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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Local primordial non-Gaussian bias from time evolution

Primordial non-Gaussianity (PNG) is a signature of fundamental physics in the early Universe that is probed by cosmological observations. Here, it is well known that the local type of PNG generates a strong signal in the two-point function of large-scale structure tracers, such as galaxies. This signal, often termed “scale-dependent bias” is a generic feature of modulation of gravitational structure formation by a large-scale mode. It is less well appreciated that the coefficient controlling this signal, b ϕ , is closely connected to the time evolution of the tracer number density. This correspondence between time evolution and local PNG can be simply explained for a universal tracer whose mass function only depends on peak height and, more generally, for nonuniversal tracers in the separate universe picture, which we validate in simulations. We also describe how to recover the bias of tracers subject to a survey selection function and perform a simple demonstration on simulated galaxies. Since the local PNG amplitude in n-point statistics ($f$ NL ) is largely degenerate with the coefficient b ϕ , this proof of concept study demonstrates that Galaxy survey data can allow for more optimal and robust extraction of local PNG information from upcoming surveys.

Sullivan, James M. [University of California, Berk↗
DOE OSTI2018

Monitoring and Modeling Caprock Integrity at the In Salah Carbon Dioxide Storage Site, Algeria

The In Salah gas development project, initiated in 2004, involves the long-term storage of waste carbon dioxide associated with natural gas production at several central Algerian fields. Rather then vent the extracted CO 2 into the atmosphere the operators, BP, Sonatrach, and Statoil chose to have the gas compressed, dehydrated, transported, and injected into a deep saline aquifer leg of the Krechba gas reservoir (Matheison et al. 2011). For this effort three horizontal state-of-the-art injection wells were drilled to a depth of 1500-1800m, using geo-steering technology to follow the roughly 20m thick reservoir. To maximize the injectivity, the wells were oriented perpendicular to the direction of maximum stress, the dominant fracture direction. Long-term plans were to store up to 17 million tonnes of carbon dioxide during the life of the program (Matheison et al. 2010). The project at In Salah was a pioneering effort in several respects and involved the investment of over 100 million dollars by the member companies. One feature that distinguishes In Salah from several other industrialscale CO 2 sequestration projects, such as Sleipner (Chadwick et al. 2012), Weyburn (White et al. 2011), Decatur (Kaven et al. 2014), and Aquastore (Worth et al. 2014) is the generally smaller storage volume in terms of overall reservoir thickness and lower average porosities of around 15%. With the exception of Weyburn, these other sites are characterized by generally thick sequences of high porosity sandstones. Therefore, one might expect that the pressure buildup near the wells could be larger at In Salah, with consequences for reservoir deformation and caprock strain. The role of fractures in providing storage and increasing reservoir permeability is one factor that would likely impact the pressure distribution around the well. However, the detailed effect of existing fractures on flow was not established prior to the injection at In Salah. The unique features of the In Salah storage site point to the importance of wellbore, geophysical, and geochemical monitoring to ensure that the integrity of the storage complex is maintained both during and after injection. In 2005 a Joint Industry Project (JIP) was set up, in an effort to use various geophysical, geochemical, and production techniques to monitor the fate of the injected carbon dioxide (Matheison et al. 2011). Here in this paper we describe the efforts made to monitoring the fate of the injected carbon dioxide, the state of the caprock, the estimated outcome of the storage effort, and some of the uncertainties that remain.

