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DOE OSTI2024

Radioisotope Identification with List-Mode Gamma Ray Data: A rigorous assessment on the value of temporal information applied to radioisotope identification.

This work explores the potential of utilizing temporal data from gamma-ray detectors, known as list-mode data, to enhance radioisotope identification. Traditional identification methods, which rely on full gamma-ray spectrum analysis, often require long dwell times and struggle with “confuser” sources, or spectra with similarly spaced spectral peaks. We hypothesize that by leveraging the probabilistic nature of nuclear decay and the time-encoded information from decay sequences and interactions with surrounding materials, we can improve classification accuracy over static spectral analysis. This research rigorously examines the temporal content of list-mode data through exploratory data analysis via correlation discovery and information theory. We further propose a basic classification model that can utilize spectral or temporal data (or both) to determine if the incorporation of temporal information can improve radioisotope identification. The findings suggest that the temporal information present in list-mode gamma-ray data has merit and should be further investigated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Detection and quantification of trace technetium in the presence of molybdenum using laser-induced breakdown spectroscopy

Technetium (Tc) is a very important element that is encountered in many aspects, from its presence in radioactive waste and its potential environmental impact to its use as a medical radioisotope. Its detection and quantification in liquid samples is traditionally cumbersome, involving detailed sample preparation and analysis by mass spectrometry or scintillation. This article demonstrates the first comprehensive emission spectral analysis of Tc from a liquid sample by immobilization in a polymer and analysis by laser-induced breakdown spectroscopy (LIBS). A survey of LIBS spectra was completed to identify the strongest analytical lines for quantification of trace Tc in the presence of Mo. The quantification of Tc in a Mo-containing matrix was selected because Tc radioisotopes are the daughter products of Mo isotope decay. The first reported calibration curves by LIBS are provided with limits of detection and quantification down to 0.710 µg mL −1 and 1.39 µg mL −1 , respectively. Ultimately, this study demonstrated the feasibility of trace Tc quantification using LIBS and will serve as a reference for future research related to monitoring this radioactive species.

Andrews, Hunter B. [Oak Ridge National Laboratory ↗

DOE OSTI2024

The Evaluation of Machine Learning Techniques for Isotope Identification Contextualized by Training and Testing Spectral Similarity

Precise gamma-ray spectral analysis is crucial in high-stakes applications, such as nuclear security. Research efforts toward implementing machine learning (ML) approaches for accurate analysis are limited by the resemblance of the training data to the testing scenarios. The underlying spectral shape of synthetic data may not perfectly reflect measured configurations, and measurement campaigns may be limited by resource constraints. Consequently, ML algorithms for isotope identification must maintain accurate classification performance under domain shifts between the training and testing data. To this end, four different classifiers (Ridge, Random Forest, Extreme Gradient Boosting, and Multilayer Perceptron) were trained on the same dataset and evaluated on twelve other datasets with varying standoff distances, shielding, and background configurations. A tailored statistical approach was introduced to quantify the similarity between the training and testing configurations, which was then related to the predictive performance. Wilcoxon signed-rank tests revealed that the OVR-wrapped XGB significantly outperformed the other algorithms, with confidence levels of 99.0% or above for the 133Ba, 60Co, 137Cs, and 152Eu sources. The findings from this work are significant as they outline techniques to promote the development of robust ML-based approaches for isotope identification.

domain adaptation↗

DOE OSTI2025

Dynamic mode decomposition for gyrokinetic eigenmode analysis

Dynamic mode decomposition (DMD) is a post-processing approach to decompose a complex time series into a set of modes via spectral analysis. DMD provides a new and powerful method to recover gyrokinetic drift-wave eigenfrequencies and eigenfunctions based only on the solution of the gyrokinetic-Maxwell initial value problem with almost no added cost to the initial value solver. In the present paper, DMD is applied to the CGYRO gyrokinetic code using a newly-developed CGYRO-DMD post-processor. CGYRO-DMD is numerically efficient, even on a single CPU. It does not set any restrictions on the plasma shape, beta (ratio of the plasma pressure to the magnetic field pressure), collisionality or number of species, and allows one to resolve numerous eigenmodes, even of comparable growth rates. In addition, DMD is not limited to unstable modes, but rather can capture stable and unstable branches simultaneously. In this work, we illustrate the accuracy of DMD through gyrokinetic analysis of mode transition for electromagnetic drift wave instabilities.

