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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Evolution of magnetic interactions in Sb-substituted MnBi 2 Te 4

The Mn(Bi 1–x Sb x ) 2 Te 4 series is purported to span from an antiferromagnetic (AF) topological insulator at x = 0 to a trivial AF insulator at x = 1. Here we report on neutron diffraction and inelastic neutron scattering studies of the magnetic interactions across this series. All compounds measured possess ferromagnetic (FM) triangular layers and we find a crossover from AF to FM interlayer coupling near x = 1 for our samples. The large spin gap at x = 0 closes rapidly and the average FM exchange interactions within the triangular layer increase with Sb substitution. Similar to a previous study of MnBi 2 Te 4 , we find severe spectral broadening which increases dramatically across the compositional series. In addition to broadening, we observe an additional sharp magnetic excitation in MnSb 2 Te 4 that may indicate the development of local magnetic modes originating from antisite disorder between Mn and Sb sublattices. Here, the results suggest that both substitutional and antisite disorder contribute substantially to the magnetism in Mn(Bi 1–x Sb x ) 2 Te 4 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1989

Data structure characterization of miltispectral data using principal component and principal factor analysis

Both principal component analysis (PCA) and principal factor analysis (PFA) were used to analyze an experimental multispectral data structure in terms of common and unique variance. Only the common variance of the multispectral data was associated with the principal factor, while higher-order principal components were associated with both common and unique variance. The unique variance was found to represent small spectral variations within each cover type as well as noise vectors, and was most abundant in the lower-order principal components. The lower-order principal components can be useful in research designed to discriminate minor physical variations within features, and to highlight localized change when using multitemporal-multispectral data. Conversely, PFA of the multispectral data provided an insight into a great potential for discriminating basic land-cover types by excluding the unique variance which was related to the noise and minor spectral variations.

Lee, Jae K.↗
NASA NTRS2006

Self-Consistent Model of Magnetospheric Ring Current and Propagating Electromagnetic Ion Cyclotron Waves: Waves, Precipitating Ring Current Ions, and Thermal Electron Heating - 2

This paper is dedicated to further presentations and discussions of the results from our new global self-consistent theoretical model of interacting ring current ions and electromagnetic ion cyclotron waves [Khazanov et al., 2006; here referred to as Paper 1]. In order to adequately take into account the wave propagation and refraction in a multi-ion plasmasphere, we explicitly include the ray tracing equations in our previous self-consistent model and use the general form of the wave kinetic equation [for details see Paper 1]. To demonstrate the effects of the EMIC wave propagation and refraction on the RC proton precipitations and heating of the thermal plasmaspheric electrons we simulate the May 1998 storm. The main findings of our simulation can be summarized as follows. Firstly, the wave induced precipitations have a quite fine structure, and are highly organized by location of the plasmapause gradient. The strongest fluxes of about 4 (raised dot) 10(exp 6) [(cm (raised dot) s (raised dot) sr)(sup -l)] are observed during the main and early recovery phases of the storm. The very interesting and probably more important finding is that in a number of cases the most intense precipitating fluxes are not simply connected to the most intense EMIC waves. The character of the EMIC wave power spectral density distribution over the equatorial wave normal angle is an extremely crucial for the effectiveness of the RC ion scattering. Secondly, comparison of the global proton precipitating patterns with the results from other ring current model [Kozyra et al., 1997] reveals that although we observe a qualitative agreement between localizations of the wave induced fluxes in the models, there is no quantitative agreement between the magnitudes of these fluxes. These differences are mainly due to a qualitative difference between the characters of the EMIC wave power spectral density distributions over the equatorial wave normal angle. Finally, the two energy sources to the plasmaspheric electrons are considered; (i) the heat fluxes caused by the EMIC wave energy absorption due to Landau resonance, and (ii) the heat fluxes due to Coulomb energy degradation of the RC o(+) ions. The heat fluxes caused by the EMIC wave energy absorption due to Landau resonance are observed in the postnoon-premidnight MLT sector, and maximize at the magnitude of 10l1 (eV/(cm(sup 2)(raised dot) s) at L=3.25, MLT=22 at 3400 UT after 1 May, 0000 UT. The greatest Coulomb energy deposition rates are about 2 (raised dot) 10(sup 10)(eV/(cm(sup 2)(raised dot) s) and observed during two periods; 32-48 hours, and 76-86 hours after 1 May, 0000 UT. The theoretically derived spatial structure of the thermal electron heating caused by interaction of the RC with plasmasphere is strongly supported by concurrent and conjugate plasma measurements from the plasmasphere, the RC, and the topside ionosphere [Gurgiolo et al., 20051.

