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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Structural, magnetic and electronic properties of Ti-doped BaFeO 3-δ exhibiting colossal dielectric permittivity

We report a systematical investigation of the structural, magnetic, electronic, and dielectric properties of BaFe 1-x Ti x O 3-δ (x = 0.05, 0.10, 0.15 and 0.20) samples synthesized via the solid-state reaction method. Rietveld refinement using a combination of room-temperature X-ray (XRD) and neutron powder diffraction (NPD) data confirms single phases with a 6H-type structure for all the samples. X-ray absorption spectroscopy (XAS) study reveals a coexistence of Fe 3+ and Fe 4+ , whose ratio remains almost unchanged with increasing Ti concentration. Magnetization measurements reveal a low-temperature inhomogeneous magnetic state with coexisting ferromagnetic (FM), AFM clusters and a paramagnetic phase. Moreover, magnetization of x = 0.10 shows a pinched hysteresis loop behavior, suggesting the coexistence of hard and soft FM phases in samples with high Ti concentrations. Low-temperature NPD measurements also confirm the absence of any long-range magnetic order in the samples. A colossal dielectric permittivity and two relaxation processes are observed for most of the studied samples. There is a change in electric conduction mechanism from the small polaron hopping to the Mott's variable-range hopping with increasing Ti concentration.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Synthesis of murdochite-type Ni{sub 6}MnO{sub 8} with variable specific surface areas and the application in methane oxidation

To synthesize a murdochite-type Ni{sub 6}MnO{sub 8} with variable specific surface areas, an oxalate precursor was calcined at 350–500 °C in flowing argon, and the calcined sample was heated to 600 °C in air. The lattice constant of the Ni{sub 6}MnO{sub 8} did not depend on the calcination temperature of the precursor, while the specific surface area decreased from 8.4 m{sup 2}/g to 2.6 m{sup 2}/g when increasing the calcination temperature of the precursor. The methane (CH{sub 4}) oxidation data indicated that the temperature corresponding to the 50% conversion (T{sub 50%}) of Ni{sub 6}MnO{sub 8} calcined at 350 °C or 400 °C was lower than that of all other Ni{sub 6}MnO{sub 8} specimens. However, the intrinsic conversion of Ni{sub 6}MnO{sub 8} calcined at 350 °C, which is defined as conversion per specific surface area, was half of that of all other Ni{sub 6}MnO{sub 8} specimens. The degree of crystallinity and catalytic performance of the Ni{sub 6}MnO{sub 8} calcined at 400 °C were high. - Graphical abstract: The conversion of CH{sub 4} into CO{sub 2} and H{sub 2}O on Ni{sub 6}MnO{sub 8}, which was heated at 600 °C in air after the calcination of the precursor at 350 °C, 400 °C, 450 °C, or 500 °C in flowing argon, was measured. Since the specific surface area was strongly affected by the calcination temperature of the precursor, intrinsic conversion (IC) was defined as conversion per the specific surface area. For comparison, the IC value on Ni{sub 6}MnO{sub 8} synthesized by the direct calcination of the precursor at 600 °C in air is plotted. - Highlights: • The oxalate precursor was calcined at 350–500 °C in flowing argon. • Murdochite-type Ni{sub 6}MnO{sub 8} was obtained by heating the calcined sample in air. • The specific surface area of Ni{sub 6}MnO{sub 8} varied with the calcination temperature. • The degree of crystallinity and catalysis of Ni{sub 6}MnO{sub 8} calcined at 400 °C were high.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Relationship between ductility and the porosity of additively manufactured AlSi10Mg

Additive manufacturing via selective laser melting can result in variable levels of internal porosity both between build plates and within components from the same build. In this work, sample porosity levels were compared to tensile properties for 176 samples spanning eight different build plates. Sample porosity was measured both by Archimedes density, which provided an estimation of overall porosity, and by observation of voids in the fracture surface, which provided an estimation of the porosity at the failure plane. The porosity observed at the fracture surface consistently demonstrated higher porosity than that suggested by Archimedes density. The porosity values obtained from both methods were compared against the mechanical results. Sample porosity appears to have some correlation to the ultimate tensile strength, yield strength, and modulus, but the strongest relationship is observed between porosity and ductility. Three different models were used to relate the fracture surface porosity to the ductility. The first method was a simple linear regression analysis, while the other two models have been used to relate porosity to ductility in cast alloys. It is shown that all three models fit the data well over the observed porosity ranges, suggesting that the models taken from casting theory can extend to additively manufactured metals. Finally, it is proposed that the non-destructive Archimedes method could be used to estimate an approximate sample ductility through the use of correlations realized here. Such a relationship could prove useful for design and for a deeper understanding of the impact of pores on tensile behavior.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Comparing deuterium excess to large-scale precipitation recycling models in the tropics

