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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 361 records · Page 20
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DOE OSTI2024

A Comprehensive Northern Hemisphere Particle Microphysics Data Set From the Precipitation Imaging Package

Microphysical observations of precipitating particles are critical data sources for numerical weather prediction models and remote sensing retrieval algorithms. However, obtaining coherent data sets of particle microphysics is challenging as they are often unindexed, distributed across disparate institutions, and have not undergone a uniform quality control process. This work introduces a unified, comprehensive Northern Hemisphere particle microphysical data set from the National Aeronautics and Space Administration precipitation imaging package (PIP), accessible in a standardized data format and stored in a centralized, public repository. Data is collected from 10 measurement sites spanning 34° latitude (37°N–71°N) over 10 years (2014–2023), which comprise a set of 1,070,000 precipitating minutes. The provided data set includes measurements of a suite of microphysical attributes for both rain and snow, including distributions of particle size, vertical velocity, and effective density, along with higher-order products including an approximation of volume-weighted equivalent particle densities, liquid equivalent snowfall, and rainfall rate estimates. The data underwent a rigorous standardization and quality assurance process to filter out erroneous observations to produce a self-describing, scalable, and achievable data set. Case study analyses demonstrate the capabilities of the data set in identifying physical processes like precipitation phase-changes at high temporal resolution. Bulk precipitation characteristics from a multi-site intercomparison also highlight distinct microphysical properties unique to each location. This curated PIP data set is a robust database of high-quality particle microphysical observations for constraining future precipitation retrieval algorithms, and offers new insights toward better understanding regional and seasonal differences in bulk precipitation characteristics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Machine Learning Classification Strategy to Improve Streamflow Estimates in Diverse River Basins in the Colorado River Basin

Streamflow in the Colorado River Basin (CRB) is significantly altered by human activities including land use/cover alterations, reservoir operation, irrigation, and water exports. Climate is also highly varied across the CRB which contains snowpack-dominated watersheds and arid, precipitation-dominated basins. Recently, machine learning methods have improved the generalizability and accuracy of streamflow models. Previous successes with LSTM modeling have primarily focused on unimpacted basins, and few studies have included human impacted systems in either regional or single-basin modeling. We demonstrate that the diverse hydrological behavior of river basins in the CRB are too difficult to model with a single, regional model. We propose a method to delineate catchments into categories based on the level of predictability, hydrological characteristics, and the level of human influence. Lastly, we model streamflow in each category with climate and anthropogenic proxy data sets and use feature importance methods to assess whether model performance improves with additional relevant data. Overall, land use cover data at a low temporal resolution was not sufficient to capture the irregular patterns of reservoir releases, demonstrating the importance of having high-resolution reservoir release data sets at a global scale. On the other hand, the classification approach reduced the complexity of the data and has the potential to improve streamflow forecasts in human-altered regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mesoscale Cellular Convection Detection and Classification Using Convolutional Neural Networks: Insights From Long-Term Observations at ARM Eastern North Atlantic Site

Marine boundary layer clouds are crucial in Earth's climate system. They frequently manifest as closed or open cell mesoscale cellular convection (MCC). MCC clouds are challenging to represent accurately in current climate models, highlighting the need for detailed observational data sets and in-depth analyses. This study utilizes over 8 years of observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) User Facility Eastern North Atlantic (ENA) site at Graciosa Island, Azores, to investigate these clouds. We first apply a convolutional neural network with a U-Net architecture to classify open and closed cells, marking the first application of such an approach for automatically detecting MCC patterns from ground-based radar measurements. This method addresses some observational gaps in satellite data related to low temporal resolution, nighttime challenges, and limited vertical structure capture. The analysis of the MCC cases shows clear differences between closed and open MCCs: Closed MCC clouds are characterized by lower cloud tops and bases, shallower cloud geometrical depth, weaker horizontal wind speeds, stronger atmospheric stability, and a more homogeneous liquid water path than open MCCs. Finally, we demonstrate two potential applications of our radar-based MCC classifications: (a) facilitating the investigation of aerosol-cloud interactions and (b) exploring meteorological factors along with MCC's evolution by integrating satellite imagery and back-trajectory analysis. The identified MCC cases offer a valuable resource for the scientific community to study MCC processes further and improve climate model accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Stable Machine‐Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection‐Permitting Simulations