58 GEOSCIENCES↗
DOE OSTI2024

Cu site differentiation in tetracopper(I) sulfide clusters enables biomimetic N 2 O reduction

Copper clusters feature prominently in both metalloenzymes and synthetic nanoclusters that mediate catalytic redox transformations of gaseous small molecules. Such reactions are critical to biological energy conversion and are expected to be crucial parts of renewable energy economies. However, the precise roles of individual metal atoms within clusters are difficult to elucidate, particularly for cluster systems that are dynamic under operating conditions. Here, we present a metal site-specific analysis of synthetic Cu 4 (μ 4 -S) clusters that mimic the Cu Z active site of the nitrous oxide reductase enzyme. Leveraging the ability to obtain structural snapshots of both inactive and active forms of the synthetic model system, we analyzed both states using resonant X-ray diffraction anomalous fine structure (DAFS), a technique that enables X-ray absorption profiles of individual metal sites within a cluster to be extracted independently. Using DAFS, we found that a change in cluster geometry between the inactive and active states is correlated to Cu site differentiation that is presumably required for efficient activation of N 2 O gas. More precisely, we hypothesize that the Cu δ+ ∙∙∙Cu δ- pairs produced upon site differentiation are poised for N 2 O activation, as supported by computational modeling. These results provide an unprecedented level of detail on the roles of individual metal sites within the synthetic cluster system and how those roles interplay with cluster geometry to impact the reactivity function. We expect this fundamental knowledge to inform understanding of metal clusters in settings ranging from (bio)molecular to nanocluster to extended solid systems involved in energy conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Robust High-Throughput Phenotyping with Deep Segmentation Enabled by a Web-Based Annotator

The abilities of plant biologists and breeders to characterize the genetic basis of physiological traits are limited by their abilities to obtain quantitative data representing precise details of trait variation, and particularly to collect this data at a high-throughput scale with low cost. Although deep learning methods have demonstrated unprecedented potential to automate plant phenotyping, these methods commonly rely on large training sets that can be time-consuming to generate. Intelligent algorithms have therefore been proposed to enhance the productivity of these annotations and reduce human efforts. We propose a high-throughput phenotyping system which features a Graphical User Interface (GUI) and a novel interactive segmentation algorithm: Semantic-Guided Interactive Object Segmentation (SGIOS). By providing a user-friendly interface and intelligent assistance with annotation, this system offers potential to streamline and accelerate the generation of training sets, reducing the effort required by the user. Our evaluation shows that our proposed SGIOS model requires fewer user inputs compared to the state-of-art models for interactive segmentation. As a case study of the use of the GUI applied for genetic discovery in plants, we present an example of results from a preliminary genome-wide association study (GWAS) of in planta regeneration in Populus trichocarpa (poplar). We further demonstrate that the inclusion of a semantic prior map with SGIOS can accelerate the training process for future GWAS, using a sample of a dataset extracted from a poplar GWAS of in vitro regeneration. The capabilities of our phenotyping system surpass those of unassisted humans to rapidly and precisely phenotype our traits of interest. The scalability of this system enables large-scale phenomic screens that would otherwise be time-prohibitive, thereby providing increased power for GWAS, mutant screens, and other studies relying on large sample sizes to characterize the genetic basis of trait variation. Our user-friendly system can be used by researchers lacking a computational background, thus helping to democratize the use of deep segmentation as a tool for plant phenotyping.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Relating the long-term and short-term vertical deformation across a transect of the forearc in the central Mexican subduction zone

Earthquake-cycle deformation, which includes earthquake ruptures, interseismic strain, and transient slow slip events, spans spatial scales ranging from fractions of a meter to thousands of kilometers. Similarly, temporal scales range from seconds during an earthquake rupture to thousands of years of strain accumulation between earthquakes. We discuss results regarding the vertical crustal deformation associated with both slow and rapid crustal deformation across a transect of the central Mexican subduction forearc in the Guerrero seismic gap, where the Cocos plate underthrusts the North America plate. This sector of the subduction zone is characterized by a flat-slab geometry with zones of sharp bending-unbending of the slab, irregularly distributed seismicity, and exceptionally large slow slip events. We used the river network, topography, geomorphic features, and morphometry on a transect across the forearc to assess Quaternary crustal deformation. The Papagayo drainage network shows that the forearc has been uplifted since the late Cenozoic (~25 Ma), and that rates of uplift increased since the beginning of the Holocene. Uplift is not homogeneous but shows a trend of increase away from the coast. This vertical deformation is strongly influenced by subduction processes. Thus, the Papagayo River network is strongly controlled by Holocene earthquake cycle processes. This is particularly true for the southern section of the drainage basin, where E-W-striking left-lateral strike-slip faults with a vertical component offset the course of the main river. These faults are accommodating part of the oblique plate convergence at the Mexican subduction zone. We measured the height of a series of terraces and dated quartz extracts by optically stimulated luminescence, and we calculated long-term rates of uplift ranging from 0.5 to 4.9 mm/yr. We discuss associations of forearc topography, faults, and long-term crustal deformation with the Cocos slab geometry, distribution of slow slip events, and earthquake-cycle deformation.

