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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

Superlattice-Like Stacking Fault Array in Ion-Irradiated GaN

Controlling defects in crystalline solids is of technological importance for realizing desirable material properties. Irradiation with energetic particles is useful for designing the spatial distribution and concentration of defects in materials. Here, we performed ion irradiation into hexagonal GaN with the wurtzite structure and demonstrated the spontaneous formation of superlattice-like stacking fault arrays. It was found that the modulation period can be controlled by varying the irradiation conditions and subsequent thermal treatments.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2020

Development and evaluation of a list mode neutron coincidence collar for spatial response measurements of fresh fuel assemblies

A traditional safeguards neutron coincidence counting system, the Neutron Coincidence Collar, has been modified to incorporate individual preamplifiers on each of its 18 3He tubes in active interrogation mode. When used with list mode data acquisition (LMDA) and analysis, a signal from each 3He tube can be recorded and analyzed to allow a spatial response measurement to be performed on an item based on count rate and 3He tube location within the system. The ultimate goal of this project is to demonstrate the capabilities of a list mode response matrix for the nondestructive assay of fresh nuclear fuel assemblies. To enable partial defect detection of fuel pin locations and absences within an assembly, the project aims to extend well-established correlated neutron analysis techniques on a preexisting Neutron Coincidence Collar by extracting a greater number of useful signatures from the system than are currently generated. LMDA, combined with the addition of multiple preamplifiers, facilitates this capability by increasing the number of simultaneous signals that can be measured; this allows an in-depth analysis of neutron coincidence events to determine a fissioning item’s location based on the measured doubles count rate in various channel logic coincidence combinations. All of this can be done from a single measurement pulse train in offline analysis, which is the major benefit provided by LMDA. Through various stages of development and testing, a Mirion Technologies model JCC-71 Neutron Coincidence Collar has been successfully retrofit with modern electronics designed in-house at Oak Ridge National Laboratory, matching preexisting JAB-01 electronics performance, while maintaining the original system footprint. This paper presents these various stages of development and experimental evaluation of the proof of concept system.

Moore, Angela S.↗
DOE OSTI2018

Simulating groundwater uptake and hydraulic redistribution by phreatophytes in a high-resolution, coupled subsurface-land surface model

Several new functions representing groundwater dependent vegetation were incorporated into a coupled subsurface-land surface model, ParFlow.CLM, in order to adequately describe groundwater water uptake, hydraulic redistribution, and plant water stress. The modified model was used to conduct three-dimensional, stand-scale simulations of a Mediterranean oak savanna in California. It performed well and captured daily, hourly and spatial water and energy dynamics, as well as groundwater evapotranspiration rates. The new model was then compared to various approaches, the original ParFlow.CLM and a version using a root water uptake compensation equation. During the dry season, the modified model closely predicted the measured transpiration rate while the original model predicted that it would become zero and the compensation approach overestimated it by nearly double. The modified model also allowed for analysis of several key ecohydrological processes, namely the hydraulic redistribution when plants were both active and dormant, the leaf water potential, and xylem cavitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Pressure and fluid-driven fracture propagation in porous media using an adaptive finite element phase field model

This work presents phase field fracture modeling in heterogeneous porous media. We develop robust and efficient numerical algorithms for pressure-driven and fluid-driven settings in which the focus relies on mesh adaptivity in order to save computational cost for large-scale 3D applications. In the fluid-driven framework, we solve for three unknowns pressure, displacements and phase field that are treated with a fixed-stress iteration in which the pressure and the displacement–phase-field system are decoupled. The latter subsystem is solved with a combined Newton approach employing a primal–dual active set method in order to account for crack irreversibility. Numerical examples for pressurized fractures and fluid filled fracture propagation in heterogeneous porous media demonstrate our developments. Finally in particular, mesh refinement allows us to perform systematic studies with respect to the spatial discretization parameter.