Modern climate projections often suffer from inadequate spatial and temporal resolution due to computational limitations, resulting in inaccurate representations of sub-grid processes. A promising technique to address this is the multiscale modeling framework (MMF), which embeds a kilometer-resolution cloud-resolving model (CRM) within each atmospheric column of a host climate model to replace traditional convection and cloud parameterizations. Machine learning offers a unique opportunity to make MMF more accessible by emulating the embedded CRM and reducing its substantial computational cost. Although many studies have demonstrated proof-of-concept success of achieving stable hybrid simulations, it remains a challenge to achieve near operational-level success with real geography and comprehensive variable emulation that includes, for example, explicit cloud condensate coupling. In this study, we present a stable hybrid model capable of integrating for at least 5 years with near operational-level complexity, including coarse-grid geography, seasonality, explicit cloud condensate and wind predictions, and land coupling. Our model demonstrates skillful online performance, achieving a 5-year zonal mean tropospheric temperature bias within 2 K, water vapor bias within 1 g/kg, and a precipitation root mean square error of 0.96 mm/day. Key factors contributing to our online performance include an expressive U-Net architecture and physical thermodynamic constraints for microphysics. With microphysical constraints mitigating unrealistic cloud formation, our work is the first to demonstrate realistic multi-year cloud condensate climatology under the MMF framework. Despite these advances, online diagnostics reveal persistent biases in certain regions, highlighting the need for innovative strategies to further optimize online performance.

Hu, Zeyuan [NVIDIA Corporation, Santa Clara, CA (U↗
DOE OSTI2025

Enhancing Streamflow Reanalysis Across the Conterminous US Leveraging Multiple Gridded Precipitation Data Sets

Streamflow observations, essential for various water resource applications, are often unavailable at critical locations in need. Although different models have been proposed to enhance streamflow predictability at ungauged locations, the challenge extends beyond model fidelity. Differences in meteorologic forcing data sets, precipitation in particular, can significantly affect the accuracy of hydrologic predictions. This challenge intensifies across regions characterized by diverse hydro-climatological and geographical conditions, such as in the conterminous US (CONUS) where a single precipitation product struggles to consistently replicate observed hydrographs, particularly peak flow dynamics. To enhance streamflow predictions, we utilize a VIC-RAPID hydrologic modeling framework driven by multiple commonly used meteorological forcing data sets, such as Daymet, PRISM, ST4, AORC, and their hybrids and create multiple sets of 40-year (1980–2019) hourly, daily, and monthly streamflow reanalysis, Dayflow Version 2, for 2.7 million river reaches across the CONUS. Most forcings lead to skillful streamflow performance, except for ST4 in the mountainous west, where severe radar blockage adversely affects the accuracy. The evaluation using over 6,000 hourly stream gauges shows that hourly AORC and ST4 lead to improved annual peak flow performance over Daymet—driven streamflow (Dayflow V1), particularly in smaller basins, highlighting the value of high temporal resolution forcings in hydrologic predictions. Compared with other benchmark data sets like National Water Model V3.0, AORC-driven VIC-RAPID exhibits improved regional streamflow performance, with comparable peak flow representation. We envision that multi-forcing streamflow reanalysis data can inform regions in need of forcing data enhancement, diagnose hydrologic model performance, and benefit diverse water resource applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Excitation spectral microscopy for highly multiplexed fluorescence imaging and quantitative biosensing

The multiplexing capability of fluorescence microscopy is severely limited by the broad fluorescence spectral width. Spectral imaging offers potential solutions, yet typical approaches to disperse the local emission spectra notably impede the attainable throughput. Here we show that using a single, fixed fluorescence emission detection band, through frame-synchronized fast scanning of the excitation wavelength from a white lamp via an acousto-optic tunable filter, up to six subcellular targets, labeled by common fluorophores of substantial spectral overlap, can be simultaneously imaged in live cells with low (~1%) crosstalks and high temporal resolutions (down to ~10 ms). The demonstrated capability to quantify the abundances of different fluorophores in the same sample through unmixing the excitation spectra next enables us to devise novel, quantitative imaging schemes for both bi-state and Förster resonance energy transfer fluorescent biosensors in live cells. We thus achieve high sensitivities and spatiotemporal resolutions in quantifying the mitochondrial matrix pH and intracellular macromolecular crowding, and further demonstrate, for the first time, the multiplexing of absolute pH imaging with three additional target organelles/proteins to elucidate the complex, Parkin-mediated mitophagy pathway. Together, excitation spectral microscopy provides exceptional opportunities for highly multiplexed fluorescence imaging. The prospect of acquiring fast spectral images without the need for fluorescence dispersion or care for the spectral response of the detector offers tremendous potential.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