58 GEOSCIENCES↗
DOE OSTI2023

Binding of uranyl cations to a Zr-based metal-organic framework by density functional theory

Zr-based metal–organic frameworks (Zr-MOFs) have been widely used as ion adsorbents for the removal or extraction of toxic and/or radionuclide species from aqueous solutions. However, the mechanisms by which uranyl cations (UO 2 2+ ) interact with Zr-MOFs have not been established. In this work, the nature of the bonding of uranyl cations with a Zr-MOF was determined using density functional theory for nineteen structurally distinct candidate complexes. Further, the results showed that in all cases the binding energy was of the order of 1.5 eV, but depended on the specific bonding site. The most stable structure involved coordination of the uranyl cation and two structurally distinct oxygens in the Zr-MOF metal node. It was also found that higher degree of deprotonation in Zr-MOF correlated with higher binding energy between the Zr-MOF and uranyl cations. These insights can aid in the design of Zr-MOFs with optimized features for efficient capture of uranyl cations.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Proton imaging of stochastic magnetic fields

Recent laser-plasma experiments report the existence of dynamically significant magnetic fields, whose statistical characterization is essential for a complete understanding of the physical processes these experiments are attempting to investigate. In this paper, we show how a proton-imaging diagnostic can be used to determine a range of relevant magnetic-field statistics, including the magnetic-energy spectrum. To achieve this goal, we explore the properties of an analytic relation between a stochastic magnetic field and the image-flux distribution created upon imaging that field. This ‘Kugland image-flux relation’ was previously derived under simplifying assumptions typically valid in actual proton-imaging set-ups. We conclude that, as with regular electromagnetic fields, features of the beam’s final image-flux distribution often display a universal character determined by a single, field-scale dependent parameter – the contrast parameter $\unicode[STIX]{x1D707}\equiv d_{s}/{\mathcal{M}}l_{B}$ – which quantifies the relative size of the correlation length $l_{B}$ of the stochastic field, proton displacements $d_{s}$ due to magnetic deflections and the image magnification ${\mathcal{M}}$ . For stochastic magnetic fields, we establish the existence of four contrast regimes, under which proton-flux images relate to their parent fields in a qualitatively distinct manner. These are linear, nonlinear injective, caustic and diffusive. The diffusive regime is newly identified and characterized. The nonlinear injective regime is distinguished from the caustic regime in manifesting nonlinear behaviour, but as in the linear regime, the path-integrated magnetic field experienced by the beam can be extracted uniquely. Thus, in the linear and nonlinear injective regimes we show that the magnetic-energy spectrum can be obtained under a further statistical assumption of isotropy. This is not the case in the caustic or diffusive regimes. We discuss complications to the contrast-regime characterization arising for inhomogeneous, multi-scale stochastic fields, which can encompass many contrast regimes, as well as limitations currently placed by experimental capabilities on one’s ability to extract magnetic-field statistics. Furthermore, the results presented in this paper are of consequence in providing a comprehensive description of proton images of stochastic magnetic fields, with applications for improved analysis of proton-flux images.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Improved Characterization and Modeling of Tight Oil Formations for CO 2 Enhanced Oil Recovery Potential and Storage Capacity Estimation

