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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

SDSS-IV DR17: final release of MaNGA PyMorph photometric and deep-learning morphological catalogues

ABSTRACT We present the MaNGA PyMorph photometric Value Added Catalogue (MPP-VAC-DR17) and the MaNGA Deep Learning Morphological VAC (MDLM-VAC-DR17) for the final data release of the MaNGA survey, which is part of the SDSS Data Release 17 (DR17). The MPP-VAC-DR17 provides photometric parameters from Sérsic and Sérsic+Exponential fits to the two-dimensional surface brightness profiles of the MaNGA DR17 galaxy sample in the g, r, and i bands (e.g. total fluxes, half-light radii, bulge-disc fractions, ellipticities, position angles, etc.). The MDLM-VAC-DR17 provides deep-learning-based morphological classifications for the same galaxies. The MDLM-VAC-DR17 includes a number of morphological properties, for example, a T-Type, a finer separation between elliptical and S0, as well as the identification of edge-on and barred galaxies. While the MPP-VAC-DR17 simply extends the MaNGA PyMorph photometric VAC published in the SDSS Data Release 15 (MPP-VAC-DR15) to now include galaxies that were added to make the final DR17, the MDLM-VAC-DR17 implements some changes and improvements compared to the previous release (MDLM-VAC-DR15): Namely, the low end of the T-Types is better recovered in this new version. The catalogue also includes a separation between early or late type, which classifies the two populations in a complementary way to the T-Type, especially at the intermediate types (−1 < T-Type < 2), where the T-Type values show a large scatter. In addition, k-fold-based uncertainties on the classifications are also provided. To ensure robustness and reliability, we have also visually inspected all the images. We describe the content of the catalogues and show some interesting ways in which they can be combined.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

A revised SALT2 surface for fitting Type Ia supernova light curves

ABSTRACT We present a revised Spectral Adaptive Light Curve Template (SALT2) surface (SALT2-2021) for fitting the light curves of Type Ia supernovae (SNe Ia), which incorporates new measurements of zero-point calibration offsets and Milky Way extinction. The most notable change in the new surface occurs in the UV region. This new surface alters the distance measurements of SNe Ia, which can be used to investigate the nature of dark energy by probing the expansion history of the Universe. Using the revised SALT2 surface on public data from the first 3 yr of the Dark Energy Survey Supernova Program (combined with an external low-z SNe Ia sample) and combining with cosmic microwave background constraints, we find a change in the dark energy equation-of-state parameter, Δw = 0.015 ± 0.004. This result highlights the continued importance of controlling and reducing systematic uncertainties, particularly with the next generation of supernova analyses aiming to improve constraints on dark energy properties.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Effective cosmic density field reconstruction with convolutional neural network

ABSTRACT We present a cosmic density field reconstruction method that augments the traditional reconstruction algorithms with a convolutional neural network (CNN). Following previous work, the key component of our method is to use the reconstructed density field as the input to the neural network. We extend this previous work by exploring how the performance of these reconstruction ideas depends on the input reconstruction algorithm, the reconstruction parameters, and the shot noise of the density field, as well as the robustness of the method. We build an eight-layer CNN and train the network with reconstructed density fields computed from the Quijote suite of simulations. The reconstructed density fields are generated by both the standard algorithm and a new iterative algorithm. In real space at z = 0, we find that the reconstructed field is 90 per cent correlated with the true initial density out to $k\sim 0.5 \, \mathrm{ h}\, \rm {Mpc}^{-1}$, a significant improvement over $k\sim 0.2 \, \mathrm{ h}\, \rm {Mpc}^{-1}$ achieved by the input reconstruction algorithms. We find similar improvements in redshift space, including an improved removal of redshift space distortions at small scales. We also find that the method is robust across changes in cosmology. Additionally, the CNN removes much of the variance from the choice of different reconstruction algorithms and reconstruction parameters. However, the effectiveness decreases with increasing shot noise, suggesting that such an approach is best suited to high density samples. This work highlights the additional information in the density field beyond linear scales as well as the power of complementing traditional analysis approaches with machine learning techniques.

