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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Hestia-SWIFL: hourly anthropogenic fossil fuel CO2 and heat on the 2km WRF grid, version 1.1

The Hestia-SWIFL version 1.1 anthropogenic heat (AH) and fossil fuel CO2 (FFCO2) emissions data product represent emissions due to the combustion of fossil fuel and cement production within the state of Arizona from 2019 to 2022. This product was developed as part of the Southwest Urban Corridor Integrated Field Laboratory (SW-IFL) project, which aims to provide new knowledge and tools that address extreme heat, air quality, climate change and related urban environmental issues by integrating high-resolution observations, modeling, and civic engagement. The emissions are generated using a bottom-up/engineering approach and are tied to results generated by the Vulcan Project version 4, an effort to quantify space/time-resolved FFCO2 & AH emissions for the entire United States landscape. A large number of data sources are combined to best estimate the emissions at fine scales such as air quality emissions data, traffic flow data, building information, sociodemographic information, and fuel statistics. The AH product provides emissions for two emissions sources (transportation and point source emissions) in units of Watts per hour per square meter (W/m2) per year (annual files) or per hour (hourly files). The FFCO2 product provides emissions from nine individual emission sectors as well as the total, and in units of tons of carbon (tC) per grid cell per year or per hour. The output made available here places the native spatial resolution of the Hestia FFCO2 & AH emissions data product (points, lines, and polygons) into a regularized 2km x 2km grid at hourly and annual temporal resolutions, and stored in netCDF files. The exact spatial extent is defined by the ASU Weather Research Forecast (WRF) simulation grid. All data are processed using R/Python pm high-performance computing system. 2-27-2026 updates: Bugs in airport hourly profile (both AH and FFCO2) and building spatial patterns (FFCO2 only) were fixed. Hourly emissions are reprocessed for all years to reflect those changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

F-Hash: Feature-Based Hash Design for Time-Varying Volume Visualization via Multi-Resolution Tesseract Encoding

Interactive time-varying volume visualization is challenging due to its complex spatiotemporal features and sheer size of the dataset. Recent works transform the original discrete time-varying volumetric data into continuous Implicit Neural Representations (INR) to address the issues of compression, rendering, and super-resolution in both spatial and temporal domains. However, training the INR takes a long time to converge, especially when handling large-scale time-varying volumetric datasets. In this work, we proposed F-Hash, a novel feature-based multi-resolution Tesseract encoding architecture to greatly enhance the convergence speed compared with existing input encoding methods for modeling time-varying volumetric data. The proposed design incorporates multi-level collision-free hash functions that map dynamic 4D multi-resolution embedding grids without bucket waste, achieving high encoding capacity with compact encoding parameters. Our encoding method is agnostic to time-varying feature detection methods, making it a unified encoding solution for feature tracking and evolution visualization. Experiments show the F-Hash achieves state-of-the-art convergence speed in training various time-varying volumetric datasets for diverse features. We also proposed an adaptive ray marching algorithm to optimize the sample streaming for faster rendering of the time-varying neural representation.

deep learning↗
DOE OSTI2024

A deep learning-based Bayesian framework for high-resolution calibration of building energy models

Calibrating building energy models (BEMs), i.e., closing discrepancy between modeling and field measurements, is of significance to support its applications in building sustainability and resilience analysis. However, as being widely used in practice, current Bayesian calibration is mostly performed in low-resolution (annual or monthly), instead of high-resolution (hourly or sub-hourly), which is crucial to support emerging BEM applications, such as building-renewable energy integration (demand response) and smart control. This is attributable to the gaps in current Bayesian calibration process, including (1) difficulty in supporting reliable high-resolution calibration with over-parameterization and multi-solution issues, (2) inadequacy of meta-model to capture temporal building dynamics in high-resolution, and (3) excessive computational burdens of covariance matrix calculation in Bayesian inference. Therefore, to close these gaps, this research proposes a novel deep learning-based Bayesian calibration framework, involving pre-calibration mechanism, Long Short-Term Memory as surrogate models, and simplified covariance matrix calculation, to calibrate BEMs in high temporal resolution (i.e., hourly) with enhanced accuracy and computational efficiency. Finally, the case study demonstrates its effectiveness to match modeling outcomes with measurements and realize CV-RMSE of < 30 % and NMBE of < 6 % in hourly resolution, as well as a significant reduction of calibration time (by > 99 %, from > 600 h to ~ 1.5 h).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Estimating Fine-Resolution Shortwave Broadband Albedo of Croplands from Harmonized Landsat and Sentinel-2 Data

