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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A machine learning approach for determining temperature-dependent bandgap of metal oxides utilizing Allen–Heine–Cardona theory and O’Donnell model parameterization

To evaluate the high temperature sensing properties of metal oxide and perovskite materials suitable for use in combustion environments, it is necessary to understand the temperature dependence of their bandgaps. Although such temperature-driven changes can be calculated via the Allen–Heine–Cardona (AHC) theory, which assesses electron–phonon coupling for the bandgap correction at given temperatures, this approach is computationally demanding. Another approach to predict bandgap temperature-dependence is the O’Donnell model, which uses analytical expressions with multiple fitting parameters that require bandgap information at 0 K. This work employs data-driven Gaussian process regression (GPR) to predict the parameters employed in the O’Donnell model from a set of physical features. We use a sample of 54 metal oxides for which density functional theory has been performed to calculate the bandgap at 0 K, and the AHC calculations have been carried out to determine the shift in the bandgap at non-zero temperatures. As the AHC calculations are impractical for high-throughput screening of materials, the developed GPR model attempts to alleviate this issue by predicting the O'Donnell parameters purely from physical features. To mitigate the reliability issues arising from the very small size of the dataset, we apply a Bayesian technique to improve the generalizability of the data-driven models as well as quantify the uncertainty associated with the predictions. The method captures well the overall trend of the O’Donnell parameters with respect to a reduced feature set obtained by transforming the available physical features. Quantifying the associated uncertainty helps us understand the reliability of the predictions of the O’Donnell parameters and, therefore, the bandgap as a function of temperature for any novel material.

36 MATERIALS SCIENCE↗
NASA NTRS2024

A Computationally Efficient Algorithm for Sampling the Rudd Differential Cross Section

Monte Carlo radiation transport codes such as RITRACKS or Geant4 are used to simulate the interaction of ions with matter. These codes rely on sampling algorithms to determine interactions and various physical properties of particles involved in the simulations. It is crucial to develop efficient sampling algorithms since Monte Carlo radiation transport simulations can be time consuming. This work presents an efficient sampling algorithm to determine the energy of secondary electrons following ion-water interactions. The applicability and intended use of the algorithm are discussed in detail, and it is shown that the new algorithm is up to 6X10 4 times faster than the method currently used in Geant4-DNA.

Floriane Poignant↗
NASA NTRS2003

Bio-Optical and Remote Sensing Observations in Chesapeake Bay

The high temporal and spatial resolution of satellite ocean color observations will prove invaluable for monitoring the health of coastal ecosystems where physical and biological variability demands sampling scales beyond that possible by ship. However, ocean color remote sensing of Case 2 waters is a challenging undertaking due to the optical complexity of the water. The focus of this SIMBIOS support has been to provide in situ optical measurements from Chesapeake Bay (CB) and adjacent mid-Atlantic bight (MAB) waters for use in algorithm development and validation efforts to improve the satellite retrieval of chlorophyll (chl a) in Case 2 waters. CB provides a valuable site for validation of data from ocean color sensors for a number of reasons. First, the physical dimensions of the Bay (> 6,500 km2) make retrievals from satellites with a spatial resolution of approx. 1 km (i.e., SeaWiFS) or less (i.e., MODIS) reasonable for most of the ecosystem. Second, CB is highly influenced by freshwater flow from major rivers, making it a classic Case 2 water body with significant concentrations of chlorophyll, particulates and chromophoric dissolved organic matter (CDOM) that highly impact the shape of reflectance spectra.

Harding, Lawrence W., Jr.↗
NASA NTRS2004

Evaluation and Validation of Case 2 Algorithms in Chesapeake Bay

The high temporal and spatial resolution of satellite ocean color observations will prove invaluable for monitoring the health of coastal ecosystems where physical and biological variability demands sampling scales beyond that possible by ship. However, ocean color remote sensing of Case 2 waters is a challenging undertaking due to the optical complexity of the water. The focus of this SIMBIOS support has been to provide in situ optical measurements form Chesapeake Bay (CB) and adjacent mid-Atlantic bight (MAB) waters for use in algorithm development and validation efforts to improve the satellite retrieval of chlorophyll (chl a) in Case 2 waters. CB provides a valuable site for validation of data from ocean color sensors for a number of reasons. First, the physical dimensions of the Bay (greater than 6,500 square kilometers) make retrievals from satellites with a spatial resolution of approximately 1 kilometer (i.e., SeaWiFS) or less (i.e., MODIS) reasonable for most of the ecosystem. Second, CB is highly influenced by freshwater flow from major rivers, making it a classic Case 2 water body with significant concentrations of chlorophyll, particulates and chromophoric dissolved organic matter (CDOM) that highly impact the shape of reflectance spectra. Finally, past and ongoing research efforts provided an expensive data set of optical observations that support the goal of this project.

