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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

A Chandra-HETG view of MCG +8-11-11

We present a spectral analysis of the 118 ks Chandra High Energy Transmission Gratings (HETG) observation of the X-ray bright Seyfert 1.5 galaxy MCG +8-11-11, in conjunction with 100 ks of archival Suzaku data, aimed at investigating the signatures of warm absorption and Compton reflection reported from previous Suzaku and XMM-Newton studies of the source. Contrary to previous results, we find that warm absorption is not required by the data. Instead, we report upper limits on absorption lines that are below previous (marginal) detections. Fe Kα line emission is clearly detected and is likely resolved with σ ∼ 0.02 keV with the HETG data. We applied self-consistent, broadband spectral-fitting models to the Chandra and Suzaku data to investigate this and other signatures of distant absorption and reflection. Utilizing in particular the MYTorus model, we find that the data are consistent with reprocessing by a distant, neutral torus that is marginally Compton-thick ( N {sub H} ∼10{sup 24}cm{sup –2}) and out of the line of sight. However, we do not find compelling evidence of a relativistically broadened Fe K emission line, which is often expected from type 1 active galactic nuclei. This is consistent with some, although not all, previous studies of MCG +8-11-11. A well-measured edge is identified by the HETG near 0.5 keV, indicating neutral absorption in the line of sight that is consistent with galactic absorption; however, the absorption may be partially intrinsic to the source. The HETG data are consistent with the presence of a soft excess, a feature that may be missed by considering the Suzaku data alone.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

MAPPRAISER: A massively parallel map-making framework for multi-kilo pixel CMB experiments

Forthcoming cosmic microwave background (CMB) polarized anisotropy experiments have the potential to revolutionize our understanding of the Universe and fundamental physics. The sought-after, tale-telling signatures will be however distributed over voluminous data sets which these experiments will collect. These data sets will need to be efficiently processed and unwanted contributions due to astrophysical, environmental, and instrumental effects characterized and efficiently mitigated in order to uncover the signatures. This poses a significant challenge to data analysis methods, techniques, and software tools which will not only have to be able to cope with huge volumes of data but to do so with unprecedented precision driven by the demanding science goals posed for the new experiments. A keystone of efficient CMB data analysis is solvers of very large linear systems of equations. Such systems appear in very diverse contexts throughout CMB data analysis pipelines, however they typically display similar algebraic structures and can therefore be solved using similar numerical techniques. Linear systems arising in the so-called map-making problem are one of the most prominent and common ones. In this work we present a massively parallel, flexible and extensible framework, comprised of a numerical library, MIDAPACK, and a high level code, MAPPRAISER, which provide tools for solving efficiently such systems. Here, the framework implements iterative solvers based on conjugate gradient techniques: enlarged and preconditioned using different preconditioners. We demonstrate the framework on simulated examples reflecting basic characteristics of the forthcoming data sets issued by ground-based and satellite-borne instruments, executing it on as many as 16,384 compute cores. The software is developed as an open source project freely available to the community at: https://github.com/B3Dcmb/midapack.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Measuring accurate optical constants of uranium minerals for use in optical modeling of infrared spectra

Knowledge of the bulk optical constants n and k of solids or liquids allows researchers to accurately predict the absorption, reflection, and scattering properties of materials for different physical forms. Indeed, chemically complex materials such as minerals can have an almost limitless variety of morphologies, particle sizes, shapes, and compositions, but the optical properties of such species can be predicted if the optical constants are known. For species such as minerals, however, there can be additional challenges due to e.g. hydration or dehydration during the course of the optical constants measurement. Here, we describe the protocols to obtain the bulk optical constants n and k of uranium-bearing minerals and ores such as uraninite or autunite. If quality n and k data are at hand, the (infrared) reflectance spectra can be predicted for different particle sizes and morphologies and the modeling results for various scenarios can be derived.