Khazanov, G. V.↗
NASA NTRS2007

Airborne High Spectral Resolution Lidar Aerosol Measurements during MILAGRO and TEXAQS/GOMACCS

Two1 field experiments conducted during 2006 provided opportunities to investigate the variability of aerosol properties near cities and the impacts of these aerosols on air quality and radiative transfer. The Megacity Initiative: Local and Global Research Observations (MILAGRO) /Megacity Aerosol Experiment in Mexico City (MAX-MEX)/Intercontinental Chemical Transport Experiment-B (INTEX-B) joint experiment conducted during March 2006 investigated the evolution and transport of pollution from Mexico City. The Texas Air Quality Study (TEXAQS)/Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS) (http://www.al.noaa.gov/2006/) conducted during August and September 2006 investigated climate and air quality in the Houston/Gulf of Mexico region. During both missions, the new NASA Langley airborne High Spectral Resolution Lidar (HSRL) was deployed on the NASA Langley B200 King Air aircraft and measured profiles of aerosol extinction, backscattering, and depolarization to: 1) characterize the spatial and vertical distributions of aerosols, 2) quantify aerosol extinction and optical thickness contributed by various aerosol types, 3) investigate aerosol variability near clouds, 4) evaluate model simulations of aerosol transport, and 5) assess aerosol optical properties derived from a combination of surface, airborne, and satellite measurements.

Ferrare, Richard↗
DOE OSTI2021

In Situ ATR-FTIR Study of the Cathode–Electrolyte Interphase: Electrolyte Solution Structure, Transition Metal Redox, and Surface Layer Evolution

We present a study of the lithium nickel manganese cobalt oxide (LiNi 0.6 Mn 0.2 Co 0.2 O 2 , NMC622) cathode-electrolyte interphase (CEI) during galvanostatic charging and discharging using in situ attenuated total reflectance Fourier transform infrared (ATR-FTIR) methods to investigate the voltage dependent electrolyte solution structure changes at the interface, transition metal (TM) redox chemistry, and cathode/electrolyte interfacial layer evolution. Furthermore, our in situ cell design provides both reliable electrochemical device testing and strong FTIR vibrational absorption signals near the cathode surface. Specifically, advanced spectral analysis elucidates changes of near-surface Li+ ion (de)solvation by solvent molecules during galvanostatic cycling. Moreover, cathode metal-oxygen vibrational absorptions, sensitive to TM redox behaviors and subsequent local structural variations, were correlated to cathode de-lithiation (and lithiation) and electrolyte solution structure changes. In addition, we have detected the formation and evolution of a CEI surface layer on the NMC622 cathode that contributes to the cell's capacity fade.

25 ENERGY STORAGE↗
DOE OSTI2021

Supercooled Liquid Water Detection Capabilities from Ka-Band Doppler Profiling Radars: Moment-Based Algorithm Formulation and Assessment

The occurrence of supercooled liquid water in mixed-phase cloud (MPC) affects their cloud microphysical and radiative properties. The prevalence of MPCs in the mid- and high latitudes translates these effects to significant contributions to Earth’s radiative balance and hydrological cycle. The current study develops and assesses a radar-only, moment-based phase partition technique for the demarcation of supercooled liquid water volumes in arctic, MPC conditions. The study utilizes observations from the Ka band profiling radar, the collocated high spectral resolution lidar, and ambient temperature profiles from radio sounding deployments following a statistical analysis of 5.5 years of data (January 2014–May 2019) from the Atmospheric Radiation Measurement observatory at the North Slope of Alaska. The ice/liquid phase partition occurs via a per-pixel, neighborhood-dependent algorithm based on the premise that the partitioning can be deduced by examining the mean values of locally sampled probability distributions of radar-based observables and then compare those against the means of climatologically derived, per-phase probability distributions. Analyzed radar observables include linear depolarization ratio (LDR), spectral width, and vertical gradients of reflectivity factor and radial velocity corrected for vertical air motion. Results highlight that the optimal supercooled liquid water detection skill levels are realized for the radar variable combination of spectral width and reflectivity vertical gradient, suggesting that radar-based polarimetry, in the absence of full LDR spectra, is not as critical as Doppler capabilities. The cloud phase masking technique is proven particularly reliable when applied to cloud tops with an Equitable Threat Score (ETS) of 65%; the detection of embedded supercooled layers remains much more uncertain (ETS = 27%).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