Altered surface albedo due to land-cover conversions and management is a significant driver of global climate change. Albedo can be directly measured at ground stations, and remote sensing data can be used to scale-up albedo values to regional and global levels. Some previous studies have retrieved fine-resolution (10–30 m) instantaneous albedo and coarse-resolution (500–1000 m) daily mean albedo from remote sensing data, but they all required the input of Moderate Resolution Imaging Spectroradiometer (MODIS) albedo information at 500-m resolution, and none have assembled both instantaneous and daily albedo based exclusively on fine-resolution satellite data. Here, to address this issue, we compiled 387 instantaneous and 346 daily albedo records using field net radiometer measurements from the bioenergy croplands at the W. K. Kellogg Biological Station in southwest Michigan. We then connected these albedo records with a suite of variables derived from harmonized Landsat and Sentinel-2 data through two machine learning algorithms (random forest regression and extreme gradient boosting) to retrieve clear-sky instantaneous and daily shortwave broadband albedo. The performance statistics indicate reasonable accuracy of model results [root-mean-square error (RMSE)] around or below 0.03 except for snow-covered surfaces), suggesting that the retrieval of both instantaneous and daily albedo based exclusively on fine-resolution satellite data is promising. To facilitate the use of fine-resolution albedo products at the global level, future efforts need to include more albedo records of diverse surface cover types, as well as to accurately model daily albedo for cloudy days to address the “clear-sky bias.”

Harmonized Landsat and Sentinel-2↗
DOE OSTI2025

Reducing Long‐Standing Surface Ozone Overestimation in Earth System Modeling by High‐Resolution Simulation and Dry Deposition Improvement

The overestimation of surface ozone concentration in low‐resolution global atmospheric chemistry and climate models has been a long‐standing issue. We first update the ozone dry deposition scheme in both high‐ (0.25°) and low‐resolution (1°) Community Earth System Model (CESM) version 1.3 runs, by adding the effects of leaf area index and correcting the sunlit and shaded fractions of stomatal resistances. With this update, 5‐year‐long summer simulations (2015–2019) using the low‐resolution CESM still exhibit substantial ozone overestimation (by 6.0–16.2 ppbv) over the U.S., Europe, eastern China, and ozone pollution hotspots. The ozone dry deposition scheme is further improved by adjusting the leaf cuticle conductance, reducing the mean ozone bias by 19%, and increasing the model resolution further reduces the ozone overestimation by 43%. We elucidate the mechanism by which model grid spacing influences simulated ozone, revealing distinctive pathways in urban versus rural areas. In rural areas, grid spacing mainly affects daytime ozone levels, where additional NO x emissions from nearby urban areas result in an ozone boost and overestimation in low‐resolution simulations. In contrast, over urban areas, daytime ozone overestimation follows a similar mechanism due to the influence of volatile organic compounds from surrounding rural areas. However, nighttime ozone overestimation is closely linked to weakened NO titration owing to the redistribution of urban NO x to rural areas. Additionally, stratosphere‐troposphere exchange may also contribute to reducing ozone bias in high‐resolution simulations, warranting further investigation. This optimized high‐resolution CESM may enhance understanding of ozone formation mechanisms, sources, and changes in a warming climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

High-Resolution Imaging of Cellulose Organization in Cell Walls by Field Emission Scanning Electron Microscopy

Field emission scanning electron microscopy (FESEM) is a powerful tool for analyzing surface structures of biological and nonbiological samples. However, when it is used to study fine structures of nanometer-sized microfibrils of epidermal cell walls, one often encounters tremendous challenges to acquire clear and undistorted images because of two major issues: (1) Preparation of samples suitable for high resolution imaging; due to the delicateness of some plant materials, such as onion epidermal cell walls, many things can happen during sample processing, which subsequently result in damaged samples or introduce artifacts. (2) Difficulties to acquire clear images of samples which are electron-beam sensitive and prone to charging artifacts at magnifications over 100,000×. In this chapter we described detailed procedures for sample preparation and conditions for high-resolution FESEM imaging of onion epidermal cell walls. Lastly, the methods can be readily adapted for other wall materials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Measuring X-Ray Emission Line Shapes in Neutral Species for XRISM Calibration

