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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Planck intermediate results: XXXV. Probing the role of the magnetic field in the formation of structure in molecular clouds

Within ten nearby (d < 450 pc) Gould belt molecular clouds we evaluate in this paper statistically the relative orientation between the magnetic field projected on the plane of sky, inferred from the polarized thermal emission of Galactic dust observed by Planck at 353 GHz, and the gas column density structures, quantified by the gradient of the column density, N H . The selected regions, covering several degrees in size, are analysed at an effective angular resolution of 10' FWHM, thus sampling physical scales from 0.4 to 40 pc in the nearest cloud. The column densities in the selected regions range from N H ≈ 10 21 to10 23 cm -2 , and hence they correspond to the bulk of the molecular clouds. The relative orientation is evaluated pixel by pixel and analysed in bins of column density using the novel statistical tool called “histogram of relative orientations”. Throughout this study, we assume that the polarized emission observed by Planck at 353 GHz is representative of the projected morphology of the magnetic field in each region, i.e., we assume a constant dust grain alignment efficiency, independent of the local environment. Within most clouds we find that the relative orientation changes progressively with increasing N H , from mostly parallel or having no preferred orientation to mostly perpendicular. In simulations of magnetohydrodynamic turbulence in molecular clouds this trend in relative orientation is a signature of Alfvénic or sub-Alfvénic turbulence, implying that the magnetic field is significant for the gas dynamics at the scales probed by Planck. Finally, we compare the deduced magnetic field strength with estimates we obtain from other methods and discuss the implications of the Planck observations for the general picture of molecular cloud formation and evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Planck intermediate results: XXXVIII. E - and B -modes of dust polarization from the magnetized filamentary structure of the interstellar medium

The quest for a B-mode imprint from primordial gravity waves on the polarization of the cosmic microwave background (CMB) requires the characterization of foreground polarization from Galactic dust. In this paper, we present a statistical study of the filamentary structure of the 353 GHz Planck Stokes maps at high Galactic latitude, relevant to the study of dust emission as a polarized foreground to the CMB. We filter the intensity and polarization maps to isolate filaments in the range of angular scales where the power asymmetry between E-modes and B-modes is observed. Using the Smoothed Hessian Major Axis Filament Finder (SMAFF), we identify 259 filaments at high Galactic latitude, with lengths larger or equal to 2° (corresponding to 3.5 pc in length for a typical distance of 100 pc). Thesefilaments show a preferred orientation parallel to the magnetic field projected onto the plane of the sky, derived from their polarization angles. We present mean maps of the filaments in Stokes I, Q, U, E, and B, computed by stacking individual images rotated to align the orientations of the filaments. Combining the stacked images and the histogram of relative orientations, we estimate the mean polarization fraction of the filaments to be 11%. Furthermore, we show that the correlation between the filaments and the magnetic field orientations may account for the E and B asymmetry and the C ℓ TE /C ℓ EE ratio, reported in the power spectra analysis of the Planck353 GHz polarization maps. Finally, future models of the dust foreground for CMB polarization studies will need to take into account the observed correlation between the dust polarization and the structure of interstellar matter.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

An Error Analysis Toolkit for Binned Counting Experiments

We introduce the MINERvA Analysis Toolkit (MAT), a utility for centralizing the handling of systematic uncertainties in HEP analyses. The fundamental utilities of the toolkit are the MnvHnD, a powerful histogram container class, and the systematic Universe classes, which provide a modular implementation of the many universe error analysis approach. These products can be used stand-alone or as part of a complete error analysis prescription. They support the propagation of systematic uncertainty through all stages of analysis, and provide flexibility for an arbitrary level of user customization. This extensible solution to error analysis enables the standardization of systematic uncertainty definitions across an experiment and a transparent user interface to lower the barrier to entry for new analyzers.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Conformational sampling enhancement of replica exchange molecular dynamics simulations using swarm particle intelligence