Harding, Lawrence W., Jr.↗
DOE OSTI2025

Plasma proteomic biomarkers of physical frailty in heart failure: a propensity score matched discovery-based pilot study

Background: Physical frailty is highly prevalent in heart failure (HF), but we lack an understanding of the underlying pathophysiology. Proteomics evaluation of plasma samples may elucidate potential mechanisms and biomarkers of physical frailty in HF. We aimed to identify plasma proteomic biomarkers that are differentially expressed between physically frail and non physically frail adults with HF. Methods: This was a secondary analysis of a subset of data and plasma samples from a study of frailty among patients with New York Heart Association (NYHA) Functional Classification I-IV HF. Physical frailty was measured using the Frailty Phenotype Criteria. Propensity score matching was used to match pairs of physically frail (n = 20) vs. non-physically frail (n = 20) patients on clinical characteristics. Plasma samples were processed using a sensitive liquid chromatography mass spectrometry platform, utilizing a multiplexed tandem mass tag-labeled quantitative proteomics approach. Differentially expressed proteins were quantified individually using paired t tests with associated log fold change of 0.3 and Fisher’s combined p values. Results: The sample (n = 40) was 62.8±16.9 years old, 58% female, and 55% NYHA Class III/IV. Proteomics analysis revealed 7 proteins differentially expressed using full differential criteria: matrix metalloproteinase-14 was downregulated in frailty, and copine-1, low affinity immunoglobulin gamma Fc region receptor III-A and III-B, probable non-functional immunoglobulin kappa variable 2D-24, glutathione S-transferase Mu 1, and argininosuccinate lyase were upregulated in frailty. Conclusions: Proteomic biomarkers related to the immune system, stress response, and detoxification were differentially expressed between physically frail and non-physically frail adults with HF.

Biomarkers↗
DOE OSTI2023

gLaSDI: Parametric physics-informed greedy latent space dynamics identification

A parametric adaptive physics-informed greedy Latent Space Dynamics Identification (gLaSDI) method is proposed for accurate, efficient, and robust data-driven reduced-order modeling of high-dimensional nonlinear dynamical systems. In the proposed gLaSDI framework, an autoencoder discovers intrinsic nonlinear latent representations of high-dimensional data, while dynamics identification (DI) models capture local latent-space dynamics. Here, an interactive training algorithm is adopted for the autoencoder and local DI models, which enables identification of simple latent-space dynamics and enhances accuracy and efficiency of data-driven reduced-order modeling. To maximize and accelerate the exploration of the parameter space for the optimal model performance, an adaptive greedy sampling algorithm integrated with a physics-informed residual-based error indicator and random-subset evaluation is introduced to search for the optimal training samples on the fly. Further, to exploit local latent-space dynamics captured by the local DI models for an improved modeling accuracy with a minimum number of local DI models in the parameter space, a -nearest neighbor convex interpolation scheme is employed. The effectiveness of the proposed framework is demonstrated by modeling various nonlinear dynamical problems, including Burgers equations, nonlinear heat conduction, and radial advection. The proposed adaptive greedy sampling outperforms the conventional predefined uniform sampling in terms of accuracy. Compared with the high-fidelity models, gLaSDI achieves 17 to 2,658× speed-up with 1 to 5% relative errors.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

The second-moment climatology of the GATE rain rate data

The first part of this paper presents the description of the GARP (Global Atmospheric Research Program) Atlantic Tropical Experiment (GATE) 1 rain-rate data and its two-dimensional spectral and correlation characteristics, which has made it possible to accomplish the following: to show the concentration of a significant power along the frequency axis in the spatiotemporal spectra; to detect a diurnal cycle (which has a range of variation of about 3.4-5.4 mm/n) as one of the sources of bias in the rain statistics of satellite data; to study the distinction between the north-south and east-west transport of spatial rain-rate field and character of its anisotropy; to evaluate the scales of the distinction between second-moment estimates associated with ground and satellite samples; and to determine the appropriate spatial and temporal scales of simple linear stochastic models fitted to averaged rain-rate fields. The second part of this paper is devoted to an analysis of the diffusion of the rain rate by establishing a relationship between the parameters of the multivariate autoregressive model and the coefficients of a diffusion equation. This analysis led to the use of rain data to estimate the rain advection velocity as well as other coefficients of the diffusion equation of the corresponding field. The results obtained can be used for comparison with corresponding estimates of other sources of data (satellite, Tropical Oceans Global Atmosphere Coupled Ocean - Atmosphere Response Experiment (TOGA, COARE) or simulated by physical models), for generating multiple samples of any size, for solving the inverse problems of some of the hydrodynamic equations, and in some other areas of rain data analysis and modeling.