Tight oil formations such as those in the Bakken petroleum system are known to hold hundreds of billions of barrels of oil in place; however, the primary recovery factor for these plays is typically less than 10%. Tight oil formations, including the Bakken Formation, therefore, may be attractive candidates for enhanced oil recovery (EOR) using CO 2 . Multiphase fluid behavior and flow in fluid-rich shales can vary substantially depending on the size of pore throats, and properties such as fluid viscosity and density are much different in nanoscale pores than in macroscale pores. Thus it is critical to understand the nature and distribution of nano-, micro-, and macroscale pores and fracture networks. To address these issues, the Energy & Environmental Research Center (EERC) has been conducting a research program entitled “Improved Characterization and Modeling of Tight Oil Formations for CO 2 Enhanced Oil Recovery Potential and Storage Capacity Estimation.” The objectives of the project are 1) the use of advanced characterization methods to better understand and quantify the petrophysical and geomechanical factors that control CO 2 and oil mobility within tight oil formation samples, 2) the determination of CO 2 permeation and oil extraction rates in tight reservoir rocks and organic-rich shales of the Bakken, and 3) the integration of the laboratory-based CO 2 permeation and oil extraction data and the characterization data into geologic models and dynamic simulations to develop predictions of CO 2 storage resource and EOR in the Bakken tight oil formation. A combination of standard and advanced petrophysical characterization techniques were applied to characterize samples of Bakken Formation tight reservoir rock and shales from multiple wells. Techniques included advanced computer tomography (CT) imaging, scanning electron microscopy (SEM) techniques, whole-core and micro x-ray CT imaging, field emission (FE) SEM, and focused ion beam (FIB) SEM. Selected samples were also analyzed for geomechanical properties. X-ray CT imaging yielded information on the occurrence of fractures, bedding planes, fossils, and bioturbation in core, as well as data on bulk density and photoelectric factor logs, which were used to interpret porosity, organic content, and mineralogy. FESEM was used for characterization of nano- and microscale features, including nanoscale pore visualization and micropore and pore throat mineralogy. FIBSEM yielded micro- to nanoscale visualization of fracture networks, porosity and pore-size distribution, connected versus isolated porosity, and distribution of organics. Results from the characterization activities provide insight on nanoscale fracture properties, pore throat mineralogy and connectivity, rock matrix characteristics, mineralogy, and organic content. Laboratory experiments demonstrated that CO 2 can permeate the tight matrix of Bakken shale and nonshale reservoir samples and mobilize oil from those samples. Geologic models were created at scales ranging from the core plug to the reservoir, and dynamic simulations were conducted. The data from the characterization and laboratory-based activities were integrated into modeling research activities to determine the fundamental mechanisms controlling fluid transport in the Bakken, which support EOR scheme design and estimation of CO 2 storage potential in tight oil formations. Simulation results suggest a CO 2 storage resource estimate range of 169 million to 1.5 billion tonnes for the Bakken in North Dakota, possibly resulting in 1.8 billion to 16 billion barrels of incremental oil.

04 OIL SHALES AND TAR SANDS↗
DOE OSTI2018

Nondestructive hydrogen analysis of steam-oxidized Zircaloy-4 by wide-angle neutron scattering