Precipitation recycling is essential to sustaining regional ecosystems and water supplies, and it is impacted by land development and climate change. This is especially true in the tropics, where dense vegetation greatly influences recycling. Unfortunately, large-scale models of recycling often exhibit high uncertainty, complicating efforts to estimate recycling. Here, we examine how deuterium excess (d-excess), a stable-isotope quantity sensitive to recycling effects, acts as an observational proxy for recycling. While past studies have connected variability in d-excess to precipitation origins at local or regional scales, our study leverages >3000 precipitation isotope samples to quantitatively compare d-excess against three contemporary recycling models across the global tropics. Using rank-correlation, we find statistically significant agreement ( $\bar \tau = 0.52$ τ ¯ = 0.52 to $0.70$ 0.70 ) between tropical d-excess and recycling that is strongly mediated by seasonal precipitation, vegetation density, and scale mismatch. Our results detail the complex relationship between d-excess and precipitation recycling, suggesting avenues for further investigation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

A NEW CORRELATION BETWEEN GRB X-RAY FLARES AND THE PROMPT EMISSION

From a sample of gamma-ray bursts (GRBs) detected by the Fermi and Swift missions, we have extracted the minimum variability timescales for temporal structures in the light curves associated with the prompt emission and X-ray flares. A comparison of this variability timescale with pulse parameters such as rise times, determined via pulse-fitting procedures, and spectral lags, extracted via the cross-correlation function, indicates a tight correlation between these temporal features for both the X-ray flares and the prompt emission. These correlations suggest a common origin for the production of X-ray flares and the prompt emission in GRBs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Ultracool dwarfs candidates based on 6 yr of the Dark Energy Survey data

ABSTRACT We present a sample of 19 583 ultracool dwarf candidates brighter than z ≤23 selected from the Dark Energy Survey DR2 coadd data matched to VHS DR6, VIKING DR5, and AllWISE covering ∼ 480 deg2. The ultracool candidates were first pre-selected based on their (i–z), (z–Y), and (Y–J) colours. They were further classified using a method that compares their optical, near-infrared, and mid-infrared colours against templates of M, L, and T dwarfs. 14 099 objects are presented as new L and T candidates and the remaining objects are from the literature, including 5342 candidates from our previous work. Using this new and deeper sample of ultracool dwarf candidates we also present: 20 new candidate members to nearby young moving groups and associations, variable candidate sources and four new wide binary systems composed of two ultracool dwarfs. Finally, we also show the spectra of 12 new ultracool dwarfs discovered by our group and presented here for the first time. These spectroscopically confirmed objects are a sanity check of our selection of ultracool dwarfs and photometric classification method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity production and direct use of hydrothermal fluids. Transmissive fuid-fow pathways are relatively rare in the subsurface, but are critical components of hydrothermal systems like Brady and many other types of fuid-fow systems in fractured rock. Here, we analyze geologic data with ML methods to unravel the local geologic controls on these pathways. The ML method, non-negative matrix factorization with k-means clustering (NMFk), is applied to a library of 14 3D geologic characteristics hypothesized to control hydrothermal circulation in the Brady geothermal field. Our results indicate that macro-scale faults and a local step-over in the fault system preferentially occur along production wells when compared to injection wells and non-productive wells. We infer that these are the key geologic characteristics that control the through-going hydrothermal transmission pathways at Brady. Our results demonstrate: (1) the specific geologic controls on the Brady hydrothermal system and (2) the efficacy of pairing ML techniques with 3D geologic characterization to enhance the understanding of subsurface processes. This submission includes the published journal article detailing this work, the published 3D geologic map of the Brady Geothermal Area used as a basis to develop structural and geological variables that are hypothesized to control or effect permeability or connectivity, 3D well data, along which geologic data were sampled for PCA analyses, and associated metadata file. This work was done using the GeoThermalCloud framework, which is part of SmartTensors (both are linked below).

