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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials (Second Annual Progress Report)

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of nuclear reactor parts. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which can introduce internal material flaws, such as pores and anisotropy. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to exposure to high temperature, radiation and corrosive environment in a nuclear reactor. Thermal tomography (TT) provides a capability for non-destructive evaluation of sub-surface defects in arbitrary size structures. Thermal tomography is a computational method for heat diffusion-based imaging of solids, which provides 3D visualization of data from flash thermography measurements. We investigate thermal tomography imaging and nondestructive evaluation of stainless steel and nickel super alloy metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing (AM) process. Metallic structures produced with LPBF contain defects, and there are limited capabilities to evaluate these structures non-destructively. Thermal tomography reconstruction of 3D apparent spatial effusivity provides information about AM structure geometry and internal material flaws. We study performance of thermal tomography in imaging of metallic structures through COMSOL computer simulations of transient heat transfer, and through reconstruction of data obtained from experimental measurements. Reconstruction of internal defects is investigated using a stainless steel 316L specimen with flat bottom hole (FBH) indentations, and Inconel 718 plate produced with laser powder bed fusion (LPBF) method, which contains imprinted hemispherical shape low density regions containing non-sintered metallic powder. The FBH’s have the same sizes as the imprinted defects in the LPBF specimens, but offer better imaging contrast. Thermal tomography reconstructions provide visualizations of internal defects, and allow for estimation of their sizes and locations. Detection sensitivity of TT is limited by noises. We investigate separation of signal from noise in thermography images using several machine learning (ML) methods, including new spatio-temporal blind source separation (STBSS) and spatio-temporal sparse dictionary learning (STSDL) methods. Performance of the ML methods is benchmarked using thermography data obtained from imaging stainless steel 316L and Inconel 718 specimens produced LPBF method with imprinted calibrated porosity defects. The ML methods are ranked by F-score and execution runtime. Finally, we investigate TT of AM stainless steel 316L specimen with imprinted internal porosity defects using relatively low-cost, small form factor infrared (IR) camera based on uncooled micro bolometer detector. Sparse coding related K-means singular value decomposition (SVD) machine learning, image processing algorithms are developed to improve quality of TT images through removal of Additive white Gaussian noise without blurring the images. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact TT can also be used for in-service nondestructive evaluation (NDE). With capability to perform in-service NDE of the AM component lifecycle, TT data can be used for development of a component digital twin.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

On the Stability Analysis of Astrophysical Cooling Functions

To model the temperature evolution of optically thin astrophysical environments at MHD scales, radiative and collisional cooling rates are typically either pretabulated or fit into a functional form and then input into MHD codes as a radiative loss function. Thermal balance requires estimates of the analogous heating rates, which are harder to calculate, and due to uncertainties in the underlying dissipative heating processes these rates are often simply parameterized. The resulting net cooling function defines an equilibrium curve that varies with density and temperature. Such cooling functions can make the gas prone to thermal instability (TI), which will cause departures from equilibrium. There has been no systematic study of thermally unstable parameter space for nonequilibrium states. Motivated by our recent finding that there is a related linear instability, catastrophic cooling instability, that can dominate over TI, here we carry out such a study. We show that Balbus instability criteria for TI can be used to define a critical cooling rate, Λ c , that permits a nonequilibrium analysis of cooling functions through the mapping of TI zones. We furthermore illustrate how thermal conduction modifies the shape of TI zones. Upon applying a Λ c -based stability analysis to coronal loop simulations, we find that loops undergoing periodic episodes of coronal rain formation are linearly unstable to catastrophic cooling instability, while TI is stabilized by thermal conduction.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

