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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

RASER MRI: Magnetic resonance images formed spontaneously exploiting cooperative nonlinear interaction

The spatial resolution of magnetic resonance imaging (MRI) is limited by the width of Lorentzian point spread functions associated with the transverse relaxation rate 1/T 2 * . Here, we show a different contrast mechanism in MRI by establishing RASER (radio-frequency amplification by stimulated emission of radiation) in imaged media. RASER imaging bursts emerge out of noise and without applying radio-frequency pulses when placing spins with sufficient population inversion in a weak magnetic field gradient. Small local differences in initial population inversion density can create stronger image contrast than conventional MRI. This different contrast mechanism is based on the cooperative nonlinear interaction between all slices. On the other hand, the cooperative nonlinear interaction gives rise to imaging artifacts, such as amplitude distortions and side lobes outside of the imaging domain. Contrast mechanism and artifacts are explored experimentally and predicted by simulations on the basis of a proposed RASER MRI theory.

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

Atomic-scale visualization of topological spin textures in the chiral magnet MnGe

Peeking into magnetic textures Topological spin textures hold promise as robust carriers of information and have been observed in bulk materials with a specific crystal structure. One of these materials, manganese germanide (MnGe), exhibits unusual textures in bulk form. Repicky et al . used spin-polarized scanning tunneling microscopy to study surface magnetism in thin films of MnGe. Achieving high spatial resolution, the researchers observed stripe-like features consistent with a helical state. In regions where the film was slightly curved due to strain, the intersection of domain walls led to characteristic closed patterns that could be manipulated with current/voltage pulses. —JS

Science & Technology - Other Topics↗
DOE OSTI2024

Supramolecular assembly of blue and green halide perovskites with near-unity photoluminescence

The metal-halide ionic octahedron is the optoelectronic unit for halide perovskites, and a crown ether–assisted supramolecular assembly approach can pack various ionic octahedra into tunable symmetries. In this work, we demonstrate near-unity photoluminescence quantum yield (PLQY) blue and green emission with the supramolecular assembly of hafnium (Hf) and zirconium (Zr) halide octahedral clusters. (18C6@K) 2 HfBr 6 powders showed blue emission with a near-unity PLQY (96.2%), and green emission was also achieved with (18C6@K) 2 ZrCl 4 Br 2 powders at a PLQY of 82.7%. In conclusion, these highly emissive powders feature facile low-temperature solution-based synthesis conditions and maintain high PLQY in solution-processable semiconductor inks under ambient conditions, and they were used in thin-film displays and emissive three-dimensional–printed architectures that exhibited high spatial resolution.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Unrecoverable lattice rotation governs structural degradation of single-crystalline cathodes

Transitioning from polycrystalline to single-crystalline nickel-rich cathodes has garnered considerable attention in both academia and industry, driven by advantages of high tap density and enhanced mechanical properties. However, cathodes with high nickel content (>70%) suffer from substantial capacity degradation, which poses a challenge to their commercial viability. Here, leveraging multiscale spatial resolution diffraction and imaging techniques, we observe that lattice rotations occur universally in single-crystalline cathodes and play a pivotal role in the structure degradation. These lattice rotations prove unrecoverable and govern the accumulation of adverse lattice distortions over repeated cycles, contributing to structural and mechanical degradation and fast capacity fade. These findings bridge the previous knowledge gap that exists in the mechanistic link between fast performance failure and atomic-scale structure degradation.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Ultrafast all-optical coherence of molecular electron spins in room-temperature water solution

The tunability and spatial precision of paramagnetic molecules makes them attractive for quantum sensing. However, usual microwave-based detection methods have poor temporal and spatial resolution, and optical methods compatible with room-temperature solutions have remained elusive. In this study, we utilized pump-probe polarization spectroscopy to initialize and track electron spin coherence in a molecule. Designed to efficiently couple spins to light, aqueous potassium hexachloroiridate(IV) enabled detection of few-picosecond free-induction decay at room temperature and micromolar concentrations. Viscosity was found to strongly vary decoherence lifetimes. This approach has improved the experimental time resolution by up to five orders of magnitude, making it possible to observe molecular electron spin coherence in a system that only exhibits coherence below 25 kelvin with traditional techniques.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Spectral kernel machines with electrically tunable photodetectors