In this study, a nondestructive neutron scattering method to precisely measure the hydrogen content in high-temperature steam-oxidized Zircaloy-4 cladding was developed. Zircaloy-4 cladding was used to produce hydrided specimens with hydrogen content up to ≈500 wppm. Following hydrogen charging, the hydrogen content of the hydrided specimens was measured using the vacuum hot extraction method, by which the samples with desired hydrogen concentrations were selected for the neutron study. The hydrided samples were then oxidized in steam up to ≈6.0wt. % at 1100°C. Optical microscopy shows that our hydriding procedure results in uniform distribution of circumferential hydrides across the wall thickness, and uniform oxide layers were formed on the sample surfaces by the steam oxidation. Small- and wide-angle neutron scattering were simultaneously performed to provide a quick (less than an hour per sample) measurement of the hydrogen content in various types of hydrided and oxidized Zircaloy-4. Our study demonstrates that the hydrogen in pre-oxidized Zircaloy-4 cladding can be measured very accurately by both small- and wide-angle neutron scattering. For steam-oxidized samples, the small-angle neutron scattering is contaminated with coherent scattering from additional structural features induced by the steam oxidation. However, the scattering intensity of the wide-angle neutron scattering increases proportionally with the hydrogen charged in the samples. The hydrogen content and wide-angle neutron scattering intensity are highly linearly correlated for the oxidized cladding samples examined in this work, and can be used to precisely determine the hydrogen content in steam-oxidized Zircaloy-4 samples. Hydrogen contents determined by neutron scattering of oxidation samples were also found to be consistent with the results of chemical analysis within acceptable margins for error.

36 MATERIALS SCIENCE↗
DOE OSTI2015

H ii REGION G46.5-0.2: THE INTERPLAY BETWEEN IONIZING RADIATION, MOLECULAR GAS, AND STAR FORMATION

H ii regions are particularly interesting because they can generate dense layers of gas and dust, elongated columns or pillars of gas pointing toward the ionizing sources, and cometary globules of dense gas where triggered star formation can occur. Understanding the interplay between the ionizing radiation and the dense surrounding gas is very important to explain the origin of these peculiar structures, and hence to characterize triggered star formation. G46.5-0.2 (G46), a poorly studied galactic H ii region located at about 4 kpc, is an excellent target for performing this kind of study. Using public molecular data extracted from the Galactic Ring Survey ({sup 13}CO J = 1–0) and from the James Clerk Maxwell Telescope data archive ({sup 12}CO, {sup 13}CO, C{sup 18}O J = 3–2, HCO{sup +}, and HCN J = 4–3), and infrared data from the GLIMPSE and MIPSGAL surveys, we perform a complete study of G46, its molecular environment, and the young stellar objects (YSOs) placed around it. We found that G46, probably excited by an O7V star, is located close to the edge of the GRSMC G046.34-00.21 molecular cloud. It presents a horse-shoe morphology opening in the direction of the cloud. We observed a filamentary structure in the molecular gas likely related to G46 and not considerable molecular emission toward its open border. We found that about 10′ to the southwest of G46 there are some pillar-like features, shining at 8 μm and pointing toward the H ii region open border. We propose that the pillar-like features were carved and sculpted by the ionizing flux from G46. We found several YSOs likely embedded in the molecular cloud grouped in two main concentrations: one, closer to the G46 open border consisting of Class II type sources, and another mostly composed of Class I type YSOs located just ahead of the pillar-like features, strongly suggesting an age gradient in the YSO distribution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Training custom light curve models of SN Ia subpopulations selected according to host galaxy properties

ABSTRACT Type Ia supernova (SN Ia) cosmology analyses include a luminosity step function in their distance standardization process to account for an observed yet unexplained difference in the post-standardization luminosities of SNe Ia originating from different host galaxy populations [e.g. high-mass ($M \gtrsim 10^{10} \, {\rm M}_{\odot }$) versus low-mass galaxies]. We present a novel method for including host-mass correlations in the SALT3 (Spectral Adaptive Light curve Template 3) light curve model used for standardizing SN Ia distances. We split the SALT3 training sample according to host-mass, training independent models for the low- and high-host-mass samples. Our models indicate that there are different average Si ii spectral feature strengths between the two populations, and that the average spectral energy distribution of SNe from low-mass galaxies is bluer than the high-mass counterpart. We then use our trained models to perform an SN cosmology analysis on the 3-yr spectroscopically confirmed Dark Energy Survey SN sample, treating SNe from low- and high-mass host galaxies as separate populations throughout. We find that our mass-split models reduce the Hubble residual scatter in the sample, albeit at a low statistical significance. We do find a reduction in the mass-correlated luminosity step but conclude that this arises from the model-dependent re-definition of the fiducial SN absolute magnitude rather than the models themselves. Our results stress the importance of adopting a standard definition of the SN parameters (x0, x1, c) in order to extract the most value out of the light curve modelling tools that are currently available and to correctly interpret results that are fit with different models.