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Soil Environmental Conditions in the East River Watershed, CO

This dataset contains depth-resolved soil environmental variables collected between June 2016 and October 2018 from the Bradley Meadow site in the East River watershed. Datalogger output from 7 Campbell CS655 12 cm Soil Moisture and Temperature Sensors including depth, temperature, volumetric water content, and electrical conductivity are included in ‘BM_Merged_T_VWC_0616_10_18.csv’. Sensors were installed in June 2016. Data have been processed to merge raw sensor data and to remove additional variables. No additional QA/QC was performed. Measured pCO2 and depth are contained in ‘BM_EGM_WELL_CO2.csv’. These data represent gas well samples measured via injection using a PP Systems EGM-5 infra-red gas analyzer as described in the methods section. Measured CO2 surface flux values are contained in 'BM_EGM_Surface_Flux.csv'. These were measured using the PP Systems EGM-5 with the Soil Respiration Chamber attachment. Multiple reps are reported for each measurement including CO2 flux rate calculations using built-in linear and quadratic function methods, and average and standard deviations are taken across all reps and calculation methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Merged Aerosol Value-Added Product Report

The Merged Aerosol Value-Added Product (VAP) simplifies scientists’ use of Atmospheric Radiation Measurement (ARM) User Facility aerosol data by performing several tedious, time-consuming tasks for the users. First, the VAP identifies the best data available when multiple datastreams exist for a single geophysical quantity so that ARM users do not have to research this for themselves. Second, the VAP consolidates multiple ARM aerosol datastreams into a single file for ARM data users so that they do not have to download, open, and read multiple files for their analysis. Next, the VAP transforms all measurements onto a common one-hour timestamp. The one-hour resolution matches the time resolution of the slowest instrument. Instruments with faster sampling rates than one measurement per hour are averaged over the time interval. Finally, the VAP reads the QA/QC variables and marks data with known issues as missing, so that users do not have to spend excessive time cleaning data. This includes incorporating Data Quality Reports (DQRs) that exist at the time when the VAP data is generated. DQRs are reports filed by instrument mentors or data users that indicate a problem with the output data of individual instruments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Custom-trained Machine-learning Interatomic Potentials: ZnCl2 Aqueous Solution

This dataset was generated using an iterative active-learning strategy implemented in the ArcaNN software package (https://github.com/arcann-chem/arcann_training) to train machine-learning interatomic potentials for aqueous ZnCl2 solutions. Each active-learning cycle consisted of three stages: training, exploration, and labeling. The initial training set combined configurations generated in this work from enhanced-sampling ab initio molecular dynamics simulations with configurations from a previously reported neural-network-potential study of aqueous ZnCl2. The enhanced-sampling ab initio molecular dynamics simulations involved Zn–Cl separation and the chloride coordination number around Zn²? as collective variables. These configurations served as the seed dataset. Subsequent active-learning cycles expanded the training set by identifying and labeling configurations that were poorly represented by the current models, thereby improving coverage of ion-association states and changes in local coordination and charge-state environments relevant to the solution free-energy landscape. For all selected configurations, single-point calculations of the total energies and atomic forces were performed within density functional theory using the CP2K Quickstep module. Reference calculations employed the revPBE-D3 and r2SCAN exchange-correlation functionals. Motivated by recent work on aqueous Zn²?, the main revPBE calculations omitted D3 dispersion contributions involving Zn²?, while retaining the D3 correction for water and chloride. For comparison, fully dispersion-corrected revPBE-D3 reference calculations were also performed, with D3 applied to all species, including Zn²?. Valence electrons were treated explicitly, while core electrons were represented using norm-conserving Goedecker–Teter–Hutter pseudopotentials. The wave functions were expanded using the mixed Gaussian-and-plane-wave scheme with TZV2P-MOLOPT basis sets for all elements and a 600 Ry auxiliary plane-wave cutoff for the electron density. Self-consistent-field convergence was accelerated using the orbital-transformation and Direct Inversion in the Iterative Subspace algorithms, with a convergence threshold of 10?6. All single-point calculations were performed in periodic orthorhombic cells. The CELL_REF keyword in CP2K was used to define a fixed reference cell with a box length of 25 Å. This treatment ensured a consistent reference for configurations extracted from NpT trajectories with fluctuating cell dimensions. The resulting DFT energies and atomic forces constitute the ground-truth labels used to train the MLIPs. The resulting MLIP was trained for aqueous ZnCl2 solutions spanning concentrations from 0 to 30 molal and a broad pH range, from strongly acidic to strongly basic conditions. Representative examples of configurations included in the MLIP training dataset are provided below. These include 1) Representative configurations from the dataset labeled at the revPBE-D3 level, with D3 dispersion interactions involving Zn2+ excluded (revPBE-wo-D3). 2) Representative configurations from the dataset labeled at the fully dispersion-corrected revPBE-D3 level, with D3 interactions applied to all species, including Zn2+ (revPBE-D3). 3) Representative configurations from the dataset labeled at the r2SCAN level of theory (r2SCAN).