42 ENGINEERING↗
DOE OSTI2021

X-ray computed tomography-based porosity analysis: Algorithms and application for porous woody biomass

The properties of lignocellulosic biomass, such as bulk physical, thermal, and mechanical properties, as well as the mobility of enzymes or catalysts, are largely affected by porosity, pore structures, and pore size distribution. While X-ray computed tomography (CT) has been introduced to effectively produce 3D volumetric images of material microstructure, a quantitative porosity analysis from the 3D images has never been done. This work introduces a first-of-its-kind X-ray CT-based quantitative porosity analysis method and applies the developed toolkit to characterize the internal porosity distribution of loblolly pine. A sample loblolly pine chip was scanned by a nano-resolution X-ray CT system and digitally reconstructed after a sequence of image processing operations. Here, a comprehensive porosity analysis was then performed to quantify the envelope porosity, the spatial distribution of local porosity, and the directional porosity. Solutions to the various challenges in image processing, porosity calculation, and large data handling are provided.

42 ENGINEERING↗
DOE OSTI2016

Toward Molecule-Specific Geochemistry of Heavy Ends: Application to the Upstream Oil Industry

Detailed molecular analysis of the composition of petroleum is typically performed on only the light (volatile) fraction, using analyses involving gas chromatography (GC). Heavier (nonvolatile) components such as kerogen, bitumen, and asphaltenes, which are relevant to conventional reservoirs and particularly to unconventional gas shale and tight oil formations, are not amenable to analysis by GC and instead are typically studied by more phenomenological techniques. This report describes a suite of analytical techniques that can provide sufficient average molecular information on the heavy ends (defined as the nonvolatile fraction) to be useful for a variety of industrial applications, expanding the discipline of molecule-specific geochemistry into the non-GC amenable fractions of petroleum materials. Heavy ends are composed of the elements C, H, N, S, and O, and the bonding environments of each can be measured by various solid state spectroscopies: nuclear magnetic resonance (NMR) and infrared (IR) spectroscopies for C, H, and O; X-ray absorption near-edge structure (XANES) spectroscopy for S and N. Additionally, advances in mass spectrometry, including techniques such as laser desorption laser ionization mass spectrometry (L2MS), can be used to measure the molecular weight and dominant molecular architecture of asphaltenes. Moreover, higher-order structures can be measured: samples of kerogen with representative pore geometry can be prepared, and those pore systems are analyzed with techniques such as X-ray diffraction and neutron scattering. Colloidal structures of asphaltenes can be measured with a variety of techniques, which reveal a hierarchical aggregation structure. These analyses provide sufficient structural data to enable structure–property and structure–function relationships to be determined, which can be applied to the characterization of conventional and unconventional resources. In gas shale and tight oil formations, which contain abundant inorganic minerals as well as kerogen, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) is used for simultaneous analysis of mineralogy, kerogen content, and maturity, typically performed at the wellsite. In conventional reservoirs, spatial variations in the asphaltene concentration measured by downhole fluid analysis logging tools are being interpreted with a recently developed equation of state to address upstream issues such as reservoir connectivity, tar mat formation, and fault block migration. Furthermore, as more heavy end analyses are developed, further scientific knowledge and industrial applications of heavy end geochemistry are anticipated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Microbial Community Changes across Time and Space in a Constructed Wetland

Constructed wetlands are artificial ecosystems designed to replicate natural wetland processes. Microbial communities play a pivotal role in cycling essential elements, particularly sulfur, which is crucial for trace metal fixation and remobilization in these ecosystems. By their response to their environment, microbial communities act as biological indicators of the wetland performance. To address knowledge gaps pertinent to the changes in trace metal bioavailability in relation to microbial activities in the H-02 constructed wetland, we performed this study to investigate temporal and spatial variations in microbial communities by using molecular biology tools. Quantitative polymerase chain reaction and next generation sequencing techniques were employed to analyze archaeal and bacterial groups associated with sulfur and methane cycling. Alpha diversity indices were used to assess species richness, evenness, and dominance. Results indicated high gene abundance of Desulfuromonas (5.37 × 10 6 g.cell –1 ), methane oxidizing bacteria (6.92 × 10 6 g.cell –1 ), and methanogenic microorganisms (3.02 × 10 5 g.cell –1 ) during cool months. Warm months were marked by sulfate reducing bacteria dominance (3.31 × 10 6 g.cell –1 ), potentially due to competitive interactions and environmental conditions, higher temperatures, and lower redox potential. Spatial variability among microbial groups was insignificant, but trends in gene abundance indicated complex factors influencing these groups. Next generation sequencing data demonstrated Firmicutes as the most abundant phylum with over 50% regardless of the season or sampling location. Cool months exhibited higher alpha diversity than warm months. Overall, this study showed that seasonal changes significantly impacted the microbial communities in the H-02 constructed wetland that are associated with the sulfur cycle and eventually trace metal biogeochemistry, revealing two distinct mechanisms of the sulfur cycle between the two main seasons, whereas spatial variability effects were not conclusive.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Interstitial Nature of Mn 2+ Doping in 2D Perovskites

