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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The Physical Parameters of Clumps Associated with Class I Methanol Masers

We present a study of the association between class I methanol masers and cold dust clumps from the APEX Telescope Large Area Survey of the Galaxy (ATLASGAL) survey. It was found that almost 100% of class I methanol masers are associated with objects listed in the ATLASGAL compact source catalog. We find a statistically significant difference in the flux density, luminosity, number and column density, and temperature distributions of ATLASGAL sources associated with 95/44 GHz methanol masers compared with those ATLASGAL sources devoid of 95 GHz methanol masers. The masers tend to arise in clumps with higher densities, luminosities, and temperatures compared with both the full sample of ATLASGAL clumps, as well as the sample of ATLASGAL sources that were cross-matched with positions previously searched for methanol masers but with no detections. Comparison between the peak position of ATLASGAL clumps and the interferometric positions of the associated class I and II methanol masers reveals that class I masers are generally located at larger physical distances from the peak submillimeter emission than class II masers. We conclude that the tight association between ATLASGAL sources and class I methanol masers may be used as a link toward understanding the conditions of the pumping of these masers and evolutionary stages at which they appear.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Probability Density Function Control for Stochastic Nonlinear Systems using Monte Carlo Simulation

This paper presents a fast implementation framework of output probability density function (PDF) control for a class of stochastic nonlinear systems which are subjected to non-Gaussian noises. The statistical properties of the system outputs can be adjusted by shaping the dynamic output probability density function to track the reference stochastic distribution. However, the dynamic probability density function evolution is very difficult to obtain analytically even if the system model and the stochastic distributions of the noises are known. Motivated by Monte Carlo simulation, the dynamic probability density function can be estimated by sampling data which forms the contribution of this paper. In particular, the sampling points are generated following the stochastic distribution of the noise for each instant. These points go through the system would generate the histogram for system outputs, then the dynamic model can be established based on the dynamic histogram which reflects the randomness and the nonlinear dynamics of the investigated system. Based on the established model, the output probability density function tracking can be achieved and the simulation results and discussions show the effectiveness and benefits of the presented framework.

Zhang, Qichun↗
DOE OSTI2020

Statistical characteristics of laser interference and its effect on IR optoelectronic observation systems

We consider statistical characteristics of laser interference recorded in the focal region of an IR optoelectronic observation system under field and out-of-field illumination by laser radiation. The applicability of the analytical description of experimental histograms of the laser interference signal distribution at the photodetector array output using the probability density approximations in the form of gamma distribution and the Gaussian function is substantiated. It is shown that the specific form of these functions is determined both by the mean value (mathematical expectation) of the interference signal and by the characteristic parameter M, which depends on the statistical properties of the laser interference. (laser applications and other issues in quantum electronics)

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Determination of the structure of lithium niobosilicate glasses by molecular dynamics simulation with a new Nb-O potential

A partial charge empirical potential for the Nb-O pair has been developed based on existing parameters of other pairs in a Teter potential to enable molecular dynamics simulations of both lithium niobate crystal and lithium niobosilicate glasses. The developed potential is capable of describing structural features of lithium niobosilicate glasses in a wide composition range, including niobium coordination number and bond length, density, bond angle distribution, polyhedral distribution and fraction of bridging oxygen. Furthermore, the results obtained using this new potential show good agreement with experimental data of density and structure from Raman spectroscopy of lithium niobosilicate glasses and X-ray absorption spectroscopy near Nb K-edge.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Chemical vapor infiltration of additively manufactured preforms: Pore-resolved simulations and experimental validation

The densification of additively manufactured porous preforms by chemical vapor infiltration (CVI) is studied using pore-resolved simulations and experiments. Experimentally, 3D printed silicon carbide (SiC) preforms are subject to CVI synthesis using methyltrichlorosilane (MTS) precursor to obtain high purity SiC/SiC composites. Optical images of the cross sections of the processed preforms are analyzed to obtain the spatial porosity distribution. The numerical method is based on a level set formulation to capture the spatial distribution and time evolution of the pore scale microstructural characteristics. The coupled transport and kinetic effects are represented using a dimensionless Thiele modulus. Simulations are initialized using representative synthetic preform geometries comprising of packed particles based on the size distribution of the powder used for 3D printing. The simulation results are validated against the experimental observations in terms of total density and the distribution of residual porosity. The densification characteristics, porosity classification, concentration profiles, and structure functions are analyzed as functions of processing temperature and Thiele modulus.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Thermal conductivity of crack-containing media: A numerical study