infrared (IR) spectroscopy, optical constants, ura↗
DOE OSTI2025

Real-time data processing for serial crystallography experiments

We report the use of streaming data interfaces to perform fully online data processing for serial crystallography experiments, without storing intermediate data on disk. The system produces Bragg reflection intensity measurements suitable for scaling and merging, with a latency of less than 1 s per frame. Our system uses the CrystFEL software in combination with the ASAP::O data framework. In a series of user experiments at PETRA III, frames from a 16 megapixel Dectris EIGER2 X detector were searched for peaks, indexed and integrated at the maximum full-frame readout speed of 133 frames per second. The computational resources required depend on various factors, most significantly the fraction of non-blank frames ('hits'). The average single-thread processing time per frame was 242 ms for blank frames and 455 ms for hits, meaning that a single 96-core computing node was sufficient to keep up with the data, with ample headroom for unexpected throughput reductions. Further significant improvements are expected, for example by binning pixel intensities together to reduce the pixel count. We discuss the implications of real-time data processing on the `data deluge' problem from recent and future photon-science experiments, in particular on calibration requirements, computing access patterns and the need for the preservation of raw data.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Evaluation of WRF simulation of deep convection in the US Southern Great Plains

The Southern Great Plains (SGP) exhibits a relatively high frequency of periods with extremely high rainfall rates (RR) and hail. Here, seven months of 2017 are simulated using the Weather Research and Forecasting (WRF) model applied at convection permitting resolution with the Mibrandt-Yau microphysics scheme. Simulation fidelity is evaluated, particularly during intense convective events, using data from ASOS stations, dual-polarization RADAR, gridded data sets and observations at the DoE Atmospheric Radiation Measurement site. The spatial gradients and temporal variability of precipitation and the cumulative density functions for both RR and wind speeds exhibit fidelity. Odds ratios >1 indicate WRF is also skillful in simulating high composite reflectivity (cREF, used as a measure of widespread convection) and RR > 5 mmhr –1 over the domain. Detailed analyses of the ten days with highest spatial coverage of cREF >30 dBZ show spatially similar reflectivity fields and high RR in both RADAR data and WRF simulations. However, during periods of high reflectivity, WRF exhibits a positive bias in terms of very high RR (> 25 mmhr –1 ) and hail occurrence, and during the summer and transition months, maximum hail size is underestimated. For some renewable energy applications fidelity is required with respect to the joint probabilities of wind speed and RR and/or hail. While partial fidelity is achieved for the marginal probabilities, performance during events of critical importance to these energy applications is currently not sufficient. Further research into optimal WRF configurations in support of potential damage quantification for these applications is warranted.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Site and endmember spectra of terrestrial vegetation and soils for the Colorado Headwaters Ecological Spectroscopy Study, June-July 2025

This dataset provides site and endmember spectra collected during the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS) campaign. The site spectra were collected to help validate airborne hyperspectral data acquired by the National Ecological Observatory Network's aerial observation platform (NEON AOP). Endmember spectra were collected to augment existing spectral libraries with additional samples of bare surfaces and non-photosynthetic vegetation. All measurements were acquired with an Analytical Spectral Devices (ASD) FieldSpec4 Hi-Res NG (Next Generation) spectroradiometer, which records radiance at 1nm (nanometer) intervals from the ultraviolet to the short-wave infrared (350-2500 nm). The dataset includes spectra measured at meadow sites where the CHESS team also collected vegetation samples for trait analyses. The site spectra were collected with the ASD FieldSpec4 palm grip attachment using an 8° field-of-view foreoptic. Site spectra are integrated measurements of the entire surface within the foreoptic’s field of view. For site-level spectra, the sun is the illumination source. A Spectralon panel mounted on a tripod was used for instrument optimization and white reference measurements for all site spectra. Site spectra were acquired within two hours of solar noon and within 48 hours of a NEON AOP overflight. Site spectra are labeled by date, sampling area, and site number according to the naming conventions of the CHESS campaign’s data management plan. The dataset also contains endmember spectra in the following categories: photosynthetic vegetation (PV), non-photosynthetic vegetation (NPV), bare (soil/rock), and flowers. Endmember measurements were acquired using either the contact probe or the leaf clip attachments of the ASD FieldSpec4. In these configurations, the bulb inside the spectrometer provides the light source for the measurements. The spectrometer was optimized and white reference measurements were recorded using the circular white pucks attached to the contact probe and leaf clip. Because they do not rely on solar illumination, contact probe and leaf clip measurements were collected during a broader time frame than the palm grip site spectra. Some endmembers were measured at CHESS meadow sites, while others were collected within the larger sampling area or in nearby locations (e.g. Gothic Townsite) with similar characteristics. Radiance, reflectance, and metadata files are split into three subfolders according to measurement type: proximal/palm grip (prx), contact probe (cp), and leaf clip (lc). Radiance spectra are provided in ASD file format (.asd file extension). All ASD files can be opened using the provided scripts. Metadata is provided in two formats: CSV file format (no geolocation) and GEOJSON file format (includes geolocation for each spectra). The dataset includes a set of pre-processed reflectance spectra as CSV files (yyyymmdd_rfl.csv). The python scripts and jupyter notebook used to calculate reflectance spectra from the ASD radiance data is included here and was previously published at: https://doi.org/10.3334/ORNLDAAC/2446. There is also a folder of JPEG photographs corresponding to selected spectra. We include a protocol document with detailed steps for ASD FieldSpec4 assembly and operations. This data additionally contains a file level metadata (flmd.csv) and data dictionary (dd.csv) file. Geospatial information: Geospatial data for mapping measurement site locations are in the files CHESS_polygons_lai_UTM.geojson, CHESS_polygons_shrub_UTM.geojson, and CHESS_polygons_meadow_UTM.geojson in the companion geospatial package for the 2025 CHESS campaign, ‘CHESS 2025: Location data for field observations and sampling’ (Henderson et al., 2026). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgment: This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004) and was funded by EMIT Extended Mission Phase E Science.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2021