Taylor, G. (ORCID:0000000157563259)↗
DOE OSTI2025

Machine-Learning-Based Multiscale Methods for 3D Modelling of Granular Materials by Incorporating History-Dependent State Variables

Over the past decades, the prevalence of machine learning (ML) methods has made the development of ML-based constitutive models for granular materials undoubtedly a popular subject. Numerous studies have been made to feature the loading path or history-dependent stress-strain response of granular media using neural networks. In this work, a novel finite element method (FEM)–ML multiscale approach was developed by incorporating internal variables to improve the simulation accuracy of 3D history-dependent granular materials for the first time. To this end, a surrogate constitutive model based on the single-step-based multi-layer perceptron (MLP) neural network was used to replace representative volume element (RVE) simulations conducted by the discrete element method (DEM) in the multiscale FEM–DEM approach. Although the prediction principle of the MLP aligns with the FEM algorithm, artificially added internal variables are required to differentiate the loading history. To address this issue, history variables associated with the Frobenius norm are proposed to be fed into the MLP coupled with the strain tensor to extract the history-dependent behaviour of granular assemblies. The developed FEM–ML approach was demonstrated in 3D conventional triaxial compression (CTC) simulations. Compared to the multiscale FEM–DEM approach, the proposed FEM–ML method exhibits a significantly improved computational efficiency.

granular materials↗
DOE OSTI2021

Molecular imaging of plant-microbe interactions on the Brachypodium seed surface

Plant growth-promoting rhizobacteria (PGPR) play a crucial role in biological control and pathogenic defense on and with-in plant tissues, however the mechanism(s) by which plants associate with PGPR to elicit such beneficial effects needs further study. Here, we present high mass resolution time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging of Brachypodium distachyon (Brachypodium) seeds with and without exposure to two model PGPR, i.e., Gram-negative Pseudomonas fluorescens SBW25::GFP (P.) and Gram-positive Arthrobacter chlorophenolicus A6::GFP (A.). Delayed image extraction was used to image PGPB-treated seed sections to reveal morphological changes. ToF-SIMS spectral compari-son, principal component analysis (PCA), and two-dimensional (2D) imaging show that the selected PGPR have different effects on the host seed surface, resulting in changes in chemical composition and morphology. Metabolite prod-ucts and biomarkers, such as flavonoids, phenolic com-pounds, fatty acids, and indole-3-acetic acid (IAA), were ob-served on the PGPR-treated seed surfaces. These compounds had different distributions on the Brachypodium seed surface for the two PGPR, indicating that the different bacteria elicited distinct responses from the host. Our results illustrate that ToF-SIMS is an effective tool to study plant-microbe interac-tions and to provide insightful information with submicrome-ter lateral resolution of the chemical distributions associated with morphological features, potentially offering a new way to study the mechanisms underlying beneficial roles of PGPR.

PGPR, Brachypodium distachyon, ToF-SIMS, metabolit↗
DOE OSTI2016

Experimental and CFD Studies of Coolant Flow Mixing within Scaled Models of the Upper and Lower Plenums of NGNP Gas-Cooled Reactors