High-speed volumetric two-photon fluorescence imaging of neurovascular dynamics

Abstract Understanding the structure and function of vasculature in the brain requires us to monitor distributed hemodynamics at high spatial and temporal resolution in three-dimensional (3D) volumes in vivo. Currently, a volumetric vasculature imaging method with sub-capillary spatial resolution and blood flow-resolving speed is lacking. Here, using two-photon laser scanning microscopy (TPLSM) with an axially extended Bessel focus, we capture volumetric hemodynamics in the awake mouse brain at a spatiotemporal resolution sufficient for measuring capillary size and blood flow. With Bessel TPLSM, the fluorescence signal of a vessel becomes proportional to its size, which enables convenient intensity-based analysis of vessel dilation and constriction dynamics in large volumes. We observe entrainment of vasodilation and vasoconstriction with pupil diameter and measure 3D blood flow at 99 volumes/second. Demonstrating high-throughput monitoring of hemodynamics in the awake brain, we expect Bessel TPLSM to make broad impacts on neurovasculature research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Ultrafast visualization of incipient plasticity in dynamically compressed matter

Plasticity is ubiquitous and plays a critical role in material deformation and damage; it inherently involves the atomistic length scale and picosecond time scale. A fundamental understanding of the elastic-plastic deformation transition, in particular, incipient plasticity, has been a grand challenge in high-pressure and high-strain-rate environments, impeded largely by experimental limitations on spatial and temporal resolution. Here, we report femtosecond MeV electron diffraction measurements visualizing the three-dimensional (3D) response of single-crystal aluminum to the ultrafast laser-induced compression. We capture lattice transitioning from a purely elastic to a plastically relaxed state within 5 ps, after reaching an elastic limit of ~25 GPa. Our results allow the direct determination of dislocation nucleation and transport that constitute the underlying defect kinetics of incipient plasticity. Large-scale molecular dynamics simulations show good agreement with the experiment and provide an atomic-level description of the dislocation-mediated plasticity.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Vanilloid-dependent TRPV1 opening trajectory from cryo EM ensemble analysis

Single particle cryo-EM often yields multiple protein conformations within a single dataset, but experimentally deducing the temporal relationship of these conformers within a conformational trajectory is not trivial. Here, we use thermal titration methods and cryo-EM in an attempt to obtain temporal resolution of the conformational trajectory of the vanilloid receptor TRPV1 with resiniferatoxin (RTx) bound. Based on our cryo-EM ensemble analysis, RTx binding to TRPV1 appears to induce intracellular gate opening first, followed by selectivity filter dilation, then pore loop rearrangement to reach the final open state. This apparent conformational wave likely arises from the concerted, stepwise, additive structural changes of TRPV1 over many subdomains. Greater understanding of the RTx-mediated long-range allostery of TRPV1 could help further the therapeutic potential of RTx, which is a promising drug candidate for pain relief associated with advanced cancer or knee arthritis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A sensitive high repetition rate arrival time monitor for X-ray free electron lasers

X-ray free-electron laser sources enable time-resolved X-ray studies with unmatched temporal resolution. To fully exploit ultrashort X-ray pulses, timing tools are essential. However, new high repetition rate X-ray facilities present challenges for currently used timing tool schemes. Here we address this issue by demonstrating a sensitive timing tool scheme to enhance experimental time resolution in pump-probe experiments at very high pulse repetition rates. Our method employs a self-referenced detection scheme using a time-sheared chirped optical pulse traversing an X-ray stimulated diamond plate. By formulating an effective medium theory, we confirm subtle refractive index changes, induced by sub-milli-Joule intense X-ray pulses, that are measured in our experiment. The system utilizes a Common-Path-Interferometer to detect X-ray-induced phase shifts of the optical probe pulse transmitted through the diamond sample. Owing to the thermal stability of diamond, our approach is well-suited for MHz pulse repetition rates in superconducting linear accelerator-based free-electron lasers.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Sub-100-fs energy transfer in coenzyme NADH is a coherent process assisted by a charge-transfer state

