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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

High-temperature active oxidation of nanocrystalline silicon-carbide: A reactive force-field molecular dynamics study

Flexible woven SiC ceramics are prone to accelerated fiber embrittlement under high temperature oxidation in dynamic oxygen environments. The nanocrystalline structure of the constituent fibers impacts the reaction kinetics and phase transformations during active oxidation. However, fundamental understanding and quantification of grain boundary effects on oxidation behavior in nanocrystalline SiC remain elusive when temperatures exceed 1500 K. This study deploys large-scale molecular dynamics simulations with a reactive force-field to elucidate the complex roles of atomic oxygen reservoir conditions and grain size on oxidation kinetics and the nature of oxides produced in both monocrystalline and nanocrystalline 3C-SiC between 1100 K and 2000 K. The simulations with dynamically replenished oxygen provide good agreement with oxidation kinetics and activation energies for the monocrystalline Si(100) and C(100) orientations published in the available literature. This study reveals that, by contrast, nanocrystalline SiC samples exhibit two distinct oxidation kinetics with a transition point at 1500 K due to surface melting, which is supported by experimental evidence. The introduction of a grain-boundary network produces a two-fold decrease in oxidation activation energies compared to monocrystalline SiC below 1500 K. Above 1500 K, however, the activation energies rise substantially due to the formation of a liquid Si phase at the SiC/Si oxide interface. Further, it is shown that the stability of the interfacial liquid phase is promoted by incoherent grain boundaries in the crystalline SiC. These findings are important for the deployment of nanocrystalline SiC fibers in advanced thermal protection systems for high-temperature applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dielectrics Under Extreme Electric Fields: In Situ Studies on Nanoscale Mechanisms (Final Technical Report)

The lack of materials that can function reliably under extreme electric fields is a critical roadblock to achieving higher energy efficiency and extended service lifetime of devices in electricity generation, transmission, and consumption. Materials typically fail at two or three orders of magnitude below their theoretical dielectric breakdown strength. Identifying the origins of premature dielectric breakdown using state-of-the-art characterization tools will, therefore, enable the design and discovery of transformational materials capable of approaching their intrinsic limits. The vast improvement in the resolution power of imaging tools, combined with the recently developed in situ electric biasing technique, has made high resolution observations of dielectric breakdown as it happens possible. The overall goal of the project is to directly image the dynamic processes of defect formation, accumulation, and interaction with preexisting defects (e.g., dislocations, domain walls, and grain boundaries in crystalline dielectric films) under electric fields up to 1,000 MV/m with a temporal resolution better than 5 microseconds. Using the newly acquired, custom-made Hysitron PI95 transmission electron microscopy (TEM) specimen holder, in situ TEM observations of breakdown at the sub nanometer resolution will be made on representative dielectric compounds with progressive complexities: the linear dielectric SiO 2 , CuO, and TiO 2 , the ferroelectric BaTiO 3 nanocrystals and nanocubes. Through direct observation of the breakdown event at high spatial and temporal resolutions, the nanoscale mechanisms for the failure of dielectrics under intense electric fields will be identified. The results of the project will be applied to the design and processing of new dielectric materials with higher efficiency, improved reliability, and a prolonged lifetime. Such new dielectrics are urgently needed for modernizing energy infrastructures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1974

The impact of space electric field research on atmospheric studies

Space measurements of electric fields have provided instrumentation for measuring atmospheric parameters and a better basis for understanding the electrical coupling between the magnetosphere and the atmosphere. Applications of an incoherent scatter radar (developed for ionospheric electric field research) to the measurement of atmospheric winds and turbulence and of Langmuir double probes (also developed for space research) for measurement of atmospheric electric fields are described. The increased knowledge of magnetospheric electric fields has focused attention on the electrical coupling between the magnetosphere and the atmosphere with conclusions that should considerably modify previous physical concepts in both domains.