Spectral machine vision collects spectral and spatial information as three-dimensional hypercubes and digitally processes them, which causes a data bottleneck, limiting power efficiency, frame rate, and spectral-spatial resolution. This work introduces spectral kernel machines (SKMs) to overcome these bottlenecks. SKM directly compresses spectral analysis through the output photocurrent and learns from example objects to identify and classify new samples in a "sniff-and-seek" mode. We experimentally demonstrated SKMs with electrically tunable bipolar black phosphorus-molybdenum disulfide (bP-MoS2) photodiodes in the near- and mid-infrared band and silicon photoconductors in the visible band, performing versatile intelligent tasks from chemometrics to semiconductor metrology. This architecture consumed substantially less power and was more than an order of magnitude faster than existing solutions for hyperspectral image analysis, defining an intelligent imaging and sensing paradigm with intriguing possibilities.

Zhang, Dehui↗
DOE OSTI2022

Capturing an Early Gene Induction Event during Wood Decay by the Brown Rot Fungus Rhodonia placenta

Brown rot fungi dominate wood decomposition in coniferous forests, and their carbohydrate-selective mechanisms are of commercial interest. Brown rot was recently described as a two-step, sequential mechanism orchestrated by fungi using differentially expressed genes (DEGs) and consisting of oxidation via reactive oxygen species (ROS) followed by enzymatic saccharification. There have been indications, however, that the initial oxidation step itself might require induction. To capture this early gene regulation event, here, we integrated fine-scale cryosectioning with whole-transcriptome sequencing to dissect gene expression at the single-hyphal-cell scale (tens of micrometers). This improved the spatial resolution 50-fold, relative to previous work, and we were able to capture the activity of the first 100 μm of hyphal front growth by Rhodonia placenta in aspen wood. This early decay period was dominated by delayed gene expression patterns as the fungus ramped up its mechanism. These delayed DEGs included many genes implicated in ROS pathways (lignocellulose oxidation [LOX]) that were previously and incorrectly assumed to be constitutively expressed. These delayed DEGs, which include those with and without predicted functions, also create a focused subset of target genes for functional genomics. However, this delayed pattern was not universal, with a few genes being upregulated immediately at the hyphal front. Most notably, this included a gene commonly implicated in hydroquinone and iron redox cycling: benzoquinone reductase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Asymptotically Compatible Reproducing Kernel Collocation and Meshfree Integration for Nonlocal Diffusion

Reproducing kernel (RK) approximations are meshfree methods that construct shape functions from sets of scattered data. We present an asymptotically compatible (AC) RK collocation method for nonlocal diffusion models with Dirichlet boundary condition. The numerical scheme is shown to be convergent to both nonlocal diffusion and its corresponding local limit as nonlocal interaction vanishes. The analysis is carried out on a special family of rectilinear Cartesian grids for a linear RK method with designed kernel support. The key idea for the stability of the RK collocation scheme is to compare the collocation scheme with the standard Galerkin scheme, which is stable. In addition, assembling the stiffness matrix of the nonlocal problem requires costly computational resources because high-order Gaussian quadrature is necessary to evaluate the integral. We thus provide a remedy to the problem by introducing a quasi-discrete nonlocal diffusion operator for which no numerical quadrature is further needed after applying the RK collocation scheme. The quasi-discrete nonlocal diffusion operator combined with RK collocation is shown to be convergent to the correct local diffusion problem by taking the limits of nonlocal interaction and spatial resolution simultaneously. The theoretical results are then validated with numerical experiments. We additionally illustrate a connection between the proposed technique and an existing optimization based approach based on generalized moving least squares.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

The cosmic muon and detector simulation framework of the extreme energy events (EEE) experiment

Abstract This paper describes the simulation framework of the extreme energy events (EEE) experiment. EEE is a network of cosmic muon trackers, each made of three multi-gap resistive plate chambers (MRPC), able to precisely measure the absolute muon crossing time and the muon integrated angular flux at the ground level. The response of a single MRPC and the combination of three chambers have been implemented in a GEANT4-based framework (GEMC) to study the telescope response. The detector geometry, as well as details about the surrounding materials and the location of the telescopes have been included in the simulations in order to realistically reproduce the experimental set-up of each telescope. A model based on the latest parametrization of the cosmic muon flux has been used to generate single muon events. After validating the framework by comparing simulations to selected EEE telescope data, it has been used to determine detector parameters not accessible by analysing experimental data only, such as detection efficiency, angular and spatial resolution.

