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At least 1,423 records · Page 79
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Dependence of Energetic Storm Particle Heavy Ion Peak Intensities and Spectra on Source CME Longitude and Speed

We examine variations in energetic storm particle (ESP) heavy ion peak intensities and energy spectra at CME-driven interplanetary shocks. We focus on their dependence with heliolongitude relative to the source region of their associated CMEs, and with CME speed, for events observed in Solar Cycle 24 at the STEREO-A, STEREO-B, and/or ACE spacecraft. We find that observations of ESP events at 1 au are organized by longitude relative to their CME solar source. The ESP event longitude distribution also showed organization with CME speed. The near-Sun CME speeds (V i ) for these events ranged from ∼560 to 2650 km s −1 while the average CME transit speeds to 1 au were significantly slower. The angular width of the events had a clear threshold at V i of ∼1300 km s −1 , above which events showed significantly larger angular extension compared to events with speeds below. High-speed events also showed larger heavy ion peak intensities near the nose of the shock compared to the flanks while their spectral index was smaller near the nose and larger near the flanks. This organization for events with V i < 1300 km s −1 was not as clear. These ESP events were observed over a narrower range of longitudes though the heavy ion peak intensities still appeared largest near the nose of the shock. Their heavy ion spectra showed no clear organization with longitude. These observations highlight the impact of spacecraft position relative to the CME source longitude and Vi on the properties of ESP events at 1 au.

Solar energetic particles↗
NASA NTRS2023

Interpretation of Flat Energy Spectra Upstream of Fast Interplanetary Shocks

Interplanetary shocks are large-scale heliospheric structures often caused by eruptive phenomena at the Sun, and represent one of the main sources of energetic particles. Several interplanetary shock crossings by spacecraft at 1 AU have revealed enhanced energetic-ion fluxes that extend far upstream of the shock. Surprisingly, in some shock events, ion fluxes with energies between 100 keV and about 2 MeV acquire similar values (which we refer to as "overlapped'' fluxes), corresponding to flat energy spectra in that range. In contrast, closer to the shock, the fluxes are observed to depend on energy. In this work, we analyze three interplanetary shock-related energetic particle events observed by the Advanced Composition Explorer spacecraft where flat ion energy spectra were observed upstream of the shock. We interpret these observations via a velocity filter mechanism for particles in a given energy range. This reveals that low energy particles tend to be confined to the shock front and cannot easily propagate upstream, while high energy particles can. The velocity filter mechanism has been corroborated from observations of particle flux anisotropy by the Solid-State Telescope of Wind/3DP.

Shock waves↗
NASA NTRS2024

Soft X-ray Energy Spectra in the Wide-Field Galactic Disk Area Revealed with HaloSat

We analyzed data from HaloSat observations for five fields in the Galactic disk located far away from the Galactic center (135° < l < 254°) to understand the nature of soft X-ray energy emission in the Galactic disk. The fields have 14° diameter and were selected to contain no significant high-flux X-ray sources. All five HaloSat soft X-ray energy spectra (0.4–7 keV with energy resolution of < 100 eV below 1 keV) show a possibility of the presence of unresolved high-temperature plasma in the Galactic disk (UHTPGD) with a temperature of 0.8–1.0 keV and an emission measure of (8–11) × 10 −4 cm −6 pc in addition to the soft X-ray diffuse background components mainly studied at higher Galactic latitudes (solar wind charge exchange emission, Local Hot Bubble, Milky Way halo emission, and the cosmic X-ray background). This suggests that the UHTPGD is present across the whole Galactic disk. We also observed UHTPGD emission in a region with no bright sources in an XMM-Newton field contained within one of the HaloSat fields. The temperature and emission measure are consistent with those measured with HaloSat. Moreover, the stacked spectra of the X-ray pointlike sources and near-infrared-identified point sources such as stars in the XMM-Newton field also show a spectral feature similar to the UHTPGD emission. This suggests that the UHTPGD may partly originate from pointlike sources such as stars.