Mozer, F. S.↗
DOE OSTI2024

Study of Magnetic Field and Turbulence in the TeV Halo around the Monogem Pulsar

Magnetic fields are ubiquitous in the interstellar medium, including extended objects such as supernova remnants and diffuse halos around pulsars. Its turbulent characteristics govern the diffusion of cosmic rays and the multiwavelength emission from pulsar wind nebulae (PWNe). However, the geometry and turbulence nature of the magnetic fields in the ambient region of PWN is still unknown. Recent gamma-ray observations from HAWC and synchrotron observations suggest a highly suppressed diffusion coefficient compared to the mean interstellar value. In this study, we present the first direct observational evidence of the orientation of the mean magnetic field and turbulent characteristics by employing a recently developed statistical parameter "Y turb " in the extended halo around the Monogem pulsar. Our study points to two possible scenarios: nearly aligned toward the line of sight (LOS) with compressible modes dominance or high inclination angle toward the LOS and characterized by Alfvénic turbulence. The first scenario appears consistent with other observational signatures. Furthermore, we report that the magnetic field has an observed correlation length of approximately 3 ± 0.6 pc in the Monogem halo. Our study highlights the pivotal role of magnetic field and turbulence in unraveling the physical processes in TeV halos and cosmic-ray transport.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1996

Studies of Westward Electrojets and Field-Aligned Currents in the Magnetotail during Substorms: Implications for Magnetic Field Models

Our studies elucidated the relationship between the auroral arcs and magnetotail phenomena. One paper examined particle energization in the source region of the field-aligned currents that intensify at substorm onset when the arc brightens to form the westward electrojet. A second paper examined the relationship between the precipitating particles in the arcs, the location of the westward electrojet, and magnetospheric source regions. Two earlier papers also investigated the roles that field aligned currents and particle acceleration have during substorms.

Source record↗
NASA NTRS2002

Satellite Studies of Ionospheric Electric Fields and Neutral Winds

We have studied mid- and low-latitude electrodynamic and neutral thermospheric dynamic processes using measurements on board the AE-E, DE-2, and UARS (Upper Atmosphere Research Satellite) satellites, and global convection and general circulation models. These studies have determined the morphology of the equatorial zonal electric fields, the response of equatorial plasma irregularities to magnetospheric disturbances, and the time dependent response of the mid- and low latitude electric fields to magnetospheric disturbances. We have also used extensive F region zonal and meridional wind data obtained by Wind Imaging Interferometer (WINDII) instrument on board the UARS to study the latitudinal dependence of daytime disturbance winds during magnetically disturbed periods and the general characteristics of the global thermospheric disturbance wind system during geomagnetically active periods. This project has supported the PhD thesis research of John Emmert.

Fejer, Bela G.↗
NASA NTRS1990

The 27-28 October 1986 FIRE IFO cirrus case study - Cloud parameter fields derived from satellite data

A cirrus parameter retrieval methodology and the results of its application over the cirrus Intensive Field Observation (IFO) area using data from the Geostationary Operational Environmental Satellite (GOES) taken during the FIRE cirrus case study days, October 27-28, 1986. An impirical cloud bidirectional reflectance model derived from another IFO analysis was combined with a theoretical ice crystal cloud albedo model to estimate visible cloud optical thickness, which was used to derive the cloud infrared emittance. Cloud altitude was adjusted based on the derived emittance and observed temperatures. The approach developed here produced a very reasonable picture of cirrus cloud fields. It was estimated that the cloud-top and cloud-center heights are derived with a precision of about 0.6 km, except in very broken cloud conditions. Cirrus cloud thicknesses were also estimated and it is found that the derived results are comparable to other case study observations.