The updated ITPA global H-mode confinement database: description and analysis

The multi-machine ITPA Global H-mode Confinement Database has been upgraded with new data from JET with the ITER-like wall and ASDEX Upgrade with the full tungsten wall. This paper describes the new database and presents results of regression analysis to estimate the global energy confinement scaling in H-mode plasmas using a standard power law. Various subsets of the database are considered, focusing on type of wall and divertor materials, confinement regime (all H-modes, ELMy H or ELM-free) and ITER-like constraints. Apart from ordinary least squares, two other, robust regression techniques are applied, which take into account uncertainty on all variables. Regression on data from individual devices shows that, generally, the confinement dependence on density and the power degradation are weakest in the fully metallic devices. Using the multi-machine scalings, predictions are made of the confinement time in a standard ELMy H-mode scenario in ITER. The uncertainty on the scaling parameters is discussed with a view to practically useful error bars on the parameters and predictions. One of the derived scalings for ELMy H-modes on an ITER-like subset is studied in particular and compared to the IPB98(y,2) confinement scaling in engineering and dimensionless form. Transformation of this new scaling from engineering variables to dimensionless quantities is shown to result in large error bars on the dimensionless scaling. Regression analysis in the space of dimensionless variables is therefore proposed as an alternative, yielding acceptable estimates for the dimensionless scaling. The new scaling, which is dimensionally correct within the uncertainties, suggests that some dependencies of confinement in the multi- machine database can be reconciled with parameter scans in individual devices. This includes vanishingly small dependence of confinement on line-averaged density and normalized plasma pressure (β), as well as a noticeable, positive dependence on effective atomic mass and plasma triangularity. Extrapolation of this scaling to ITER yields a somewhat lower confinement time compared to the IPB98(y, 2) prediction, possibly related to the considerably weaker dependence on major radius in the new scaling (slightly above linear). Further studies are needed to compare more flexible regression models with the power law used here. In addition, data from more devices concerning possible ‘hidden variables’ could help to determine their influence on confinement, while adding data in sparsely populated areas of the parameter space may contribute to further disentangling some of the global confinement dependencies in tokamak plasmas.

Database↗
DOE OSTI2021

SSRS (Stochastic Soaring Raptor Simulator)

SSRS (Stochastic Soaring Raptor Simulator) is a generalizable, probabilistic, and predictive tool for wind energy developers, ecologists, wildlife managers and industry consultants to estimate the potential for soaring raptors to interact with operating wind turbines, without the need for site-specific data collection. Rapid expansion of wind energy development across the world has exposed the risk of turbine collisions for birds and bats. The risk to obligate soaring raptors such as golden eagles is of particular concern due to their small population and influence on ecological balance. Golden eagles rely heavily on updrafts to subsidize their flight, putting them in direct conflict with operational wind turbines that utilize the same wind resource. Understanding the behavior of soaring raptors with varying atmospheric conditions is crucial for predicting and mitigating the risk of turbine collision. This software contains a predictive movement model that simulates individual flight paths of golden eagles during updraft-subsidized long-distance flight, including migration. For a given set of atmospheric conditions, the model simulates thousands of eagles at turbine-scale spatial resolution (50m) to produce a relative presence density map. The simulated eagles rely on updrafts to pursue uninterrupted directional flight with minimal energy expenditure, following fluid-flow principles. The simulator includes a stochastic model of eagle behavior and a systematic method of accounting for spatiotemporal variations in atmospheric conditions. This framework only requires publicly available atmospheric data to estimate orographic and thermal updrafts, ensuring general usability.

Sandhu, Rimple↗
DOE OSTI2020

Magnetism and its coexistence with superconductivity in CaK(Fe 0.949 Ni 0.051 ) 4 As 4 : Muon spin rotation/relaxation studies

Here, the magnetic response of Ca K ( Fe 0.949 Ni 0.051 ) 4 As 4 was investigated by means of the muon spin rotation/relaxation. The long-range commensurate magnetic order sets in below the Néel temperature T N = 50.0 ( 5 ) K. The density-functional theory calculations have identified three possible muon stopping sites. The experimental data were found to be consistent with only one type of magnetic structure, namely, the long-range magnetic spin-vortex-crystal order with the hedgehog motif within the a b plane and the antiferromagnetic stacking along the c direction. The value of the ordered magnetic moment at T ≈ 3 K was estimated to be m Fe = 0.38 ( 11 ) μ B ( μ B is the Bohr magneton). A microscopic coexistence of magnetic and superconducting phases accompanied by a reduction of the magnetic order parameter below the superconducting transition temperature T c ≃ 9 K is observed. Comparison with 11, 122, and 1144 families of Fe-based pnictides points to existence of correlation between the reduction of the magnetic order parameter at T → 0 and the ratio of the transition temperatures T c / T N . Such correlations were found to be described by Machida's model for coexistence of itinerant spin-density-wave magnetism and superconductivity [K. Machida, J. Phys. Soc. Jpn. 50 , 2195 (1981) ; S. L. Bud'ko et al. , Phys. Rev. B 98 , 144520 (2018) ].