X-rays: diffuse background↗
NASA NTRSDate not supplied

JWST Photometry and Spectra Reveal Dust and Ice in Super Star Cluster Located in N79

Super star clusters (SSCs) are the most extreme mode of star formation; however they are rare in the local universe. With the serendipitous discovery of SSC candidate H72.97-69.39 in the N79 Region of the Large Magellanic Cloud, we have a unique opportunity to study the early phases of an SSC formation. H72.97-69.39 has an uncertain luminosity with a lower limit of 1,500,000 L⊙, based on spectral energy distribution fit, with a potential to reach the luminosity of the R136 SSC in 30 Doradus (10,000,000 L⊙). We will present James Webb Space Telescope (JWST) near- and mid-infrared (NIRCam and MIRI) observations of H72.97-69.39, including mid-infrared spectra of six young stellar objects taken with the MIRI instrument. The emission and absorption lines seen in the high-resolution spectra include fine-structure, molecular hydrogen, polyaromatic hydrocarbon, and ice features. Hydrogen recombination lines indicate these protostars have accretion rates as high as 0.02 M⊙ per year. Photometry is accomplished using the software package StarbugII, which was developed for JWST imaging of crowded fields and complex backgrounds. Near- and mid-infrared photometry from JWST reveal over 100 young stellar objects within a 30-pc x 40 pc (120” x 160”) region with spectral energy distribution fits indicating the masses of these objects areas low as 0.5 M⊙ and as high as 40 M⊙. We use color magnitude diagrams to separate the young stellar objects from the red giant branch and asymptotic giant branch stellar populations. We compare our JWST observations to ALMA, HST, and Chandra observations to present a clearer picture of how star formation takes place within an SSC.

Isha Nayak↗
DOE OSTI2021

Reconstruction of the Density Power Spectrum from Quasar Spectra using Machine Learning

We describe a novel end-to-end approach using Machine Learning to reconstruct the power spectrum of cosmological density perturbations at high redshift from observed quasar spectra. State-of-the-art cosmological simulations of structure formation are used to generate a large synthetic dataset of line-of-sight absorption spectra paired with 1-dimensional fluid quantities along the same line-of-sight, such as the total density of matter and the density of neutral atomic hydrogen. With this dataset, we build a series of data-driven models to predict the power spectrum of total matter density. We are able to produce models which yield reconstruction to accuracy of about 1% for wavelengths $k \leq 2 h Mpc^{-1}$, while the error increases at larger $k$. We show the size of data sample required to reach a particular error rate, giving a sense of how much data is necessary to reach a desired accuracy. This work provides a foundation for developing methods to analyse very large upcoming datasets with the next-generation observational facilities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Neural Network Analysis of Nuclear Magnetic Resonance and Infrared Spectra

Nuclear magnetic resonance (NMR) spectroscopy and infrared (IR) spectroscopy are powerful chemical characterization techniques with broad general usage. However, the manual evaluation of the resulting spectra is time-consuming and requires significant expertise, preventing insights from being used in real-time applications. With recent advances in computation and artificial intelligence (AI), new tools are available for automating spectral interpretation. In this work, machine learning (ML) algorithms using 1-dimensional convolutional neural networks (CNNs) were applied to identify common functional groups from spectral information. Raw spectra were collected virtually from the Human Metabolome Database (HMDB) and National Institute of Standards and Technology (NIST) Chemistry WebBook and processed into a suitable standard. Algorithm design was tailored to best fit the nature of the problem, with built-in flexibility to accommodate relevant parameters beyond the raw spectral input, specifically solvent identity and magnetic frequency for NMR. The predictive capability of the algorithm in identifying functional groups is displayed in several examples. This methodology has been compiled into a code repository and could easily be modified to adapt alternative data sources, including other spectrum types. To mitigate overfitting, a common problem in mathematical modeling where overfamiliarity with training data produces trends that are not representative of the general data, a novel metric was developed, referred to as Accufit. Accufit includes a parameter that penalizes substantial differences in the training accuracy and the accuracy of an independent validation set. Examples are presented showing the effectiveness of Accufit in maintaining the model’s predictive capability while controlling the overfitting when used as a custom metric for hyperparameter tuning.

Sturgill, James↗
DOE OSTI2026

Nonlinear Information from DESI Luminous Red Galaxies: An Emulator-Based Analysis of Pre- and Post-Reconstruction Power Spectra