Development and application of marginal likelihood optimization for integral parameter adjustment

When adjusting nuclear data with integral experiments, care must be taken that spurious adjustments are not made by assimilating poorly characterized integral parameters. If there are unaccounted for biases or poorly estimated uncertainties in the calculated and experimental values for an integral parameter, the Bayesian data assimilation may adjust the nuclear data in a manner that does not reflect the physics of the integral parameter. To identify and lessen the impact of these inconsistent integral parameters, in this study we present a Marginal Likelihood Optimization algorithm. In a data-driven way, the marginalized likelihood is used to modulate hyperparameter terms that decrease the influence of inconsistent integral parameters on the adjustment. The advantage of this approach over other methods in the literature is that it incorporates correlation information and does not remove an integral parameter from the adjustment. Herein, we present and motivate the algorithm, and apply it to an integral data assimilation case study.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Cryogenic single-port calibration for superconducting microwave resonator measurements

Superconducting circuit testing and materials loss characterization requires robust and reliable methods for the extraction of internal and coupling quality factors of microwave resonators. Additionally, a common method, imposed by limitations on the device design or experimental configuration, is the single-port reflection geometry, i.e. reflection-mode. However, impedance mismatches in cryogenic systems must be accounted for through calibration of the measurement chain while it is at low temperatures. In this paper, we demonstrate a data-based, single-port calibration using commercial microwave standards and a vector network analyzer with samples at millikelvin temperature in a dilution refrigerator, making this method useful for measurements of quantum phenomena. Finally, we cross reference our data-based, single-port calibration and reflection measurement with over-coupled 2D- and 3D-resonators against well established two-port techniques corroborating the validity of our method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

High Miller-Index Germanium Crystals For High-Energy X-ray Imaging Applications

Near-normal-incidence bent crystals are widely used for x-ray imaging applications. Advantages include high collection solid angle and potentially high efficiency for narrow-band sources, while disadvantages include relatively large (several Å) interatomic spacings and a limited number of suitable matches between a crystal 2d value and an integral multiple of useful emission line wavelengths. The disadvantages become more significant at x-ray energies >10 keV. The former disadvantage can be mitigated by using high-order reflections from crystal planes having low Miller indices, but both disadvantages can be mitigated by using low-order reflections from crystal planes having high Miller indices. We report here on integrated reflectivity measurements we performed of Ge (15,7,7) (2d=0.6296 Å), a candidate for imaging Ru He-α (θ(B)=87°). We find good agreement with calculations, and the data show a multitude of closely spaced reflections with slightly different Bragg angles including a fifth-order reflection of Ge (3,1,1) that has comparable reflectivity. This demonstrates that arbitrary choices of Miller indices in Ge crystals can be used to fine-tune Bragg angles for near-normal-incidence x-ray imaging at tens of kiloelectron volt x-ray energies with minimal lower-energy contamination from lower-order reflections, and that existing calculational tools can be used to reliably estimate integrated reflectivity.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Neural net detection of seismic features related to gas hydrates and free gas accumulations on the northern U.S. Atlantic margin

