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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Extrapolation of Type Ia Supernova Spectra into the Near-infrared Using Principal Component Analysis

Abstract We present a method of extrapolating the spectroscopic behavior of Type Ia supernovae (SNe Ia) in the near-infrared (NIR) wavelength regime up to 2.30 μ m using optical spectroscopy. Such a process is useful for accurately estimating K-corrections and other photometric quantities of SNe Ia in the NIR. A principal component analysis is performed on data consisting of Carnegie Supernova Project I & II optical and NIR FIRE spectra to produce models capable of making these extrapolations. This method differs from previous spectral template methods by not parameterizing models strictly by photometric light-curve properties of SNe Ia, allowing for more flexibility of the resulting extrapolated NIR flux. A difference of around −3.1% to −2.7% in the total integrated NIR flux between these extrapolations and the observations is seen here for most test cases including Branch core-normal and shallow-silicon subtypes. However, larger deviations from the observation are found for other tests, likely due to the limited high-velocity and broad-line SNe Ia in the training sample. Maximum-light principal components are shown to allow for spectroscopic predictions of the color-stretch light-curve parameter, s BV , within approximately ±0.1 units of the value measured with photometry. We also show these results compare well with NIR templates, although in most cases the templates are marginally more fitting to observations, illustrating a need for more concurrent optical+NIR spectroscopic observations to truly understand the diversity of SNe Ia in the NIR.

Astronomy & Astrophysics↗
DOE OSTI2022

Superconductivity device comprising a phononic crystal

The invention is directed to a device and method to engineer the superconducting transition width by suppressing the phonon populations responsible for the Cooper-pair decoherence below the superconducting transition temperature via phononic bandgap engineering. The device uses phononic crystals to engineer a phononic frequency gap that suppresses the decohering thermal phonon population just below the Cooper-frequency, and thus the normal conduction electron population. For example, such engineering can relax the cooling requirements for a variety of circuits yielding higher operational quality factors for superconducting electronics and interconnects.

El-Kady, Ihab Fathy↗
DOE OSTI2023

3D Source Reconstruction Using Coded Aperture Gamma-Ray Imaging

Recent measurements with coded-aperture imagers demonstrate material mass determination in a holdup setting to an accuracy within a few percent. This capability is of particular interest to the Surplus Plutonium Disposition (SPD) project, which aims to dilute and dispose of surplus plutonium oxide. Gamma-ray imagers can be used to determine holdup without interrupting normal operations. In this work, we examine techniques for 3D source localization and mass determination using gamma-ray imagers. Coded-aperture imagers provide excellent source localization within the 2D image plane; however, multiple imagers operating in tandem are necessary to identify source location in 3D space. A Maximum Likelihood Expectation-Maximization (MLEM) method for fitting detector mappings is a powerful tool for accomplishing this task. MLEM allows 3D source localization to be simultaneously constrained using multiple gamma-ray imagers by constructing the basis for the MLEM fit using detector mappings from different detector locations stitched together. Each of these basis points represents a singular response from a source in 3D space and is generated using Monte Carlo simulations of sources placed individually at different locations throughout the imager’s field of view. Additionally, implementing knowledge of the physical equipment in the simulations of the glovebox used for the SPD project incorporates attenuation effects that are needed to calculate material holdup.

Laminack, Alex↗
DOE OSTI2024

Modern deep neural networks for Direct Normal Irradiance forecasting: A classification approach

The escalating energy demand and the adverse environmental impacts of fossil-fuel use necessitate a shift towards cleaner and renewable alternatives. Concentrated Solar Power (CSP) technology emerges as a promising solution, offering a carbon-free alternative for power generation. The efficiency and profitability of CSP depend on the Direct Normal Irradiance (DNI) component of solar radiation; hence, accurate DNI forecasting can help optimize CSP plants’ operations and performance. The unpredictable nature of weather phenomena, particularly cloud cover, introduces uncertainty into DNI projections. Existing DNI forecasting models use meteorological factors, which are both challenging to estimate numerically over short prediction windows and expensive to model through data at a sufficiently high spatial and temporal resolution. This research addresses the challenge by presenting a novel approach that formulates DNI prediction as a multi-class classification problem, departing from conventional regression-based methods. The primary objective of this classification framework is to identify optimal periods aligning with specific operational thresholds for CSP plants, contributing to enhanced dispatch optimization strategies. We model the DNI classification problem using four advanced deep neural networks – rectified linear unit (ReLU) networks, 1D residual networks (ResNets), bidirectional long short-term memory (BiLSTM) networks, and transformers – achieving accuracies up to 93.5% without requiring meteorological parameters.