In this paper, we present a new method based on swarm particle social intelligence for use in replica exchange molecular dynamics simulations. In this method, the replicas (representing the different system configurations) are allowed communicating with each other through the individual and social knowledge, in additional to considering them as a collection of real particles interacting through the Newtonian forces. The new method is based on the modification of the equations of motion in such way that the replicas are driven towards the global energy minimum. The method was tested for the Lennard-Jones clusters of N = 4, 5, and 6 atoms. Our results showed that the new method is more efficient than the conventional replica exchange method under the same practical conditions. In particular, the new method performed better on optimizing the distribution of the replicas among the thermostats with time and, in addition, ergodic convergence is observed to be faster. We also introduce a weighted histogram analysis method allowing analyzing the data from simulations by combining data from all of the replicas and rigorously removing the inserted bias.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Morphological, structural and thermal studies of gallium nitride ferrite

We report the synthesis and Characterization of III-V doped Nano ferrite Ga{sub (2x+2)}N Fe{sub 2(49-x)}O{sub 3} for x=1 and x=5 by Sol-Gel method. The Morphological, structural and Thermal characterisation studies are done by using Transmission Electron Microscopy, Energy Dispersive X-ray Analysis, Selected Area Electron Diffraction, Thermo-Gravimetric Analysis and Differential Thermal Analysis. Using the Sci-Finder software we could not trace any reports related to GaNFe{sub 2}O{sub 3} in the literature. It has been observed from our studies that the particles are in the Cylindrical and the Globular structure. The particle diameter values from the Histograms are in good agreement with the XRD values that were communicated by us earlier. The SAED and the EDAX studies reveal the confirmation of the composition and also that the synthesized Ferrite exhibits crystalline nature. The TG-DTA results show that the compound indicates constant sample weight.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

Single-photon emission of InAs/InP quantum dashes at 1.55 μm and temperatures up to 80 K

We report on single photon emission from a self-assembled InAs/InGaAlAs/InP quantum dash emitting at 1.55 μm at the elevated temperatures. The photon auto-correlation histograms of the emission from a charged exciton indicate clear antibunching dips with as-measured g{sup (2)}(0) values significantly below 0.5 recorded at temperatures up to 80 K. It proves that the charged exciton complex in a single quantum dash of the mature InP-based material system can act as a true single photon source up to at least liquid nitrogen temperature. This demonstrates the huge potential of InAs on InP nanostructures as the non-classical light emitters for long-distance fiber-based secure communication technologies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Molecular simulation of CO chemisorption on Co(0001) in presence of supercritical fluid solvent: A potential of mean force study

For several decades, heterogeneous catalytic processes have been improved through utilizing supercritical fluids (SCFs) as solvents. While numerous experimental studies have been established across a range of chemistries, such as oxidation, pyrolysis, amination, and Fischer-Tropsch synthesis, still there is little fundamental, molecular-level information regarding the role of the SCF on elementary heterogeneous catalytic steps. In this study, the influence of hexane solvent on the adsorption of carbon monoxide on Co(0001), as the first step in the reaction mechanism of many processes involving syngas conversion, is probed. Simulations are performed at various bulk hexane densities, ranging from ideal gas conditions (no SCF hexane) to various near- and super-critical hexane densities. For this purpose, both density functional theory and molecular dynamics simulations are employed to determine the adsorption energy and free energy change during CO chemisorption. Potential of mean force calculations, utilizing umbrella sampling and the weighted histogram analysis method, provide the first commentary on SCF solvent effects on the energetic aspects of the chemisorption process. Simulation results indicate an enhanced stability of CO adsorption on the catalyst surface in the presence of supercritical hexane within the reduced pressure range of 1.0–1.5 at a constant temperature of 523 K. Furthermore, it is shown that the maximum stability of CO in the adsorbed state as a function of supercritical hexane density at 523 K nearly coincides with the maximum isothermal compressibility of bulk hexane at this temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Fabrication and characterization of a co-planar detector in diamond for low energy single ion implantation

We demonstrate low energy single ion detection using a co-planar detector fabricated on a diamond substrate and characterized by ion beam induced charge collection. Histograms are taken with low fluence ion pulses illustrating quantized ion detection down to a single ion with a signal-to-noise ratio of approximately 10. We anticipate that this detection technique can serve as a basis to optimize the yield of single color centers in diamond. In conclusion, the ability to count ions into a diamond substrate is expected to reduce the uncertainty in the yield of color center formation by removing Poisson statistics from the implantation process.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