Polyak, Ilya↗
DOE OSTI2021

GANplifying event samples

A critical question concerning generative networks applied to event generation in particle physics is if the generated events add statistical precision beyond the training sample. We show for a simple example with increasing dimensionality how generative networks indeed amplify the training statistics. We quantify their impact through an amplification factor or equivalent numbers of sampled events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Effect of hydromagnesite addition on the properties and water resistance of magnesium oxysulfate (MOS) cement

Magnesium oxysulfate (MOS) cement exhibits excessive cracking when exposed to water because of the reaction of residual MgO that forms extensive Mg(OH){sub 2}, which significantly limits the application breadth of MOS cement. This study investigates the effects of the addition of hydromagnesite ((MgCO{sub 3}){sub 4}·Mg(OH){sub 2}·4H{sub 2}O) on the hydration products of MOS cement and the microstructure and physical properties of MOS paste samples. It was found that the addition of hydromagnesite increased the compressive strength and water resistance of MOS cement. This effect is mainly due to the reaction between hydromagnesite and free MgO present in the cement that forms magnesium carbonate (MgCO{sub 3}·Mg(OH){sub 2}·3H{sub 2}O) and acts as an additional binding phase. The use of hydromagnesite as an additive for improving the water resistance of MOS cement leads to a decrease in the residual MgO content and improves the water stability of amorphous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

The DREAMS Project: Disentangling the Impact of Halo-to-halo Variance and Baryonic Feedback on Milky Way Satellite Galaxies

We analyze the properties of satellite galaxies around 1024 Milky Way–mass hosts from the DREAMS Project, simulated within a ΛCDM cosmology. Utilizing the TNG galaxy-formation model, the DREAMS simulations incorporate both baryonic physics and cosmological uncertainties for a large sample of galaxies with diverse environments and formation histories. We investigate the relative impact of the physical uncertainty from the galaxy-formation model on predicted satellite properties using four metrics: the satellite stellar mass function, radial distribution, inner slope of the dark matter density profile, and stellar half-light radius. We compare these predictions to observations from the SAGA survey and the DREAMS N-body simulations and find that uncertainties from baryonic physics modeling are subdominant to the scatter arising from halo-to-halo variance. Where baryonic modeling does affect satellites, the supernova wind energy has the largest effect on the satellite properties that we investigate. Specifically, increased supernova wind energy suppresses the stellar mass of satellites and results in more extended stellar half-light radii. The adopted wind speed has only a minor impact, and other astrophysical and cosmological parameters show no measurable effect. Our findings highlight the robustness of satellite properties against uncertainties in baryonic physics modeling.

Rose, Jonah C. [Princeton University, NJ (United S↗
NASA NTRS2024

Seismic Velocities of the Tagish Lake Meteorite: Exploring Sample Size Limits for Elastic Property Determination

Understanding the mechanical and elastic properties of rocks comprising asteroids is be-coming of greater practical importance as more spacecraft interact with them (e.g. OSIRIS-REx, Hayabusa2, DART). However, knowledge of asteroid lithologies’ physical properties is limited due to sample paucity and the resulting challenges that come with working with small samples. Measuring seismic velocities is one way to directly and indirectly (through relation-ships established with analog materials) explore elastic and strength properties, respectively, while minimizing use of available material. While sample preparation requires cutting, the seismic measurements are non-destructive.

physical properties↗
NASA NTRS1975

A sample holding technique for study of crystal growth in silicate melts

A thin platinum wire loop is an effective way to hold silicate melts during experimentation in a gas-mixing furnace. This method results in a minimum of physical and chemical interaction between the sample and container but maximum interaction between sample and gas mixture. However, volatilization of sodium occurs while the silicate is molten. By minimizing the chance of heterogeneous nucleation, the method is ideal for experimental investigation of the origin of rock textures.

Donaldson, C. H.↗
DOE OSTI2024

The ion-gas-neutral interactions with surfaces-2 (IGNIS-2) facility for the study of plasma–material interactions

The Ion-Gas-Neutral Interactions with Surfaces-2 (IGNIS-2) surface science facility has been designed at the Pennsylvania State University with the specific purpose of enabling experiments to study plasma–material interactions. This in situ surface modification and characterization facility consists of multiple reconfigurable substations that are connected through a central transfer chamber. This fully connected vacuum system ensures that the physical and chemical properties of samples are not altered between surface modification and analysis. The modification techniques in IGNIS-2 include a low-energy (<300 eV), high-flux (up to 1016 cm−2 s−1) broad-beam ion source, a liquid metal dropper, a lithium injection system, an RF sputter source, and an evaporator. Its characterization techniques include charged particle-based techniques, such as low-energy ion scattering (enabled by two <5 keV ion sources) and x-ray photoelectron spectroscopy, and photon and light-based techniques, such as x-ray fluorescence, multi-beam optical stress sensors, and optical cameras. All of these techniques can be utilized up to mTorr pressures, allowing both in situ and in operando studies to be conducted. Results are presented on lithium wetting experiments of argon-irradiated tungsten-based composites, surface stress measurements of tungsten films during deuterium ion irradiation, and temperature-programmed desorption of deuterium-irradiated graphite to demonstrate the in situ capabilities of this new facility.

