning, non-precessing binary black hole mergers whose waveforms include the higher order gravitational wave modes ($\ell$, |m|) = {(2,2), (2,1), (3,3), (3,2), (4,4)}, and mode mixing effects in the $\ell$ = 3, |m| = 2 harmonics. These AI models combine hybrid dilated convolution neural networks to accurately model both short- and long-range temporal sequential information of gravitational waves; and graph neural networks to capture spatial correlations among gravitational wave observatories to consistently describe and identify the presence of a signal in a three detector network encompassing the Advanced LIGO and Virgo detectors. We first trained these spatiotemporal-graph AI models using synthetic noise, using 1.2 million modeled waveforms to densely sample this signal manifold, within 1.7 h using 256 NVIDIA A100 GPUs in the Polaris supercomputer at the Argonne Leadership Computing Facility. This distributed training approach exhibited optimal classification performance, and strong scaling up to 512 NVIDIA A100 GPUs. With these AI ensembles we processed data from a three detector network, and found that an ensemble of 4 AI models achieves state-of-the-art performance for signal detection, and reports two misclassifications for every decade of searched data. We distributed AI inference over 128 GPUs in the Polaris supercomputer and 128 nodes in the Theta supercomputer, and completed the processing of a decade of gravitational wave data from a three detector network within 3.5 h. Finally, we fine-tuned these AI ensembles to process the entire month of February 2020, which is part of the O3b LIGO/Virgo observation run, and found 6 gravitational waves, concurrently identified in Advanced LIGO and Advanced Virgo data, and zero false positives. This analysis was completed in one hour using one NVIDIA A100 GPU.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Fine-scale vegetation composition and structure shape spatiotemporal variation in surface albedo across a low Arctic tundra landscape

The unprecedented rate of warming in the Arctic is driving changes in the structure and composition of tundra vegetation. Increases in deciduous tall shrub cover, height, and density are of particular concern, as these changes alter local surface albedo in ways that could amplify effects on the regional surface energy budget (SEB). Despite this importance, significant uncertainties remain in understanding the interplay between fine-scale vegetation patterns and emergent albedo dynamics across space and time. Here, we address these uncertainties by (1) quantifying spatiotemporal variation in surface shortwave albedo and (2) determining the relative influence of fine-scale vegetation composition, structure, and environmental conditions on albedo across a representative low-Arctic tundra landscape on Alaska’s Seward Peninsula. To do this, we synthesized multi-scale, multi-platform remote sensing observations, including a novel Landsat-derived albedo time series, a fine-scale map of Arctic plant functional type (PFT) fractional cover, and airborne LiDAR estimates of canopy height and topography. We show that there are substantial reductions in winter albedo for pixels dominated by tall, woody PFTs (28.13%) relative to pixels dominated by non-woody vegetation, but almost no change in summer albedo (3% increase). Further, we identified a unimodal trend in the relationship between canopy height and the timing of the springtime transition from high (snowy) to low (leafy) albedo (peak at 5.5 m), possibly because of competing ‘snow-fence’ and ‘protrusion’ snow-shrub interactions. To explore the primary drivers of albedo, we constructed a random forest model and found that canopy height and the fractional cover of woody PFTs were as- or more important predictors of winter albedo than topographic features. These findings provide strong evidence for the impacts of local vegetation characteristics on regional surface albedo, highlighting the need for better quantification of snow-shrub interactions to accurately predict the Arctic’s SEB under future environmental change.

Arctic↗
DOE OSTI2026

Comprehensive earthquake catalogue update and spatiotemporal distribution analysis for Iraq and surrounding regions, northeastern Arabian Plate

The updated earthquake catalogue for Iraq covers the period from 1900 to the end of 2021 and includes over 37 000 recorded earthquakes. To create this comprehensive catalogue, five key steps were taken: compiling bulletins, calculating moment magnitudes, harmonizing magnitudes, establishing empirical conversion relations and evaluating the completeness of the catalogue. A notable enhancement in this update is the direct calculation of moment magnitudes for approximately 2800 earthquakes, achieved through the coda envelope technique and waveform data from the Mesopotamian Seismological Network (MPSN) in Iraq. This updated catalogue serves as a valuable resource for examining the spatiotemporal distribution of earthquakes, with respect to earthquake density, maximum moment magnitude and seismogenic depths. Additionally, the Gutenberg–Richter relationship was applied to calculate the a- and b-values specific to Iraq. The findings show that the Zagros Fold-Thrust Belt has a seismogenic layer (source) that ranges from 2 to 33 km deep and experiences high seismic activity. In contrast, the Mesopotamian Foredeep has a seismogenic layer ranging from 1 to 25 km deep and has lower seismic activity. The greatest seismic activity is concentrated around the Mandili-Badra-Teeb fault, which has experienced significant ruptures over time. The Outer Arabian Platform is identified as the main area of seismic activity, while additional activity occurs on the Inner Arabian Platform. Three major tectonic boundaries define the distribution of earthquakes in the northeastern Arabian Plate. These boundaries are defined by the Main Zagros Reverse Fault, the Zagros Foredeep Fault and the Anah Graben and Abu Jir-Euphrates Fault Zone. These boundaries highlight variations in seismicity levels and the spatial distribution of deformation in the region. The updated earthquake catalogue presented in this study is expected to play a vital role in regional seismicity assessments and seismic hazard analyses for Iraq and its surrounding areas.