Mesoscale monitoring of the soil freeze/thaw boundary from orbital microwave radiometry

A technique was developed for mapping the spatial extent of frozen soils from the spectral characteristics of the 10.7 to 37 GHz radiobrightness. Through computational models for the spectral radiobrightness of diurnally heated freesing soils, a distinctive radiobrightness signature was identified for frozen soils, and the signature was cast as a discriminant for unsupervised classification. In addition to large area images, local area spatial averages of radiobrightness were calculated for each radiobrightness channel at 7 meteorologic sites within the test region. Local area averages at the meteorologic sites were used to define the preliminary boundaries in the Freeze Indicator discriminate. Freeze Indicator images based upon Nimbus 7, Scanning Multichannel Microwave Radiometer (SMMR) data effectively map temporal variations in the freeze/thaw pattern for the northern Great Plains at the time scale of days. Diurnal thermal gradients have a small but measurable effect upon the SMMR spectral gradient. Scale-space filtering can be used to improve the spatial resolution of a freeze/thaw classified image.

Dobson, Craig↗
NASA NTRS1998

Spatial Distribution of Ionospheric Plasma and Field Structures in the High-Latitude F Region

Ion density and velocity measurements from the Dynamics Explorer 2 (DE 2) spacecraft are used to obtain the average magnetic local time versus invariant latitude distribution of irregularities in the high-latitude F region ionosphere. To study the small-scale structure and its relationship to background conditions in the ionosphere, we have formed a reduced database using 2-s (approx. = 16 km) segments of the ion density and velocity data. The background gradients associated with each 2-s segment and the spectral characteristics, such as power at 6 Hz (approx. = 1.3 km) and spectral index, are among the reduced parameters used in this study. The relationship between the observed plasma structure and its motion is complex and dependent on the externally applied fields as well as locally generated plasma structure. The evolution of plasma structures also depends critically on the conductivity of the underlying ionosphere. Observations indicate an enhancement of irregularity amplitudes in two spatially isolated regions in both the ion density and the velocity. Convective properties seem to play a more important role in winter hemisphere where smaller-scale structures are maintained outside the source regions. (Delta)V irregularity amplitudes are enhanced in the cusp and the polar cap during northward interplanetary magnetic field regardless of season. The power in (Delta)V is usually higher than that associated with local polarization electric fields, suggesting that the observed structure in (Delta)N/N is strongly influenced by (Delta)V structure applied to large density gradients.

Kivanc, O.↗
NASA NTRS2012

Assessing Spectral Shortwave Cloud Observations at the Southern Great Plains Facility

The Atmospheric Radiation Measurement (ARM) program (now Atmospheric System Research) was established, in part, to improve radiation models so that they could be used reliably to compute radiation fluxes through the atmosphere, given knowledge of the surface albedo, atmospheric gases, and the aerosol and cloud properties. Despite years of observations, discrepancies still exist between radiative transfer models and observations, particularly in the presence of clouds. Progress has been made at closing discrepancies in the spectral region beyond 3 micron, but the progress lags at shorter wavelengths. Ratios of observed visible and near infrared cloud albedo from aircraft and satellite have shown both localized and global discrepancies between model and observations that are, thus far, unexplained. The capabilities of shortwave surface spectrometry have been improved in recent years at the Southern Great Plains facility (SGP) of the ARM Climate Research Facility through the addition of new instrumentation, the Shortwave Array Spectroradiometer, and upgrades to existing instrumentation, the Shortwave Spectroradiometer and the Rotating Shadowband Spectroradiometer. An airborne-based instrument, the HydroRad Spectroradiometer, was also deployed at the ARM site during the Routine ARM Aerial Facility Clouds with Low Optical Water Depths (CLOWD) Optical Radiative Observations (RACORO) field campaign. Using the new and upgraded spectral observations along with radiative transfer models, cloud scenes at the SGP are presented with the goal of characterizing the instrumentation and the cloud fields themselves.