Bottom-simulating reflections (BSRs) that sometimes mark the base of the gas hydrate stability zone in marine sediments are often identified based on the reverse polarity reflections that cut across stratigraphic layering in seismic amplitude data. On the northern U.S. Atlantic margin (USAM) between Cape Hatteras and Hudson Canyon, legacy seismic data have revealed pronounced BSRs south of the deepwater extension of Hudson Canyon and more subtle ones from offshore Delaware south to Cape Hatteras, where the reflections sometimes follow stratigraphic layering. Using high-resolution seismic data acquired during the 2018 Mid-Atlantic Resource Imaging Experiment and a supervised neural net, we identify seismic features associated with gas hydrates and/or the top of gas between Hudson Canyon and Cape Hatteras. Using seismic attributes especially sensitive to the presence of gas, we train a neural network algorithm on seismic data from an area with strong BSRs and then apply the model to the rest of the data set. The results indicate that gas hydrate and/or shallow free gas are significantly more widespread on the northern part of the USAM than previously known. Seismic indicators of gas extend landward from the 2000 m isobath to the upper continental slope in sectors with (offshore Virginia) and, to a lesser extent, without (offshore New Jersey) pervasive upper slope methane seeps. Higher sand content and intermediate sediment thickness, factors related to the container size and gas charge in a petroleum systems framework, are associated with more robust gas indicators.

Geochemistry & Geophysics↗
DOE OSTI2014

Big-Data RHEED analysis for understanding epitaxial film growth processes

Reflection high energy electron diffraction (RHEED) has by now become a standard tool for in-situ monitoring of film growth by pulsed laser deposition and molecular beam epitaxy. Yet despite the widespread adoption and wealth of information in RHEED image, most applications are limited to observing intensity oscillations of the specular spot, and much additional information on growth is discarded. With ease of data acquisition and increased computation speeds, statistical methods to rapidly mine the dataset are now feasible. Here, we develop such an approach to the analysis of the fundamental growth processes through multivariate statistical analysis of RHEED image sequence. This approach is illustrated for growth of LaxCa1-xMnO3 films grown on etched (001) SrTiO3 substrates, but is universal. The multivariate methods including principal component analysis and k-means clustering provide insight into the relevant behaviors, the timing and nature of a disordered to ordered growth change, and highlight statistically significant patterns. Fourier analysis yields the harmonic components of the signal and allows separation of the relevant components and baselines, isolating the assymetric nature of the step density function and the transmission spots from the imperfect layer-by-layer (LBL) growth. These studies show the promise of big data approaches to obtaining more insight into film properties during and after epitaxial film growth. Furthermore, these studies open the pathway to use forward prediction methods to potentially allow significantly more control over growth process and hence final film quality.

Big-Data↗
DOE OSTI2018

Transient superconductivity without superconductivity

Recent experiments on K 3 C 60 and layered copper-oxide materials have reported substantial changes in the optical response following application of an intense THz pulse. These data have been interpreted as the stimulation of a transient superconducting state even at temperatures well above the equilibrium transition temperature. We propose an alternative phenomenology based on the assumption that the pulse creates a nonsuperconducting, though nonequilibrium, situation in which the linear response conductivity is negative. The negative conductivity implies that the spatially uniform prepulse state is unstable and evolves to a new state with a spontaneous electric polarization. Furthermore, this state exhibits coupled oscillations of entropy and electric charge whose coupling to incident probe radiation modifies the reflectivity, leading to an apparently superconductinglike response that resembles the data. Dependencies of the reflectivity on polarization and angle of incidence of the probe are predicted and other experimental consequences are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2016