The cluster charge identification in the GEM detector for fusion plasma imaging by soft X-ray diagnostics

The measurement system based on gas electron multiplier detector is developed for soft X-ray diagnostics of tokamak plasmas. The multi-channel setup is designed for estimation of the energy and the position distribution of an X-ray source. The focal measuring issue is the charge cluster identification by its value and position estimation. The fast and accurate mode of the serial data acquisition is applied for the dynamic plasma diagnostics. The charge clusters are counted in the space determined by 2D position, charge value, and time intervals. Radiation source characteristics are presented by histograms for a selected range of position, time intervals, and cluster charge values corresponding to the energy spectra.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Advances in utilizing event based data structures for neutron scattering experiments

This article strives to expand on existing work to demonstrate advancements in data processing made available using event mode measurements. Most spallation neutron sources in the world have data acquisition systems that provide event recording. The new science that is enabled by utilizing event mode has only begun to be explored. In the past, these studies were difficult to perform because histograms forced dealing with either large chunks of time or a large number of files. With event based data collection, data can be explored and rebinned long after the measurement has completed. This article will review some of the principles of event data and how the method opens up new possibilities for in situ measurements, highlighting techniques that can be used to explore changes in the data. We also demonstrate the statistical basis for determining data quality and address the challenge of determining how long to measure mid-measurement. Lastly, we demonstrate a model independent method of grouping data via hierarchical clustering methods that can be used to improve calibration, reduction, and data exploration.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2019

Rate constants in spatially inhomogeneous systems

Here, we introduce a theory and accompanying importance sampling method for computing rate constants in spatially inhomogeneous systems. Using the relationship between rate constants and path space partition functions, we illustrate that the relative change in the rate of a rare event through space is isomorphic to the calculation of a free energy difference, albeit in a trajectory ensemble. Like equilibrium free energies, relative rate constants can be estimated by importance sampling. An extension to transition path sampling is proposed that combines biased path ensembles and weighted histogram analysis to accomplish this estimate. We demonstrate that rate constants can also be decomposed into different contributions, including relative changes in stability, barrier height, and flux. This decomposition provides a means of interpretation and insight into rare processes in complex environments. We confirm these ideas with a simple model of diffusion with spatially varying diffusivity and illustrate their utility in a model of ion pair dissociation near an electrochemical interface.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Studying vapor-liquid transition using a generalized ensemble

Homogeneous vapor-liquid nucleation is studied using the generalized Replica Exchange Method (gREM). The generalized ensemble allows the study of unstable states that cannot directly be studied in the canonical ensemble. Along with replica exchange, this allows for efficient sampling of the multiple states in a single simulation. Statistical Temperature Weighted Histogram Analysis Method is used for postprocessing to get a continuous free energy curve from bulk vapor to bulk liquid. gREM allows the study of planar, cylindrical, and spherical interfaces in a single simulation. The excess Gibbs free energy for the formation of a spherical liquid droplet in vapor for a Lennard-Jones system is calculated from the free energy curve and compared against the umbrella sampling results. The nucleation free energy barrier obtained from gREM is then used to calculate the nucleation rate without relying on any classification scheme for separating the vapor and liquid.

Ballal, Deepti (ORCID:0000000315694749)↗
DOE OSTI2020

Reconstruction and uncertainty quantification of lattice Hamiltonian model parameters from observations of microscopic degrees of freedom

The emergence of scanning probe and electron beam imaging techniques has allowed quantitative studies of atomic structure and minute details of electronic and vibrational structure on the level of individual atomic units. These microscopic descriptors, in turn, can be associated with local symmetry breaking phenomena, representing the stochastic manifestation of the underpinning generative physical model. In this work, we explore the reconstruction of exchange integrals in the Hamiltonian for a lattice model with two competing interactions from observations of microscopic degrees of freedom and establish the uncertainties and reliability of such analysis in a broad parameter-temperature space. In contrast to other approaches, we specifically specify a loss function inherent to thermodynamic systems and utilize it to estimate uncertainty in simulated realizations of different models. As an ancillary task, we develop a machine learning approach based on histogram clustering to predict phase diagrams efficiently using a reduced descriptor space. We further demonstrate that reconstruction is possible well above the phase transition and in the regions of parameter space when the macroscopic ground state of the system is poorly defined due to frustrated interactions. This suggests that this approach can be applied to the traditionally complex problems of condensed matter physics such as ferroelectric relaxors and morphotropic phase boundary systems, spin and cluster glasses, and quantum systems once the local descriptors linked to the relevant physical behaviors are known.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

