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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Evidence for a high-energy tail in the gamma-ray spectra of globular clusters

Millisecond pulsars are very likely the main source of gamma-ray emission from globular clusters. However, the relative contributions of two separate emission processes – curvature radiation from millisecond pulsar magnetospheres versus inverse Compton emission from relativistic pairs launched into the globular cluster environment by millisecond pulsars – have long been unclear. To address this, we search for evidence of inverse Compton emission in 8-yr Fermi–LAT data from the directions of 157 Milky Way globular clusters. We find a mildly statistically significant (3.8σ) correlation between the measured globular cluster gamma-ray luminosities and their photon field energy densities. However, this may also be explained by a hidden correlation between the photon field densities and the stellar encounter rates of globular clusters. Analysed in toto, we demonstrate that the gamma-ray emission of globular clusters can be resolved spectrally into two components: (i) an exponentially cut-off power law and (ii) a pure power law. The latter component – which we uncover at a significance of 8.2σ – has a power index of 2.79 ± 0.25. It is most naturally interpreted as inverse Compton emission by cosmic-ray electrons and positrons injected by millisecond pulsars. Here, we find the luminosity of this power-law component is comparable to, or slightly smaller than, the luminosity of the curved component, suggesting the fraction of millisecond pulsar spin-down luminosity into relativistic leptons is similar to the fraction of the spin-down luminosity into prompt magnetospheric radiation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Measurement and analysis of the Doppler broadened energy spectra of gamma radiation originating from the annihilation of positrons incident on clean and adsorbate-covered surfaces

We present measurements and theoretical modeling demonstrating the capability of coincidence Doppler broadened (CDB) annihilation gamma spectroscopy to provide element-specific information from the topmost atomic layer of surfaces. Our measurements show that the energy spectra of Doppler-shifted annihilation gamma photons emitted following the annihilation of positrons from the topmost atomic layers of clean and adsorbate covered surfaces of gold (Au), silver (Ag) and copper (Cu) differ significantly. The shape of the Doppler-broadened gamma spectrum, as analyzed using ratio curves, indicates that the elemental composition of the surface can still be identified despite contributions from positronium annihilation and a significant reduction in core electron annihilation. We estimate the chemical composition of the various probed surfaces by modeling the ratios of the measured Doppler spectra with respect to the Doppler spectra from a clean Cu surface using a linear combination of calculated ratio curves. The fitting of the experimental ratio curves was used to obtain an estimate of the elemental composition of Cu surfaces with sulfur segregation, oxygen adsorption, a thin film of Selenium (Se), and a single layer of graphene (SLG). A similar analysis was performed on the Ag surface with environmental adsorbates, the same surface after argon ion sputtering, as well as a sputter cleaned Au surface. The surface compositions obtained from the analysis of the CDB data were compared to the compositions obtained using positron annihilation induced Auger electron spectroscopy (PAES). Our results show that CDB can detect, identify, and quantify, sub-monolayer adsorbates and a single atomic layer deposited on metal substrates.

Lotfimarangloo, Sima [Univ. of Texas, Arlington, T↗
DOE OSTI2025

RadSim: Detector Response

This package simulates the expected output gamma spectra from a gamma detector for given configuration.

Hangal, DhanushA [Lawrence Livermore National Labo↗
DOE OSTI2022

Gamma-ray spectra analyses of molten salts in spent nuclear fuels pyroprocessing facilities for mass measurement