14 SOLAR ENERGY↗
DOE OSTI2023

Depletion-driven thermochemistry of molten salt reactors: review, method, and analysis

Molten salt reactors (MSRs) are innovative advanced nuclear reactors that utilize nuclear fuel by dissolving it in a high-temperature liquid salt. This unique feature differentiates MSRs from other types of reactors and allows for enhanced safety and economic performance. The liquid fuel also entails several multiphysics effects that can complicate reactor design and operation. One primary effect termed here as depletion-driven thermochemistry is a driving force in altering the multiphysics behavior of the reactor. Essentially, depletion-driven thermochemistry is the effect that fuel depletion has on changing the chemical redox potential of the fuel salt over time. As the fuel is consumed, the redox potential shifts toward a more oxidizing state. Without active control, the changing chemistry due to depletion increases corrosion thereby limiting reactor component lifetimes. Additionally, the changing redox potential of the fuel salt alters the vapor pressures of chemical species dissolved in the fuel salt. Changing vapor pressures of species in the fuel salt is an important parameter to understand when off-gassing volatile species during normal reactor operation, and for source term characterization during accident scenario transients. The present work represents a fundamental step toward modeling and coupling the driving physics (i.e., neutronics and chemistry) involved in altering the redox potential in an MSR. Here, the neutronic code Griffin models the depletion of the fuel-salt system, while the chemical equilibrium code Thermochimica calculates the thermochemical state of the isotopic inventory, using the Molten Salt Thermodynamic Database - Thermochemical (MSTDB-TC). These two codes are tightly coupled to predict the impact of fuel depletion in altering the chemistry in MSR systems. Redox potential control methods are discussed and can be modeled using this multiphysics approach. The vapor pressures of chemical species that could be extracted to an off-gas system, as determined by the reactor’s thermochemical state, are examined. The neutronics-chemistry coupling developed in this work is expected to have potential application for analyzing corrosion, source term evolution, and material safeguards in MSR systems. Lastly, suggestions for areas of further improvements of the models to expand these capabilities by incorporating other coupled physics effects is provided.

Walker, Samuel A.↗
DOE OSTI2024

Contrasting roles of rice root iron plaque in retention and plant uptake of silicon, phosphorus, arsenic, and selenium in diverse paddy soils

Abstract Background and aims Iron (Fe) plaque on rice roots is a mixture of Fe oxide and oxyhydroxide minerals thought to protect rice from high levels of arsenic (As) in flooded paddy soils. Silicon (Si), phosphorus (P), and selenium (Se) also exist as oxyanions in rice paddies, but the impacts of Fe plaque on uptake of these nutrients are unknown. Methods We used natural variation in paddy soil chemistry to test how Si, P, As, and Se move from porewater to plaque to plant via multiple techniques. In a pot study, we monitored Fe plaque deposition and porewater chemistry in 5 different soils over time and measured plaque/plant chemistry and Fe plaque mineralogy at harvest. We normalized oxyanion concentrations by Fe to determine the preferential retention on plaque or plant uptake. Results Low phosphorus availability increased root Fe-oxidizing activity, while Fe, Si, P, As, and Se concentrations in plaque were strongly correlated with porewater. Plaque did not appreciably retain Si and Se, and the oxyanions did not compete for adsorption sites on the Fe plaque. Conclusion Root Fe plaque seems to protect rice from As uptake, does not interfere with Si and Se uptake, and roots adapt to maintain P nutrition even with retention of porewater P on plaque.

Agriculture↗
DOE OSTI2023

Influence of the irradiated pulmonary microenvironment on macrophage and T cell dynamics

The lung is sensitive to radiation, which increases the risk of normal tissue toxicity following radiation therapy. Adverse outcomes include pneumonitis and pulmonary fibrosis, which are thought to result from dysregulated intercellular communication within the pulmonary microenvironment. Macrophage accumulation in the lung following radiation exposure is implicated in these pathogenic outcomes. Here we investigate the role of the microenvironment in macrophage and T cell dynamics. Materials and methods C57Bl/6 mice received 6Gyx5 x-ray irradiation to the right lung. Macrophage and T cell dynamics were investigated in ipsilateral right lungs, contralateral left lungs and compared to those from non-irradiated control subjects at 4-26wk post exposure. Lungs were evaluated by flow cytometry, histology and proteomics. Results In uni-lung irradiated subjects, focal regions of macrophage accumulation were noted in both lungs by 8wk, however fibrotic lesions were observed only in ipsilateral lungs by 26wk. Both infiltrating and alveolar macrophages populations transiently expanded in both lungs, however a transitional CD11b+ alveolar macrophage population persisted only in ipsilateral lungs and expressed lower CD206. Concurrently, arginase-1+ macrophages were noted within areas of macrophage accumulation in ipsilateral but not contralateral lungs at 8 and 26wk post exposure, while CD206+ macrophages were absent from these accumulations. While CD8+ T cells were present in both lungs of irradiated subjects, T regulatory cells were only increased in ipsilateral lungs. Unbiased proteomics analysis of immune cells revealed a substantial number of differentially expressed proteins in ipsilateral lungs when compared to either contralateral or non-irradiated lungs, as well as between contralateral lungs from irradiated subjects and non-irradiated controls. Conclusions Pulmonary macrophage and T cell dynamics are impacted by the microenvironmental conditions that develop in the lung following radiation exposure, both locally and systemically. Our findings demonstrate that while macrophages and T cells infiltrate and expand in both lungs, they diverge phenotypically depending on their environment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Identification of KLHL12 Ligands Using Fragment-Based Methods