Astronomy & Astrophysics↗
DOE OSTI2026

Microwave Vortex Motion Characterization of Nb$_{3}$ Sn Coatings for Applications in High Magnetic Fields

In this work, microwave measurements carried out in dielectric-loaded resonators exposed to high magnetic fields are exploited to yield the surface impedance of Nb$_3$ Sn superconducting coatings deposited via two different techniques: vapor tin diffusion, and DC magnetron sputtering. The obtained data lead to qualitative interpretations on both the Nb$_3$ Sn superconducting properties, and vortex-dynamics and pinning, of each coating separately, as well as simple distinctive features when comparing those. When examining the respective surface impedances at varying field, it is expected that the studied films perform at substantially diverse magnitudes of flux-flow resistivity, but also in well-differentiated pinning regimes, yet the obtained surface resistances of both samples are comparable, thus demonstrating that there is room for film optimization at the expense of certain compromise between the parameters involved.

Nb3Sn↗
DOE OSTI2025

Seasonal Host Shifts for Legionella Within an Industrial Water‐Cooling System

Legionella is a genus of environmental bacteria containing pathogenic species such as Legionella pneumophila that are responsible for Legionnaires' disease, a potentially fatal respiratory infection. Disease aetiology can involve Legionella replication intracellularly within protists and this study aimed to characterise the Legionella -protist relationship to develop novel outbreak prevention targets. Water and sediment samples were collected from a water-cooling tower in South Carolina over a 6-month period. Concomitantly, multiple environmental parameters were recorded. Bacterial and eukaryotic communities were characterised using 16S rRNA gene V4 region and a 252 bp fragment of 18S rRNA gene, respectively. Co-occurrence network analyses were performed to elucidate Legionella -protist correlations through time. We found that Legionella correlated with different protists as the seasons progressed. Acanthamoeba correlated with Legionella in early spring followed by Vannella and Korotnevella in late spring and early summer, and were joined by Echinamoeba in mid-summer. Vannella and Acanthamoeba are known potential hosts for Legionella , while Korotnevella is a potential undocumented host. Of the environmental parameters, temperature showed strong correlation with protists genera, suggesting that Legionella abundance was driven by temperature-dependent protist availability. Our results highlight ecological shifts that are associated with elevated Legionella levels, which offers potential targets to help predict and prevent disease outbreaks.

microbial communities↗
DOE OSTI2022

Simulation of X-ray Hartmann wavefront sensing with the Synchrotron Radiation Workshop

X-ray wavefront measurement is an important beam diagnostic tool, especially for the diffraction-limited X-ray beam. These in situ diagnostics give a better understanding of beam imperfections, and they enable feedback for possible corrections and/or optical alignment improvements. Hartmann wavefront sensing is one of the promising techniques to perform in situ X-ray wavefront measurements. In this work, a simulation tool of the X-ray Hartmann Wavefront Sensor (HWS) is developed under the Synchrotron Radiation Workshop (SRW) framework. Using this new simulation capability, one can take advantage of the full SRW package to simulate Hartmann wavefront sensing with the beam traveling from the X-ray source to the sample through different X-ray optical components. This SRW HWS simulation tool can help to optimize the wavefront sensor parameters for a specific X-ray energy range. It can also simulate an in situ wavefront measurement experiment with a particular beamline optical layout and predict the expected results of the wavefront measurement under different beamline configurations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

CROCUS Air Quality Dataset from the University of Illinois Chicago (UIC), July 2024

This dataset was collected by the measurement system in the Atmosphere, Climate, and Ecosystems (ACE) Lab at the University of Illinois Chicago (UIC) from July 12 to July 31, 2024, as part of the Community Research on Climate and Urban Science (CROCUS) Urban Integrated Field Laboratory (UIFL) project, led by Argonne National Laboratory.To enhance understanding of urban air quality dynamics in Chicago, and as part of the CROCUS 2024 Urban Canyon Intensive Observation Period (IOP), several instruments were set up to provide continuous measurements of air quality parameters in Chicago during July 2024. These measurements cover both aerosols and gas-phase species. It focuses on particle size distribution (2.5–478 nm) measured by two Scanning Mobility Particle Sizers (SMPS) at a 4-min resolution, total particle number concentrations at a 1-s resolution, and chemical composition from a High-Resolution Time-of-Flight Aerosol Mass Spectrometer (AMS) at a 1-min resolution. Key gas-phase species, including NO, NO₂, SO₂, and O₃, are measured at a 1-min resolution, along with high-resolution NO and dimethyl sulfide (DMS) data from a Chemical Ionization Mass Spectrometer (CIMS). Volatile organic compound (VOC) data for toluene, isoprene, and benzene are provided by a GC-PID with a time resolution of 25 minutes.The data are formatted as NetCDF (.nc) files, making them easily accessible using common software such as MATLAB, R, and Python. Each parameter is stored in an individual dataset, which includes detailed instrument information in the header, as well as the corresponding sample start time and concentration/distribution data for each sample.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Fast and Accurate Core Analysis by the Full-Immersion Pressure-Pulse Decay: Part 1—Theory