To evaluate radioactive tracer dilution and gamma spectroscopy as a safeguards technique for monitoring the mass of liquid salt in molten salt systems, the gamma spectroscopy data of salt samples from the pyroprocessing facilities in Idaho National Laboratory were acquired and analyzed. The primary focus is the uncertainty analysis of the gamma radioactivity of 154 Eu isotope in the molten salts. The facilities include an electrorefiner for pyroprocessing spent oxide fuels (SOF-ER) and Mark-IV ER for processing the metallic fuels from Experimental Breeder Reactor-II (EBR-II). The relative gamma radioactivity uncertainty was consistently at 3% for 137 Cs for both Mark-IV ER and SOF-ER salts. However, for 154 Eu, it was 8% for SOF-ER salt and 7% for Mark-IV ER salt. Here, the main reason for the higher uncertainty for 154 Eu is believed to be the lower counting statistics in gamma spectroscopy. To improve the gamma radioactivity uncertainty of isotope 154 Eu, a longer data acquisition time (12 h instead of 4 h) and a higher count rate gamma detector for gamma spectroscopy were tested and it was found that the uncertainty for 154 Eu was significantly improved from 7% or 8–3%.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Dense autoencoders, clustering techniques, and semi-supervised learning for HPGe $γ$-spectra

Classifying high-resolution gamma spectra by their isotopic content is an essential task in nuclear forensics and other applications. Traditional analysis methods are often time-intensive, but machine learning (ML) may help analysts quickly process many spectra. Such methods tend to rely on abundant, well-labeled data for training. Historical gamma data exists in various fields but is not uniformly useful for supervised ML due to inconsistent labeling. Here, to address some of these challenges, we present a method to classify and organize unlabeled data from high-purity germanium detectors using an autoencoding neural network (autoencoder). We trained dense autoencoders to compress gamma data into latent representations that enable efficient data characterization. By clustering the encoded spectra or lower-dimensional mappings of them, we identified and removed portions of over-abundant data categories, resulting in a more balanced dataset and improved autoencoder performance. This encoding and clustering pipeline also enabled the organization of spectra into self-consistent categories. Finally, we found that encoded representations showed potential as inputs for semi-supervised learning of nuclide identification (NID) labels, achieving an average F1 score of 0.85 ± 0.03 when mapping encodings to a set of 65 isotope labels.

Autoencoders↗
NASA NTRS1994

An iron absorption model of gamma-ray burst spectra

Most gamma-ray bursts (GRBs) exhibit deficits of X-rays below approximately 200 keV. Here we consider a spectral model in which the burst source is shielded by an optically thick layer of circumburster material (CBM) rich in iron-group elements whose photoelectric absorption opacity exceeds the Thomson opacity below approximately 120 keV. For power-law distributions of absorption depths along the lines of sight the absorbed spectrum can indeed mimic the typial GRB spectrum. This model predicts that (a) the spectrum should evolve monotonically from hard to soft during each energy release, which is observed in most bursts, especially in fast rise exponential decay bursts; (b) Fe spectral features near 7 keV may be present in some bursts; and (c) the ratio of burst distances to the CBM and to Earth should be approximately 10(exp -11) if the spectral evolution is purely due to Fe stripping by the photons.

Liang, Edison P.↗
NASA NTRS1992

Analysis of Phobos mission gamma ray spectra from Mars

The determination of the elemental composition of the surface of a planetary body can be achieved, in many cases, by remote-sensing gamma ray spectroscopy. A gamma ray spectrometer was carried on the Soviet spacecraft Phobos-2, and obtained data while in an elliptical orbit around Mars. Results of two independent approaches to data analysis, one by the Soviet group and one by an American group are reported. The results for five elements are given for two different orbits of Mars. Major geologic units that contribute to the signal for each orbit have been identified. The results from the two techniques are in general agreement and there appear to be no geologically significant differences between the results for each orbit.

Trombka, J. I.↗
DOE OSTI2019

Fission Gamma-Ray Spectra Relevant to Post-Detonation Debris Analysis

A terrorist-generated nuclear attack would invoke unprecedented pressure for a rapid and accurate nuclear forensics characterization of the event. In-situ fission product gamma-ray spectroscopy offers the potential for a significant reduction in analysis time while still providing high fidelity identification of the primary composition of the detonated device. The in-situ spectroscopic approach we are proposing can rapidly identify the species that underwent fission as well as the fission-inducing neutron energy spectrum. To demonstrate this goal, we have used the gammaray history from our previously obtained LLNL-LANL-TUNL fission product-yield (FPY) data to provide insights for post-detonation debris analysis. The proposed method relies on the ratio of photopeak areas for selected gamma-rays representing the FPYs of sixteen fission products generated using mono-energetic neutrons at energies between 0.5 MeV to 14.8 MeV on highlyenriched 239 Pu, 235 U, and 238 U sealed targets. In addition to the fission product ratio measurements we have applied a new regression analysis based on our experimental FPY data and validated the approach using relevant Godiva FPY data and (surrogate) photofission product yields of 240 Pu. The main advantage of the regression analysis is that it investigates the FPY data set as a whole, rather than focusing on individual FPY ratios.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1998