drift-wave eigenmodes↗

DOE OSTI2020

GADRAS Batch Inject Tool User Guide

Gamma Detector Response and Analysis Software (GADRAS) is used by the radiation detection and emergency response community to perform modeling and spectral analysis for gamma detector systems. Built into GADRAS is the ability to define a detector, geometry, background characteristics and source composition to generate synthetic spectra for drills and exercises (injects). Consequence Management is currently in development of a sample result data simulator tool in which a deposition model is probed for source conditions at moments in time and locations in space. These values are used to generate realistic sample results for use in drills and exercises. In addition to sample results, there is a need to simulate the actual spectra that would be observed in the field by downlooking HPGe instruments given a deposition activity. This way, the FRMAC Gamma Spectroscopist can practice their process of generating quantified results from spectra on realistic data as well. Recognizing the decades of work done in GADRAS to accurately generate synthetic spectra, this team decided to build a link between the new simulator and GADRAS to generate these spectra quickly and easily. The simulator tool will generate a file that specifies the name of the spectra, its location, date/time of measurement, duration of measurement, height off the ground, and the deposition activity and age for every radionuclide in the simulation. Then, a new tool within the Inject Tab of GADRAS was developed to read in this file given a detector selection and generate In-Situ spectra for each row in the file in any file format the user chooses. This way, simulation cell staff can take these files and then upload them to the appropriate data system (RAMS or RadResponder) for use during drills and exercises. An advanced feature of this tool allows for generating any spectra given an appropriate model and mapping of source to model layer in the batch inject tool. This way, spectra from field sample counts, mobile laboratories, or even fixed laboratories can be generated in bulk given an estimate of the radioactivity concentration or total radioactivity in an import file. This expands the capabilities of this tool a great deal and will make it a more useful tool for CM and others to help estimate detector response for nearly any situation. This user guide will explain the steps needed to perform a batch inject file generation.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2021

Studying Interfacial Dark Reactions of Glyoxal and Hydrogen Peroxide Using Vacuum Ultraviolet Single Photon Ionization Mass Spectrometry

Aqueous secondary organic aerosol (aqSOA) formation from volatile and semivolatile organic compounds at the air–liquid interface is considered as an important source of fine particles in the atmosphere. However, due to the lack of in situ detecting techniques, the detailed interfacial reaction mechanism and dynamics still remain uncertain. In this study, synchrotron-based vacuum ultraviolet single-photon ionization mass spectrometry (VUV SPI-MS) was coupled with the System for Analysis at the Liquid Vacuum Interface (SALVI) to investigate glyoxal dark oxidation products at the aqueous surface. Mass spectral analysis and determination of appearance energies (AEs) suggest that the main products of glyoxal dark interfacial aging are carboxylic acid related oligomers. Furthermore, the VUV SPI-MS results were compared and validated against those of in situ liquid time-of-flight secondary ion mass spectrometry (ToF-SIMS). The reaction mechanisms of the dark glyoxal interfacial oxidation, obtained using two different approaches, indicate that differences in ionization and instrument operation principles could contribute to their abilities to detect different oligomers. Therefore, the mechanistic differences revealed between the VUV SPI-MS and ToF-SIMS indicate that more in situ and real-time techniques are needed to investigate the contribution of the air–liquid interfacial reactions leading to aqSOA formation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

The Vertical Structure of Turbulence Kinetic Energy Near the Arctic Sea‐Ice Surface