Targeted protein degradation can be induced by recruiting a protein of interest to an E3 ligase, resulting in its ubiquitination and subsequent proteasome-mediated degradation. However, only a small number of E3 ligases have been utilized for degradation. Expansion of the repertoire of useful E3 ligases via the identification of ligands to those ligases could broaden the scope and applicability of the degradation paradigm. We have identified KLHL12 as an E3 ligase with higher expression in cancer over normal tissues. We report here the use of NMR-based screening to identify fragments that bind to KLHL12, and X-ray structures of a fragment hit bound to KLHL12. Using this structural information, we optimized the hits, leading to the first reported small molecules that bind to KLHL12 with submicromolar affinity. Derivatives of these compounds may be useful for the construction of PROTACs to selectively degrade protein targets in tumors while sparing normal cells.

Amines↗
DOE OSTI2022

Methods to capture proteomic and metabolomic signatures from cerebrospinal fluid and serum of healthy individuals

Discovery of reliable signatures for the empirical diagnosis of neurological diseases—both infectious and non-infectious—remains unrealized. One of the primary challenges encountered in such studies is the lack of a comprehensive database representative of a signature background that exists in healthy individuals, and against which an aberrant event can be assessed. For neurological insults and injuries, it is important to understand the normal profile in the neuronal (cerebrospinal fluid) and systemic fluids (e.g., blood). Here, we present the first comparative multi-omic human database of signatures derived from a population of 30 individuals (15 males, 15 females, 23–74 years) of serum and cerebrospinal fluid. In addition to empirical signatures, we also assigned common pathways between serum and CSF. Together, our findings provide a cohort against which aberrant signature profiles in individuals with neurological injuries/disease can be assessed—providing a pathway for comprehensive diagnostics and therapeutics discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Using heterogeneous data to identify signatures of dengue outbreaks at fine spatio-temporal scales across Brazil

Dengue virus remains a significant public health challenge in Brazil, and seasonal preparation efforts are hindered by variable intra- and interseasonal dynamics. Here, we present a framework for characterizing weekly dengue activity at the Brazilian mesoregion level from 2010–2016 as time series properties that are relevant to forecasting efforts, focusing on outbreak shape, seasonal timing, and pairwise correlations in magnitude and onset. In addition, we use a combination of 18 satellite remote sensing imagery, weather, clinical, mobility, and census data streams and regression methods to identify a parsimonious set of covariates that explain each time series property. The models explained 54% of the variation in outbreak shape, 38% of seasonal onset, 34% of pairwise correlation in outbreak timing, and 11% of pairwise correlation in outbreak magnitude. Regions that have experienced longer periods of drought sensitivity, as captured by the “normalized burn ratio,” experienced less intense outbreaks, while regions with regular fluctuations in relative humidity had less regular seasonal outbreaks. Both the pairwise correlations in outbreak timing and outbreak trend between mesoresgions were best predicted by distance. Our analysis also revealed the presence of distinct geographic clusters where dengue properties tend to be spatially correlated. Forecasting models aimed at predicting the dynamics of dengue activity need to identify the most salient variables capable of contributing to accurate predictions. Our findings show that successful models may need to leverage distinct variables in different locations and be catered to a specific task, such as predicting outbreak magnitude or timing characteristics, to be useful. This advocates in favor of “adaptive models” rather than “one-size-fits-all” models. The results of this study can be applied to improving spatial hierarchical or target-focused forecasting models of dengue activity across Brazil.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

An intensity-based post-processing tool for 3D instance segmentation of organelles in soft X-ray tomograms