Gamma-Ray Spectra and Variability of Cygnus Z-1 Observed by BATSE

We present new BATSE earth occultation observations of the 25 keV-1.8 MeV spectrum and variability of Cygnus X-1 made between August 1993 and May 1994. We observed that the normal soft gamma ray spectrum (gamma2) of Cygnus X-1 has two components: a Comptonized part seen below 300 keV, and a high-energy tail in the 0.3 - 2 MeV range. We interpret it in terms of a two-layer region, consisting of a high-energy core (with an equivalent electron temperature of approximately 210-250 keV) near the event horizon, embedded in an about 50 keV corona. In this scenario, the observed 25-300 keV photons were produced by Compton scattering of soft photons (about 0.5 keV) by the hot electrons in the outer corona. These same hard x rays were further up-scattered by a population of energetic electrons in the inner core, producing the spectral tail above 300 keV. Cygnus X-1 went through an extended sequence of transitions between August 1993 and May 1994, when the 45-140 keV flux first decreased steadily from approximately gamma2 to roughly one-quarter of its intensity over a period of about 140 days. The flux remained at this low level for about 40 days before returning, swiftly (approximately 20 days) to approximately the initial gamma2 level. During the transition, the spectrum evolved to a shape consistent with either a power law with photon index of about 2.6 or a single temperature Compton model with electron temperature kT = 110 +/- 11 keV, and optical depth t = 0.40 +/- 0.06, and then returned essentially to the original gamma2 spectrum at the end of the active period. The overall cooling of the system during the low flux period may be due to an increase in the soft photon population which effectively quenched the hot electrons in these regions through Compton scattering.

Ling, J. C.↗
NASA NTRS1996

Gamma-Ray Spectra & Variability of Cygnus X-1 Observed by BATSE

We present new BATSE Earth occultation observations of the 25 keV-1.8 MeV spectrum and variability of Cygnus X-1 made between August 1993 and May 1994. We observed that the normal soft gamma-ray spectrum (gamma2) of Cygnus X-1 has two components: a Comptonized part seen below 30keV, and a high-energy tail in the 0.3-2 MeV range.

Black holes gamma rays occultation↗
DOE OSTI2021

Identification of Auger mechanisms responsible for low energy electron emission from graphene on copper using Auger-gamma coincidence spectroscopy

We have applied positron annihilation induced Auger-gamma coincidence spectroscopy to identify important mechanisms responsible for the emission of low energy electrons following the sudden creation of holes in bilayer graphene on copper substrate. The novel surface spectroscopic method measures the energy of the Doppler shifted annihilation gamma photon in coincidence with the Auger electron emitted following the relaxation of the hole created by the annihilation of a surface electron with a surface trapped positron. By extracting and theoretically modelling the annihilation gamma spectra coincident with low energy electrons, we associate majority of the intensity in the low energy (7 eV–25 eV) region of the Auger spectrum to electron emission following Auger decays of 2s holes in adsorbed oxygen and deep valence holes in graphene. We provide additional support to this conclusion by showing that most of the Auger electrons with energy less than ~ 25 eV are coincident with gamma photons with small Doppler shift (511 keV–512 keV) indicating that the primary electron whose annihilation resulted in low energy Auger electron emission had small momentum parallel to the gamma emission direction. On the other hand, majority of the Auger electrons measured in coincidence with the photons having maximum Doppler shift (515 keV–521 keV) were emitted following the decay of core holes (C 1s and O 1s). Furthermore, by selecting annihilation gamma photons coincident only with the O KVV (from surface adsorbed oxygen), C KVV (graphene), and Cu MVV (copper substrate) Auger electrons, we have also experimentally derived the energy spectrum of Doppler shifted gamma photons resulting from the annihilation of positrons with 1s electrons of O, 1s electrons of C and 3p electrons of Cu respectively. Model Doppler broadened gamma spectra produced using ab-initio calculations agree well with the experimentally derived line shapes. This demonstrates the ability of Auger-gamma coincidence method to experimentally resolve the Doppler broadened annihilation gamma spectrum from surfaces into its veiled electronic level constituents which has, heretofore, relied solely on theoretical analysis. Our results also demonstrate that the line shape of the Doppler broadened annihilation gamma peak reflect the chemical composition of the topmost atomic layer and can thus be used to characterize both external and inaccessible surfaces of porous materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Integration of the Kromek D3S Detector and Spot Robot For Secondary Inspections