We present joint measurements of the pre- and post-reconstruction power spectra, $P_{\rm pre}$ and $P_{\rm post}$, together with their cross-power spectrum, $P_{\rm cross}$, for the Luminous Red Galaxies (LRGs) in the DESI Data Release 1 (DR1). We jointly analyse these observables with an emulator-based full-shape modeling framework, thereby, for the first time, we extract complementary nonlinear information from the galaxy density field before and after reconstruction in real survey data. Specifically, including $P_{\rm post}$ and $P_{\rm cross}$ in addition to $P_{\rm pre}$ (hereafter $P_{\rm all}$) yields an improvement of approximately $18$-$27\%$ in the $σ_8$ constraint in both $Λ$CDM and $w$CDM, depending on the redshift bin, relative to the $P_{\rm pre}$-only analysis with the cosmic microwave background distance priors (hereafter CMB). In $w$CDM, the joint CMB+$P_{\rm all}$ analysis can tighten the constraints on $w$ by approximately $5$-$15\%$ across the two LRG redshift bins, compared to the CMB+$P_{\rm pre}$ combination. Further incorporating the Type Ia supernova dataset and comparing the cosmological constraints in $w$CDM from each individual power-spectrum component with those from the full combination, we find that $P_{\rm all}$ consistently provides the tightest constraints. From the joint CMB+$P_{\rm all}$+DES-Dovekie dataset, we obtain $Ω_m = 0.314 \pm 0.0048$ and $w = -0.988 \pm 0.023$ for the \texttt{LRG1} sample, and $Ω_m = 0.318 \pm 0.0046$ and $w = -0.988 \pm 0.025$ for \texttt{LRG2}. These results demonstrate that combining pre- and post-reconstruction power spectra with their cross-correlation enables DESI to harvest additional nonlinear information, leading to tighter constraints on cosmological parameters.

Wang, Yuting [NAOC, Beijing; Beijing, GUCAS] (ORCI↗
DOE OSTI2024

Extracting and Interpreting Electrochemical Impedance Spectra (EIS) from Physics-Based Models of Lithium-Ion Batteries

This paper implements a highly efficient algorithm to extract electrochemical impedance spectra (EIS) from physics-based battery models (e.g., a P2D model). The mathematical approach is different from how EIS is practiced experimentally. Experimentally, the voltage (current) is harmonically perturbed over a wide range of frequencies and the amplitude and phase shift of the corresponding current (voltage) is measured. The experimental approach can be implemented in simulation software, but is computationally expensive. The approach here is to determine locally linear state-space models from the full physical model. The four Jacobian matrices that are the basis of the state-space models can be derived by numerical differentiation of the physical model. The EIS is then extracted from the state-space model using computationally efficient matrix-manipulation techniques. The algorithm can evaluate the full EIS at an instant in time during a transient, independent of whether the battery is in a stationary state. The approach is also able to separate the full-cell impedance to evaluate partial EIS, such as for a battery anode alone. Although such partial EIS is difficult to measure experimentally, the partial EIS provides valuable insights in interpreting the full-cell EIS.

25 ENERGY STORAGE↗
DOE OSTI2021

Accretion of matter and spectra of binary X-ray sources in massive gravity

We study low-mass binary X-ray sources involving stellar mass black holes within massive gravity. Regarding the accretion disk, we adopt the standard model for an optically thick, cool, and geometrically thin disk by Shakura–Sunyaev. For the gravitational field generated by the black hole, we consider the analogue of the Schwarzschild–de Sitter space–time of Einstein’s theory in massive gravity, for which we found an additional term linear in the radial coordinate. Then, we compute the radial velocity, the energy density and the pressure as a function of the radial coordinate, and the X-ray emission’s soft spectral component expected from the disk. We also investigated in detail the impact of this new geometry. Our result indicates that by using observed spectra from confirmed X-ray binaries involving astrophysical black holes, we can put strong constraints on alternative theories of gravity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Machine learning-assisted identification of potential sources of bias in measurements of prompt-fission neutron spectra

Unrecognized sources of uncertainty (USU) can bias the reported mean and/or covariance of experimental nuclear data. These biases, in turn, can propagate through evaluated nuclear data to application simulations or may poorly inform nuclear theory that is fitted to the experimental data. Such unknown sources of bias must be tied to the inherent physical constituents of the measurements such as the characteristics of a detector response or a background reduction technique. Here, in this article, a sparse Bayesian learning model is used to support experts in their efforts to identify and characterize USU in experimental prompt fission neutron spectra (PFNS) for spontaneous fissioning of 252 Cf by linking observed biases to features of the measurement system. Three different bias components were found. The first acts as a verification case for the algorithm as it identifies a bias coming from a well-known source related to the use of 6 Li in the neutron detection system. The second two cases demonstrate how this method can benefit the evaluation of experimental nuclear data by identifying, quantifying, and relating unknown biases to potential causes.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

A novel methodology for gamma-ray spectra dataset procurement over varying standoff distances and source activities