Minnis, Patrick↗
DOE OSTI2021

Inferring pesticide toxicity to honey bees from a field‐based feeding study using a colony model and Bayesian inference

Abstract Honey bees are crucial pollinators for agricultural crops but are threatened by a multitude of stressors including exposure to pesticides. Linking our understanding of how pesticides affect individual bees to colony‐level responses is challenging because colonies show emergent properties based on complex internal processes and interactions among individual bees. Agent‐based models that simulate honey bee colony dynamics may be a tool for scaling between individual and colony effects of a pesticide. The U.S. Environmental Protection Agency (USEPA) and U.S. Department of Agriculture (USDA) are developing the VarroaPop + Pesticide model, which simulates the dynamics of honey bee colonies and how they respond to multiple stressors, including weather, Varroa mites, and pesticides. To evaluate this model, we used Approximate Bayesian Computation to fit field data from an empirical study where honey bee colonies were fed the insecticide clothianidin. This allowed us to reproduce colony feeding study data by simulating colony demography and mortality from ingestion of contaminated food. We found that VarroaPop + Pesticide was able to fit general trends in colony population size and structure and reproduce colony declines from increasing clothianidin exposure. The model underestimated adverse effects at low exposure (36 µg/kg), however, and overestimated recovery at the highest exposure level (140 µg/kg), for the adult and pupa endpoints, suggesting that mechanisms besides oral toxicity‐induced mortality may have played a role in colony declines. The VarroaPop + Pesticide model estimates an adult oral LD 50 of 18.9 ng/bee (95% CI 10.1–32.6) based on the simulated feeding study data, which falls just above the 95% confidence intervals of values observed in laboratory toxicology studies on individual bees. Overall, our results demonstrate a novel method for analyzing colony‐level data on pesticide effects on bees and making inferences on pesticide toxicity to individual bees.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

On-the-fly machine learned force fields for the study of warm dense matter: Application to diffusion and viscosity of CH

We develop a framework for on-the-fly machine learned force field (MLFF) molecular dynamics (MD) simulations of warm dense matter (WDM). In particular, we employ an MLFF scheme based on the kernel method and Bayesian linear regression, with the training data generated from the Kohn–Sham density functional theory (DFT) using the Gauss spectral quadrature method, within which we calculate energies, atomic forces, and stresses. We verify the accuracy of the formalism by comparing the predicted properties of warm dense carbon with recent Kohn–Sham DFT results in the literature. In so doing, we demonstrate that ab initio MD simulations of WDM can be accelerated by up to three orders of magnitude, while retaining ab initio accuracy. We apply this framework to calculate the diffusion coefficients and shear viscosity of CH at a density of 1 g/cm3 and temperatures in the range of 75 000–750 000 K. We find that the self- and inter-diffusion coefficients and the viscosity obey a power law with temperature, and that the diffusion coefficient results suggest a weak coupling between C and H in CH. In addition, we find agreement within standard deviation with previous results for C and CH but disagreement for H, demonstrating the need for ab initio calculations as presented here.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1965

Studies in the fields of space flight and guidance theory progress report no. 7, 23 jul. 1964 - 1 apr. 1965

The progress reports of NASA-sponsored studies in the areas of space flight and guidance theory are presented. The studies are carried on by several universities and industrial companies. This progress report covers the period from July 23, 1964 to April 1, 1965. The contracts are technically supervised by personnel of the Astrodynamics and Guidance Theory Division, Aero-Astrodynamics Laboratory, Marshall Space Flight Center.

NASA Program↗
NASA NTRS1980

Study of intermittent field hardware failure data in digital electronics

The collection and analysis of data concerning intermittent dailures in digital devices was performed using data from a computer design for shipboard usage. The failure data consisted of actual field failures classified by failure mechanisms and their likelihood of having been intermittent, potentially intermittent, or hard. Each class was studies with respect to computer operation in the ranges of 0 to 2,000 hours, 0 to 5, hours, and 0 to 10,000 hours. The study was done at the computer level as well as the microcircuit level. Results indicate that as age increases, the quasi-intermittent failure rate increases and the mean time to failure descreases.