A 1/16th scaled VHTR experimental model was constructed and the preliminary test was performed in this study. To produce benchmark data for CFD validation in the future, the facility was first run at partial operation with five pipes being heated. PIV was performed to extract the vector velocity field for three adjacent naturally convective jets at statistically steady state. A small recirculation zone was found between the pipes, and the jets entered the merging zone at 3 cm from the pipe outlet but diverged as the flow approached the top of the test geometry. Turbulence analysis shows the turbulence intensity peaked at 41-45% as the jets mixed. A sensitivity analysis confirmed that 1000 frames were sufficient to measure statistically steady state. The results were then validated by extracting the flow rate from the PIV jet velocity profile, and comparing it with an analytic flow rate and ultrasonic flowmeter; all flow rates lie within the uncertainty of the other two methods for Tests 1 and 2. This test facility can be used for further analysis of naturally convective mixing, and eventually produce benchmark data for CFD validation for the VHTR during a PCC or DCC accident scenario. Next, a PTV study of 3000 images (1500 image pairs) were used to quantify the velocity field in the upper plenum. A sensitivity analysis confirmed that 1500 frames were sufficient to precisely estimate the flow. Subsequently, three (3, 9, and 15 cm) Y-lines from the pipe output were extracted to consider the output differences between 50 to 1500 frames. The average velocity field and standard deviation error that accrued in the three different tests were calculated to assess repeatability. The error was varied, from 1 to 14%, depending on Y-elevation. The error decreased as the flow moved farther from the output pipe. In addition, turbulent intensity was calculated and found to be high near the output. Reynolds stresses and turbulent intensity were used to validate the data by comparing it with benchmark data. The experimental data gave the same pattern as the benchmark data. A turbulent single buoyant jet study was performed for the case of LOFC in the upper plenum of scaled VHTR. Time-averaged profiles show that 3,000 frames of images were sufficient for the study up to second-order statistics. Self-similarity is an important feature of jets since the behavior of jets is independent of Reynolds number and a sole function of geometry. Self-similarity profiles were well observed in the axial velocity and velocity magnitude profile regardless of z/D where the radial velocity did not show any similarity pattern. The normal components of Reynolds stresses have self-similarity within the expected range. The study shows that large vortices were observed close to the dome wall, indicating that the geometry of the VHTR has a significant impact on its safety and performance. Near the dome surface, large vortices were shown to inhibit the flows, resulting in reduced axial jet velocity. The vortices that develop subsequently reduce the Reynolds stresses that develop and the impact on the integrity of the VHTR upper plenum surface. Multiple jets study, including two, three and five jets, were investigated.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Elucidating Actinide–Pertechnetate and Actinide–Perrhenate Bonding via a Family of Th–TcO 4 and Th–ReO 4 Frameworks and Solutions

Technetium-99, a β-emitter produced from 235 U fission, poses a challenge for the nuclear industry due to co-extraction of pertechnetate (TcO 4 – ) with the actinides (An) during nuclear fuel reprocessing. Previous studies suggested that direct coordination of pertechnetate with An plays an important role in the coextraction process. However, few studies have provided direct evidence for An–TcO 4 – bonding in the solid state, and even fewer in solution. The present study describes synthesis and structural elucidation of a family of thorium(IV)-pertechnetate/perrhenate (ReO 4 – , nonradioactive surrogate) compounds, which is obtained by dissolution of thorium oxyhydroxide in perrhenic/pertechnic acid followed by crystallization, with or without heating. For reaction ratios of 3:1, 4:1, and 6:1 MO 4 – /Th(IV) (M = Tc, Re), the crystallized compounds reflect the same ratio, suggesting facile and flexible coordination. Furthermore, nine structures reveal 1-dimensional and 2-dimensional frameworks with varying topologies. While a multitude of compounds isolated from 4:1 (and 6:1) reaction solutions feature Th monomers linked by MO 4 – , the 3:1 reaction solution yielded the well-known dihydroxide-bridged thorium dimer, linked, and capped by MO 4 – . Density functional theory calculations on ReO 4 – /TcO 4 – isomorphs suggest similar bonding characteristics in the solid state, but experimental solution characterization noted differences. Specifically, small-angle X-ray scattering studies suggest the bonding of Th–TcO 4 – persists in solution, while Th–ReO 4 – bonding is less apparent.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Optical properties of nearly lattice-matched GaN/(Al,In)N quantum wells