X-ray multi-probe data acquisition: A novel technique for laser pump x-ray transient absorption spectroscopy

We report the development and implementation of a novel data acquisition (DAQ) technique for synchrotron-based laser pump X-ray Transient Absorption (XTA) spectroscopy, called X-ray Multi-Probe DAQ (XMP DAQ). This technique utilizes high performance analog to digital converters and home-built software to efficiently measure and process the XTA signal from all x-ray pulses between laser excitations. XMP DAQ generates a set of time resolved x-ray absorption spectra at thousands of different pump–probe time delays simultaneously. Two distinct XMP DAQ schemes are deployed to accommodate different synchrotron storage ring filling patterns. Current Integration (CI) DAQ is a quasi-analog technique that implements a fitting procedure to extract the time resolved absorption intensity from the averaged fluorescence detector response. The fitting procedure eliminates issues associated with small drifts in the voltage baseline and greatly enhances the accuracy of the technique. Photon Counting (PC) DAQ is a binary technique that uses a time resolved histogram to calculate the XTA spectrum. While PC DAQ is suited to measure XTA data with closely spaced x-ray pulses (~10 ns) and a low count rate (<1 detected photon/pulse), CI DAQ works best for widely spaced pulses (tens of ns or greater) with a high count rate (>1 detected photon/pulse). XMP DAQ produces a two-dimensional XTA dataset, enabling efficient quantitative analysis of photophysical and photochemical processes from the sub-nanosecond timescale to 100 μs and longer.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Thermonuclear neutron emission from a sheared-flow stabilized Z-pinch

We report the fusion Z-pinch experiment (FuZE) is a sheared-flow stabilized Z-pinch designed to study the effects of flow stabilization on deuterium plasmas with densities and temperatures high enough to drive nuclear fusion reactions. Results from FuZE show high pinch currents and neutron emission durations thousands of times longer than instability growth times. While these results are consistent with thermonuclear neutron emission, energetically resolved neutron measurements are a stronger constraint on the origin of the fusion production. This stems from the strong anisotropy in energy created in beam-target fusion, compared to the relatively isotropic emission in thermonuclear fusion. In dense Z-pinch plasmas, a potential and undesirable cause of beam-target fusion reactions is the presence of fast-growing, “sausage” instabilities. This work introduces a new method for characterizing beam instabilities by recording individual neutron interactions in plastic scintillator detectors positioned at two different angles around the device chamber. Histograms of the pulse-integral spectra from the two locations are compared using detailed Monte Carlo simulations. These models infer the deuteron beam energy based on differences in the measured neutron spectra at the two angles, thereby discriminating beam-target from thermonuclear production. An analysis of neutron emission profiles from FuZE precludes the presence of deuteron beams with energies greater than 4.65 keV with a statistical uncertainty of 4.15 keV and a systematic uncertainty of 0.53 keV. This analysis demonstrates that axial, beam-target fusion reactions are not the dominant source of neutron emission from FuZE. These data are promising for scaling FuZE up to fusion reactor conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Accurate prediction of global-density-dependent range-separation parameters based on machine learning