The adoption of machine learning approaches for gamma-ray spectroscopy has received considerable attention in the literature. Many studies have investigated the deployment of various algorithm architectures to a specific task. However, little attention has been afforded to the development of the datasets leveraged to train the models. Such training datasets typically span a set of environmental or detector parameters to encompass a problem space of interest to a user. Variations in these measurement parameters will also induce fluctuations in the detector response, including expected pile-up and ground scatter effects. Fundamental to this work is the understanding that 1) the underlying spectral shape varies as the measurement parameters change and 2) the statistical uncertainties associated with two spectra impact their level of similarity. While previous studies attribute some arbitrary discretization to the measurement parameters for the generation of their synthetic training data, this work introduces a principled methodology for efficient spectral-based discretization of a problem space. A signal-to-noise ratio (SNR) respective spectral comparison measure and a Gaussian Process Regression (GPR) model are used to predict the spectral similarity across a range of measurement parameters. This innovative approach effectively showcased its capability by dividing a problem space, ranging from 5 cm to 100 cm standoff distances and 5 μCi–100 μCi of 137 Cs, into three unique combinations of measurement parameters. The findings from this work will aid in creating more robust datasets, which incorporate many possible measurement scenarios, reduce the number of required experimental test set measurements, and possibly enable experimental training data collection for gamma-ray spectroscopy.

data science↗
DOE OSTI2023

Temperature and anion ligand field dependence of LnCl 3 (Ln = Nd, Dy, Sm) electronic absorption spectra in LiCl–KCl eutectic molten salt

A comprehensive knowledge of the coordination, bonding, and speciation of elements in molten salt mixtures is necessary to understand and predict the chemical and physical properties of the salt. Absorption spectroscopy can yield information about the chemistry of species of interest in alkali halide molten salt mixtures by revealing information about the electronic structure and transitions of those species. In this study, ultraviolet (UV), visible (vis), and near-infrared (NIR) absorption spectroscopy was used to examine changes to the electronic structure of trivalent Nd, Sm, and Dy in LiCl–KCl eutectic molten salt with changes in temperature and the anion composition of the melt. With increasing temperature, changes to spectral features suggest a distortion of the coordination complexes. Changes to lineshape with the substitution of alternative halide anions were examined and analyzed, revealing differences in the coordination for I – versus F – with the lanthanides. Gaussian peak fitting was used to show that the changes in lineshape with the progressive addition of F – anions can be explained by the superposition of a set of absorption bands from complexes with all Cl – anion ligands and a set of blueshifted absorption bands from complexes containing both F – and Cl – anion ligands. Finally, this work yields a new method to analyze and interpret change to electronic absorption spectra for f-block elements dissolved in alkali halide molten salts as well as new observations of the interactions of larger and smaller halide anions with lanthanides in Cl – -based molten salts.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

Time domain probabilistic seismic risk analysis using ground motion prediction equations of Fourier amplitude spectra

Modeling of Fourier amplitude spectra (FAS) of seismic motions has gained much attention in engineering seismology. In the past few years, several ground motion prediction equations (GMPEs) and inter-frequency correlation structure of FAS have been established. Due to many preferable characteristics of FAS, probabilistic seismic hazard/risk analysis is rapidly changing from ergodic, spectrum acceleration Sa(T 0 )-based approach to non-ergodic, site-specific, FAS-based approach. This paper presents time domain intrusive framework for probabilistic seismic risk analysis using GMPE of FAS. Herein, methodology for time domain stochastic ground motion modeling based on GMPEs of FAS is presented in some detail. The simulated uncertain motions are modeled as a random process and represented by polynomial chaos Karhunen-Loève expansion. The random process excitations are further propagated into the uncertain structural system using Galerkin stochastic finite element method (SFEM). Probabilistic evolution of structural response is solved, and such solution is used to develop seismic risk for any damage state. The presented framework is illustrated through seismic risk analysis of a four-story building subjected to possible earthquakes from two strike slip faults. The influences of the epistemic uncertainties in source stress drop Δσ and site attenuation κ0 on seismic risk are investigated. The need for non-ergodic seismic risk analysis with source-specific and site specific characterizations is emphasized.

58 GEOSCIENCES↗
DOE OSTI2024

Flux and estimated spectra from a low-intensity laser-driven X-ray source

Laser-driven X-rays as probes for high-energy-density physics spans an extremely large parameter space with laser intensities varying by 8 orders of magnitude. We have built and characterized a soft X-ray source driven by a modest intensity laser of 4 × 10 13 W/cm 2 . Emitted X-rays were measured by diamond radiation detectors and a filtered soft X-ray camera. A material-dependence study on Al, Ti, stainless steel alloy 304, Fe, Cu and Sn targets indicated 5-μm-thick Cu foils produced the highest X-ray yield. X-ray emission in the laser direction and emission in the reverse direction depend strongly on the foil material and the thickness due to the opacity and hydrodynamic disassembly time. The time-varying X-ray signals are used to measure the material thinning rate and is found to be ~1.5 μm/ns for the materials tested implying thermal temperature around 0.6 eV. The X-ray spectra from Cu targets peaks at ~2 keV with no emission >4 keV and was estimated using images with eight different foil filters. One-dimensional hydrodynamic and spectral calculations using HELIOS-CR provide qualitative agreement with experimental results. Modest intensity lasers can be an excellent source for nanosecond bursts of soft X-rays.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Raman scattering spectra of boron imidazolate frameworks containing different magnetic ions