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗
DOE OSTI2020

Dynamic Topology Reconfiguration of Boltzmann Machines on Quantum Annealers

Boltzmann machines have useful roles in deep learning applications, such as generative data modeling, initializing weights for other types of networks, or extracting efficient representations from high-dimensional data. Most Boltzmann machines use restricted topologies that exclude looping connectivity, as such connectivity creates complex distributions that are difficult to sample. We have used an open-system quantum annealer to sample from complex distributions and implement Boltzmann machines with looping connectivity. Further, we have created policies mapping Boltzmann machine variables to the quantum bits of an annealer. These policies, based on correlation and entropy metrics, dynamically reconfigure the topology of Boltzmann machines during training and improve performance.

Liu, Jeremy (ORCID:0000000172299417)↗
DOE OSTI2016

A STUDY OF BROADBAND FARADAY ROTATION AND POLARIZATION BEHAVIOR OVER 1.3–10 GHz IN 36 DISCRETE RADIO SOURCES

We present a broadband polarization analysis of 36 discrete polarized radio sources over a very broad, densely sampled frequency band. Our sample was selected on the basis of polarization behavior apparent in narrowband archival data at 1.4 GHz: half the sample shows complicated frequency-dependent polarization behavior (i.e., Faraday complexity) at these frequencies, while half shows comparatively simple behavior (i.e., they appear Faraday simple ). We re-observed the sample using the Australia Telescope Compact Array in full polarization, with 6 GHz of densely sampled frequency coverage spanning 1.3–10 GHz. We have devised a general polarization modeling technique that allows us to identify multiple polarized emission components in a source, and to characterize their properties. We detect Faraday complex behavior in almost every source in our sample. Several sources exhibit particularly remarkable polarization behavior. By comparing our new and archival data, we have identified temporal variability in the broadband integrated polarization spectra of some sources. In a number of cases, the characteristics of the polarized emission components, including the range of Faraday depths over which they emit, their temporal variability, spectral index, and the linear extent of the source, allow us to argue that the spectropolarimetric data encode information about the magneto-ionic environment of active galactic nuclei themselves. Furthermore, the data place direct constraints on the geometry and magneto-ionic structure of this material. We discuss the consequences of restricted frequency bands on the detection and interpretation of polarization structures, and the implications for upcoming spectropolarimetric surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Processing of Neutron Diffraction Data for Strain Measurement in Geological Materials

: Conventional rock mechanics testing techniques typically involve the loading of samples and measurement of displacements or strains on the outer boundary of the specimen surface. Neutron diffraction based strain measurement techniques represent a unique and powerful tool for measuring the strain within geological materials under load. The structural variability and non-uniform crystallinity of geological materials, however, create many complexities in the intensity patterns that must be analyzed to quantify strains within the material. The attenuating and scattering properties of the pressure cell housing the sample further add difficulties to the data analysis. This paper describes the methods and processes used to process neutron scattering data for strain measurement in geological materials. It is intended to provide a primer for those in the rock mechanics community that are interested in utilizing this technique along with additional discussion of neutron diffraction experimental factors that may affect data quality.