Excitation energy transfer (EET) is a key photoinduced process in biological chromophoric assemblies. Here we investigate the factors which can drive EET into efficient ultrafast sub-ps regimes. We demonstrate how a coherent transport of electronic population could facilitate this in water solvated NADH coenzyme and uncover the role of an intermediate dark charge-transfer state. High temporal resolution ultrafast optical spectroscopy gives a 54 ± 11 fs time constant for the EET process. Nonadiabatic quantum dynamical simulations computed through the time-evolution of multidimensional wavepackets suggest that the population transfer is mediated by photoexcited molecular vibrations due to strong coupling between the electronic states. The polar aqueous solvent environment leads to the active participation of a dark charge transfer state, accelerating the vibronically coherent EET process in favorably stacked conformers and solvent cavities. Our work demonstrates how the interplay of structural and environmental factors leads to diverse pathways for the EET process in flexible heterodimers and provides general insights relevant for coherent EET processes in stacked multichromophoric aggregates like DNA strands.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Spatiotemporal dynamics of fast electron heating in solid-density matter via XFEL

Abstract High-intensity, short-pulse lasers are crucial for generating energetic electrons that produce high-energy-density (HED) states in matter, offering potential applications in igniting dense fusion fuels for fast ignition laser fusion. High-density targets heated by these electrons exhibit spatially non-uniform and highly transient conditions, which have been challenging to characterize due to limitations in diagnostics that provide simultaneous high spatial and temporal resolution. Here, we employ an X-ray Free Electron Laser (XFEL) to achieve spatiotemporally resolved measurements at sub-micron and femtosecond scales on a solid-density copper foil heated by laser-driven fast electrons. Our X-ray transmission imaging reveals the formation of a solid-density hot plasma localized to the laser spot size, surrounded by Fermi degenerate, warm dense matter within a picosecond, and the energy relaxation occurring within the hot plasma over tens of picoseconds. These results validate 2D particle-in-cell simulations incorporating atomic processes and provide insights into the energy transfer mechanisms beyond current simulation capabilities. This work significantly advances our understanding of rapid fast electron heating and energy relaxation in solid-density matter, serving as a key stepping stone towards efficient high-density plasma heating and furthering the fields of HED science and inertial fusion energy research using intense, short-pulse lasers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Improving the creation of SiV centers in diamond via sub-μs pulsed annealing treatment

Silicon-vacancy (SiV) centers in diamond are emerging as promising quantum emitters in applications such as quantum communication and quantum information processing. Here, we demonstrate a sub-μs pulsed annealing treatment that dramatically increases the photoluminescence of SiV centers in diamond. Using a silane-functionalized adamantane precursor and a laser- heated diamond anvil cell, the temperature and energy conditions required to form SiV centers in diamond were mapped out via an optical thermometry system with an accuracy of ±50 K and a 1 μs temporal resolution. Annealing scheme studies reveal that pulsed annealing can obviously minimize the migration of SiV centers out of the diamond lattice, and a 2.5-fold increase in the number of emitting centers was achieved using a series of 200-ns pulses at a 50 kHz repetition rate via acousto-optic modulation. Our study provides a novel pulsed annealing treatment approach to improve the efficiency of the creation of SiV centers in diamond.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Decoupled few-femtosecond phase transitions in vanadium dioxide

Abstract The nature of the insulator-to-metal phase transition in vanadium dioxide (VO 2 ) is one of the longest-standing problems in condensed-matter physics. Ultrafast spectroscopy has long promised to determine whether the transition is primarily driven by the electronic or structural degree of freedom, but measurements to date have been stymied by their sensitivity to only one of these components and/or their limited temporal resolution. Here we use ultra-broadband few-femtosecond pump-probe spectroscopy to resolve the electronic and structural phase transitions in VO 2 at their fundamental time scales. Our experiments show that the system transforms into a bad-metallic phase within 10 fs after photoexcitation, but requires another 100 fs to complete the transition, during which we observe electronic oscillations and a partial re-opening of the bandgap, signalling a transient semi-metallic state. Comparisons with tensor-network simulations and density-functional theory calculations show these features result from an unexpectedly fast structural transition, in which the vanadium dimers separate and untwist with two different timescales. Our results resolve the structural and electronic nature of the light-induced phase transition in VO 2 and establish ultra-broadband few-femtosecond spectroscopy as a powerful tool for studying quantum materials out of equilibrium.