36 MATERIALS SCIENCE↗
DOE OSTI2025

Direct deflection of Millicharged radiation

Millicharged particles are generic in theories of dark sectors. A cosmic or local abundance of them may be produced by the early universe, stellar environments, or the decay or annihilation of dark matter/dark energy. Furthermore, if such particles are light, these production channels result in a background of millicharged radiation. We show that light-shining-through-wall experiments employing superconducting RF cavities can also be used as “direct deflection” experiments to search for this relativistic background. The millicharged plasma is first subjected to an oscillating electromagnetic field of a driven cavity, which causes charge separation in the form of charge and current perturbations. In turn, these perturbations can propagate outwards and resonantly excite electromagnetic fields in a well-shielded cavity placed nearby, enabling detection. We estimate that future versions of the existing Dark SRF experiment can probe orders of magnitude of currently unexplored parameter space, including millicharges produced from the Sun, the cosmic neutrino background, or other mechanisms that generate a thermal abundance with energy density as small as ~ 10$^{−4}$ that of the cosmic microwave background.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

System efficiency and power assessment of the all-aqueous copper thermally regenerative ammonia battery

Thermally regenerative ammonia batteries (TRABs) use low-temperature (T < 100 °C) heat to provide stationary energy and power with higher power densities and efficiency relative to other waste heat devices. TRABs are an active area of research in waste heat devices, but currently there is little consensus on what aspect of the system is limiting TRAB performance and what maximum efficiencies are possible. Experiments and numerical models were used here to examine the sensitivity of the battery and distillation column in a TRAB system to key operating variables, thereby establishing practical limits and identifying focus areas for improving performance. Battery power was eight times more sensitive to ohmic losses than kinetic and mass transfer losses, regardless of the operating temperature, and the peak power density was simulated to be 18.8 mW cm –2 at 75 °C. Theoretical energy efficiency limits were defined for a series of ammonia concentrations and operating pressures, ranging from 5 – 12%, which is 2–3 times higher than previous experimental estimations. Atmospheric pressure column operation used a larger amount of waste heat compared to sub-atmospheric pressure. It is estimated that the volume of the battery would take up 9.2m 3 for every 1% of the power output of a natural gas turbine, but with realistic improvements to cell conductivity, the size would reduce to 2.5 m 3 . Finally, the results presented in this work will help streamline future development by focusing on minimizing ohmic losses and provide specific data for full system evaluation of future TRABs.

25 ENERGY STORAGE↗
DOE OSTI2026

ROADRUNNER uranium nitride MiniFuel: Experimental design, fabrication and pre-irradiation baseline characterization for accelerated burnup testing

Uranium nitride (UN) is a promising fuel candidate for advanced reactor systems owing to its high uranium density and thermal conductivity; however, its qualification remains constrained by the scarcity of well-controlled irradiation performance data. Here, to address this limitation, the ROADRUNNER (Research On ADvancing the peRformance of UraNium Nitrides in Extreme enviRonments) campaign employs the MiniFuel platform in the High Flux Isotope Reactor (HFIR) to enable accelerated burnup irradiation testing under tightly controlled and largely isothermal conditions. This paper presents the experimental design, fuel fabrication, and pre-irradiation baseline characterization of the ROADRUNNER UN MiniFuel campaign. Thirty-six UN minidisc specimens were fabricated with systematically varied as-fabricated density (86–96% of theoretical density), carbon impurity content (961–5240 ppm), oxygen content (≤ ∼2000 ppm), and grain size (2.5–24 μm). The irradiation matrix spans nominal fuel temperatures of 873 K, 1173 K, and 1473 K and target burnups of 3.75%, 6.0%, and 7.5% fissions per initial metal atom (FIMA). Neutronic and thermal analyses were performed to define specimen-specific burnup accumulation and temperature histories, establishing the boundary conditions for subsequent in-pile behavior. Comprehensive pre-irradiation characterization—including dimensional metrology, density verification, impurity analysis, X-ray diffraction, Raman spectroscopy, scanning electron microscopy, X-ray computed tomography, and confocal profilometry—provides a detailed baseline for post-irradiation examination. Pre-irradiation data were further used to generate predictive estimates of fission gas release and swelling using existing empirical correlations. This quantitative comparison reveals substantial inter-model divergence at intermediate and elevated temperatures that exceeds propagated input uncertainties, highlighting structural gaps in the historical irradiation database. The ROADRUNNER irradiation campaign is currently underway in HFIR, with initial firs cycle completed in late 2025 and remaining targets scheduled through 2027. The experimental design and baseline dataset presented here establish the framework needed to interpret forthcoming post-irradiation measurements and to provide discriminating data for the validation and refinement of physics-based UN fuel performance models.