Inspecting vehicles and containers for the presence of nuclear material is a challenging task for border control and security. When performed manually by inspectors, this task also has an associated risk of exposing the inspectors to unknown radiation. With the advent of agile, easy-to-program, quadruped robots like the Boston Dynamics Spot, automation of secondary inspection can improve the efficiency of the inspection process and alleviates the radiation risks to inspectors. In this project, Brookhaven National Laboratory and the University of Massachussetts at Lowell explored how to automate a simple secondary inspection mission. The Spot robot comes with its own software development kit (SDK) that allows clients/users to write custom code in the Python programming language to control the robot. Spot also has a payload computer called Spot-CORE, which runs the Ubuntu Linux operating system and allows users to integrate external sensors, such as a radiation detector, with Spot. In this study, the Kromek D3S detector has been integrated with Spot via the Spot-CORE, allowing Spot to capture gamma spectra and neutron counts for a specified acquisition period. Two custom routines, search and confirmation, have been developed and executed in this specified order. The search routine directs Spot to go around the nearest obstacle, e.g., vehicle and container, in a preset distance and step to collect gamma and neutron gross counts with the D3S detector. The radiation data and the robot location corresponding to each step are stored and fed to the confirmation routine at the end of the search. The confirmation routine then navigates Spot to the locations of the highest gamma or neutron counts to perform a long, e.g., one minute, measurement, and gives the operators the signature gamma spectra and neutron counts at the hotspots. This paper presents a detailed description of this automated system along with results of the preliminary tests in identifying the location and signature of a 137Cs radiation source in a vehicle.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2017

Isotope Identification

The objective of this training modules is to examine the process of using gamma spectroscopy for radionuclide identification; apply pattern recognition to gamma spectra; identify methods of verifying energy calibration; and discuss potential causes of isotope misidentification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Gamma-ray Spectra from a 3x3 CsPbBr 3 Array

CsPbBr 3 is a promising semiconductor material for X- and γ-ray detection at room temperature due to a wide bandgap of 2.3eV, high stopping power, and relatively high mobility-lifetime products of electrons and holes, and the capability of growing large crystals. In this paper we report on fabrication and testing of a 3.8 mm thick, 3 X 3 array with 1.2 mm pitch. Raw 137 Cs spectra were acquired with applied bias of 400 V, 500 V, and 600 V. Energy resolution of between 2 and 3 % FWHM at 662 keV was obtained from most pixels without any correction at room temperature. After 15 days under continuous bias at 600 V, no polarization effects were observed.

36 MATERIALS SCIENCE↗
DOE OSTI2023

A Better Method to Calculate Fuel Burnup in Pebble Bed Reactors Using Machine Learning