Halide perovskites doped with magnetic impurities (such as the transition metals Mn 2+ , Co 2+ , Ni 2+ ) are being explored for a wide range of applications beyond photovoltaics, such as spintronic devices, stable light-emitting diodes, single-photon emitters, and magneto-optical devices. However, despite several recent studies, there is no consensus on whether the doped magnetic ions will predominantly replace the octahedral B-site metal via substitution or reside at interstitial defect sites. Here, by performing correlated nanoscale X-ray microscopy, spatially and temporally resolved photoluminescence measurements, and magnetic force microscopy on the inorganic 2D perovskite Cs 2 PbI 2 Cl 2 , we show that doping Mn 2+ into the structure results in a lattice expansion. The observed lattice expansion contrasts with the predicted contraction expected to arise from the B-site metal substitution, thus implying that Mn 2+ does not replace the Pb 2+ sites. Photoluminescence and electron paramagnetic resonance measurements confirm the presence of Mn 2+ in the lattice, while correlated nano-XRD and X-ray fluorescence track the local strain and chemical composition. Density functional theory calculations predict that Mn 2+ atoms reside at the interstitial sites between two octahedra in the triangle formed by one Cl – and two I – atoms, which results in a locally expanded structure. These measurements show the fate of the transition metal dopants, the local structure, and optical emission when they are doped at dilute concentrations into a wide band gap semiconductor.

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

Modeling the Transmission of Optical Lightning Signals Through Complex 3‐D Cloud Scenes

Abstract Space‐based lightning imagers have shown that complex cloud scenes consisting of multiple tall convective features, anvil clouds, and warm boundary cloud layers are illuminated by lightning in many different ways depending on where the lightning occurs and how energetic it is. Modifications to the optical lightning signals from radiative transfer in the cloud medium can lead to reductions in detection efficiency and location accuracy for these instruments and can also cause some of the optical signals that are detected to have unexpected spatial energy distributions. In this study, we perform Monte Carlo radiative transfer simulations of optical lightning emissions in clouds with complex 3‐D geometries to shed some light on the origins of certain irregular radiance patterns that have been recorded from orbit. We show that diffuse reflections off nearby cloud faces can explain lightning signals in nonelectrified clouds, tall clouds can result in poor optical transmission and suppressed radiances that could lead to missed events and that particularly favorable viewing conditions can cause otherwise normal lightning to produce a superbolt that is orders of magnitude brighter than the same flash seen from a different angle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Detection of a 2.8 THz quantum cascade laser with a semiconductor nanowire field-effect transistor coupled to a bow-tie antenna

The use of a high-electron mobility semiconductor nanowire as transistor channel has recently allowed the extension of the spectral coverage of THz field-effect transistor detectors up to 1.5 THz. In this report, we demonstrate efficient operation of a field-effect transistor detector based on a semiconductor nanowire at a much higher frequency, 2.8 THz, with a responsivity ≈5 V/W in a bandwidth ≈100 kHz, thus proving the full potential of such approach for the detection of THz quantum cascade lasers. Finally, such a THz sensing system is exploited to perform raster scan transmission imaging, with high spatial resolution, signal-to-noise ratio, and acquisition rate.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Bayesian inference in band excitation scanning probe microscopy for optimal dynamic model selection in imaging