Space X-ray spectrometers such as the Resolve instrument on XRISM require precise calibration in order to interpret the spectra of astrophysical objects. Key components of the calibration are the energy scale and the core line spread function, both of which vary with photon energy. A major issue in the calibration of high-resolution spectrometers is locating good calibrators with well-known and stable intrinsic line shapes. Neutral fluorescence is widely used, but inner-shell transitions in neutral atoms often exhibit complex, poorly documented line shapes that vary with excitation conditions. Here, in this study, we present empirical measurements of K-shell transitions in neutral O and F below 1 keV using an engineering model XRISM calorimeter array, an electron bombardment modulated X-ray source, and an electron beam ion trap (EBIT) to provide a precise energy reference. In addition, we report measurements of the Mo Lα complex with the transition-edge microcalorimeter spectrometer (TEMS), which reveal strong satellite structure and sensitivity of the line shape to the incident exciting spectrum. Together, these results demonstrate the need for empirical line-shape models, highlight the nonstationary nature of neutral fluorescence features, and define a path toward developing transfer standards for XRISM and future precision instruments such as Athena/X-IFU.

Astronomy and AstroPhysics↗
DOE OSTI2022

Joint Survey Processing. I. Compact Oddballs in the COSMOS Field—Low-luminosity Quasars at z > 6?

The faint-end slope of the quasar luminosity function at z ~ 6 and its implication on the role of quasars in reionizing the intergalactic medium at early times has been an outstanding problem for some time. The identification of faint high-redshift quasars with luminosities of <10 44.5 erg s –1 is challenging. They are rare (few per square degree), and the separation of these unresolved quasars from late-type stars and compact star-forming galaxies is difficult from ground-based observations alone. In addition, source confusion becomes significant at >25 mag, with ~30% of sources having their flux contaminated by foreground objects when the seeing resolution is ~0''.7. We mitigate these issues by performing a pixel-level joint processing of ground and space-based data from Subaru/Hyper-SuprimeCam (HSC) and Hubble Space Telescope (HST) Advanced Camera for Surveys (ACS). We create a deconfused catalog over the 1.64 deg 2 of the COSMOS field, after accounting for spatial varying point-spread functions and astrometric differences between the two data sets. We identify twelve low-luminosity (M UV ~ –21 mag) z > 6 quasar candidates through (i) their red color measured between ACS/F814W and HSC/i band and (ii) their compactness in the space-based data. Nondetections of our candidates in Hubble DASH data argues against contamination from late-type stars. Our constraints on the faint end of the quasar luminosity function at z ~ 6.4 suggest a negligibly small contribution to reionization compared to the star-forming galaxy population. The confirmation of our candidates and the evolution of number density with redshift could provide better insights into how supermassive galaxies grew in the first billion years of cosmic time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Cathodoluminescence of Ultrathin Twisted Ge 1–x Sn x S van der Waals Nanoribbon Waveguides

Ultrathin van der Waals semiconductors have shown extraordinary optoelectronic and photonic properties. Propagating photonic modes make layered crystal waveguides attractive for photonic circuitry and for studying hybrid light-matter states. Accessing guided modes by conventional optics is challenging due to limited spatial resolution and poor out-of-plane far field coupling. Scanning near-field optical microscopy (SNOM) can overcome these issues and can characterize waveguide modes down to tens of nm resolution, albeit for planar samples or nanostructures with moderate height variations. Electron microscopy provides atomic-scale localization also for more complex geometries, and recent advances extended the accessible excitations from interband transitions to phonons. In this work, bottom-up synthesized layered semiconductor (Ge 1-x Sn x S) nanoribbons with axial twist and deep sub-wavelength thickness are demonstrated as a platform for realizing waveguide modes, and cathodoluminescence (CL) spectroscopy is introduced as a tool to characterize them. Combined experiments and simulations show the excitation of guided modes by the electron beam and their efficient detection via photons emitted in the ribbon plane, which enables measuring key properties such as the evanescent field into the vacuum cladding with nanometer resolution. The results identify van der Waals waveguides operating in the infrared and highlight an electron microscopy-based approach for probing complex-shaped nanophotonic structures.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Grid generation, coupling strategies, and spatially-dependent time stepping for ocean-tidal/estuary systems and other ESM components (Final Report)

There are many multiple scale issues in the ocean modeling, including different mesh resolutions (local) and different physical processes (global). In order to gain efficiency and fidelity in modern ESMs, it is vital to develop high quality, highly nonuniform meshes and spatially-dependent time stepping strategies for coupling various climate system components. The USC/FSU team has worked on the design, analysis, and implementation of fast CVT grid generation and novel time- stepping schemes that could address all the requirements for global and regional ocean models on highly nonuniform meshes.