Atmospheric turbulence over the Arctic sea-ice surface has been understudied due to the lack of observational data. In this study, we focus on the turbulence kinetic energy (TKE) over sea ice and distinguish its two different vertical structures, the “Surface” type and the “Elevated” type, using observations during the Multidisciplinary drifting Observatory for the Study of Arctic Climate expedition (MOSAiC). The “Surface” type has the maximum TKE near the surface (at 2 m), while the “Elevated” type has the maximum TKE at a higher level (6 m). The TKE budget analysis indicates that the “Elevated” type is caused by the increased shear production of TKE at 6 m. In addition, spectral analysis reveals that the contribution to TKE by horizontal large eddies is enhanced in the “Elevated” type. Finally, how the vertical structure of TKE affects the parameterization of turbulent momentum flux is discussed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Interpretable machine learning models classify minerals via spectroscopy

Developing methods to identify mineral species confidently and rapidly from Raman spectral analysis is critical to numerous fields. Traditionally, analysis relies on pattern matching the Raman spectrum of an unknown dataset with a supporting library of well-characterized spectral data, which may prove difficult for environmental samples that are poorly crystalline or phase mixtures. Here, we developed interpretable machine learning models that can classify uranium minerals by secondary oxyanion chemistry and other physicochemical properties based solely on Raman spectra. This new ML method produces a mineral profile of physical and chemical properties for an unknown sample and can rapidly classify or identify unknown minerals from Raman data, without the need for an exact pattern match in a spectral library. Training models are validated by 1. Strong correlation of high confidence model regions with published spectroscopic assignments and 2. Correct classification of a mineral not present in training data. Training data are from the Compendium of Uranium Raman and Infrared Experimental Spectra and available crystallographic information files within the open-source Smart Spectral Matching scientific framework. Physically meaningful classifier models can rapidly identify key structural and chemical information about unknown uranium minerals and the overall methodology is broadly applicable for mineral phases.

Machine learning↗

DOE OSTI2022

The Physical Properties of Low-redshift FeLoBAL Quasars. III. The Location and Geometry of the Outflows

We present continued analysis of a sample of low-redshift iron low-ionization broad-absorption-line quasars (FeLoBALQs). Choi et al. presented SimBAL spectral analysis of broad-absorption-line (BAL) outflows in 50 objects. Leighly et al. analyzed the optical emission lines of 30 of those 50 objects and found that they are characterized by either a high accretion rate (L Bol /L Edd > 0.3) or low accretion rate (0.03 < L Bol /L Edd < 0.3). We report that the outflow velocity is inversely correlated with the BAL location among the high-accretion-rate objects, with the highest velocities observed in parsec-scale outflows. In contrast, the low-Eddington-ratio objects showed the opposite trend. We confirmed the known relationship between the outflow velocity and L Bol /L Edd and found that the scatter plausibly originates in the force multiplier (launch radius) in the low(high)-accretion-rate objects. A log volume filling factor between –6 and –4 was found in most outflows but was as high as –1 for low-velocity compact outflows. We investigated the relationship between the observed [O III ] emission and that predicted from the BAL gas. We found that these could be reconciled if the emission-line covering fraction depends on the Seyfert type and BAL location. The difference between the predicted and observed [O III ] luminosity is correlated with the outflow velocity, suggesting that [O III ] emission in high-Eddington-ratio objects may be broad and hidden under Fe ii emission. We suggest that the physical differences in the outflow properties as a function of location in the quasar and accretion rate point to different formation, acceleration, and confinement mechanisms for the two FeLoBALQ types.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Efficient analysis routines for single and double peaked Type 2 AGN spectra

Driven by the imminent need to rapidly process and classify millions of AGN spectra drawn from next generation astronomical facilities, we present a spectral fitting routine for Type 2 AGN spectra optimized for high volume processing, using the quasar spectral fitting library (qsfit). We analyse an optically selected sample of 813 luminous Type 2 AGN spectra at z < 0.83 from the Sloan Digital Sky Survey (SDSS) to qualify its performance. We report a median narrow line H α/H β Balmer decrement of 4.5 ± 0.8, alluding to the presence of dust in the narrow line region (NLR). We publish a specialized QSFIT fitting routine for high signal-to-noise ratio spectra and general fitting routine for double peaked Type 2 AGN spectra applied on a subsample of 45 spectra from our parent sample. We report a median red and blue peak velocity separation of 390 ± 60 kms −1 . No trend is found for red or blue peaks to exhibit systematically different luminosity or ionization properties. Emission line diagnostics show that the double peaks in all sources are illuminated by an AGN-powered ionizing continuum. Finally, we examine the morphology of host galaxies of our double peaked sample. We find double peaked Type 2 AGN reside in merging systems at a comparable frequency to single peaked AGN. This suggests that the double peaked AGN phenomenon is likely to have a bi-conical outflow origin in the majority of cases. We publicly release the code used for spectral analysis and produced catalogues used in this work.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