58 GEOSCIENCES↗
DOE OSTI2025

Spatiotemporal Energy Cascade in Three-Dimensional Magnetohydrodynamic Turbulence

We present a new scale decomposition method to investigate turbulence in wavenumber-frequency space. Using 3D magnetohydrodynamic turbulence simulations, we show that magnetic fluctuations with time scales longer than the nonlinear time exhibit an inverse cascade toward even smaller frequencies. Low frequency magnetic fluctuations support turbulence, acting as an energy reservoir that is converted into plasma kinetic energy, the latter cascading toward large wavenumbers and frequencies, where it is dissipated. Our results shed new light on the spatiotemporal properties of turbulence, potentially explaining the origin and role of low frequency turbulent fluctuations in the solar wind.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

KamNet: An integrated spatiotemporal deep neural network for rare event searches in KamLAND-Zen

Rare event searches allow us to search for new physics at energy scales inaccessible with other means by leveraging specialized large-mass detectors. Machine learning provides a new tool to maximize the information provided by these detectors. The information is sparse, which forces these algorithms to start from the lowest level data and exploit all symmetries in the detector to produce results. In this work we present KamNet, which harnesses breakthroughs in geometric deep learning and spatiotemporal data analysis to maximize the physics reach of KamLAND-Zen, a kiloton scale spherical liquid scintillator detector searching for 0⁢νβ⁢β. Using a simplified background model for KamLAND, we show that KamNet outperforms a conventional convolutional neural network (CNN) on benchmarking Monte Carlo simulations with an increasing level of robustness. Using simulated data, we then demonstrate KamNet's ability to increase KamLAND-Zen's sensitivity to 0ν⁢ββ and 2⁢ν⁢β⁢β decay to excited states. A key component of this work is the addition of an attention mechanism to elucidate the underlying physics KamNet is using for the background rejection.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Spatiotemporal spread of perturbations in power-law models at low temperatures: Exact results for classical out-of-time-order correlators

Here, we present exact results for the classical version of the out-of-time-order commutator (OTOC) for a family of power-law models consisting of N particles in one dimension and confined by an external harmonic potential. These particles are interacting via power-law interaction of the form ∝ $Σ_{i,j=(i≠j)}^{N}$ |x i -x j | -k for every k>1 where x i is the position of the i th particle. We present numerical results for the OTOC for finite N at low temperatures and short enough times so that the system is well approximated by the linearized dynamics around the many-body ground state. In the large-N limit, we compute the ground-state dispersion relation in the absence of external harmonic potential exactly and use it to arrive at analytical results for OTOC. We find excellent agreement between our analytical results and the numerics. We further obtain analytical results in the limit where only linear and leading nonlinear (in momentum) terms in the dispersion relation are included. The resulting OTOC is in agreement with numerics in the vicinity of the edge of the “light cone.” We find remarkably distinct features in OTOC below and above k=3 in terms of going from non-Airy behavior (1 < k < 3) to an Airy universality class (k>3). We present certain additional rich features for the case k=2 that stem from the underlying integrability of the Calogero-Moser model. We present a field theory approach that also assists in understanding certain aspects of OTOC such as the sound speed. Our findings are a step forward towards a more general understanding of the spatiotemporal spread of perturbations in long-range interacting systems.

1-dimensional systems↗
DOE OSTI2021

Spatiotemporal Crossover between Low- and High-Temperature Dynamical Regimes in the Quantum Heisenberg Magnet

The stranglehold of low temperatures on fascinating quantum phenomena in one-dimensional quantum magnets has been challenged recently by the discovery of anomalous spin transport at high temperatures. Whereas both regimes have been investigated separately, no study has attempted to reconcile them. For instance, the paradigmatic quantum Heisenberg spin-$1/2$ chain falls at low-temperature within the Tomonaga-Luttinger liquid framework, while its high-temperature dynamics is superdiffusive and relates to the Kardar-Parisi-Zhang universality class in $1+1$ dimensions. This work aims at reconciling the two regimes. Building on large-scale matrix product state simulations, we find that they are connected by a temperature-dependent spatiotemporal crossover. In this work, as the temperature $T$ is reduced, we show that the onset of superdiffusion takes place at longer length and time scales $\propto 1/T$. This prediction has direct consequences for experiments including nuclear magnetic resonance: it is consistent with earlier measurements on the nearly ideal Heisenberg $S=1/2$ chain compound Sr$_2$CuO$_3$ yet calls for new and dedicated experiments.