We report a systematic study of the photoluminescence (PL) properties of a series of nearly lattice-matched (LM) GaN/(Al,In)N single quantum well (SQW) samples, with well thickness ranging from 1.5 to 5 nm, grown by metalorganic vapor phase epitaxy. Temperature dependent PL and time-resolved PL measurements reveal similar trends among the studied SQW samples, which also indicate strong localization effects. The observed PL energy behavior, akin to the S-shape, accompanied first by a narrowing and then a broadening of the PL line width with increasing temperature, closely resemble previous observations made on the more established (In,Ga)N/GaN QW system. The similar trends observed in the PL features of those two QW systems imply that the PL properties of LM GaN/(Al,In)N SQW samples are also governed by localized states. The effects of carrier transfer among these localization sites are clearly observed for the 3 nm thick QW, evidenced by an increasing PL intensity in the lower energy spectral window and a concomitant increase in the corresponding PL decay time. Time-resolved data corroborate the picture of strongly localized carriers and also indicate that above a well thickness dependent delocalization temperature carrier distribution across the localized sites reaches thermal equilibrium, as the PL decay times over different spectral regions converge to the same value. Based on the difference between the calculated QW ground state transition energy, obtained using the envelope wave function formalism, and the measured PL energy, a localization energy of at least a few hundreds of meV has been extracted for all of the studied SQW samples. This rather large value also implies that In-related localization effects are more pronounced in the GaN/(Al,In)N system with respect to those in the (In,Ga)N/GaN one for a similar In content.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Exoplanets in the Antarctic Sky. IV. Dual-band Photometry of Variables Found by the CSTAR-II Commissioning Survey at the North Sky

From the experiences learned in three decades of exoplanet search, wide-field transit surveys have proven to be one of the most effective ways to detect exoplanets. Wide field of view, however, suffers from high false-positive rates caused by blended eclipsing binaries. The chromaticity in eclipse depth is an effective feature to distinguish low-depth eclipsing binaries from transiting exoplanets, making multiple-band photometry follow-up advantageous before a target is passed onto more expensive spectroscopic follow-up. Moreover, a multiple-band photometric survey is itself a powerful method to find and vet planetary candidates and narrow down the candidate list of high-priority targets. In this work, we report the first results of a dual-band (Sloan-g and -i) wide-field photometry survey—the Chinese Small Telescope ARray II (CSTAR-II), an updated version of the original CSTAR. As a key component of the Chinese Exoplanet Searching Program from Antarctica, CSTAR-II has been tested thoroughly at a remote arctic site near Mohe during the winter of 2014. In total, 13,531 light curves with the best overall photometric precision of ∼3 mmag were extracted from 7721 stars in the Sloan-g and -i bands. Using a robust method, we have detected 63 variables, of which 48 are newly discovered. The dual-band photometric results as well as the stellar properties of the detected sources are provided in this work.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The northeast materials database for magnetic materials

The discovery of magnetic materials with high operating temperature ranges and optimized performance is essential for advanced applications. Current data-driven approaches are limited by the lack of accurate, comprehensive, and feature-rich databases. This study aims to address this challenge by using Large Language Models (LLMs) to create a comprehensive, experiment-based, magnetic materials database named the Northeast Materials Database (NEMAD), which consists of 67,573 magnetic materials entries (www.nemad.org). The database incorporates chemical composition, magnetic phase transition temperatures, structural details, and magnetic properties. Enabled by NEMAD, we trained machine learning models to classify materials and predict transition temperatures. Our classification model achieved an accuracy of 90% in categorizing materials as ferromagnetic (FM), antiferromagnetic (AFM), and non-magnetic (NM). The regression models predict Curie (Néel) temperature with a coefficient of determination (R 2 ) of 0.87 (0.83) and a mean absolute error (MAE) of 56K (38K). These models identified 25 (13) FM (AFM) candidates with a predicted Curie (Néel) temperature above 500K (100K) from the Materials Project. This work shows the feasibility of combining LLMs for automated data extraction and machine learning models to accelerate the discovery of magnetic materials.

Ferromagnetism↗