The present study aims to evaluate the effective thermal conduction behavior of crack-containing media through micromechanical modeling. Numerical analyses were performed using the finite element method, first using periodic arrays of elliptical pores and then reducing the elliptical minor axis to reach the crack limit. This parametric approach was seen to be able to capture the effect of discontinuity across the crack face in a straightforward manner. The overall thermal conductivity of the model structures, encompassing a range of crack densities and spatial distributions, was investigated. It was found that, for cracks with mixed orientations, the effective thermal conductivity is insensitive to the actual crack alignment and can be uniquely represented by the crack density. The mixed-orientation periodic crack configurations are also representative of random sizes, orientations, and spatial distributions of cracks, thus exhibiting a high degree of generality. The modeling analyses can also be used to determine simple empirical expressions for two- and three-dimensional media containing random cracks.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bayesian Cross-matching of High Proper-motion Stars in Gaia DR2 and Photometric Metallicities for ∼1.7 million K and M Dwarfs

We present a Bayesian method to cross-match 5,827,988 high proper-motion Gaia sources (μ > 40 mas yr{sup −1}) to various photometric surveys: Two Micron All Sky Survey, AllWISE data release from the Wide-field Infrared Explorer (WISE) mission, Galaxy Evolution Explorer, Radial Velocity Experiment, Sloan Digital Sky Survey, and Panoramic Survey Telescope and Rapid Response System (Pan-STARRS). To efficiently associate these objects across catalogs, we develop a technique that compares the multidimensional distribution of all sources in the vicinity of each Gaia star to a reference distribution of random field stars obtained by extracting all sources in a region on the sky displaced 2′. This offset preserves the local field stellar density and magnitude distribution, allowing us to characterize the frequency of chance alignments. The resulting catalog with Bayesian probabilities >95% has a marginally higher match rate than current internal Gaia data release 2 (DR2) matches for most catalogs. However, a significant improvement is found with Pan-STARRS, where ∼99.8% of the sample within the Pan-STARRS footprint is recovered, as compared to a low ∼20.8% in Gaia DR2. Using these results, we train a Gaussian process regressor to calibrate two photometric metallicity relationships. For dwarfs of 3500 < T{sub eff} < 5280 K, we use metallicity values of 4378 stars from the Apache Point Observatory Galactic Evolution Experiment and Hejazi et al. to calibrate the relationship, producing results with a 1σ precision of 0.12 dex and few systematic errors. We then indirectly infer the metallicity of 4018 stars with 2850 < T{sub eff} < 3500 K, which are wide companions of primaries whose metallicities are estimated with our first regressor, to produce a relationship with a 1σ precision of 0.21 dex and significant systematic errors. Additional work is needed to better remove unresolved binaries from this second sample to reduce these systematic errors.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Direct Characterization of Atomically Dispersed Catalysts: Nitrogen-Coordinated Ni Sites in Carbon-Based Materials for CO 2 Electroreduction

Metal, nitrogen-doped carbon materials have attracted interest as heterogenous catalysts that contain MN x active sites that are analogous to molecular catalysts. Of particular interest is Ni,N-doped carbon, a catalyst that is active for the electrochemical reduction of CO 2 to CO. Critical to the understanding of these materials is proof of single atomic sites and characterization of the environment surrounding the metal atom; however, directly probing this coordination remains challenging. This challenge is addressed in this study by combining scanning transmission electron microscopy (STEM), single atom electron energy loss spectroscopy (EELS), and time-of-flight secondary ion mass spectrometry (ToF-SIMS). Through STEM imaging, atomic dispersion of Ni in the carbon framework is confirmed and image analyses are utilized to give semiquantitative estimates of neighbor distance distributions and site densities of Ni atoms. Atomic resolution EELS demonstrates that N and Ni are colocated at the single Ni atom sites suggesting Ni–N coordination. ToF-SIMS reveals a distribution of NiN x C y - fragments that reflect the Ni–N bonding environments within Ni,N-doped carbon. The fragmentation from Ni,N-doped carbon is similar to Ni phthalocyanine, suggesting the existence of heterogenized, molecular-like NiN 4 active sites which motivates future studies that leverage insight from molecular catalysis design to develop next-generation heterogeneous catalysts.