The X-ray view of optically selected dual AGN

We present a study of optically selected dual Active Galactic Nuclei (AGN) with projected separations of 3–97 kpc. Using multiwavelength (MWL) information (optical, X-ray, mid-IR), we characterized the intrinsic nuclear properties of this sample and compared them with those of isolated systems. Among the 124 X-ray-detected AGN candidates, 52 appear in pairs and 72 as single X-ray sources. Through MWL analysis, we confirmed the presence of the AGN in >80 per cent of the detected targets in pairs (42 out of 52). X-ray spectral analysis confirms the trend of increasing AGN luminosity with decreasing separation, suggesting that mergers may have contributed to triggering more luminous AGN. Through X-ray/mid-IR ratio versus X-ray colours, we estimated a fraction of Compton-thin AGN (with 10 22 cm −2 < N H < 10 24 cm −2 ) of about 80 per cent, while about 16 per cent are Compton-thick sources (with N H > 10 24 cm −2 ). These fractions of obscured sources are larger than those found in samples of isolated AGN, confirming that pairs of AGN show higher obscuration. This trend is further confirmed by comparing the de-reddened [O III ] emission with the observed X-ray luminosity. However, the derived fraction of Compton-thick sources in this sample at the early stages of merging is lower than that reported for late-merging dual-AGN samples. Comparing N H from X-rays with that derived from E(B − V ) from narrow-line regions, we found that the absorbing material is likely to be associated with the torus or broad-line regions. We also explored the X-ray detection efficiency of dual-AGN candidates, finding that, when observed properly (at on-axis positions and with long exposures), X-ray data represent a powerful way to confirm and investigate dual-AGN systems.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Optical polarization and spectral properties of the hydrogen-poor superluminous supernovae SN 2021bnw and SN 2021fpl

ABSTRACT New optical photometric, spectroscopic, and imaging polarimetry data are combined with publicly available data to study some of the physical properties of the two hydrogen-poor superluminous supernovae (SLSNe) SN 2021bnw and SN 2021fpl. For each SLSN, the best-fitting parameters obtained from the magnetar model with Modular Open-Source Fitter for Transients do not depart from the range of parameter obtained on other SLSNe discussed in the literature. A spectral analysis with SYN++ shows that SN 2021bnw is a W type, fast evolver, while SN 2021fpl is a 15bn type, slow evolver. The analysis of the polarimetry data obtained on SN 2021fpl at four epochs (+1.8, +20.6, +34.1, and +43.0 d, rest frame) shows >3σ polarization detections in the range of 0.8–1 per cent. A comparison of the spectroscopy data suggests that SN 2021fpl underwent a spectral transition a bit earlier than SN 2015bn, during which, similarly, it could have underwent a polarization transition. The analysis of the polarimetry data obtained on SN 2021bnw does not show any departure from symmetry of the photosphere at an empirical diffusion time-scale of ≈2 (+81.1 d rest frame). This result is consistent with those on the sample of W-type SLSN observed at empirical diffusion time-scale ≤ 1 with that technique, even though it is not clear the effect of limited spectral windows varying from one object to the other. Measurements at higher empirical diffusion time-scale may be needed to see any departure from symmetry as it is discussed in the literature for SN 2017egm.