Instruments & Instrumentation↗
NASA NTRS2007

Effect of LEO Exposure on Aromatic Polymers Containing Phenylphosphine Oxide Groups

As part of the Materials on The International Space Station Experiment (MISSE), aromatic polymers containing phenylphosphine oxide groups were exposed to low Earth orbit (LEO) for approximately 4 years. All of the aromatic polymers containing phenylphosphine oxide groups survived the exposure despite the high fluence of atomic oxygen that completely eroded other polymer films such as Kapton and Mylar of comparable or greater thickness. The samples consisted of a colorless polyimide film and a poly(arylene ether benzimidazole) film and thread. The samples were characterized for changes in physical properties, thermal/optical properties (i.e. solar absorptivity and thermal emissivity), surface chemistry (X-ray photoelectron spectroscopy), and surface topography (atomic force microscopy). The data from the polymer samples on MISSE were compared to samples from the same batch of material stored under ambient conditions on Earth. In addition, comparisons were made between the MISSE samples and those subjected to shorter term space flight exposures. The results of these analyses will be presented.

Watson, K. A.↗
DOE OSTI2025

Electrical conductivity of multilayered Cu/Nb composites fabricated by accumulative roll bonding

The electrical conductivity of nanolayered copper/niobium composites fabricated using accumulative roll bonding was investigated as a function of layer thickness. Cu/Nb was used as a model system to evaluate the processing-structure–property relationship stemming from the accumulative roll bonding process. The physical properties were compared against samples of individual average layer heights ranging from 193 to 25 nm. The electrical resistivity was measured over a temperature range of ~3–300 K. Analysis on the role of interfaces on temperature dependence is conducted including the residual resistivity ratio and temperature coefficient of resistivity. It was found that electrical resistivity increases with decreasing layer height.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Elevated ionizing photon production efficiency in faint high-equivalent-width Lyman-α emitters

ABSTRACT While low-luminosity galaxies dominate number counts at all redshifts, their contribution to cosmic reionization is poorly understood due to a lack of knowledge of their physical properties. We isolate a sample of 35 z ≈ 4–5 continuum-faint Lyman-α emitters from deep VLT/MUSE spectroscopy and directly measure their H α emission using stacked Spitzer/IRAC Ch. 1 photometry. Based on Hubble Space Telescope imaging, we determine that the average UV continuum magnitude is fainter than −16 (≈ 0.01 L⋆), implying a median Lyman-α equivalent width of 259 Å. By combining the H α measurement with the UV magnitude, we determine the ionizing photon production efficiency, ξion, a first for such faint galaxies. The measurement of log10 (ξion [Hz erg−1]) = 26.28 ($^{+0.28}_{-0.40}$) is in excess of literature measurements of both continuum- and emission line-selected samples, implying a more efficient production of ionizing photons in these lower luminosity, Lyman-α-selected systems. We conclude that this elevated efficiency can be explained by stellar populations with metallicities between 4 × 10−4 and 0.008, with light-weighted ages less than 3 Myr.

Maseda, Michael V.↗
DOE OSTI2022

KaRMMa – kappa reconstruction for mass mapping

ABSTRACT We present KaRMMa, a novel method for performing mass map reconstruction from weak-lensing surveys. We employ a fully Bayesian approach with a physically motivated lognormal prior to sample from the posterior distribution of convergence maps. We test KaRMMa on a suite of dark matter N-body simulations with simulated DES Y1-like shear observations. We show that KaRMMa outperforms the basic Kaiser–Squires mass map reconstruction in two key ways: (1) our best map point estimate has lower residuals compared to Kaiser–Squires; and (2) unlike the Kaiser–Squires reconstruction, the posterior distribution of KaRMMa maps is nearly unbiased in all summary statistics we considered, namely: one-point and two-point functions, and peak/void counts. In particular, KaRMMa successfully captures the non-Gaussian nature of the distribution of κ values in the simulated maps. We further demonstrate that the KaRMMa posteriors correctly characterize the uncertainty in all summary statistics we considered.

79 ASTRONOMY AND ASTROPHYSICS↗