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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

White-light interferometry for early-stage metal oxide growth characterization

Oxidation of metals can provide a functional oxide film or an oxide layer that can lead to material degradation causing performance limiting concerns. Because of the technological and economic impacts of oxidation, understanding early-stage oxidation growth and its mechanisms is of high importance. Unfortunately, poor empirical data during early-stage oxidation has left our current understanding of oxidation incomplete and woefully inadequate. Measurement techniques previously used for oxidation kinetics characterization include microbalance, x-ray diffraction, Fourier-transform infrared spectroscopy, and spectroscopic ellipsometry. However, these techniques lack the necessary time-resolution or vertical resolution in addition to not providing any spatial data, which is essential to early-stage oxidation studies to understand both oxidation kinetics and mechanisms. Here, a novel rapid and surface-sensitive data collection technique that provides three-dimensional spatial data of a growing oxide layer with sub-nanometer thickness resolution using white-light interferometry has been developed. This technique will be the first technique capable of providing real-time spatial results of early-stage oxidation growth. The effectiveness of this characterization tool is shown by observing the early-stage oxidation kinetics and film cracking of uranium heated to 90 °C under 500 torr of pure O 2 . Initially a parabolic oxidation growth is observed. Once the oxide layer reaches ≈ 30 nm, the epitaxial stresses between the uranium substrate and oxide film layer causes localized cracking in addition to the observed transition of the parabolic growth rate to a linear growth rate. The results of the white-light interferometry are verified by glancing incidence x-ray diffraction.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

A time-resolved imaging system for the diagnosis of x-ray self-emission in high energy density physics experiments

A diagnostic capable of recording spatially and temporally resolved x-ray self-emission data was developed to characterize experiments on the MAGPIE pulsed-power generator. The diagnostic used two separate imaging systems: a pinhole imaging system with two-dimensional spatial resolution and a slit imaging system with one-dimensional spatial resolution. The two-dimensional imaging system imaged light onto the image plate. The one-dimensional imaging system imaged light onto the same piece of image plate and a linear array of silicon photodiodes. This design allowed the cross-comparison of different images, allowing a picture of the spatial and temporal distribution of x-ray self-emission to be established. The design was tested in a series of pulsed-power-driven magnetic-reconnection experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Characterization of River Networks: A GIS Approach and Its Applications

Abstract Fluvial geomorphology provides the basis for characterizing complex river networks and evaluating biophysical processes within watersheds. Understanding the spatial organization of morphological features, their influencing processes, and resultant geomorphic diversity in stream networks are important for efficient restoration, river health assessment, and improving our knowledge of the resilience of riverine landscapes. River characterization is a means to determine the biophysical character of river networks but many methods are fraught with pitfalls, such as the use of incorrect variables and limited acknowledgment of the hierarchical organization of rivers. In this paper, a top‐down geographic information system‐based approach for determining the physical typology of river networks is outlined. A suite of multivariate analyses are used to develop a nomenclature for functional process zones (FPZs) — large tracts of the river network with similar hydro‐geomorphological character. Applied to the Little Miami River, Ohio, six distinct FPZs emerged, which had a nonuniform distribution along the river network. Some FPZs repeated downstream; others were rare in terms of total length and number of FPZ segments. The physical structure of the Little Miami River network was analyzed using a series of community metrics. Application of this approach for river monitoring, establishing reference conditions, as well as management of threatened and endangered species and asset trading is highlighted.

Thoms, Martin↗
DOE OSTI2016

Superintermolecular orbitals in the C 60 -pentacene complex

In this work, we report a group of unusually big molecular orbitals in the C 60 -pentacene complex. Our first-principles density-functional calculation shows that these orbitals are very delocalized and cover both C 60 and pentacene, which we call superintermolecular orbitals (SIMOs). Their spatial extension can reach 1 nm or larger. Optically, SIMOs are dark. Different from ordinary unoccupied molecular orbitals, SIMOs have a very weak Coulomb and exchange interaction. Their energy levels are very similar to the native superatomic molecular orbitals in C 60 and can be approximately characterized by orbital angular momentum quantum numbers. They have a distinctive spatial preference. These features fit the key characters of charge-generation states that channel initially bound electrons and holes into free-charge carriers. Thus, our finding is important for C 60 -pentacene photovoltaics.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS2003

NASA Scientific Data Purchase Laboratory Characterization of Positive Systems ADAR 5500 Sensor

This report summarizes the laboratory characterization of the Positive Systems ADAR 5500 SN4 multi-spectral imager measured dirijg the period of April 10-11, 2000 in the NASA CRSP Commercial Instrumentation Validation Laboratory (CIVL). This characterization is one component of the NASA Scientific Data Purchase (SDP) validation and verification process. A complete characterization will require analysis of airborne data. The spectral, radiometric, and spatial characteristics of this system were measured and compared with the product data specifications as defined in the SDP contract. These results are summarized in the specification compliance matrices in this summary. A complete description of the system, the SDP product specification and the sensor laboratory characterization is provided in the body of the main report.