Investigating the 3D structures and rearrangements of organelles within a single cell is critical for better characterizing cellular function. Imaging approaches such as soft X-ray tomography have been widely applied to reveal a complex subcellular organization involving multiple inter-organelle interactions. However, 3D segmentation of organelle instances has been challenging despite its importance in organelle characterization. Here we propose an intensity-based post-processing tool to identify and separate organelle instances. Our tool separates sphere-like (insulin vesicle) and columnar-shaped organelle instances (mitochondrion) based on the intensity of raw tomograms, semantic segmentation masks, and organelle morphology. We validate our tool using synthetic tomograms of organelles and experimental tomograms of pancreatic β -cells to separate insulin vesicle and mitochondria instances. As compared to the commonly used connected regions labeling, watershed, and watershed + Gaussian filter methods, our tool results in improved accuracy in identifying organelles in the synthetic tomograms and an improved description of organelle structures in β -cell tomograms. In addition, under different experimental treatment conditions, significant changes in volumes and intensities of both insulin vesicle and mitochondrion are observed in our instance results, revealing their potential roles in maintaining normal β -cell function. Our tool is expected to be applicable for improving the instance segmentation of other images obtained from different cell types using multiple imaging modalities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Fuel Salt Qualification and Associated Fuel Cycle Opportunities & Issues

NRC staff have defined fuel qualification as a process which provides high confidence that the physical and chemical behavior of fuel is sufficiently understood so that it can be adequately modeled for both normal and accident conditions, reflecting the role of the fuel design in the overall safety of the facility. Uncertainties are defined so that calculated fission product releases include the appropriate margins to ensure conservative calculation of radiological dose consequences. The Advisory Committee on Reactor Safeguards (ACRS) has accepted the methodology described in NUREG/CR-7299 as an acceptable method for fuel qualification for molten salt reactors. The fuel salt qualification process described in NUREG/CR-7299 is based upon understanding the role that the fuel salt plays in achieving the fundamental safety functions, which in-turn is based on the fuel salt thermophysical and thermochemical properties.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Determining reference standard strength for neutron-irradiated reduced activation ferritic/martensitic steel F82H by Bayesian method

The deterministic approach widely adopted in the design of structural components relies on systematically defined design limits using empirically determined safety factors. However, this approach is not always appropriate because structures are subjected to a variety of loads in the practical environment, which may result in excessively conservative design limits. In recent years, a more rigorous probabilistic approach that incorporates material strength distributions has become an important solution. In the probabilistic approach, the probability density functions of material strength properties underpin the design criteria. Here, the objective of this study is to identify the density distribution functions that best describe tensile properties of irradiated F82H to define a reference strength for DEMO design. Due to the limited number of existing data, this study specifically employs a Bayesian prediction method based on Monte Carlo simulations to determine a material reference value with statistical reliability and to investigate its effectiveness. For example, the dependence of tensile properties of 300 °C irradiated materials on irradiation damage and the range predicted by 95% Bayesian estimation was evaluated. As a statistical model for the dose dependence of statistical parameters, the normal distribution exhibited a better fit for 0.2% proof strength and tensile strength, whereas the distribution of total elongation data gave comparable reference values for both the normal and Weibull distribution models. Both models gave comparable criteria for the distribution of total elongation data. The Weibull model also gave better results for uniform elongation. The function best describing the model was a logarithmic law for both 0.2% proof strength and tensile strength, while a power law for both total and uniform elongation, which allowed for more comprehensive data prediction of irradiation data with statistical accuracy for DEMO reactor design.

36 MATERIALS SCIENCE↗
DOE OSTI2021

InterCarb: A Community Effort to Improve Interlaboratory Standardization of the Carbonate Clumped Isotope Thermometer Using Carbonate Standards

Abstract Increased use and improved methodology of carbonate clumped isotope thermometry has greatly enhanced our ability to interrogate a suite of Earth‐system processes. However, interlaboratory discrepancies in quantifying carbonate clumped isotope (Δ 47 ) measurements persist, and their specific sources remain unclear. To address interlaboratory differences, we first provide consensus values from the clumped isotope community for four carbonate standards relative to heated and equilibrated gases with 1,819 individual analyses from 10 laboratories. Then we analyzed the four carbonate standards along with three additional standards, spanning a broad range of δ 47 and Δ 47 values, for a total of 5,329 analyses on 25 individual mass spectrometers from 22 different laboratories. Treating three of the materials as known standards and the other four as unknowns, we find that the use of carbonate reference materials is a robust method for standardization that yields interlaboratory discrepancies entirely consistent with intralaboratory analytical uncertainties. Carbonate reference materials, along with measurement and data processing practices described herein, provide the carbonate clumped isotope community with a robust approach to achieve interlaboratory agreement as we continue to use and improve this powerful geochemical tool. We propose that carbonate clumped isotope data normalized to the carbonate reference materials described in this publication should be reported as Δ 47 (I‐CDES) values for Intercarb‐Carbon Dioxide Equilibrium Scale.