58 GEOSCIENCES↗
DOE OSTI2022

LAMP Manufacturing Survey (Final Report)

This report presents the results of a market manufacturing survey performed for fabricating radiofrequency quadrupoles (RFQ) and Drift Tube Linear Accelerator (DTL) components needed for the Los Alamos Neutron Science Center (LANSCE) Modernization Project (LAMP). A review on existing RFQs and DTLs with their parameters, a summary of specific capabilities needed to manufacture them, the common issues during the fabrication process, their consequences, and resolutions to these problems is presented in this report. The goal of this study is to identify potential collaborators and companies capable of manufacturing the necessary accelerator equipment, while minimizing cost and schedule risks that could impact the future modernization of the LANSCE facility.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Resolving the Discontinuity Between Thermal Scattering Data and Fast Data

The task of resolving discontinuities between thermal cross sections and fast cross sections in AMPX processing is part of a broader project to provide guidance on the potential effect of unknown thermal neutron scattering law (TNSL) data, primarily from the standpoint of criticality safety. The primary goal of this work is to deliver code fixes in AMPX that increase confidence that SCALE libraries provide physically correct cross sections across the full range of neutron energies encountered in transport applications. This report discusses the resolution of two sources of discontinuity. The first issue occurs when the Bragg edges in an evaluated nuclear data file do not extend to 5 eV. The second issue concerns parameters chosen during the processing of the nuclear data library—specifically, the parameter that defines the energy at which the thermal data ends and the fast nuclide data begins. This report also discusses a third issue, which is related to the calculation of probability distributions from a densely gridded double-differential cross section.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

A Review of the Use of Wearables in Indoor Environmental Quality Studies and an Evaluation of Data Accessibility from a Wearable Device

An understanding of indoor environmental quality (IEQ) and its effects on occupant well-being can inform building system design and operation. The use of wearables in field studies to collect subjective and objective health performance indicators (HPIs) from a large number of occupants could deliver important improvements in IEQ. To facilitate the use of wearables in IEQ studies, there is a need to identify which HPIs should be collected and to evaluate data accessibility from these devices. To address this issue, a literature review of previous IEQ studies was conducted to identify relationships between different IEQ factors and HPIs, with a focus on HPIs that were collected using wearables. A preliminary assessment of data accessibility from a selected wearable device (Fitbit Versa 2) was performed and documented. The review suggested the need to further investigate and collect sleep quality parameters, heart rate, stress response, as well as subjective ratings of comfort using wearables. The data accessibility assessment revealed issues related to missing data points and data resolution from the examined device. A set of recommendations is outlined to inform future studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Hyperspectral and Nanosecond Temporal Resolution Widefield Infrared Photothermal Heterodyne Imaging

Label-free, bond-selective imaging offers new opportunities for fundamental and applied studies in chemistry, biology, and materials science. Preventing its broader application to investigating spectrally congested specimens are issues related to low sensitivity as well as low spatial and temporal resolution. Here, we demonstrate a widefield, mid-infrared (MIR) photothermal imaging technique, called widefield Infrared Photothermal Heterodyne imaging (wIR-PHI), that massively parallelizes acquisition of MIR absorption data through use of a high-speed complementary metal-oxide-semiconductor camera. wIR-PHI possesses notable features that include: spatial resolution significantly below the MIR diffraction limit, hyperspectral imaging capabilities, high sensitivity, and ~100 ns temporal resolution. Here, the first two features are highlighted by hyperspectral imaging of proximally close poly(methyl methacrylate) (PMMA) and polystyrene (PS) nanoparticles where clear, bond-specific imaging of nanoparticles, separated by less than the MIR diffraction limit, is demonstrated. Sensitivity is highlighted by imaging individual PMMA and PS nanoparticles with radii between r = 97-556 nm. This leads to a current, peak absorption cross-section limit-of-detection of σ abs = 1.9× 10 –16 cm 2 . wIR-PHI's 100 ns temporal resolution is simultaneously demonstrated by observing the decay of photothermal contrast on individual nanoparticles on a ~200-6000 ns timescale. In whole, wIR-PHI’s dramatic increase in acquisition speed opens opportunities for future MIR kinetic imaging and spectroscopic studies of important chemical, biological, and material processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