Astronomy & Astrophysics↗

DOE OSTI2022

Near-field radiative heat transfer between irregularly shaped dielectric particles modeled with the discrete system Green's function method

Near-field radiative heat transfer (NFRHT) between irregularly shaped dielectric particles made of SiO 2 and morphology characterized by Gaussian random spheres is studied. Particles are modeled using the discrete system Green's function (DSGF) approach, which is a volume integral numerical method based on fluctuational electrodynamics. This method is applicable to finite, three-dimensional objects, and all system interactions are defined independent of thermal excitation by a generalized system Green's function. The DSGF method is deemed suitable to model NFRHT between irregularly shaped particles after verification against the analytical solution for chains of two and three SiO 2 spheres. The NFRHT results reveal that geometric irregularity in particles leads to a reduction of the total conductance from that of comparable perfect spheres at vacuum separation distances smaller than the particle size, a regime in which NFRHT is a surface phenomenon. At vacuum separation distances larger than the particle size, NFRHT becomes a volumetric process, and the total conductance between irregularly shaped particles converges to that of comparable perfect spheres. Spectral analysis reveals, however, that particle irregularity leads to damping and broadening of resonances at all separation distances, thereby highlighting the importance of the DSGF method for spectral engineering in the near field. The reduced spectral coherence when particle size is larger than the vacuum separation distance is attributed to coupling of surface phonon-polaritons within the randomly generated, distorted particle features. For particle size smaller than the vacuum separation distance, resonance broadening and damping are linked with the multiple localized surface phonon modes supported by the composite spherical harmonic morphologies of the Gaussian random spheres. In conclusion, this paper has direct implications for thermal management of packed particle systems, with applications in radiative property control, electronics, energy conversion, and nanomanufacturing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Rovibronic molecular line list for the $N_2(C^3Π_u–B^3Π_g)$ second positive system

Here, a line list for the N second positive system, $B^3Π_g—C^3Π_u$, has been compiled using the PGOPHER spectral simulation software. The line list extends the number of vibrational states of the $B^3Π_g$ up to v=29 and a maximum rotational state of J=150 for simulation temperatures up to 7000 K. New electronic–vibrational transition moments were calculated using refined potential energy curves and a transition dipole moment with the DUO software. Comparisons to experimental data and the SPECAIR software have been used to validate the new line list. The results are available in ASCII ExoMol .state and .trans files and as a PGOPHER input file for use in spectral analysis.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Long‐Term Observations of Turbulence Vertical Velocity Spectra in a Convective Mixed Layer: Dependence on Land‐Surface Forcing in the U.S. Southern Great Plains

Doppler lidar vertical velocity retrievals were analyzed for the scale and structure of mixed-layer turbulence over a 7-year period, on fair-weather warm season days (442 cases) in the U.S. Southern Great Plains. Based on the hypothesized influence of land-surface forcing and updraft size on convective boundary layer clouds, a spectral analysis was performed to quantify effects of surface forcing (surface buoyancy flux, friction velocity, and evaporative fraction) on turbulence scale. Significant (order-of-magnitude) variations in spectral density were found in the energy-production subrange and mesoscale regimes. Integral scale decreased with increasing buoyancy flux (and Monin-Obukhov stability parameter), while spectral density in the energy-production subrange increased, implying a transition to buoyancy-driven cellular structures with narrower updrafts. The influence of stability parameter was limited to the neutral to convective transition, and could not explain the wide variation in spectral density in the mesoscale regime. However, high friction velocity (u* > 0.5 m s –1 ) was associated with larger integral scale (updraft width), and a greater portion of spectral density in the mesoscale regime. Lidar profiles and radar reflectivity for individual cases revealed evidence of roll and wave-like structures contributing to mesoscale variability on high friction velocity days, suggesting shear instabilities on days with wetter land surface conditions and smaller buoyancy flux. The role of friction velocity emphasizes the multivariate nature of surface influences on turbulence, and implies that variance-based turbulence closures may not be adequate for capturing effects of surface forcing on updraft size.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Wind Conditions for Solar Energy Facility Design Based on Field Measurements at Nevada Solar One