Oneill, E. J.↗
NASA NTRSDate not supplied

A Field Campaign to Study Lightning that Ignites the Bush

The impact of recent wildland fires in the United States and Australia have received much attention in the past several years. As a result, NASA has developed a new Earth Science program to better understand, predict, and manage this phenomenon, as well as a future suborbital mission to studying pyro-cumulonimbus clouds and their effects on the Earth system. In Australia, government and philanthropic stakeholders are supporting a series of field campaigns over the next few years to inform science requirements and advance technology for a future satellite mission to monitor Bushfires. Lightning flashes are a major source of wildland fires, but uncertainties remain about the physical characteristics of lightning and their parent thunderstorms responsible for igniting wildfires. It was long believed that most lightning-ignited wildfires are largely caused by positive flashes to the ground (CGs) and multi-stroke CGs, but a recent study looking at 26-years of NLDN data indicate otherwise. Perhaps this finding is due to statistical chance—there are more negative CGs that occur globally—or perhaps there is some unknown electrical property of the thundercloud from which the igniting flashes emanate. Regardless, new observing strategies are needed. Additionally, long continuing current CGs, which are more likely to ignite a fire, can elude detection by operational ground-based lightning location systems, making it difficult to efficiently identify potential wildland fires and manage them before they have adverse impacts. To address these science and operational gaps, NASA’s Lightning Mapping Array along with electric and magnetic field change meters will be deployed for the Australian Bushfire campaign to document the electrical structure and properties of thunderstorms and lightning that occur in a wildland fire susceptible region. Another aspect of the campaign will be the use of NASA’s airborne lightning observatory, which includes a spectrometer and high-speed imager, to document the radiometric attributes of these flashes coincident with the ground-based RF observations. These observations will be used to better understand the properties of lightning that ignite wildland fires as well as inform design of a lightning detection system for the future Bushfire Monitoring satellite mission.

lightning↗
DOE OSTI2020

Development of neural network force fields for corrosion studies

To fully understand the chemistry and physics of corrosion, novel methods of simulation must be developed. One approach is designing machine learning (ML) algorithms integrated with density functional theory to develop adaptive force fields to gain insight into corrosion behavior namely at the surface of metal oxides. Current methods of modeling corrosion are slow due to the computational cost of resolving both reaction mechanics and mass transport processes. Machine learning methods can be implemented to obtain structure-activity relationships at both the molecular and bulk scale while still retaining the accuracy of density functional theory (DFT) and significantly decreasing the time needed for simulations of complex chemical processes in the various environments of corrosion. Multiscale models are needed for corrosion studies to fully understand its processes not only at the atomic length scale (chemical bonding, energies, and forces), but also at the nano and meso length scales (solid-state physics and material science processes). Current methods of study include DFT, molecular dynamics, and Monte Carlo. The limitation of DFT is that only a small number of atoms or molecules can be simulated at that level of theory. Density functional theory is used to study the electronic structure of atoms and molecules, and calculate the force component of each atom. However, these calculations are limited to about 1000 atoms. Custom periodic boundary conditions (PBC) can be used to describe the various environments and defects that affect the atomic forces to produce a large data set from which a training set can be derived. Machine learning can be utilized to overcome the barrier of modeling macroscopic and multi-scale processes from ab initio calculations through the development of adaptive force fields. Local environments determine the atomic forces of a given system, therefore adaptive force fields must be created to produce reliable quantum mechanical calculations. This can be achieved by developing a learning algorithm that uses the mapped atomic forces or fingerprint as an input to produce energies and magnetic moments as output. A systematic approach was used to begin to build a data set in order to accurately describe the atomic forces in various environments. In Figure 4 below, a simple PBC cell of Fe{sub 2}O{sub 3} was first optimized. A surface optimization was performed next, followed by a hydroxylated surface optimization. Once this calculation has converged, the adsorption of halide species to the hydroxylated surface will be investigated. TensorFlow is an open source platform for machine learning developed by Google. Using a high level application program interface (API) such as Keras allows for building and training ML models easily in a number of different environments and languages. For this project, a neural network was developed within Anaconda in Python. Future Work: Further development of reference data set; Refining neural network and learning algorithm; Fingerprinting atomic environment to enable mapping of atomic force components; Choosing appropriate training set from reference data; Learning from training set and enabling non-linear mapping of training set fingerprints and the atomic forces; Estimation of uncertainty to identify ranges of outside applicability; Testing and analysis of molecular dynamic simulations.

36 MATERIALS SCIENCE↗