Summary Core-scale measurements are considered the ground truth that oil and gas or electric utility companies use to predict the migration of fluids such as oil, natural gas, carbon dioxide, or brine deep underground during their extraction or injection operations. To provide a greater understanding of petrophysical properties of low-permeability geologic formations such as shales and tight gas sandstones, this study introduces a novel core-analysis procedure. The technique follows conventional pressure-pulse-decay permeametry, where the pressure in an inlet chamber adjacent to a cylindrical core plug undergoes a rapid pressurization, the system is shut in, and the pressure reaches a new equilibrium. However, unlike a standard unidirectional pressure-pulse decay, the full-immersion pressure-pulse decay (Hannon 2019) applies a pressure disturbance to the entire outer surface area of the sample. This article covers the numerical simulator designed to model flow through an anisotropic porous sample in this scenario. The model assumes distinct but uniform permeabilities along the radial and axial directions of the cylindrical plug sample. When extracting a plug vertically (or perpendicular to bedding), the permeability along the radial direction associates with the horizontal permeability (i.e., parallel to bedding), whereas in the axial direction, flow occurs perpendicular to bedding (a vertical permeability). Investigations of these model outputs demonstrate an approximately 20-fold decrease in time to complete a full-immersion experiment compared with conventional pressure-pulse decay. Furthermore, the pressure-decay curves resulting from the full-immersion method have slightly different shapes than those resulting from other unidimensional transient methods. These differences begin to demonstrate that, under achievable experimental conditions, the analysis of pressure data from one full-immersion test could enable the simultaneous estimation of the apparent permeabilities parallel and perpendicular to bedding of a cylindrical sample in addition to its porosity. A follow-up article finalizes the proof of this capability with a parameter-estimation procedure and presents experimental verification through a proof-of-concept study. Described in greater detail in that article, the parameter estimator requires multiple forward simulations to analyze the data, which behooves minimizing the compute time for each simulation. By using an alternating direction implicit time-marching scheme and a structured but variably spaced grid, the numerical simulator built for this purpose provides a forward model output with suitable accuracy in approximately 0.5 seconds.

Energy & Fuels↗
DOE OSTI2022

Chemical Cartography with APOGEE: Mapping Disk Populations with a 2-process Model and Residual Abundances

We apply a novel statistical analysis to measurements of 16 elemental abundances in 34,410 Milky Way disk stars from the final data release (DR17) of APOGEE-2. Building on recent work, we fit median abundance ratio trends [X/Mg] versus [Mg/H] with a 2-process model, which decomposes abundance patterns into a "prompt" component tracing core-collapse supernovae and a "delayed" component tracing Type Ia supernovae. For each sample star, we fit the amplitudes of these two components, then compute the residuals Δ[X/H] from this two-parameter fit. The rms residuals range from ~0.01–0.03 dex for the most precisely measured APOGEE abundances to ~0.1 dex for Na, V, and Ce. The correlations of residuals reveal a complex underlying structure, including a correlated element group comprised of Ca, Na, Al, K, Cr, and Ce and a separate group comprised of Ni, V, Mn, and Co. Selecting stars poorly fit by the 2-process model reveals a rich variety of physical outliers and sometimes subtle measurement errors. Residual abundances allow for the comparison of populations controlled for differences in metallicity and [α/Fe]. Relative to the main disk (R = 3–13 kpc), we find nearly identical abundance patterns in the outer disk (R = 15–17 kpc), 0.05–0.2 dex depressions of multiple elements in LMC and Gaia Sausage/Enceladus stars, and wild deviations (0.4–1 dex) of multiple elements in ω Cen. The residual abundance analysis opens new opportunities for discovering chemically distinctive stars and stellar populations, for empirically constraining nucleosynthetic yields, and for testing chemical evolution models that include stochasticity in the production and redistribution of elements.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Astrometric microlensing probes of the isolated neutron star population with Roman