McBride, P. J.↗
DOE OSTI2021

Deep-Learning-Derived Evaluation Metrics Enable Effective Benchmarking of Computational Tools for Phosphopeptide Identification

Tandem mass spectrometry (MS/MS)-based phosphoproteomics is a powerful technology for global phosphorylation analysis. However, applying four computational pipelines to a typical mass spectrometry (MS)-based phosphoproteomic dataset from a human cancer study, we observed a large discrepancy among the reported phosphopeptide identification and phosphosite localization results, underscoring a critical need for benchmarking. While efforts have been made to compare performance of computational pipelines using data from synthetic phosphopeptides, evaluations involving real application data have been largely limited to comparing the numbers of phosphopeptide identifications due to the lack of appropriate evaluation metrics. We investigated three deep learning-derived features as potential evaluation metrics: phosphosite probability, Delta RT and spectral similarity. Predicted phosphosite probability is computed by MusiteDeep, which provides high accuracy as previously reported; Delta RT is defined as the absolute retention time (RT) difference between RTs observed and predicted by AutoRT; and spectral similarity is defined as the Pearson’s correlation coefficient between spectra observed and predicted by pDeep2. Using a synthetic peptide dataset, we found that both Delta RT and spectral similarity provided excellent discrimination between correct and incorrect peptide-spectrum matches (PSMs) both when incorrect PSMs involved wrong peptide sequences and even when incorrect PSMs were caused by only incorrect phosphosite localization. Based on these results, we used all the three deep learning-derived features as evaluation metrics to compare different computational pipelines on diverse set of phosphoproteomic datasets and showed their utility in benchmarking performance of the pipelines. The benchmark metrics demonstrated in this study will enable users to select computational pipelines and parameters for routine analysis of phosphoproteomics data and will offer guidance for developers to improve computational methods.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1986

Infrasonic emissions from local meteorological events: A summary of data taken throughout 1984

Records of infrasonic signals, propagating through the Earth's atmosphere in the frequency band 2 to 16 Hz, were gathered on a three microphone array at Langley Research Center throughout the year 1984. Digital processing of these records fulfilled three functions: time delay estimation, based on an adaptive filter; source location, determined from the time delay estimates; and source identification, based on spectral analysis. Meteorological support was provided by significant meteorological advisories, lightning locator plots, and daily reports from the Air Weather Service. The infrasonic data are organized into four characteristic signatures, one of which is believed to contain emissions from local meteorological sources. This class of signature prevailed only on those days when major global meteorological events appeared in or near to eastern United States. Eleven case histories are examined. Practical application of the infrasonic array in a low level wing shear alert system is discussed.

Zuckerwar, A. J.↗
DOE OSTI2020

A Closer Look at Corrugated Au Tips

A series of optical and electron microscopies are utilized in concert to unravel the structural, optical, and plasmonic properties of corrugated metallic tips. While the overall microscopic shapes of the tips dictate their optical resonances and plasmonic field enhancement factors, nanometric structural details govern their tip-enhanced Raman (TER) spectra and images. Using 4-thiobenzonitrile (TBN) as a molecular reporter, spatially resolved TER spectra reveal that optical rectification and molecular charging are among the prominent observables in the tip-tip TER geometry. The comparisons we provide reinforce the complexity of what otherwise may be regarded as sharp tip probes. We show the spurious appearance of anions is driven by highly localized resonances that appear as a result of surface corrugation and their manifestation throughout the course of TER nano-spectroscopy complicates spectral assignments, particularly in works aimed at understanding plasmon-enhanced/induced chemical transformations through enhanced Raman spectroscopy and imaging. Overall, nanoscale spatial variations in the TERS spectra suggest that the tip-tip geometry sustains junction plasmons that appear very different from what may be expected from the hybridization of the bulk tip resonances.