Abbrescia, M.↗
DOE OSTI2023

Spatiotemporal Variability of Electric System Reliability Metrics

As urbanization continues to grow, urban density also rises, placing significant stress on critical infrastructure. Cities often face challenges in investing in new infrastructure or upgrading existing ones. One area of infrastructure that has come under strain is the electric grid, leading to prolonged power outages. According to data from the U.S. Energy Information Administration, the average duration of power outages has steadily doubled from 2013 to 2021, primarily due to extreme weather events. The IEEE has developed a series of reliability metrics to assess the reliability of the electric system. However, these metrics are only applied at the utility level, making it challenging to comprehend the variations in these indices at finer spatial resolutions and, consequently, evaluate reliability at the non-utility level. In this study, we leveraged electric outage data collected at 15-minute intervals at the county level to estimate electric system reliability over a six-year period using a novel data analysis approach. Our findings reveal a gradual decline in reliability in the U.S. Southwest compared to national averages. Furthermore, the duration of outages per customer per event has significantly decreased in large portions of California and Florida. These discoveries can be valuable for utility companies as they seek to pinpoint regional anomalies and plan for prioritized remediation efforts.

Singh, Nagendra↗
DOE OSTI2020

High-Energy X-Ray Diffraction Microscopy in Materials Science

High-energy diffraction microscopy (HEDM) is an implementation of three-dimensional X-ray diffraction microscopy. HEDM yields maps of internal crystal orientation fields, strain states, grain shapes and locations as well as intragranular orientation distributions, and grain boundary character. Because it is nondestructive in hard materials, notably metals and ceramics, HEDM has been used to study responses of these materials to external fields including high temperature and mechanical loading. Currently available sources and detectors lead to a spatial resolution of ~1 μm and an orientation resolution of <0.1°. With the penetration characteristic of high energies ( E ≥ 50 keV), sample cross-section dimensions of ~1 mm can be studied in materials containing elements across much of the Periodic Table. This review describes hardware and software associated with HEDM as well as examples of applications. Overall, these applications include studies of grain growth, recrystallization, texture development, orientation gradients, deformation twinning, annealing twinning, plastic deformation, and additive manufacturing. We also describe relationships to other X-ray-based methods as well as prospects for further development.

36 MATERIALS SCIENCE↗
DOE OSTI2024

In Situ Liquid Electron Microscope Cells Strongly Attenuate Electrochemical Behavior

In situ electrochemical Scanning Transmission Electron Microscopy (ec-S/TEM) probes the dynamics of electrochemical processes in real time and at high spatial resolution. This method utilizes microfabricated electrochemical cells, with enclosed dimensions of 800 μm wide, 800 μm long, and 1–2 μm tall, with electron-transparent silicon nitride windows. Working, counter, and reference electrodes in the configuration studied are deposited Pt with a planar surface area of about 1 μm 2 and a height of 50 nm. The cell confines the electrolyte within a 1 μm tall channel, and the microfabricated electrodes have a non-standard geometry, are coplanar, and are not front-facing. As such, standard assumptions of electrochemical experiments do not apply. COMSOL modeling was used to compare and contrast differences in electrochemical behavior between conventional experimental setups and the in situ ec-S/TEM cells. Cell height strongly affected voltammogram measurements: peak magnitudes and shifts correlate directly to cell height. Reactant concentration above the electrode quickly decreases during deposition, leading to a planar diffusion-dominated regime. The concentration gradient prioritizes particle growth along the thin edges of the electrode and not on the planar part of the electrode. Experiments done in the ec-S/TEM ex situ of a TEM verify the model’s accuracy.

Wittman, Reed M. [Oak Ridge National Laboratory (O↗
DOE OSTI2021

AD_LTEM

This software uses AI tools for enhanced functional imaging using Lorentz transmission electron microscopy by retrieving phase shift at higher spatial resolution, and under noisy conditions. This is a companion code for a publication that is currently being submitted (APT # 164160).