Lopes, Denise Adorno [Oak Ridge National Laborator↗
DOE OSTI2025

A multifrequency study of sub-parsec jets with the Event Horizon Telescope

Context. The 2017 observing campaign of the Event Horizon Telescope (EHT) delivered the first very long baseline interferometry (VLBI) images at the observing frequency of 230 GHz, leading to a number of unique studies on black holes and relativistic jets from active galactic nuclei (AGN). In total, eighteen sources were observed, including the main science targets, Sgr A* and M 87, and various calibrators. Sixteen sources were AGN.Aims. We investigated the morphology of the sixteen AGN in the EHT 2017 data set, focusing on the properties of the VLBI cores: size, flux density, and brightness temperature. We studied their dependence on the observing frequency in order to compare it with the Blandford-Königl (BK) jet model. In particular, we aimed to study the signatures of jet acceleration and magnetic energy conversion.Methods. We modeled the source structure of seven AGN in the EHT 2017 data set using linearly polarized circular Gaussian components (1749+096, 1055+018, BL Lac, J0132–1654, J0006–0623, CTA 102, and 3C 454.3) and collected results for the other nine AGN from dedicated EHT publications, complemented by lower frequency data in the 2–86 GHz range. Combining these data into a multifrequency EHT+ data set, we studied the dependences of the VLBI core component flux density, size, and brightness temperature on the frequency measured in the AGN host frame (and hence on the distance from the central black hole), characterizing them with power law fits. We compared the observations with the BK jet model and estimated the magnetic field strength dependence on the distance from the central black hole.Results. Our observations spanning event horizon to parsec scales indicate a deviation from the standard BK model, particularly in the decrease of the brightness temperature with the observing frequency. Only some of the discrepancies may be alleviated by tweaking the model parameters or the jet collimation profile. Either bulk acceleration of the jet material, energy transfer from the magnetic field to the particles, or both are required to explain the observations. For our sample, we estimate a general radial dependence of the Doppler factor δ ∝ r≤0.5. This interpretation is consistent with a magnetically accelerated sub-parsec jet. We also estimate a steep decrease of the magnetic field strength with radius B ∝ r−3, hinting at jet acceleration or efficient magnetic energy dissipation.Key words: techniques: interferometric / galaxies: active / galaxies: jets / galaxies: nuclei / quasars: general / quasars: supermassive black holes⋆⋆ Deceased.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Deep Learning and Likelihood Approaches for Viral Phylogeography Converge on the Same Answers Whether the Inference Model Is Right or Wrong

Abstract Analysis of phylogenetic trees has become an essential tool in epidemiology. Likelihood-based methods fit models to phylogenies to draw inferences about the phylodynamics and history of viral transmission. However, these methods are often computationally expensive, which limits the complexity and realism of phylodynamic models and makes them ill-suited for informing policy decisions in real-time during rapidly developing outbreaks. Likelihood-free methods using deep learning are pushing the boundaries of inference beyond these constraints. In this paper, we extend, compare, and contrast a recently developed deep learning method for likelihood-free inference from trees. We trained multiple deep neural networks using phylogenies from simulated outbreaks that spread among 5 locations and found they achieve close to the same levels of accuracy as Bayesian inference under the true simulation model. We compared robustness to model misspecification of a trained neural network to that of a Bayesian method. We found that both models had comparable performance, converging on similar biases. We also implemented a method of uncertainty quantification called conformalized quantile regression that we demonstrate has similar patterns of sensitivity to model misspecification as Bayesian highest posterior density (HPD) and greatly overlap with HPDs, but have lower precision (more conservative). Finally, we trained and tested a neural network against phylogeographic data from a recent study of the SARS-Cov-2 pandemic in Europe and obtained similar estimates of region-specific epidemiological parameters and the location of the common ancestor in Europe. Along with being as accurate and robust as likelihood-based methods, our trained neural networks are on average over 3 orders of magnitude faster after training. Our results support the notion that neural networks can be trained with simulated data to accurately mimic the good and bad statistical properties of the likelihood functions of generative phylogenetic models.