Bhattarai, Ashish↗
DOE OSTI2024

Localizing Low-Grade Heat Using Hybrid Photonic-Phononic Materials

Creating next-generation devices capable of transducing waste heat into useful work will require building blocks designed to direct low-grade thermal energy at length scales well below the diffraction limit. Characterizing thermally induced energy transfer at the nanoscale, however, is a formidable task due to the simultaneous demand of high spatial and spectral resolution at infrared energies. Leveraging recent advancements in electron energy loss (EEL) and gain (EEG) spectroscopy, we reveal that individual nanostructures can concentrate energy by the resonant thermal excitation of their photonic Fabry–Pérot modes. Specifically, we show that the spatially localized gain signal increases upon in situ heating. Finally, theoretical modeling elucidates the mechanism for these observations by showing that a Purcell enhancement in the local photonic density of states drives the increased rate of infrared energy transfer from the ambient environment to each nanostructure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Highly sensitive 2D X-ray absorption spectroscopy via physics informed machine learning

Abstract Improving the spatial and spectral resolution of 2D X-ray near-edge absorption structure (XANES) has been a decade-long pursuit to probe local chemical reactions at the nanoscale. However, the poor signal-to-noise ratio in the measured images poses significant challenges in quantitative analysis, especially when the element of interest is at a low concentration. In this work, we developed a post-imaging processing method using deep neural network to reliably improve the signal-to-noise ratio in the XANES images. The proposed neural network model could be trained to adapt to new datasets by incorporating the physical features inherent in the latent space of the XANES images and self-supervised to detect new features in the images and achieve self-consistency. Two examples are presented in this work to illustrate the model’s robustness in determining the valence states of Ni and Co in the LiNi x Mn y Co 1-x-y O 2 systems with high confidence.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Electrical Tuning of Tin-Vacancy Centers in Diamond

Group-IV color centers in diamond have attracted significant attention as solid-state spin qubits because of their excellent optical and spin properties. Among these color centers, the tin-vacancy (Sn-V - ) center is of particular interest because its large ground-state splitting enables long spin coherence times at temperatures above 1 K. However, color centers typically suffer from inhomogeneous broadening, which can be exacerbated by nanofabrication-induced strain, hindering the implementation of quantum nodes emitting indistinguishable photons. Although strain and Raman tuning have been investigated as promising tuning techniques to overcome the spectral mismatch between distinct group-IV color centers, other approaches need to be explored to find methods that can offer more localized control without sacrificing emission intensity. Here, we study the electrical tuning of Sn-V - centers in diamond via the direct-current Stark effect. We demonstrate a tuning range beyond 1.7 GHz. We observe both quadratic and linear dependence on the applied electric field. Further, we also confirm that the tuning effect we observe is a result of the applied electric field and is distinct from thermal tuning due to Joule heating. Stark tuning is a promising avenue toward overcoming detunings between emitters and enabling the realization of multiple identical quantum nodes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Energy and momentum conservation in spin transfer

We utilize simulations of spin-polarized electron scattering by a chain of localized quantum spins to show that energy and linear momentum conservation laws impose strong constraints on the properties of magnetic excitations induced by spin transfer. In turn, orbital and spin dynamics of conduction electrons depends on the dynamical characteristics of the local spins. Furthermore, our results suggest the possibility to achieve precise control of spin-transfer-driven magnetization dynamics by tailoring the spectral characteristics of the magnetic systems and of the driving electrons.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Evaluating Scalograms for Seismic Event Denoising

Denoising contaminated seismic signals for later processing is a fundamental problem in seismic signals analysis. The most straightforward denoising approach, using spectral filtering, is not effective when noise and seismic signal occupy the same frequency range. Neural network approaches have shown success denoising local signal when trained on short-time Fourier transform spectrograms (Zhu et al 2018; Tibi et al 2021). Scalograms, a wavelet-based transform, achieved ~15% better reconstruction as measured by dynamic time warping on a seismic waveform test set than spectrograms, suggesting their use as an alternative for denoising. We train a deep neural network on a scalogram dataset derived from waveforms recorded by the University of Utah Seismograph Stations network. We find that initial results are no better than a spectrogram approach, with additional overhead imposed by the significantly larger size of scalograms. A robust exploration of neural network hyperparameters and network architecture was not performed, which could be done in follow on work.

58 GEOSCIENCES↗