Polsky, Yarom↗
DOE OSTI2025

Hyperspectral Cathodoluminescence of Bastnäsite at the Mountain Pass Mine, USA: Implications for REE Mineralisation and Mining

This study uses micro-analyses including hyperspectral cathodoluminescence to image and obtain mineral spectral to help evaluate REE deportment via from Mountain Pass Mine in California. It presents the first known CL-based spectra for bastnäsite, new information regarding baryte CL spectra, providing insights on the coeval and spatial relationship between REE, Ba, and S in carbonatite systems. Bastnäsite, baryte, and monazite are often intergrown in both brecciated, “blue ore” samples, and these minerals occur as an apparent intercumulus texture in the dolomite-rich, “white ore” samples. Bastnäsite luminescence is present, but very low compared to baryte in the visible spectrum. Bastnäsite illustrates some textural variability related to its main luminescent peak ~1.4 eV, which is indicative of Nd3+. It also exhibits several other small peaks comprised of multiple activators related to various REE, including Ce3+, Sm3+, Eu3+, and potentially Eu2+. Baryte displays textures of variable complexity but often with darker rims near crystal margins. It luminesces mainly at 1.4-1.52 eV, 2.05 eV, and 3.59-4.08 eV. The 2.05 eV peak is likely attributed to Ag+, but the other peaks are more enigmatic.

58 - GEOSCIENCES↗
DOE OSTI2017

The Slowly Varying Corona. I. Daily Differential Emission Measure Distributions Derived from EVE Spectra

Daily differential emission measure (DEM) distributions of the solar corona are derived from spectra obtained by the Extreme-ultraviolet Variability Experiment (EVE) over a 4 yr period starting in 2010 near solar minimum and continuing through the maximum of solar cycle 24. The DEMs are calculated using six strong emission features dominated by Fe lines of charge states viii, ix, xi, xii, xiv, and xvi that sample the nonflaring coronal temperature range 0.3–5 MK. A proxy for the non-Fe xviii emission in the wavelength band around the 93.9 Å line is demonstrated. There is little variability in the cool component of the corona (T < 1.3 MK) over the 4 yr, suggesting that the quiet-Sun corona does not respond strongly to the solar cycle, whereas the hotter component (T > 2.0 MK) varies by more than an order of magnitude. A discontinuity in the behavior of coronal diagnostics in 2011 February–March, around the time of the first X-class flare of cycle 24, suggests fundamentally different behavior in the corona under solar minimum and maximum conditions. This global state transition occurs over a period of several months. The DEMs are used to estimate the thermal energy of the visible solar corona (of order 10{sup 31} erg), its radiative energy loss rate ((2.5–8) × 10{sup 27} erg s{sup −1}), and the corresponding energy turnover timescale (about an hour). The uncertainties associated with the DEMs and these derived values are mostly due to the coronal Fe abundance and density and the CHIANTI atomic line database.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

BEYONDPLANCK X. Planck Low Frequency Instrument frequency maps with sample-based error propagation

We present Planck Low Frequency Instrument (LFI) frequency sky maps derived within the BEYONDPLANCK framework. This framework draws samples from a global posterior distribution that includes instrumental, astrophysical, and cosmological parameters, and the main product is an entire ensemble of frequency sky map samples, each of which corresponds to one possible realization of the various modeled instrumental systematic corrections, including correlated noise, time-variable gain, as well as far sidelobe and bandpass corrections. This ensemble allows for computationally convenient end-to-end propagation of low-level instrumental uncertainties into higher-level science products, including astrophysical component maps, angular power spectra, and cosmological parameters. We show that the two dominant sources of LFI instrumental systematic uncertainties are correlated noise and gain fluctuations, and the products presented here support – for the first time – full Bayesian error propagation for these effects at full angular resolution. We compared our posterior mean maps with traditional frequency maps delivered by the Planck Collaboration, and find generally good agreement. The most important quality improvement is due to significantly lower calibration uncertainties in the new processing, as we find a fractional absolute calibration uncertainty at 70 GHz of Δg 0 /g 0 = 5 x 10 -5 , which is nominally 40 times smaller than that reported by Planck 2018. However, we also note that the original Planck 2018 estimate has a nontrivial statistical interpretation, and this further illustrates the advantage of the new framework in terms of producing self-consistent and well-defined error estimates of all involved quantities without the need of ad hoc uncertainty contributions. We describe how low-resolution data products, including dense pixel-pixel covariance matrices, may be produced from the posterior samples directly, without the need for computationally expensive analytic calculations or simulations. We conclude that posterior-based frequency map sampling provides unique capabilities in terms of low-level systematics modeling and error propagation, and may play an important role for future Cosmic Microwave Background (CMB) B-mode experiments aiming at nanokelvin precision.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings: Preprint

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape of the load profile is the most significant predictor of the size of the battery.

25 ENERGY STORAGE↗