Notoriously hard to detect and study, isolated neutron stars (NSs) might provide valuable answers to fundamental questions about stellar evolution and explosion physics. With the upcoming Roman Space Telescope, scheduled for launch in 2026, a new and powerful channel for their detection will become available: astrometric microlensing. We set out to create a realistic sample of simulated gravitational microlensing events as observed by Roman with the Galactic Bulge Time Domain Survey. We focus in particular on the population of NS lenses, which has until now been largely understudied. We used dedicated Galactic models tailored for application to microlensing by compact objects. In addition to populations of stars, white dwarfs, and black holes, we simulated four different NS populations with Maxwellian natal kick distributions: v = (150, 250, 350, 450) km/s. For each simulation, we applied projected Roman precision, cadence, and detectability criteria. We found that the parameter space log10 t E –log 10 θ E , which will be accessible to Roman observations, is efficient for the classification of stellar remnants. We found a feature in this space that is characteristic of NSs; using this feature, optimal samples of NS candidates can be constructed from Roman -like datasets. We describe the dependence of the observable parameter distributions on the assumed mean kick velocities. As the effects of natal kicks are very complex and mutually counteracting, we suggest that more detailed studies focused on the dynamics of NSs are needed in anticipation of Roman and future surveys. We estimate that Roman will observe approximately 11 000 microlensing events, including ~100 with NS lenses, whose photometric and astrometric signals are detectable; the event yield decreases by 38% when gap-filling low-cadence observations are not included. We make all simulated microlensing event datasets publicly available in preparation for Roman data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Interpretable AI forecasting for numerical relativity waveforms of quasicircular, spinning, nonprecessing binary black hole mergers

We present a deep-learning artificial intelligence model (AI) that is capable of learning and forecasting the late-inspiral, merger and ringdown of numerical relativity waveforms that describe quasicircular, spinning, nonprecessing binary black hole mergers. We used the NRHybSur3dq8 surrogate model to produce train, validation and test sets of ℓ = |m| = 2 waveforms that cover the parameter space of binary black hole mergers with mass ratios q ≤ 8 and individual spins |s$^{z}_ {(1,2)}$| ≤ 0.8. These waveforms cover the time range t ∊ [-5000 M, 130 M], where t = 0M marks the merger event, defined as the maximum value of the waveform amplitude. We harnessed the ThetaGPU supercomputer at the Argonne Leadership Computing Facility to train our AI model using a training set of 1.5 million waveforms. We used 16 NVIDIA DGX A100 nodes, each consisting of 8 NVIDIA A100 Tensor Core GPUs and 2 AMD Rome CPUs, to fully train our model within 3.5 h. Our findings show that artificial intelligence can accurately forecast the dynamical evolution of numerical relativity waveforms in the time range t ∊ [-100 M, 130 M]. Sampling a test set of 190,000 waveforms, we find that the average overlap between target and predicted waveforms is ≳99% over the entire parameter space under consideration. We also combined scientific visualization and accelerated computing to identify what components of our model take in knowledge from the early and late-time waveform evolution to accurately forecast the latter part of numerical relativity waveforms. This work aims to accelerate the creation of scalable, computationally efficient and interpretable artificial intelligence models for gravitational wave astrophysics

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Origin, parameters, and underlying deformation mechanisms of propagating deformation bands in irradiated 316L stainless steel

Lüders-type propagating deformation bands were observed in specimens of irradiated 316L stainless steel samples removed from Spallation Neutron Source target vessels after service. Mechanical testing with digital image correlation (DIC) and in-situ tensile testing with scanning electron microscopy electron backscatter diffraction showed that the observed Lüders-type behavior was not related to the known transformation-induced plasticity or twinning-induced plasticity behavior. Instead, the phenomenon occurs at small local strain values before a significant amount of martensite or deformation twins appear in the microstructure. Microstructural analysis and in-situ mechanical test results suggest Lüders-type band formation and propagation were related to the appearance and evolution of defect-free channels—analogous to slip bands. A modified Swift equation with a Ludwigson-like component was offered to rationalize the phenomenon and model the strain-softening processes at small strain values. Finally, the results indicate complex microstructural processes and deformation mechanisms were active at small strain values and underline the benefits of advanced mechanical test approaches such as DIC.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Raman Spectroscopy Based On-Line, Real-Time Monitoring to Reduce Composition Uncertainties: Enhanced sensitivity through optimization of Raman Parameters