United States multi-sector land use and land cover base maps to support human and Earth system models

Abstract Earth System Models (ESMs) require current and future projections of land use and landcover change (LULC) to simulate land-atmospheric interactions and global biogeochemical cycles. Among the most utilized land systems in ESMs are the Community Land Model (CLM) and the Land-Use Harmonization 2 (LUH2) products. Regional studies also use these products by extending coarse projections to finer resolutions via downscaling or by using multisector dynamic (MSD) models. One such MSD model is the Global Change Analysis Model (GCAM), which has its own independent land module, but often relies on CLM or LUH2 as spatial inputs for its base years. However, this requires harmonization of thematically incongruent land systems at multiple spatial resolutions, leading to uncertainty and error propagation. To resolve these issues, we develop a thematically consistent LULC system for the conterminous United States adaptable to multiple MSD frameworks to support research at a regional level. Using empirically derived spatial products, we developed a series of base maps for multiple contemporary years of observation at a 30-m resolution that support flexibility and interchangeability amongst LUH2, CLM, and GCAM classification systems.

Oliver, Jay↗
DOE OSTI2026

Risk-Aware Measurement Synchronization and Recovery for DSSE With Heterogeneous Data Sources

Power distribution systems are increasingly integrating heterogeneous sensors with varying data reporting rates and types, which pose challenges to achieving observability at the desired temporal resolution of distribution system state estimation (DSSE). Multisensor failures caused by extreme events exacerbate these issues, introducing substantial uncertainties into DSSE. This article proposes a novel solution to these challenges by ensuring high-resolution system observability despite heterogeneous data sources and multisensor failures. First, a deep learning architecture combining long short-term memory (LSTM) and graph convolutional network (GCN) is employed to synchronize meters with different reporting rates, aiming to achieve system observability. A random-walk-model-based approach is introduced to generate pseudo-measurements while properly characterizing their uncertainties under multisensor failures. Finally, a disaster-risk-informed observability metric (RiOM) is defined to quantify the uncertainty associated with state estimation results. The proposed framework offers deeper insights into the system observability on the fly compared with conventional analysis. The effectiveness of the framework is demonstrated on an IEEE standard test case and a large-scale real-world distribution feeder in mid-Minnesota in the U.S.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Enhanced read resolution in reconfigurable memristive synapses for Spiking Neural Networks

Abstract The synapse is a key element circuit in any memristor-based neuromorphic computing system. A memristor is a two-terminal analog memory device. Memristive synapses suffer from various challenges including high voltage, SET or RESET failure, and READ margin issues that can degrade the distinguishability of stored weights. Enhancing READ resolution is very important to improving the reliability of memristive synapses. Usually, the READ resolution is very small for a memristive synapse with a 4-bit data precision. This work considers a step-by-step analysis to enhance the READ current resolution or the read current difference between two resistance levels for a current-controlled memristor-based synapse. An empirical model is used to characterize the $${\hbox {HfO}}_{2}$$ HfO 2 based memristive device. $$1\textrm{st}$$ 1 st and $$2\textrm{nd}$$ 2 nd stage device of our proposed synapse design can be scaled to enhance the READ current margin up to $$\sim$$ ∼ 4.3 $$\times$$ × and $$\sim$$ ∼ 21%, respectively. Moreover, READ current resolution can be enhanced with run-time adaptation techniques such as READ voltage scaling and body biasing. The READ voltage scaling and body biasing can improve the READ current resolution by about 46% and 15%, respectively. TENNLab’s neuromorphic computing framework is leveraged to evaluate the effect of READ current resolution on classification, control, and reservoir computing applications. Higher READ current resolution shows better accuracy than lower resolution even when facing different levels of read noise.

97 MATHEMATICS AND COMPUTING↗