1-dimensional spin chains↗
DOE OSTI2022

Ephemeral antibubbles: Spatiotemporal evolution from direct numerical simulations

Antibubbles, which consist of a shell of a low-density fluid inside a high-density fluid, have several promising applications. We show, via extensive direct numerical simulations (DNSs), in both two and three dimensions, that the spatiotemporal evolution of antibubbles can be described naturally by the coupled Cahn-Hilliard-Navier-Stokes (CHNS) equations for a binary fluid. Our DNSs capture elegantly the gravity-induced thinning and breakup of an antibubble via the time evolution of the Cahn-Hilliard scalar-order-parameter field $\phi$, which varies continuously across interfaces, so we do not have to enforce complicated boundary conditions at the moving antibubble interfaces. To ensure that our results are robust, we supplement our CHNS simulations with sharp-interface volume-of-fluid DNSs. We track the thickness of the antibubble and calculate the dependence of the lifetime of an antibubble on several parameters; we show that our DNS results agree with various experimental results; in particular, the velocity with which the arms of the antibubble retract after breakup scales as σ 1/2 , where σ is the surface tension.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Spatiotemporal control of two-color terahertz generation

A laser pulse composed of a fundamental and properly phased second harmonic exhibits an asymmetric electric field that can drive a time-dependent current of photoionized electrons. The current produces an ultrashort burst of terahertz (THz) radiation. When driven by a conventional laser pulse, the THz radiation is emitted into a cone with an angle determined by the dispersion of the medium. Here we demonstrate that the programmable-velocity intensity peak of a spatiotemporally structured, two-color laser pulse can be used to control the emission angle, focal spot, and spectrum of the THz radiation. Of particular interest for applications, a structured pulse with a subluminal intensity peak can drive highly focusable, on-axis THz radiation. Published by the American Physical Society 2024

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Hybrid Approaches for Data Reduction of Spatiotemporal Scientific Applications

Scientists conduct large-scale simulations to compute derived quantities from primary data. Thus, it is crucial that data compression techniques maintain bounded errors on these derived quantities or quantities of interest (QOI). For many spatiotemporal applications, these QOIs are binary in nature and represent presence or absence of a physical phenomenon. In this work, we propose to use a hybrid approah for differential compression for such applications. We use a neural network (NN) approach to determine regions-of-interest (ROIs) where the binary QOIs are going to be prevalent. This is then used with traditional approaches that compress at a lower level (and higher accuracy) for these ROIs as compared to other regions.

Li, Xiao↗
DOE OSTI2023

Statistical Generation of Ocean Forcing With Spatiotemporal Variability for Ice Sheet Models

Melting of ice at the base of floating ice shelves that fringe the Antarctic ice sheet has been identified as a significant source of uncertainty in sea level rise projections. Part of this uncertainty derives from chaotic internal variability of the coupled ocean-atmosphere system. For numerical ice sheet model projections, this uncertainty has not previously been quantified because of the prohibitive computational expense of running large climate model ensembles. Here, we develop and demonstrate a technique that generates independent realizations of internal climate variability from a single climate model simulation. Building on previous developments in model emulation, this technique uses empirical orthogonal function decomposition and Fourier-phase randomization to generate statistically consistent realizations of spatiotemporal variability fields for the target climate variable. The method facilitates efficient sampling of a wide range of climate trajectories, which can also be incorporated within ice sheet or other physical models to represent feedback processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A composite electrodynamic mechanism to reconcile spatiotemporally resolved exciton transport in quantum dot superlattices

Quantum dot (QD) solids are promising optoelectronic materials; further advancing their device functionality requires understanding their energy transport mechanisms. The commonly invoked near-field Förster resonance energy transfer (FRET) theory often underestimates the exciton hopping rate in QD solids, yet no consensus exists on the underlying cause. In response, we use time-resolved ultrafast stimulated emission depletion (STED) microscopy, an ultrafast transformation of STED to spatiotemporally resolve exciton diffusion in tellurium-doped cadmium selenide–core/cadmium sulfide–shell QD superlattices. We measure the concomitant time-resolved exciton energy decay due to excitons sampling a heterogeneous energetic landscape within the superlattice. The heterogeneity is quantified by single-particle emission spectroscopy. This powerful multimodal set of observables provides sufficient constraints on a kinetic Monte Carlo simulation of exciton transport to elucidate a composite transport mechanism that includes both near-field FRET and previously neglected far-field emission/reabsorption contributions. Uncovering this mechanism offers a much-needed unified framework in which to characterize transport in QD solids and additional principles for device design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Spatiotemporal Visualization and Chemical Identification of the Metal Diffusion Layer at the Electrochemical Interface

The diffusion layer created by transition metal dissolution is ubiquitous at the electrochemical solid-liquid interface and plays a key role in determining electrochemical performance. Tracking the spatiotemporal dynamics of the diffusion layer has remained an unresolved challenge. With spatially resolved synchrotron X-ray fluorescence microscopy and micro-X-ray absorption spectroscopy, we demonstrate the in situ visualization and chemical identification of the dynamic diffusion layer near the electrode surface under electrochemical operating conditions. Finally, our method allows for direct mapping of the reactive electrochemical interface and provides insights into engineering the diffusion layer for improving electrochemical performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