Optical spectroscopy-based on-line monitoring of Hanford processing streams can enable real-time characterization of chemical composition of process streams and batches, ultimately enabling and enhancing process control. It can provide immediate feedback on process conditions and has the potential to reduce the needed number of grab sample collections, thereby reducing times and costs associated with laboratory processing. Here we discuss the utilization of Raman spectroscopy to quantify multiple target analytes that are common within Hanford tanks and waste processing streams. Analytes include: nitrate, nitrite, carbonate, chromate, sulfate, phosphate, hydroxide, oxalate, ammonia, and aluminate. Most notably in this work, Raman applications to low-concentration streams are explored and optimized. Raman instrument specifications are compared; specifically, the impact of utilizing three different Raman excitation wavelengths, 405, 532, and 671 nm, is discussed. Also, Raman data collection parameters such as collection time and spectral averaging are measured and discussed. Finally, optical libraries of chemical targets were collected using optimized collection parameters and chemometric models were built to automate quantification of chemical targets. These models were validated through application to simulants and real Hanford process samples. Chemometric models performed well on both training and validation sets, suggesting these approaches can be successfully applied to on-line and real-time monitoring of low concentration Hanford processing streams. The use of the combine Raman wave lengths with the enhanced chemometric models for the low concentration streams significantly improved the chemical detection levels and significantly reduced uncertainties of those measurements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Constraining primordial non-Gaussianity with DESI 2024 LRG and QSO samples

We analyse the large-scale clustering of the Luminous Red Galaxy (LRG) and Quasar (QSO) sample from the first data release (DR1) of the Dark Energy Spectroscopic Instrument (DESI). In particular, we constrain the primordial non-Gaussianity (PNG) parameter f NL loc via the large-scale scale-dependent bias in the power spectrum using 1,631,716 LRGs (0.6 < z < 1.1) and 1,189,129 QSOs (0.8 < z < 3.1). This new measurement takes advantage of the enormous statistical power at large scales of DESI DR1 data, surpassing the latest data release (DR16) of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). For the first time in this kind of analysis, we use a blinding procedure to mitigate the risk of confirmation bias in our results. We improve the model of the radial integral constraint proposing an innovative technique allowing the correction through the window matrix convolution. We also carefully test the mitigation of the dependence of the target selection on the photometry qualities by incorporating an angular integral constraint contribution to the window function, and validate our methodology with the blinded data. Finally, combining the two samples, we measure f NL loc = -3.6 -9.1 +9.0 at 68% confidence, where we assume the universality relation for the LRG sample and a recent merger model for the QSO sample about the response of bias to primordial non-Gaussianity. Adopting the universality relation for the PNG bias in the QSO analysis leads to f NL loc = 3.5 -7.4 +10.7 at 68% confidence. Due to restricted selection in the LRG sample, the inclusion of the LRGs allows for 10% improvement. This measurement is the most precise determination of primordial non-Gaussianity using large-scale structure to date, surpassing the latest result from eBOSS by a factor of 2.3.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

The need for multicomponent dust attenuation in modeling nebular emission: Constraints from SDSS-IV MaNGA

A fundamental assumption adopted in nearly every extragalactic study that analyzes optical emission lines is that the attenuation of different emission lines can be described by a single attenuation curve, scaled by a single reddening parameter, usually E(B - V). Here we show this assumption fails in many cases with important implications for derived results. We developed a new method to measure the differential nebular attenuation among three kinds of transitions: the Balmer lines of hydrogen; high-ionization transitions (> 13.6 eV) including [Ne III], [O III], and [S III]; and low-ionization transitions (≲13.6 eV) including [O II], [N II], and [S II]. This method bins the observed data in a multidimensional space spanned by attenuation-insensitive line ratios. Within each small bin, the variations in nebular parameters such as the metallicity and ionization parameter are negligible compared to the variation in the nebular attenuation. This allowed us to measure the nebular attenuation using both forbidden lines and Balmer lines. We applied this method to a sample of 2.4 million star-forming (SF) spaxels from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. We found that the attenuation of high ionization lines and Balmer lines can be well described by a single Fitzpatrick (1999, PASP, 111, 63) extinction curve with R V = 3.1. However, no single attenuation curve can simultaneously account for these transitions and the derived attenuation of low-ionization lines. This strongly suggests that different lines have different effective attenuations, likely because spectroscopy at hundreds of parsecs to kiloparsecs of resolution mixes multiple physical regions that exhibit different intrinsic line ratios and different levels of attenuation. As a result, the assumption that different lines follow the same attenuation curve breaks down. Using a single attenuation curve determined by Balmer lines to correct attenuation-sensitive forbidden line ratios could bias the nebular parameters derived by 0.06–0.25 dex at A V = 1, depending on the details of the dust attenuation model. Observations of a statistically large sample of H II regions with high spatial resolutions and large spectral coverage are vital for improved modeling and deriving accurate corrections for this effect.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Nature of the galaxies on top of quasars producing Mg ii absorption