Science & Technology - Other Topics↗
DOE OSTI2026

Time-resolved X-ray imaging of the current filamentation instability in solid-density plasmas

The streaming of energetic charged particles can magnetize astrophysical and laboratory plasmas via the current filamentation instability. Despite its importance, the experimental characterization of this instability has remained a challenge. Here, we report an experiment combining a high-intensity optical laser with a high-brightness X-ray free electron laser that successfully images the instability in solid-density plasmas with 200 nm spatial and 50 fs temporal resolution. We characterize the development of μm-scale filamentary structures and their evolution over tens of picoseconds through a non-linear merging process. The measured plasma density modulations and long merging time reveal the critical importance of space-charge effects and ion motion on this electron-driven instability. Supporting theoretical analysis and kinetic simulations help distinguish the relative role of space-charge and resistive effects. Our findings indicate that magnetic fields on the order of 10 megagauss are produced, with important implications for transport and radiation emission of energetic particles in plasmas.

Schoenwaelder, Christopher [SLAC National Accelera↗
DOE OSTI2026

Pattern-enhanced Resonant Soft X-ray Scattering for Operando monitoring of electrochemical solid-liquid interfaces

Unveiling interfaces at sub-nanometer scales is essential for advancing the understanding of complex chemical transformations. However, characterizing solid-liquid interfaces with high dimensional sensitivity and temporal resolution remains challenging, due to their dynamic nature and inaccessibility by conventional probes. Here we present an approach, Pattern-enhanced Resonant Soft X-ray Scattering, to overcome the challenges. Rooted in a “sample-as-optics” philosophy, this technique utilizes precisely engineered line-grating nanopatterns to modulate near-field X-ray illumination, coherently enhancing scattering signals from the line-gratings. We implement the method using Ni line-grating nanopatterns in electrochemical water oxidation. The periodic nanostructures serve as diffractive optical elements to reveal the Ni oxidation gradients and structural dynamics at the electrode-electrolyte interfaces. Finite-element simulations corroborate the observed trends by modeling variations in compositions and structures during electrocatalysis. Through integrating advanced sample design with coherent wave nature of soft X-rays, our approach opens accessible pathways to operando exploring chemical evolution and sub-nanometer dimensional variations simultaneously in electrochemical systems. This non-destructive method is efficient and element-specific, making it valuable for probing chemical and dimensional dynamics with appropriate modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Switching speed limits in electrically driven VO 2 structural Mott–Peierls transition

Mott materials are archetypal quantum systems actively explored as next-generation electronic and photonic platforms, with potential applications spanning non-Von Neumann computing, robotics, energy storage, and microwave technologies. Among these, vanadium dioxide (VO 2 ) has emerged as one of the most intensively studied compounds, owing to its sharp, near-room-temperature insulator-to-metal phase transition. VO 2 also serves as a benchmark system for testing cutting-edge theories and experimental techniques. Here, we directly visualize the electrically driven transition dynamics in VO 2 using a microwave-driven, frequency-tunable pulsed transmission electron microscope that combines nanometer spatial and picosecond temporal resolution. Under high-frequency (MHz–GHz) excitation, we capture the ultrafast nucleation, propagation, and dissolution of metallic domains within an operating device over millions of reversible cycles. We observe the ultrafast formation of consistent metallic nuclei beneath the electrodes, followed by the propagation of a structural phase front at 4.54 nm/ns. Our experiments show that phonon-mediated structural recovery ultimately limits reversible switching of VO 2 at GHz frequencies, and that a tunable regime for reversible operation spans from kHz to GHz through device engineering. Beyond VO 2 , our approach provides a powerful framework for probing non-equilibrium structural transformations in correlated and functional materials under realistic electrical stimuli.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Seeing is believing: visualization of antiferromagnetic domains

Abstract Understanding and utilizing novel antiferromagnetic (AFM) materials has been recently one of the central issues in condensed matter physics, as well as in materials science and engineering. The relevant contemporary topics include multiferroicity, topological magnetism and AFM spintronics. The ability to image magnetic domains in AFM materials is of key importance for the success of these exciting fields. While imaging techniques of magnetic domains on the surfaces of ferro-(ferri)magnetic materials with, for example, magneto-optical Kerr microscopy and magnetic force microscopy have been available for a number of decades, AFM domain imaging is a relatively new development. We review various experimental techniques utilizing scanning, optical, and synchrotron X-ray probes to visualize AFM domains and domain walls, and to unveil their physical properties. We also discuss the existing challenges and opportunities in these techniques, especially with further increase of spatial and temporal resolution.

36 MATERIALS SCIENCE↗