Evolutionary Biology↗
DOE OSTI2024

Quantum order by disorder in frustrated spin nanotubes

Here we investigate quantum order by disorder in a frustrated spin nanotube formed by wrapping a J1–J2 Heisenberg model at 45° around a cylinder. Using Schwinger boson theory and density matrix renormalization group (DMRG), we have computed the ground-state phase diagram to reveal a Z2 phase in which collinear spin stripes form a right- or left-handed helix around the nanotube. We have derived an analytic estimate for the critical η c = J 1 /2J 2 of the Z 2 -helical phase transition, which is in agreement with the DMRG results. By evaluating the entanglement spectrum and nonlocal string order parameters we discuss the topology of the Z 2 -helical phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Bulk viscosity from Urca processes: npeμ matter in the neutrino-trapped regime

In this work, we extend our previous study of the bulk viscosity of hot and dense npe matter induced by the Urca process in the neutrino trapped regime to npeμ matter by adding the muonic Urca processes as well as the purely leptonic electroweak processes involving electron-muon transition. Here, the nuclear matter is modeled in a relativistic density functional approach with two different parametrizations which predict neutrino dominated matter (DDME2 model) and anti-neutrino dominated matter (NL3 model) at temperatures for which neutrinos/anti-neutrinos are trapped. In the case of neutrino-dominated matter, the main equilibration mechanism is lepton capture, whereas in the case of antineutrino-dominated matter this is due to neutron decay. We find that the equilibration rates of Urca processes are higher than that of the pure leptonic processes, which implies that the Urca bulk viscosity can be computed with the leptonic reactions assumed to be frozen. We find that the bulk viscosity decreases with temperature as ζ~T –2 at moderate temperatures. At high temperatures this scaling breaks down by sharp drops of the bulk viscosity close to the temperature where the proton fraction is density-independent and the matter becomes scale-invariant. This occurs also when the matter undergoes a transition from the antineutrino-dominated regime to the neutrino-dominated regime where the bulk viscosity attains a local maximum. We also estimate the bulk viscous dissipation timescales and find that these are in the range ≳ 1 s for temperatures above the neutrino trapping temperature. These timescales would be relevant only for long-lived objects formed in binary neutron star mergers and hot proto-neutron stars formed in core-collapse supernovas.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Low-Cost Radiant Heater for Rapid Response, High-Temperature Heating

High-temperature processing has an irreplaceable role in many research and industrial applications. Despite remarkable development spanning over a century, the pursuit of even higher thermal flux density and more rapid thermal transients has not slowed down. As part of the ongoing energy evolution, many industrial applications are transitioning from direct combustion of fossil fuels as primary energy sources to increasing electrification, capable of adapting to renewable power grids. Thus, there is an emerging need for electrical heaters that can replace burners and supply the heat demand, especially at the highest temperatures. In this study, we report on a radiant heater design that can achieve cyclic heating/cooling rates of up to 400 K min –1 and a temperature range in excess of 1,800 K, comparable to those of commercial infrared gold image furnaces, at high surface and volumetric power densities. The heater consists of a modular unit of incandescent tungsten filament and is enclosed in an evacuated ceramic envelope, chemically inert, tolerant of thermal shock, and impervious to gasses. The material and manufacture cost of such heaters, which is estimated at ~$0.05/W, is less than 0.03% of that for infrared gold image furnaces, which is at >$2/W. Tests of more than 10,000 demanding cycles (high temperature and high heating/cooling rate) over 350 h of total operational time and in different temperature ranges confirm the robust performance of radiant heater prototypes. The design is widely applicable to high-temperature reactor and furnace designs. In thermochemistry research and practice, these radiant heaters could offer multiple benefits compared to solar simulators, lasers, infrared gold furnaces, ceramic heaters, or direct concentration of solar input.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Three-dimensional signatures of self-similarity in a high-energy-density plasma shear-driven mixing layer