ION INJECTION AT QUASI-PARALLEL SHOCKS SEEN BY THE CLUSTER SPACECRAFT

Collisionless shocks in space plasma are known to be capable of accelerating ions to very high energies through diffusive shock acceleration (DSA). This process requires an injection of suprathermal ions, but the mechanisms producing such a suprathermal ion seed population are still not fully understood. We study acceleration of solar wind ions resulting from reflection off short large-amplitude magnetic structures (SLAMSs) in the quasi-parallel bow shock of Earth using in situ data from the four Cluster spacecraft. Nearly specularly reflected solar wind ions are observed just upstream of a SLAMS. The reflected ions are undergoing shock drift acceleration (SDA) and obtain energies higher than the solar wind energy upstream of the SLAMS. Our test particle simulations show that solar wind ions with lower energy are more likely to be reflected off the SLAMS, while high-energy ions pass through the SLAMS, which is consistent with the observations. The process of SDA at SLAMSs can provide an effective way of accelerating solar wind ions to suprathermal energies. Therefore, this could be a mechanism of ion injection into DSA in astrophysical plasmas.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Leaf Nitrogen, Leaf Mass Area, Leaf Water Content, Seward Peninsula, Alaska, 2017

Nitrogen and carbon content, leaf mass per area and leaf water content of leaves sampled from the NGEE Arctic Teller study site, Seward Peninsula, Alaska in 2017. Data is included for 13 species from the deciduous shrub, forb and graminoid plant functional types. See related dataset for leaf reflective spectra, sample photographs and dGPS locations. This data package includes leaf sample information and trait data (*.csv). Note that leaf nitrogen content analysis was performed on a subset of samples. Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA103_flmd.csv. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A Web-based application for the collection, management and release of Alignment and Calibration configurations used in data processing at the Compact Muon Solenoid experiment

The Compact Muon Solenoid (CMS) experiment makes a vast use of alignment and calibration measurements in several data processing workflows: in the High Level Trigger, in the processing of the recorded collisions and in the production of simulated events for data analysis and studies of detector upgrades. A complete alignment and calibration scenario is factored in approximately three-hundred records, which are updated independently and can have a time-dependent content, to reflect the evolution of the detector and data taking conditions. Given the complexity of the CMS condition scenarios and the large number (50) of experts who actively measure and release calibration data, in 2015 a novel web-based service has been developed to structure and streamline their management. The cmsDbBrowser provides an intuitive and easily accessible entry point for the navigation of existing conditions by any CMS member, for the bookkeeping of record updates and for the actual composition of complete calibration scenarios. This paper describes the design, choice of technologies and the first year of usage in production of the cmsDbBrowser.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Evaluation of Electrical Resistivity Tomography to Monitor the Transport of Past Releases Beneath Tank Farms

Underground storage tanks at the Hanford Site, in southeastern Washington State, hold radioactive waste generated from four decades of plutonium production. The 149 single-shell tanks and the 28 double-shell tanks have all exceeded their initial design life of approximately 25 years. At least 67 tanks are assumed to have leaked in the past, resulting in radioactive releases into the vadose zone. Gamma ray logging within dry monitoring wells is currently the primary method for tracking the migration of leaked tank waste through the vadose zone. While this approach provides an accurate assessment of radioactive contamination, that information is only provided near (within ~1m) the borehole, leaving most of the vadose zone unmonitored, particularly the important region directly beneath the tank. This report describes a numerical study that investigates the feasibility and performance of time-lapse 3D electrical resistivity tomography (ERT) for long-term monitoring of a hypothetical tank waste location and migration through the vadose zone. ERT is a method of remotely imaging the bulk electrical conductivity (EC) of the subsurface, which is significantly impacted by the presence of conductive solid and liquid tank waste. The release of liquid tank wastes increases subsurface fluid conductivity and saturation over time, creating a target to use time-lapse ERT for long-term monitoring. Although the presence of metallic infrastructure can cause ERT interference, recent advancements in ERT data processing enable the deleterious effects of buried metallic infrastructure (e.g. pipes, wellbore casings, tanks) to be removed to better determine the liquid tank waste migration over time. Three hypothetical realistic scenarios were simulated in the ERT evaluation. The first two scenarios assume the same leak amount and rate (i.e., between 1/1/1951 and 12/31/1951 at the rate of 347 m 3 per year) but different leaky tanks. Scenario 1 assumes leaks under tank B-102, which is located on the edge of the B-tank farm and surrounded by a few metallic infrastructure including cased pipes/wells/tanks. Scenario 2 assumes leaks under tank B-108, which is located near the center of the B-tank farm and surrounded by larger amount of metallic infrastructure than B-102. Scenario 3 assumes the same metallic infrastructure as B-102, with a more recent contaminant leak that was simulated to have occurred between 1/1/2018 and 12/31/2023 at a rate of 1.89 m 3 per year. The leak time in Scenarios 1 and 2 corresponds to a historical overfill event in 1951 and Scenario 3 corresponds to a recent found tank leak in 2019. In each scenario, a “true” bulk EC model vs. time reflecting contaminant migration was generated. ERT data was simulated from these “true” bulk EC models and a time-lapse ERT inversion produced “imaged” bulk EC vs. time. Three electrode configurations in two, four and eight boreholes surrounding the leak tank were used in the ERT simulations in each scenario. These borehole configurations were considered logistically feasible and cost-effective for monitoring. The hypothetical ERT boreholes are assumed to have non-metallic casing. By comparing the “imaged” bulk EC with the “true” bulk EC, it was demonstrated that the three configurations of wells used (two, four, and eight wells) were able to successfully monitor the migration of tank leaks through the vadose zone, with bulk EC resolution increasing with the number of down borehole ERT arrays for all scenarios. Therefore, the use of eight boreholes to perform ERT monitoring beneath the tanks provided the best spatiotemporal information.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