The universal tendency in scanning probe microscopy (SPM) over the last two decades is to transition from simple 2D imaging to complex detection and spectroscopic imaging modes. The emergence of complex SPM engines brings forth the challenge of reliable data interpretation, i.e., conversion from detected signals to descriptors specific to tip–surface interactions and subsequently to material’s properties. In this work, we implemented a Bayesian inference approach for the analysis of the image formation mechanisms in band excitation SPM. Compared to the point estimates in classical functional fit approaches, Bayesian inference allows for the incorporation of extant knowledge of materials and probe behavior in the form of corresponding prior distribution and return the information on the material functionality in the form of readily interpretable posterior distributions. We explore the nonlinear mechanical behaviors spatially in a classical ferroelectric material, PbTiO 3 . We observe the non-trivial evolution of the Duffing stiffness term and the nonlinearity of the sample surface, determine spatial clustering of the nonlinear response, and perform a Landau analysis on predicting the nonlinear coefficient, which indicates that ferroelectric behavior can be a cause of the observed results. These observations suggest that the spectrum of anomalous behaviors at the ferroelectric domain walls may be broader than previously believed and can extend to non-conventional mechanical properties in addition to static and microwave conductance.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Source size of x rays from self-modulated laser wakefield accelerators

A comparative study of x-ray sources generated with different mechanisms from self-modulated laser wakefield acceleration (SM-LWFA) electrons was performed to compare the source size or spatial resolution for use in high energy density science applications. We examine the source size of betatron, inverse Compton scattering, and bremsstrahlung radiation with a Fresnel diffraction based formalism and a modified x-ray ray tracing model. We observe the dependence of source size on the radiation generation process, laser parameters, and compare to what is possible in other regimes of LWFA, as well as current methods. This information is significant as we begin to explore the use of light sources driven by SM-LWFA for use as a diagnostic at large-scale laser facilities where blowout regime LWFA is not possible.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Modeling freight mode choice using machine learning classifiers: a comparative study using Commodity Flow Survey (CFS) data

This study explores the usefulness of machine learning classifiers for modeling freight mode choice. We investigate eight commonly used machine learning classifiers, namely Naïve Bayes, Support Vector Machine, Artificial Neural Network, K-Nearest Neighbors, Classification and Regression Tree, Random Forest, Boosting and Bagging, along with the classical Multinomial Logit model. US 2012 Commodity Flow Survey data are used as the primary data source; we augment it with spatial attributes from secondary data sources. The performance of the classifiers is compared based on prediction accuracy results. The current research also examines the role of sample size and training-testing data split ratios on the predictive ability of the various approaches. In addition, the importance of variables is estimated to determine how the variables influence freight mode choice. The results show that the tree-based ensemble classifiers perform the best. Specifically, Random Forest produces the most accurate predictions, closely followed by Boosting and Bagging. With regard to variable importance, shipment characteristics, such as shipment distance, industry classification of the shipper and shipment size, are the most significant factors for freight mode choice decisions.

42 ENGINEERING↗
DOE OSTI2024

Using graph neural networks to reconstruct charged pion showers in the CMS High Granularity Calorimeter

A novel method to reconstruct the energy of hadronic showersin the CMS High Granularity Calorimeter (HGCAL) is presented. TheHGCAL is a sampling calorimeter with very fine transverse andlongitudinal granularity. The active media are silicon sensors andscintillator tiles readout by SiPMs and the absorbers are acombination of lead and Cu/CuW in the electromagnetic section, andsteel in the hadronic section. The shower reconstruction method isbased on graph neural networks and it makes use of a dynamicreduction network architecture. It is shown that the algorithm isable to capture and mitigate the main effects that normally hinderthe reconstruction of hadronic showers using classicalreconstruction methods, by compensating for fluctuations in themultiplicity, energy, and spatial distributions of the shower'sconstituents. The performance of the algorithm is evaluated usingtest beam data collected in 2018 prototype of the CMS HGCALaccompanied by a section of the CALICE AHCAL prototype. Thecapability of the method to mitigate the impact of energy leakagefrom the calorimeter is also demonstrated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

A new data-driven map predicts substantial undocumented peatland areas in Amazonia