ABSTRACT Quasar–galaxy pairs at small separations are important probes of gas flows in the disc–halo interface in galaxies. We study host galaxies of 198 Mg ii absorbers at 0.39 ≤ zabs ≤ 1.05 that show detectable nebular emission lines in the Sloan Digital Sky Survey (SDSS) spectra. We report measurements of impact parameter (5.9 ≤ D [kpc] ≤ 16.9) and absolute B-band magnitude (−18.7 ≤ MB ≤ −22.3 mag) of host galaxies of 74 of these absorbers using multiband images from the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Survey, more than doubling the number of known host galaxies with D ≤ 17 kpc. This has allowed us to quantify the relationship between Mg ii rest equivalent width (W2796) and D, with best-fitting parameters of W2796 (D = 0) = 3.44 ± 0.20 Å and an exponential scale length of 21.6$^{+2.41}_{-1.97}\, \mathrm{ kpc}$. We find a significant anticorrelation between MB and D, and MB and W2796, consistent with the brighter galaxies producing stronger Mg ii absorption. We use stacked images to detect average emissions from galaxies in the full sample. Using these images and stacked spectra, we derive the mean stellar mass (9.4 ≤ log(M*/M⊙) ≤ 9.8), star formation rate (2.3 ≤ SFR [M⊙ yr−1] ≤ 4.5), age (2.5–4 Gyr), metallicity (12 + log(O/H) ∼ 8.3), and ionization parameter (log q [cm s−1] ∼ 7.7) for these galaxies. The average M* found is less than that of Mg ii absorbers studied in the literature. The average SFR and metallicity inferred are consistent with that expected in the main sequence and the known stellar mass–metallicity relation, respectively. High spatial resolution follow-up spectroscopic and imaging observations of this sample are imperative for probing gas flows close to the star-forming regions of high-z galaxies.

Astronomy & Astrophysics↗
DOE OSTI2024

Atomic-scale visualization of a cascade of magnetic orders in the layered antiferromagnet GdTe3

Abstract GdTe 3 is a layered antiferromagnet which has attracted attention due to its exceptionally high mobility, distinctive unidirectional incommensurate charge density wave (CDW), superconductivity under pressure, and a cascade of magnetic transitions between 7 and 12 K, with as yet unknown order parameters. Here, we use spin-polarized scanning tunneling microscopy to directly image the charge and magnetic orders in GdTe 3 . Below 7 K, we find a striped antiferromagnetic phase with twice the periodicity of the Gd lattice and perpendicular to the CDW. As we heat the sample, we discover a spin density wave with the same periodicity as the CDW between 7 and 12 K; the viability of this phase is supported by our Landau free energy model. Our work reveals the order parameters of the magnetic phases in GdTe 3 and shows how the interplay between charge and spin can generate a cascade of magnetic orders.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Physical and Hydraulic Properties of RCRA Borehole Samples from the Hanford Site : Final Report, Fiscal Years 2023-2024

Sediment from 44 core samples collected from Resource Conservation and Recovery Act (RCRA) boreholes drilled in the 200 East and 200 West areas of the Hanford Site were characterized for physical and hydraulic properties (Table S.1). Characterization data included gravimetric water contents and matric potentials, grain-size distributions, saturated hydraulic conductivity, water retention characteristics, and unsaturated hydraulic conductivity. These properties provide site-specific data and parameters that can be used in subsurface flow and contaminant transport models to assess the transport and fate of contaminants in the vadose zone and underlying aquifer systems. The analyzed core samples come from specific areas and depth intervals at the Hanford Site that were targeted for sampling to address data gaps identified by site contractors (Khaleel 2020). X-ray computed tomography (XCT) was used to evaluate the general textural characteristics of the samples and to determine which samples to use for further physical and hydraulic property characterization. Subsequent sample selection was determined by consensus after review of the XCT images by Pacific Northwest National Laboratory, Central Plateau Cleanup Company, and INTERA staff.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