This study characterises near-surface wind conditions at the Nevada Solar One (NSO) concentrated solar power plant using two years of measurements from a 15-m mast located 30 m west of the solar arrays. The surrounding terrain is fairly flat within 3 km, but nearby solar photovoltaic (PV) and concentrated solar power (CSP) installations introduce strong directional wind inhomogeneity, which motivates a sector-based analysis that distinguishes undisturbed inflow from waked flow. The analysis uses data from three sonic anemometers to assess whether turbulence in the surface layer can be represented as Gaussian and whether standard surface-layer scaling remains valid below 10 m height. The roughness length and displacement height are estimated for twelve directional sectors under near-neutral wind conditions, and all three velocity components show departures from Gaussian behaviour. Spectral analysis indicates that the turbulence contains low-frequency fluctuations with amplitudes higher than those predicted by standard models such as the Kaimal model or the Simiu and Scanlan model. The study introduces a new turbulence spectral model based on the eddy-surface-layer framework to better represent near-surface wind turbulence. The analysis further quantifies the influence of the surrounding power plants on mean wind profiles, one-point spectra, and vertical coherence for all velocity components. The solar collector arrays located 30 m east of the mast significantly modify the turbulence structure, whereas PV installations situated a few hundred metres away have only a limited influence on the turbulence measured at the mast. These findings highlight the limitations of conventional turbulence models for near-surface wind over solar infrastructure and provide improved parameterisations to support the structural design. The implications for the structural response of parabolic troughs and PV modules to such turbulence remain uncertain and require further investigation.

14 SOLAR ENERGY↗

DOE OSTI2025

HD 143811 AB b: A Directly Imaged Planet Orbiting a Spectroscopic Binary in Sco-Cen

We present confirmation of HD 143811 AB b, a substellar companion to spectroscopic binary HD 143811 AB through direct imaging with the Gemini Planet Imager (GPI) and Keck NIRC2. HD 143811 AB was observed as a part of the GPI Exoplanet Survey in 2016 and 2019 and is a member of the Sco-Cen star formation region. The exoplanet is detected ∼430 mas from the host star by GPI. With two GPI epochs and one from Keck/NIRC2 in 2022, we confirm through common proper motion analysis that the object is bound to its host star. We derive an orbit with a semimajor axis of $64^{+32}_{-14}$ au and eccentricity $0.23^{+0.24}_{-0.16}$. Spectral analysis of the GPI H-band spectrum and NIRC2 L′ photometry provides additional proof that this object is a substellar companion. We compare the spectrum of HD 143811 AB b to PHOENIX stellar models and Exo-Radioactive-Convective Equilibrium Model (REM) exoplanet atmosphere models and find that Exo-REM models provide the best fits to the data. From the Exo-REM models, we derive an effective temperature of $1042^{+178}_{-132}$ K for the planet and translate the derived luminosity of the planet to a mass of 5.6 ± 1.1 M Jup assuming hot-start evolutionary models. HD 143811 AB b is the first directly imaged planet around a binary that is not on an ultrawide orbit. Future characterization of this object will shed light on the formation of planets around binary star systems.

Astronomy and AstroPhysics↗

DOE OSTI2024

Prediction of the Cu oxidation state from EELS and XAS spectra using supervised machine learning

Abstract Electron energy loss spectroscopy (EELS) and X-ray absorption spectroscopy (XAS) provide detailed information about bonding, distributions and locations of atoms, and their coordination numbers and oxidation states. However, analysis of XAS/EELS data often relies on matching an unknown experimental sample to a series of simulated or experimental standard samples. This limits analysis throughput and the ability to extract quantitative information from a sample. In this work, we have trained a random forest model capable of predicting the oxidation state of copper based on its L-edge spectrum. Our model attains an R 2 score of 0.85 and a root mean square error of 0.24 on simulated data. It has also successfully predicted experimental L-edge EELS spectra taken in this work and XAS spectra extracted from the literature. We further demonstrate the utility of this model by predicting simulated and experimental spectra of mixed valence samples generated by this work. This model can be integrated into a real-time EELS/XAS analysis pipeline on mixtures of copper-containing materials of unknown composition and oxidation state. By expanding the training data, this methodology can be extended to data-driven spectral analysis of a broad range of materials.

36 MATERIALS SCIENCE↗