Burnup measurement is an important step in material control and accountancy (MC&A) at nuclear reactors, and may be done by examining gamma spectra of fuel samples. Traditional approaches rely on known correlations to specific photopeaks (e.g. 137 Cs) and operate via a standard linear regression method. However, the quality of these regression methods is limited even in the best case, and is significantly poorer at short fuel cool-down times, due to the elevated radiation background by short life-time isotopes, and self-shielding effect of the fuel. For practical operation of pebble bed reactors (PBRs), quick measurements (in minutes) and short cooling times (in hours) are required from a safety and security perspective. We investigated the efficacy and performance of machine learning (ML) methods to predict the burnup of the pebble fuel from full gamma spectra (rather than specific discrete photopeaks) and found a full-spectrum ML approach to far outperform baseline regression predictions in all measurement and cooling conditions - including in operational-like measurement conditions. We also performed model and data ablation experiments to determine the relative performance impact of our ML methods' capacity to model data nonlinearities and the inherent additional information in full spectra. Applying our ML methods, we found a number of surprising results, including improved accuracy at shorter fuel cooling times (the opposite of the norm), remarkable robustness to spectrum compression (via rebinning), and competitive burnup predictions even when using background signal only (i.e. explicitly omitting known isotope photopeaks).

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

Controlling radioisotope proportions when randomly sampling from Dirichlet distributions in PyRIID

As machine learning models for radioisotope quantification become more powerful, likewise the need for high-quality synthetic training data grows as well. For problem spaces that involve estimating the relative isotopic proportions of various sources in gamma spectra it is necessary to generate training data that accurately represents the variance of proportions encountered. In this report, we aim to provide guidance on how to target a desired variance of proportions which are randomly when using the PyRIID Seed Mixer, which samples from a Dirichlet distribution. We provide a method for properly parameterizing the Dirichlet distribution in order to maintain a constant variance across an arbitrary number of dimensions, where each dimension represents a distinct source template being mixed. We demonstrate that our method successfully parameterizes the Dirichlet distribution to target a specific variance of proportions, provided that several conditions are met. This allows us to follow a principled technique for controlling how random mixture proportions are generated which are then used downstream in the synthesis process to produce the final, noisy gamma spectra.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

FIER: Software for analytical modeling of delayed gamma-ray spectra

We report a new software package, the Fission Induced Electromagnetic Response (FIER) code, has been developed to analytically predict delayed γ-ray spectra following fission. FIER uses evaluated nuclear data and solutions to the Bateman equations to calculate the time-dependent populations of fission products and their decay daughters resulting from irradiation of a fissionable isotope. These populations are then used in the calculation of γ-ray emission rates to obtain the corresponding delayed γ-ray spectra. FIER output was compared to experimental data obtained by irradiation of a 235 U sample in the Godiva critical assembly. This investigation illuminated discrepancies in the input nuclear data libraries, showcasing the usefulness of FIER as a tool to address nuclear data deficiencies through comparison with experimental data. Finally, FIER provides traceability between γ-ray emissions and their contributing nuclear species, decay chains, and parent fission fragments, yielding a new capability for the nuclear science community.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Uranium Attenuated by a Wetland 50 Years after Release into a Stream

: Wetlands have several important roles in the hydrological cycle, including maintaining water quality by removing surface and groundwater contaminants. Over time, the wetlands themselves can become contaminated, posing a secondary environmental threat. The objective of this study was to calculate the inventory of uranium (U) remaining in a wetland 50 years after the Fuel Fabrication Facility on the Savannah River Site located in South Carolina released 43.5 Mg of U into the nearby environment. Over 232 700 gamma spectra and their associated global positioning system (GPS) coordinates were collected and collated into a map of the contaminated land area. Five core samples were also collected that contained U concentrations as high as 14 099 mg/kg (background levels are about 2.7 mg/kg U). The contaminated area was 278 000 m2 , and it contained 36.2 Mg U, about 83% of the U released. About 80% of the U in the wetland was concentrated in a former beaver pond, a 73 000 m2 area (26% of the contaminated area). This contaminated wetland area was almost 2 km from the source, indicating that it comprised unique hydro-biogeochemical properties for immobilizing the released U. To the best of our knowledge, this is the first data-rich study to quantify the long-term effectiveness of a wetland to immobilize inorganic contaminants. Significant environmental changes to the system, such as those associated with hydrology, forest fires, or anthropogenic land use, may alter the complex hydro-biogeochemical interactions necessary for the long-term immobilization of the U.

Contaminant inventory↗