58 GEOSCIENCES↗
DOE OSTI2023

Locating the Source of Forced Oscillations in Transmission Power Grids

A forced oscillation event in power grids refers to a state where malfunctioning or abnormally operating equipment causes persisting periodic disturbances in the system. While power grids are designed to damp most perturbations during standard operations, some of them can excite normal modes of the system and cause significant energy transfers across the system, creating large oscillations thousands of miles away from the source. Localization of the source of such disturbances remains an outstanding challenge due to a limited knowledge of the system parameters outside of the zone of responsibility of system operators. Here, we propose a new method for locating the source of forced oscillations that addresses this challenge by performing a simultaneous dynamic model identification using a principled maximum likelihood approach. We illustrate the validity of the algorithm on a variety of examples where forcing leads to resonance conditions in the system dynamics. Our results establish that an accurate knowledge of system parameters is not required for a successful inference of the source and frequency of a forced oscillation. We anticipate that our method will find a broader application in general dynamical systems that can be well described by their linearized dynamics over short periods of time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

High-resolution mapping of nitrogen oxide emissions in large US cities from TROPOMI retrievals of tropospheric nitrogen dioxide columns

Satellite-derived spatiotemporal patterns of nitrogen oxide (NOx) emissions can improve accuracy of emission inventories to better support air quality and climate research and policy studies. In this study, we develop a new method by coupling the chemical transport Model-Independent SATellite-derived Emission estimation Algorithm for Mixed-sources (MISATEAM) with a divergence method to map high-resolution NO x emissions across US cities using TROPOspheric Monitoring Instrument (TROPOMI) tropospheric nitrogen dioxide (NO 2 ) retrievals. The accuracy of the coupled method is validated through application to synthetic NO 2 observations from the NASA-Unified Weather Research and Forecasting (NU-WRF) model, with a horizontal spatial resolution of 4 km × 4 km for 33 large and mid-size US cities. Validation reveals excellent agreement between inferred and NU-WRF-provided emission magnitudes (R= 0.99, normalized mean bias, NMB = —0.01) and a consistent spatial pattern when comparing emissions for individual grid cells (R = 0.88 ± 0.06). We then develop a TROPOMI-based database reporting annual emissions for 39 US cities at a horizontal spatial resolution of 0.05° × 0.05° from 2018 to 2021. This database demonstrates a strong correlation (R= 0.90) with the National Emission Inventory (NEI) but reveals some bias (NMB = —0.24). There are noticeable differences in the spatial patterns of emissions in some cities. Our analysis suggests that uncertainties in TROPOMI-based emissions and potential misallocation of emissions and/or missing sources in bottom-up emission inventories both contribute to these differences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Computational Spectroscopy of the Cr–Cr Bond in Coordination Complexes

In this work, we report the accurate computational vibrational analysis of the Cr–Cr bond in dichromium complexes using second-order multireference complete active space methods (CASPT2), allowing direct comparison with experimental spectroscopic data both to facilitate interpreting the low-energy region of the spectra and to provide insights into the nature of the bonds themselves. Recent technological development by the authors has realized such computation for the first time. Accurate simulation of the vibrational structure of these compounds has been hampered by their notorious multiconfigurational electronic structure that yields bond distances that do not correlate with bond order. Some measured Cr–Cr vibrational stretching modes, ν(Cr 2 ), have suggested weaker bonding, even for so-called ultrashort Cr–Cr bonds, while others are in line with the bond distance. Here, we optimize geometries and compute ν(Cr 2 ) with CASPT2 for three well-characterized complexes, Cr 2 (O 2 CCH 3 ) 4 (H 2 O) 2 , Cr 2 (mhp) 4 , and Cr 2 (dmp) 4 . We obtain CASPT2 harmonic ν(Cr 2 ) modes in good agreement with experiment at 282 cm –1 for Cr 2 (mhp) 4 and 353 cm –1 for Cr 2 (dmp) 4 , compute 50 Cr and 54 Cr isotope shifts, and demonstrate that the use of the so-called IPEA shift leads to improved Cr–Cr distances. Additionally, normal mode sampling was used to estimate anharmonicity along ν(Cr 2 ), leading to an anharmonic mode of 272 cm –1 for Cr 2 (mhp) 4 and 333 cm –1 for Cr 2 (dmp) 4 .

36 MATERIALS SCIENCE↗