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

Perovskite-driven solar C 2 hydrocarbon synthesis from CO 2

Photoelectrochemistry (PEC) presents a direct pathway to solar fuel synthesis by integrating light absorption and catalysis into compact electrodes. Yet, PEC hydrocarbon production remains elusive due to high catalytic overpotentials and insufficient semiconductor photovoltage. Here we demonstrate ethane and ethylene synthesis by interfacing lead halide perovskite photoabsorbers with suitable copper nanoflower electrocatalysts. The resulting perovskite photocathodes attain a 9.8% Faradaic yield towards C 2 hydrocarbon production at 0 V against the reversible hydrogen electrode. The catalyst and perovskite geometric surface areas strongly influence C 2 photocathode selectivity, which indicates a role of local current density in product distribution. The thermodynamic limitations of water oxidation are overcome by coupling the photocathodes to Si nanowire photoanodes for glycerol oxidation. These unassisted perovskite–silicon PEC devices attain partial C 2 hydrocarbon photocurrent densities of 155 µA cm -2 , 200-fold higher than conventional perovskite–BiVO 4 artificial leaves for water and CO 2 splitting. These insights establish perovskite semiconductors as a versatile platform towards PEC multicarbon synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Flow Channeling in Fracture Networks: Characterizing the Effect of Density on Preferential Flow Path Formation

Flow channelization is a commonly observed phenomenon in fractured subsurface media where the flow of fluids is restricted primarily to highly transmissive fracture networks surrounded by a low-permeability rock matrix. The multiscale structural heterogeneity of these networks results in multiscale flow channelization where preferential flow paths form at length scales ranging from the entire system down to the subfracture size. We present an analysis of how one of the largest scales in fractured media, the network density, influences the degree of flow channeling that occurs using an ensemble of semigeneric three-dimensional discrete fracture network (DFN) simulations. We construct 10 DFNs, whose fracture lengths follow a power law distribution, at four densities for a total of 40 networks. We characterize their structure in terms of the network topology and geometry. Eulerian and Lagrangian observations of the steady-state flow fields obtained within the networks are used to quantify the degree of flow channelization at the network scale. We introduce a measure for the importance-ranking/hierarchy of different flow paths in the network using graph-based analysis of Lagrangian transport by which the degree of flow channeling between networks is compared. These flow observations are then linked to the structural properties of the networks. In general, network-scale flow channeling decreases as the network density increases. However, at low densities, there is more uniform flow within the entire connected network than in high-density networks. We also demonstrate how standard transport observables can be used to infer the degree of flow channelization occurring within a fracture network.

58 GEOSCIENCES↗
DOE OSTI2021

Depth-resolved cathodoluminescence and surface photovoltage spectroscopies of gallium vacancies in β-Ga 2 O 3 with neutron irradiation and forming gas anneals

The gallium vacancy is one of the dominant native point defects in β-Ga 2 O 3 , one that, together with its complexes, can have a major effect on free carrier densities and transport in this wide bandgap semiconductor. We used a combination of depth-resolved cathodoluminescence spectroscopy and surface photovoltage spectroscopy to identify the optical and energy-level properties of these defects as well as how their defect densities and spatial distributions vary with neutron irradiation and temperature-dependent-forming gas anneals. These studies reveal optical signatures that align closely with theoretical energy-level predictions. Likewise, our optical techniques reveal variations in these defect densities that are consistent with hydrogen passivation of gallium vacancies as a function of temperature and depth from the free Ga 2 O 3 surface. These techniques can help guide the understanding and control of dominant native point defects in Ga 2 O 3 .