A hydrodynamic shear mixing layer experiment at the National Ignition Facility had previously demonstrated Eulerian scaling of integrated, late-time quantities, including turbulent kinetic energy. In this manuscript, the experiment is repeated with new materials. In this work, using the new dataset, we demonstrate that Euler-number scalings hold not just for late time, but dynamically throughout the experiment, for measurements in all three spatial dimensions. Incorporating the dynamic scaling leads to an enhanced calculation that the heavier of the two scaled experiments has approached three generations of mergers of its primary instability's structures and a consistent observation of such a merger in action in the lighter of the two scaled experiments. Furthermore, the improved scrutiny of the time evolution of instability structures leads to sharper estimates of turbulent kinetic energy, including a demonstration of different behaviors correlating with surface roughness (quantitatively consistent with transitions between laminar and turbulent initial states), as predicted by a Reynolds-averaged turbulent model, which evidently correctly handles the differing shock-roughness interactions to drive its internal state of the model into different regimes. Altogether, a picture arises of the analytical improvements in treating these variations (of times, densities, and roughnesses) as a unified whole and of multiple ways by which deviations from the scaling could indicate an onset of non-hydrodynamic behavior. Such deviations were not expected for these experiments (which models correctly indicated would remain hydrodynamic) but could be introduced by, for example, imposing external fields or increasing drive energy to test conditions relevant to inertial confinement fusion or other high-energy-density experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

How galaxies populate halos in extreme density environments: An analysis of the halo occupation distribution in SDSS

Recent works have shown that the properties of galaxy populations in simulated dark matter halos vary with large-scale environments. These results suggest a variation in the halo occupation distribution (HOD) in extreme density environments since the dynamical and astrophysical conditions prevailing in these regions may significantly affect the formation and evolution of their halos and residing galaxies, influencing the mean number of satellite galaxies. To analyse these effects, we identify cosmic voids and future virialised structures (FVS) in the Sloan Digital Sky Server Data Release 12 (SDSS-DR12) and estimate the HOD within these super-structures using group catalogues as dark matter halo proxies. Our goal is to use observational galaxy data to characterise the HOD within cosmic voids and FVS, explore the different properties of these galaxies populations and compare them with the general results outside these super-structures. We use a publicly available observational galaxy catalogue with information on redshifts, positions, magnitudes and other astrophysical features to build a volume complete galaxy sample and identify cosmic voids and FVS. Using a publicly available galaxy group catalogue as a proxy to dark matter halos, we compute the HOD within both types of super-structures for different absolute magnitude thresholds. We also study the dependence on the results on the main void and FVS properties, density and volume. We also analysed the main characteristics of the stellar content of galaxies inside these extreme-density regions such as the mean stellar age and the galaxy light concentration index. In all cases, we compare the results with those derived from the Field sample, defined by objects outside both types of environments. Inside cosmic voids, we find a strong decrease in HOD concerning the Field results. In the most extreme cases, the mean number of satellites fall to ~ 50%. Inside FVS, the HOD shows a significant increase to the Field, with a ~ 40% excess in the mean number of satellites. These results are present for the different galaxy luminosity ranges explored. In both environments, the differences with respect to the Field increases for the extreme values of the density environments. However, we obtain no signs of variations related to intrinsic characteristics of the super-structures, indicating that the effects depend mainly on the density of the large-scale environment. In addition, we find that the cumulative distribution of the mean age of stars of the central galaxy also varies in the different regions, this suggests that the history of the formation of the dark matter halos may be different. Finally, we explore the HOD for the 25% youngest (oldest) galaxies, based on the mean age of their stars. We find that for the low-mass groups the youngest galaxies are only present inside voids and are generally central galaxies. On the other hand, for the high-mass groups the FVS environments show the same increase in the HOD concerning the Field as previously mentioned. We find that cosmic voids lack a significant fraction of galaxies with the oldest stellar population.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Bayesian Estimation of the D(p,γ) 3 He Thermonuclear Reaction Rate