In this work, we develop an accurate and efficient XGBoost machine learning model for predicting the global-density-dependent range-separation parameter, ωGDD, for long-range corrected functional (LRC)-ωPBE. This ωGDDML model has been built using a wide range of systems (11 466 complexes, ten different elements, and up to 139 heavy atoms) with fingerprints for the local atomic environment and histograms of distances for the long-range atomic correlation for mapping the quantum mechanical range-separation values. The promising performance on the testing set with 7046 complexes shows a mean absolute error of 0.001 117 a0−1 and only five systems (0.07%) with an absolute error larger than 0.01 a0−1, which indicates the good transferability of our ωGDDML model. In addition, the only required input to obtain ωGDDML is the Cartesian coordinates without electronic structure calculations, thereby enabling rapid predictions. LRC-ωPBE(ωGDDML) is used to predict polarizabilities for a series of oligomers, where polarizabilities are sensitive to the asymptotic density decay and are crucial in a variety of applications, including the calculations of dispersion corrections and refractive index, and surpasses the performance of all other popular density functionals except for the non-tuned LRC-ωPBE. Finally, LRC-ωPBE (ωGDDML) combined with (extended) symmetry-adapted perturbation theory is used in calculating noncovalent interactions to further show that the traditional ab initio system-specific tuning procedure can be bypassed. The present study not only provides an accurate and efficient way to determine the range-separation parameter for LRC-ωPBE but also shows the synergistic benefits of fusing the power of physically inspired density functional LRC-ωPBE and the data-driven ωGDDML model.

Chemistry↗
DOE OSTI2024

Data Science Shows that Entropy Correlates with Accelerated Zeolite Crystallization in Monte Carlo Simulations

We have performed a data science study of Monte Carlo simulation trajectories to understand factors that can accelerate formation of zeolite nanoporous crystals, a process that can take days or even weeks. In previous work, Monte Carlo simulations predicted and experiments confirmed that using a secondary organic structure-directing agent (OSDA) accelerates crystallization of all-silica LTA zeolite, with experiments finding a three-fold speedup [PCCP 24, 142-148 (2022)]. However, it remains unclear what physical factors cause the speed-up. Here, we apply data science to analyze the simulation trajectories to discover what drives accelerated zeolite crystallization in Monte Carlo going from a one-OSDA synthesis (1OSDA) to a two-OSDA version (2OSDA). We encoded simulation snapshots using the Smooth Overlap of Atomic Positions approach, which represents all 2- and 3-body correlations within a given cutoff distance. Principal component analyses failed to discriminate datasets of structures from 1OSDA and 2OSDA simulations, while the Support Vector Machine (SVM) approach succeeded at classifying such structures with an area-under-curve (AUC) score of 0.99 (where AUC = 1 is a perfect classification) with all 3-body correlations, and as high as 0.94 with only 2-body correlations. SVM decision functions reveal relatively broad / narrow histograms for 1OSDA / 2OSDA datasets, suggesting that the two simulations differ strongly in information heterogeneity. Informed by these results, we performed pair (2-body) entropy calculations during crystallization, resulting in entropy differences that semi-quantitatively account for the speedup observed in the previous Monte Carlo simulations. We conclude that altering synthesis conditions in ways that substantially changes the entropy of labile silica networks may accelerate zeolite crystallization, and we discuss possible approaches for achieving such acceleration.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Algorithm to extract direction in 2D discrete distributions and a continuous Frobenius norm

In this study, we present a novel algorithm for determining directionality in 2D distributions of discrete data. We compare a reference dataset with a known direction to a measured dataset with an unknown direction by the Frobenius norm of the difference (FND) to find the unknown direction. To generalize this concept, we develop a continuous Frobenius norm of the difference (CFND) as a continuous analog of the FND and derive its analytical expression. By relating fitted and normalized 2D Gaussian distributions, we show that the CFND approximates the FND, and we validate this relationship with computer simulations. We find that a first-order approximation of the CFND between two similar Gaussian distributions takes the form of an absolute sine function, offering a simple analytical form with potential applications in specialized areas such as segmented inverse beta decay neutrino detectors, astronomy, machine learning, and more. Our methodology consists of modeling a 2D Gaussian distribution, binning the data into a histogram, and encoding it as a square matrix. Rotating this matrix around its geometric center and comparing it to a measured dataset using the FND gives us rotational data that we fit with an absolute sine function. The location of the minimum of this fit is the angle closest to the true angle of the direction in the measured dataset. We present the derivation and discuss initial applications of the CFND in our novel algorithm, demonstrating its success in approximating directionality in 2D distributions.

Physics↗