PHATAK, CHARUDATTA↗
DOE OSTI2021

SSRS (Stochastic Soaring Raptor Simulator)

SSRS (Stochastic Soaring Raptor Simulator) is a generalizable, probabilistic, and predictive tool for wind energy developers, ecologists, wildlife managers and industry consultants to estimate the potential for soaring raptors to interact with operating wind turbines, without the need for site-specific data collection. Rapid expansion of wind energy development across the world has exposed the risk of turbine collisions for birds and bats. The risk to obligate soaring raptors such as golden eagles is of particular concern due to their small population and influence on ecological balance. Golden eagles rely heavily on updrafts to subsidize their flight, putting them in direct conflict with operational wind turbines that utilize the same wind resource. Understanding the behavior of soaring raptors with varying atmospheric conditions is crucial for predicting and mitigating the risk of turbine collision. This software contains a predictive movement model that simulates individual flight paths of golden eagles during updraft-subsidized long-distance flight, including migration. For a given set of atmospheric conditions, the model simulates thousands of eagles at turbine-scale spatial resolution (50m) to produce a relative presence density map. The simulated eagles rely on updrafts to pursue uninterrupted directional flight with minimal energy expenditure, following fluid-flow principles. The simulator includes a stochastic model of eagle behavior and a systematic method of accounting for spatiotemporal variations in atmospheric conditions. This framework only requires publicly available atmospheric data to estimate orographic and thermal updrafts, ensuring general usability.

Sandhu, Rimple↗
DOE OSTI2024

Deep Learning-based Non-Stationary Bias Correction (NSBC)

This work develops the NSBC (non-stationary bias correction) methodology to correct temperature projection bias from E3SM. The NSBC deep learning framework consists of a three-part architecture: an auto-encoder for compressing the spatial information, an LSTM for predicting annual temperature mean, and a U-Net for capturing the residual bias in temperature. The non-stationary bias correction (NSBC) framework can correct the non-stationarity of the biases of the climate models, which significantly improves the accuracy of future temperature prediction and improves the overestimation of extreme high temperatures that many existing bias correction methods suffer from. Getting started 1. Obtain the historical climate simulation and observation data. The E3SM simulation data are available through https://aims2.llnl.gov/search/cmip6/. The pseudo observations, the Geophysical Fluid Dynamics Laboratory (GFDL)-ESM4 model (Krasting et al., 2018) are available through https://aims2.llnl.gov/search/cmip6/. The spatial resolution of E3SM and pseudo observation datasets are both regridded to a common 1° resolution grid using conservative interpolation. The regridded E3SM and pseudo observation with 1° resolution can be found throught ./data/. 2. Train the Auto-encoder model. Python 0-autoencoder.py 3. Train the LSTM Python 1-LSTM.py 4. Generate the annual mean temperature based on trained LSTM Python 2-generate_annual_mean_LSTM.py 5. Train the U-Net. Python 3-unet.py 6. Evaluation and compared with the baseline Python 4_evaluation.py Is there a deadline approaching that requires the release of yo

Lucas, Donald↗
DOE OSTI2024

UFNet: Joint U-Net and Fully Connected Neural Network to Bias Correct Precipitation Predictions from

Paper information. Shuang Yu, Indrasis Chakraborty, Gemma J. Anderson, Donald D. Lucas, Yannic Lops, and Daniel Galea. UFNet: Joint U-Net and fully connected neural network to bias correct precipitation predictions from climate models. Artificial Intelligence for the Earth Systems, 2024. Overview. This work develops the UFNet methodology to correct E3SM historical precipitation projection bias. The UFNet deep learning framework consists of a two-part architecture: a U-Net convolutional network to capture the spatiotemporal distribution of precipitation and a fully connected network to capture the distribution of higher-order statistics. The joint network, termed UFNet, can simultaneously improve the spatial structure of the modeled precipitation and capture the distribution of extreme precipitation values. Below we provide guidance for applying UFNet to correct the Energy Exascale Earth System Model (E3SM; Golaz et al. 2019) daily precipitation projection over the contiguous United States (CONUS). Getting started 1. Obtain the historical climate simulation and observation data. The E3SM historical simulation data are available through https://aims2.llnl.gov/search/cmip6/. The CPC unified gauge-based analysis of daily precipitation can be found through https://psl.noaa.gov/data/gridded/data.cpc.globalprecip.html. The ECMWF atmospheric reanalysis of the 20th century (ERA-20C) data are available through https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era-20c. The spatial resolution of E3SM and observed datasets are both regridded to a common 1° resolution grid using conservative interpolation. The regridded E3SM, CPC and ERA-20C with 1° resolution can be found throught ./data/. 2. Train the fully connected network (DNN) Python train_dnn.py 3. Train the UFNet Python train_ufnet.py 4. Evaluation and compared with the baseline Python evaluation.py