Big bang nucleosynthesis (BBN) is the standard model theory for the production of the light nuclides during the early stages of the universe, taking place for a period of about 20 minutes after the big bang. Deuterium production, in particular, is highly sensitive to the primordial baryon density and the number of neutrino species, and its abundance serves as a sensitive test for the conditions in the early universe. The comparison of observed deuterium abundances with predicted ones requires reliable knowledge of the relevant thermonuclear reaction rates, and their corresponding uncertainties. Recent observations reported the primordial deuterium abundance with percent accuracy, but some theoretical predictions based on BBN are at tension with the measured values because of uncertainties in the cross section of the deuterium-burning reactions. In this work, we analyze the S-factor of the D(p,γ) 3 He reaction using a hierarchical Bayesian model. We take into account the results of eleven experiments, spanning the period of 1955--2021; more than any other study. We also present results for two different fitting functions, a two-parameter function based on microscopic nuclear theory and a four-parameter polynomial. Furthermore, our recommended reaction rates have a 2.2\% uncertainty at 0.8~GK, which is the temperature most important for deuterium BBN. Differences between our rates and previous results are discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Experimental evidence of early-time saturation of the ion-Weibel instability in counterstreaming plasmas of CH, Al, and Cu

The collisionless ion-Weibel instability is a leading candidate mechanism for the formation of collisionless shocks in many astrophysical systems, where the typical distance between particle collisions is much larger than the system size. Multiple laboratory experiments aimed at studying this process utilize laser-driven (I≳10 15 W/cm 2 ), counterstreaming plasma flows (V≲ 2000 km/s) to create conditions unstable to Weibel-filamentation and growth. This technique intrinsically produces temporally varying plasma conditions at the midplane of the interaction where Weibel-driven B fields are generated and studied. Experiments discussed herein demonstrate robust formation of Weibel-driven B fields under multiple plasma conditions using CH, Al, and Cu plasmas. Linear theory based on benchmarked radiation-hydrodynamic FLASH calculations is compared with Fourier analyses of proton images taken ~5–6 linear growth times into the evolution. Our new analyses presented here indicate that the low-density, high-velocity plasma-conditions present during the first linear-growth time (~300–500 ps) sets the spectral characteristics of Weibel filaments during the entire evolution. It is shown that the dominant wavelength (~300 μm) at saturation persists well into the nonlinear phase, consistent with theory under these experimental conditions. However, estimates of B-field strength, while difficult to determine accurately due to the path-integrated nature of proton imaging, are shown to be in the ~10–30 T range, an order of magnitude above the expected saturation limit in homogenous plamas but consistent with enhanced B fields in the midplane due to temporally varying plasma conditions in experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Reaction Chemistry at Discrete Organometallic Fragments on Black Phosphorus

Abstract Black phosphorus (bP) is a two‐dimensional van der Waals material unique in its potential to serve as a support for single‐site catalysts due to its similarity to molecular phosphines, ligands quintessential in homogeneous catalysis. However, there is a scarcity of synthetic methods to install single metal centers on the bP lattice. Here, we demonstrate the functionalization of bP nanosheets with molecular Re and Mo complexes. A suite of characterization techniques, including infrared, X‐ray photoelectron and X‐ray absorption spectroscopy as well as scanning transmission electron microscopy corroborate that the functionalized nanosheets contain a high density of discrete metal centers directly bound to the bP surface. Moreover, the supported metal centers are chemically accessible and can undergo ligand exchange transformations without detaching from the surface. The steric and electronic properties of bP as a ligand are estimated with respect to molecular phosphines. Sterically, bP resembles tri(tolyl)phosphine when monodentate to a metal center, and bis(diphenylphosphino)propane when bidentate, whereas electronically bP is a σ‐donor as strong as a trialkyl phosphine. This work is foundational in elucidating the nature of black phosphorus as a ligand and underscores the viability of using bP as a basis for single‐site catalysts.

Mitra, Kendahl L. Walz↗