42 ENGINEERING↗
DOE OSTI2021

Light transport with weak angular dependence in fog

Random scattering and absorption of light by tiny particles in aerosols, like fog, reduce situational awareness and cause unacceptable down-time for critical systems or operations. Computationally efficient light transport models are desired for computational imaging to improve remote sensing capabilities in degraded optical environments. To this end, we have developed a model based on a weak angular dependence approximation to the Boltzmann or radiative transfer equation that appears to be applicable in both the moderate and highly scattering regimes, thereby covering the applicability domain of both the small angle and diffusion approximations. An analytic solution was derived and validated using experimental data acquired at the Sandia National Laboratory Fog Chamber facility. The evolution of the fog particle density and size distribution were measured and used to determine macroscopic absorption and scattering properties using Mie theory. A three-band (0.532, 1.55, and 9.68 µ m) transmissometer with lock-in amplifiers enabled changes in fog density of over an order of magnitude to be measured due to the increased transmission at higher wavelengths, covering both the moderate and highly scattering regimes. The meteorological optical range parameter is shown to be about 0.6 times the transport mean free path length, suggesting an improved physical interpretation of this parameter.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Investigation of radiated-power for low aspect ratio fusion plasmas

Investigating radiated power in fusion plasmas is of utmost importance to understand the effect of undesired impurities, such as metals, in present devices, or also desired impurities, such as noble gasses, to purposefully radiate a large fraction of power in future devices. These studies are especially important for high Z impurities which will play a crucial role in future generation fusion pilot plants. In this work, we have developed a power radiation analysis module, which is used to investigate 2D distributions of impurity densities and radiated power asymmetries caused due to both plasma rotation and the cooling rate dependence on temperature profile for the cases of experimental NSTX plasmas and designed scenarios for the spherical tokamak advanced reactor (STAR), both being low aspect ratio tokamaks. Two different atomic databases have been tested during this work to study their impact on the radiated power distribution, especially for high Z impurities. Also in PRAM, self-consistent calculations of two-dimensional electron, main ion, and impurity ion densities are carried out using one-dimensional input density, temperature, and rotation profiles. In the case of NSTX, discharges with high rotation of ∼ 170 km s, measured with charge exchange recombination spectroscopy, have been investigated. Rotation-induced charge separation, leading to an electrostatic potential, is calculated iteratively to a self-consistent solution while testing high Z impurities to observe any 2D asymmetry in the core radiated power due to centrifugal forces. The STAR design, being much larger (R = 4 m), is projected to have a much lower rotation, and is shown to have low rotation-induced asymmetries, on the order of ten percent or less, between the low field and high field sides. However, another effect not due to rotation but to the dependence of impurity cooling rates on temperature can lead to radiation peaking off-axis, near the plasma edge. This effect is noticeable for argon in NSTX, for example, but can also be enhanced for certain impurities at much higher temperatures projected for STAR (T e0 ~ 32 keV), for example for undesired tungsten or possibly desired xenon.

NSTX↗
DOE OSTI2023

The hidden structure of hydrodynamic transport in random fracture networks

We study the large-scale dynamics and prediction of hydrodynamic transport in random fracture networks. The flow and transport behaviour is characterized by first passage times and displacement statistics, which show heavy tails and anomalous dispersion with a strong dependence on the injection condition. The origin of these behaviours is investigated in terms of Lagrangian velocities sampled equidistantly along particle trajectories, unlike classical sampling strategies at a constant rate. The velocity series are analysed by their copula density, the joint distribution of the velocity unit scores, which reveals a simple, albeit hidden, correlation structure that can be described by a Gaussian copula. Based on this insight, we derive a Langevin equation for the evolution of equidistant particle speeds. In this framework, particle motion is quantified by a stochastic time-domain random walk, the joint density of particle position, and speed satisfies a Klein–Kramers equation. The upscaled theory quantifies particle motion in terms of the characteristic fracture length scale and the distribution of Eulerian flow velocities. That is, it is predictive in the sense that it does not require the a priori knowledge of transport attributes. The upscaled model captures non-Fickian transport features, and their dependence on the injection conditions in terms of the velocity point statistics and average fracture length. It shows that the first passage times and displacement moments are dominated by extremes occurring at the first step. The presented approach integrates the interaction of flow and structure into a predictive model for large-scale transport in random fracture networks.