HTESP (High-throughput electronic structure package): A package for high-throughput ab initio calculations

High-throughput ab initio calculations are the indispensable parts of data-driven discovery of new materials with desirable properties, as reflected in the establishment of several online material databases. The accumulation of extensive theoretical data through computations enables data-driven discovery by constructing machine learning and artificial intelligence models to predict novel compounds and forecast their properties. Efficient usage and extraction of data from these existing online material databases can accelerate the next stage materials discovery that targets different and more advanced properties, such as electron–phonon coupling for phonon-mediated superconductivity. However, extracting data from these databases, generating tailored input files for different ab initio calculations, performing such calculations, and analyzing new results can be demanding tasks. Here, in this work, we introduce a software package named “HTESP” (High-Throughput Electronic Structure Package) written in Python and Bash languages, which automates the entire workflow including data extraction, input file generation, calculation submission, result collection and plotting. Our HTESP will help speed up future computational materials discovery processes.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Physical properties of metallic antiferromagneticCaCo1.86As2 single crystals

X-ray powder diffraction (XRD), magnetic susceptibility χ, isothermal magnetization M, heat capacity Cp, and in-plane electrical resistivity ρ measurements as a function of temperature T and magnetic field H are presented for CaCo1.86As2 single crystals. The electronic structure is probed by angle-resolved photoemission spectroscopy (ARPES) measurements of CaCo1.86As2 and by full-potential linearized augmented-plane-wave calculations for the supercell Ca8Co15As16 (CaCo1.88As2). Our XRD crystal structure refinement is consistent with the previous combined refinement of x-ray and neutron powder diffraction data showing a collapsed-tetragonal ThCr2Si2-type structure with 7(1)% vacancies on the Co sites corresponding to the composition CaCo1.86As2 [D. G. Quirinale et al., Phys. Rev. B 88, 174420 (2013)]. The anisotropic χ(T) data are consistent with the magnetic neutron diffraction data of Quirianale et al. that demonstrate the presence of A-type collinear antiferromagnetic order below the Néel temperature TN=52(1) K with the easy axis being the tetragonal c axis. However, no clear evidence from the ρ(T) and Cp(T) data for a magnetic transition at TN is observed. A metallic ground state is demonstrated from the band calculations and the ρ(T), Cp(T), and ARPES data, and spin-polarized calculations indicate a competition between the A-type AFM and FM ground states. The Cp(T) data exhibit a large Sommerfield electronic coefficient reflecting a large density of states at the Fermi energy D(EF) that is enhanced compared with the band structure calculation where the bare D(EF) arises from Co 3d bands. At 1.8 K, the M(H) data for H∥c exhibit a well-defined first-order spin-flop transition at an applied field of 3.5 T. The small ordered moment of ≈0.3μB/Co obtained from the M(H) data at low T, the large exchange enhancement of χ and the lack of a self-consistent interpretation of the χ(T) and M(H,T) data in terms of a local moment Heisenberg model together indicate that the magnetism of CaCo1.86As2 is itinerant.

36 MATERIALS SCIENCE↗