Tropical peatlands are among the most carbon-dense terrestrial ecosystems yet recorded. Collectively, they comprise a large but highly uncertain reservoir of the global carbon cycle, with wide-ranging estimates of their global area (441 025–1700 000 km 2 ) and below-ground carbon storage (105–288 Pg C). Substantial gaps remain in our understanding of peatland distribution in some key regions, including most of tropical South America. Here we compile 2413 ground reference points in and around Amazonian peatlands and use them alongside a stack of remote sensing products in a random forest model to generate the first field-data-driven model of peatland distribution across the Amazon basin. Our model predicts a total Amazonian peatland extent of 251 015 km 2 (95th percentile confidence interval: 128 671–373 359), greater than that of the Congo basin, but around 30% smaller than a recent model-derived estimate of peatland area across Amazonia. The model performs relatively well against point observations but spatial gaps in the ground reference dataset mean that model uncertainty remains high, particularly in parts of Brazil and Bolivia. For example, we predict significant peatland areas in northern Peru with relatively high confidence, while peatland areas in the Rio Negro basin and adjacent south-western Orinoco basin which have previously been predicted to hold Campinarana or white sand forests, are predicted with greater uncertainty. Similarly, we predict large areas of peatlands in Bolivia, surprisingly given the strong climatic seasonality found over most of the country. Very little field data exists with which to quantitatively assess the accuracy of our map in these regions. Data gaps such as these should be a high priority for new field sampling. This new map can facilitate future research into the vulnerability of peatlands to climate change and anthropogenic impacts, which is likely to vary spatially across the Amazon basin.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Phase-resolving spin-wave microscopy using infrared strobe light

The need for sensitively and reliably probing magnetization dynamics has been increasing in various contexts such as studying novel hybrid magnonic systems, in which the spin dynamics strongly and coherently couple to other excitations, including microwave photons, light photons, or phonons. Recent advances in quantum magnonics also highlight the need for employing the magnon phase as quantum state variable, which is to be detected and mapped out with high precision in on-chip micro- and nanoscale magnonic devices. Here, in this study, we demonstrate a facile optical technique that can directly perform concurrent spectroscopic and imaging functionalities with spatial and phase resolutions, using infrared strobe light operating at 1550-nm wavelength. To showcase the methodology, we spectroscopically studied the phaseresolved spin dynamics in a bilayer of Permalloy and yttrium iron garnet Y 3 Fe 5 O 12 (YIG), and spatially imaged the backward-volume spin-wave modes of YIG in the dipolar spin-wave regime. Using the strobe light probe, the detected precessional phase contrast can be directly used to construct the map of the spin wave's wave front, in the continuous-wave regime of spin-wave propagation and in the stationary state, without needing any optical reference path. By selecting the applied field, frequency, and detection phase, the spin-wave images can be made sensitive to the precession amplitude and phase. Our results demonstrate that infrared optical strobe light can serve as a versatile platform for magneto-optical probing of magnetization dynamics, with potential implications in investigating hybrid magnonic systems.

Xiong, Yuzan [University of North Carolina, Chapel↗
DOE OSTI2015

Finite-size effects of hysteretic dynamics in multilayer graphene on a ferroelectric

The origin and influence of finite-size effects on the nonlinear dynamics of space charge stored by multilayer graphene on a ferroelectric and resistivity of graphene channel were analyzed. In this paper, we develop a self-consistent approach combining the solution of electrostatic problems with the nonlinear Landau-Khalatnikov equations for a ferroelectric. The size-dependent behaviors are governed by the relations between the thicknesses of multilayer graphene, ferroelectric film, and the dielectric layer. The appearance of charge and electroresistance hysteresis loops and their versatility stem from the interplay of polarization reversal dynamics and its incomplete screening in an alternating electric field. These features are mostly determined by the dielectric layer thickness. The derived analytical expressions for electric fields and space-charge-density distribution in a multilayer system enable knowledge-driven design of graphene-on-ferroelectric heterostructures with advanced performance. We further investigate the effects of spatially nonuniform ferroelectric domain structures on the graphene layers’ conductivity and predict its dramatic increase under the transition from multi- to single-domain state in a ferroelectric. Finally, this intriguing effect can open possibilities for the graphene-based sensors and explore the underlying physical mechanisms in the operation of graphene field-effect transistor with ferroelectric gating.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Universal Self-Similar Scaling of Spatial Wilson Loops Out of Equilibrium

Here we investigate strongly correlated non-Abelian plasmas out of equilibrium. Based on numerical simulations, we establish a self-similar scaling property for the time evolution of spatial Wilson loops that characterizes a universal state of matter far from equilibrium. Most remarkably, it exhibits a generalized area law which holds for a sufficiently large ratio of spatial area and fractional power of time. Performing calculations also for the perturbative regime at higher momenta, we are able to characterize the full nonthermal scaling properties of SU(2) and SU(3) symmetric plasmas from short to large distance scales in terms of two independent universal exponents and associated scaling functions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