Lucas, DonaldD↗
DOE OSTI2025

Evaluating Entrainment–Mixing Characteristics through Direct Comparisons of Drop Size Distributions Using In Situ Observations from ACE-ENA

Abstract Constraining the impacts of entrainment and associated mixing (i.e., entrainment–mixing) on cloud properties continues to be difficult, partly due to observational uncertainties as well as a lacking consensus of which methodologies for diagnosing entrainment–mixing are most appropriate. This study introduces a novel method to evaluate the presence and degree of inhomogeneous and homogeneous mixing using ∼100 h of in situ observations from a research aircraft over the northeastern Atlantic. Specifically, drop size distributions are compared between regions containing negligible and significant entrainment for select flight legs, making a direct characterization of the degree of homogeneous and inhomogeneous mixing possible. A measure of drop concentration variance is used as a proxy variable to diagnose entrainment–mixing. Results correspond well with entrainment–mixing metrics, showing lower Damköhler numbers where drop size distributions shift toward smaller drop sizes (i.e., inhomogeneous mixing) and greater transition length scales where drop size distributions do not (i.e., homogeneous mixing). Inhomogeneous mixing occurs in most samples from Aerosol and Cloud Experiment in the Eastern North Atlantic (ACE-ENA) (regardless of homogeneous mixing frequencies increasing with increasing spatial resolution from ∼100 to ∼10 m) and is associated with decreased drop size relative dispersion and both greater aerosol and drop concentrations compared with homogeneous mixing. Precipitating clouds have a greater frequency of homogeneous mixing compared with nonprecipitating clouds. The proposed methodology is similarly applied to in situ observations of southeast Pacific stratocumulus, shallow convective clouds over central Oklahoma and low-level clouds over the Southern Ocean. All four locations are primarily dominated by inhomogeneous mixing with minimal variability among each region.

Clouds↗
DOE OSTI2025

An Alternative Ensemble Streamflow Prediction Approach Using Improved Subseasonal Precipitation Forecasts from the North America Multi-Model Ensemble Phase II

In this article, streamflow forecasting at a subseasonal time scale (10–30 days into the future) is important for various human activities. The ensemble streamflow prediction (ESP) is a widely applied technique for subseasonal streamflow forecasting. However, ESP’s reliance on the randomly resampled historical precipitation limits its predictive capability. Available dynamical subseasonal precipitation forecasts provide an alternative to the randomly resampled precipitation in ESP. Prior studies found the predictive performance of raw subseasonal precipitation forecast is limited in many regions such as the central south of the United States, which raises questions about its effectiveness in assisting streamflow forecasting. To further assess the hydrologic applicability of dynamical subseasonal precipitation forecasts, we test the subseasonal precipitation forecast from North America Multi-Model Ensemble Phase II (NMME-2) at four watersheds in the central south region of the United States. The subseasonal precipitation forecasts are postprocessed with bias correction and spatial disaggregation (BCSD) to correct bias and improve spatial resolution before replacing the randomly resampled precipitation in ESP for streamflow predictions. The performance of the resulting streamflow predictions is benchmarked with ESP. Evaluation is conducted using Kling–Gupta Efficiency (KGE), continuous ranked probability score (CRPS), probability of detection (POD), false alarm ratios (FARs), as well as reliability diagrams. Our results suggest that BCSD-corrected subseasonal precipitation forecasts lead to overall improved streamflow predictions due to added skills in winter and spring. Our results also suggest that BCSD-corrected subseasonal precipitation forecasts lead to improved predictions on the occurrence of high-percentile streamflow values above 75%. Overall, BCSD-corrected subseasonal precipitation has shown promising performance, highlighting its potential broader applications for river and flood forecasting.

54 ENVIRONMENTAL SCIENCES↗