We present a Raman scattering spectroscopic study of boron imidazolate metal-organic frameworks (BIFs) with three different magnetic metal ions and one non-magnetic in a wide frequency range from 25 to 1700 cm−1, which covers local vibrations of the imidazolate linkers as well as collective lattice vibrations. We show that the spectral region above 800 cm−1 belongs to the local vibrations of the linkers, which have the same frequencies for the studied BIFs without any dependence on the structure of the BIFs and are easily interpreted based on the spectra of imidazolate linkers. In contrast, collective lattice vibrations, observed below 100 cm−1, show a distinction between cage and two-dimensional BIFs structures, with a weak dependence on the metal node. We identify the range of vibrations around 200 cm−1, which are distinct for each metal-organic framework, depending on a metal node. Our work demonstrates the energy hierarchy in the vibrational response of BIFs.

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

Interpreting scattered neutron spectra on omega cryogenic implosions with measured backgrounds and higher-order scattering

Measurements of the areal density (⁠ρR⁠) of inertially confined implosions are critical to evaluate their performance. On OMEGA, ρR is inferred from measurements of the scattered neutron spectrum via neutron-time-of-flight (nTOF) and magnetic recoil spectrometer detectors. The nTOF measurements, in particular, have the ability to measure a wide range of neutron energies and thus scattering angles, with high precision. However, the neutrons that are backscattered into the detector must transit through the entire dense fuel assembly, and as a result are subject to rescattering effects, which have been heretofore neglected in the interpretation of OMEGA neutron spectra. At the backscatter edge, neglecting rescattering on OMEGA can lead to a ~10 to 20% reduction of the apparent areal density and therefore must be included in the analysis. The low ρR s on OMEGA also mean that backgrounds from non-target physics effects, such as scattering in the target chamber or slow scintillator decays, can significantly alter the measured signal. Here, we discuss how the Monte Carlo neutron spectrum postprocessor IRIS is used to include second-order scattering effects in the interpretation of the scattered neutron spectrum in OMEGA implosion experiments, and how dedicated implosion experiments are used to measure nTOF backgrounds in order to infer backscattered areal densities on OMEGA.

Deuterium↗
DOE OSTI2025

Twin Polaritons: Classical versus Quantum Features in Polaritonic Spectra

Understanding whether a polaritonic phenomenon is fundamentally quantum or classical is essential for building accurate theoretical models and guiding experimental design. Here, in this work, we address this question in the context of polaritonic spectra and report an intriguing new feature: the twin polariton, an additional splitting beyond the primary resonant polariton splitting originating from vacuum field fluctuations. We show that the twin polariton persists in the many-molecule limit under permutationally symmetrical initial-state constraint and that it follows the same linear dependence on coupling strength as the primary polariton splitting. This establishes a novel mechanism by which a quantum feature (the twin polariton) can be tuned through a classical one (the primary polariton), offering new opportunities to probe and control the fundamental nature of polaritonic systems.

classical optics↗
DOE OSTI2024

In-house synthesized poly(ether ether ketone) ionenes. II. ToF-SIMS spectra in the negative ion mode

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) was used to analyze poly(ether ether ketone) (PEEK) based membranes. PEEK membranes have been shown to be effective in the separation of CO 2 from flue gases (post-combustion technique). The PEEK membranes were synthesized using novel aromatic ether-ketone linkages inspired by PEEK with polymeric backbone bistriflimide [Tf2N]− counterions. One of the keys to advancing this technology is developing membranes that are selective and permeable toward CO 2 , in which PEEK based membranes have been shown to be. Furthermore, the compatibility between various water lean solvents also needs to be investigated. Surface analytical techniques such as x-ray photoelectron spectroscopy and ToF-SIMS are useful for investigating chemical changes between membranes. Herein, we present ToF-SIMS data obtained in the negative ion mode for four different PEEK membranes designed for use in CO 2 capture systems. Positive ion mode spectra are reported in Paper I.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