42 ENGINEERING↗
DOE OSTI2021

Application of the locally self-consistent embedding approach to the Anderson model with non-uniform random distributions

Highlights: • Typical Medium Theory (TMT) for the Anderson Localization. • Locally Self-Consistent Multiple Scattering Method (LSMS) for Random Disordered Systems. • Linear Scaling Computational Method for Random Disordered Systems. We apply the recently developed embedding scheme for the locally self-consistent method to random disorder electrons systems. The method is based on the locally self-consistent multiple scattering theory and the typical medium theory. The locally self-consistent multiple scattering theory divides a system into many small designated local interaction zones. The subsystem within each local interaction zone is embedded in a self-consistent field from the typical medium theory. This approximation allows the study of random systems with large numbers of sites. We present results for the three dimensional Anderson model with different random disorder potential distributions. Using the typical density of states as an indicator of Anderson localization, we find that the method can capture the localization for commonly studied disorder potentials. These include the uniform distribution, the Gaussian distribution, and even the unbounded Cauchy distribution.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

The driving mode of shock-driven turbulence

Turbulence in the interstellar medium (ISM) is crucial in the process of star formation. Shocks produced by supernova explosions, jets, radiation from massive stars, or galactic spiral-arm dynamics are amongst the most common drivers of turbulence in the ISM. However, it is not fully understood how shocks drive turbulence, in particular whether shock driving is a more solenoidal (rotational, divergence-free) or a more compressive (potential, curl-free) mode of driving turbulence. The mode of turbulence driving has profound consequences for star formation, with compressive driving producing three times larger density dispersion, and an order of magnitude higher star formation rate than solenoidal driving. Here, we use hydrodynamical simulations of a shock inducing turbulent motions in a structured, multiphase medium. This is done in the context of a laser-induced shock, propagating into a foam material, in preparation for an experiment to be performed at the National Ignition Facility (NIF). Specifically, we analyse the density and velocity distributions in the shocked turbulent medium, and measure the turbulence driving parameter $b=(\sigma _{\rho /\langle \rho \rangle }^{2\Gamma }-1)^{1/2}(1-\sigma _{\rho /\langle \rho \rangle }^{-2})^{-1/2}\mathcal {M}^{-1}\Gamma ^{-1/2}$, with the density dispersion σρ/<ρ>, the turbulent Mach number $\mathcal {M}$, and the polytropic exponent Γ. Purely solenoidal and purely compressive driving correspond to b ~ 1/3 and b ~ 1, respectively. As a result, using simulations in which a shock is driven into a multiphase medium with structures of different sizes and Γ < 1, we find b ~ 1 for all cases, showing that shock-driven turbulence is consistent with strongly compressive driving.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Classification of Intensity Distributions of Transmission Eigenchannels of Disordered Nanophotonic Structures Using Machine Learning

Light-matter interaction optimization in complex nanophotonic structures is a critical step towards the tailored performance of photonic devices. The increasing complexity of such systems requires new optimization strategies beyond intuitive methods. For example, in disordered photonic structures, the spatial distribution of energy densities has large random fluctuations due to the interference of multiply scattered electromagnetic waves, even though the statistically averaged spatial profiles of the transmission eigenchannels are universal. Classification of these eigenchannels for a single configuration based on visualization of intensity distributions is difficult. However, successful classification could provide vital information about disordered nanophotonic structures. Emerging methods in machine learning have enabled new investigations into optimized photonic structures. In this work, we combine intensity distributions of the transmission eigenchannels and the transmitted speckle-like intensity patterns to classify the eigenchannels of a single configuration of disordered photonic structures using machine learning techniques. Specifically, we leverage supervised learning methods, such as decision trees and fully connected neural networks, to achieve classification of these transmission eigenchannels based on their intensity distributions with an accuracy greater than 99%, even with a dataset including photonic devices of various disorder strengths. Simultaneous classification of the transmission eigenchannels and the relative disorder strength of the nanophotonic structure is also possible. Our results open new directions for machine learning assisted speckle-based metrology and demonstrate a novel approach to classifying nanophotonic structures based on their electromagnetic field distributions. These insights can be of paramount importance for optimizing light-matter interactions at the nanoscale.

79 ASTRONOMY AND ASTROPHYSICS↗