Ryan, James↗
DOE OSTI2018

Characterization of a large-area iQID imager for safeguards applications

Environmental sampling and sample analyses by the International Atomic Energy Agency is a key method for verifying declarations in international safeguards agreements. Quantitative Digital Autoradiography for Environmental Samples is a system developed by Pacific Northwest National Laboratory to examine environmental swipe samples (ESS) prior to subsequent, destructive analysis. This approach is passive and noninvasive for imaging beta and gamma emissions, which transmit through the plastic bags containing the ESS. Alpha particle imaging is also possible with different ESS containers. This technology is based on a portable, real-time, event-counting, high spatial resolution system called iQID (ionizing-radiation Quantum Imaging Detector), which is made from commercial, off-the-shelf components. This includes a scintillator in direct contact with a micro-channel plate image intensifier and a lens for imaging the intensified scintillation events onto a CCD/CMOS camera. The QDARES large-area iQID includes a fiber-optic taper coupled to the image intensifier which increases the imaging area to a ~100 cm square with a 105 mm x 105 mm taper. In this study, we describe new characterization results, including spatial resolution, energy response, minimum detectable activity for several isotopes, detector uniformity, and count-rate capability.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2026

Image Distinguishability Analysis Testing Through Principal Components and Its Application to Hot Spot Scale Invariance

Hot spots are spatial regions of intense energy localization that govern initiation of secondary high explosives. Studies that characterize or compare simulated hot spots are frequently either qualitatively descriptive or resort to quantitative distribution functions that neglect stochastic variations and spatial correlations—effects that are also neglected in common comparison tests like the Kolmogorov–Smirnov test. To this end, we develop an image distinguishability analysis (IDA) test based on principal component (PC) analysis that makes pixel-by-pixel comparisons between small, for example, O(<10), image data sets. The IDA test makes comparisons through a generalized distance metric in the PC space and a test statistic that is derived to calculate mathematical equation-values. Here, we derive a statistical distribution and criticality criterion to determine whether images are distinguishable from established baselines. We apply the IDA test on images generated from molecular dynamics simulations of hot spots from pore collapse in TATB to assess scale invariance in the complex patterns of hot spots that form in a representative high explosive crystal. The IDA test shows that TATB hot spot spatial temperature fields and their derived temperature histograms exhibit scale-invariant features over specific intervals of shock orientation, strength, and initial pore diameter. However, the IDA test also shows that qualitatively different conclusions regarding invariance can be reached depending on whether the hot spot is treated as a spatially correlated field as opposed to a distribution function that lacks spatial information.

organic↗
NASA NTRS2019

Redefining Temperate Forest Responses to Climate and Disturbance in the Eastern United States: New Insights at the Mesoscale

Climate and disturbance alter forest dynamics, from individual trees to biomes and from years to millennia, leaving legacies that vary with local, meso and macroscales. Motivated by recent insights in temperate forests, we argue that temporal and spatial extents equivalent to that of the underlying drivers are necessary to characterize forest dynamics across scales. We focus specifically on characterizing mesoscale forest dynamics because they bridge fine‐scale (local) processes and the continental scale (macrosystems) in ways that are highly relevant for climate change science and ecosystem management. We revisit ecological concepts related to spatial and temporal scales and discuss approaches to gain a better understanding of climate–forest dynamics across scales.

climate↗
DOE OSTI2021

Detecting multi‐scale riverine topographic variability and its influence on Chinook salmon habitat selection

Abstract Quantifying geomorphic conditions that impact riverine ecosystems is critical in river management due to degraded riverine habitat, changing flow and thermal conditions, and increasing anthropogenic pressure. Geomorphic complexity at different scales directly impacts habitat heterogeneity and affects aquatic biodiversity resilience. Here we showed that the combination of continuous spatial survey at high resolution, topobathymetric light detection and ranging (LiDAR), and continuous wavelet analysis can help identify and characterize that complexity. We used a continuous wavelet analysis on 1‐m resolution topobathymetry in three rivers in the Salmon River Basin, Idaho (USA), to identify different scales of topographic variability and the potential effects of this variability on salmonid redd site selection. On each river, wavelet scales characterized the topographic variability by portraying repeating patterns in the longitudinal profile. We found three major representative spatial wavelet scales of topographic variability in each river: a small wavelet scale associated with local morphology such as pools and riffles, a mid‐wavelet scale that identified larger channel unit features, and a large wavelet scale related to valley‐scale controls. The small wavelet scale was used to identify pools and riffles along the entire lengths of each river as well as areas with differing riffle‐pool development. Areas along the rivers with high local topographic variability (high wavelet power) at all wavelet scales contained the largest features (i.e., deepest or longest pools) in the systems. By comparing the wavelet power for each wavelet scale to Chinook salmon redd locations, we found that higher small‐scale wavelet power, which is related to pool‐riffle topography, is important for redd site selection. The continuous wavelet methodology objectively identified scales of topographic variability present in these rivers, performed efficient channel‐unit identification, and provided geomorphic assessment without laborious field surveys.

Duffin, Jenna↗
DOE OSTI2021

Understanding the Design Space of Sparse/Dense Multiphase Dataflows for Mapping Graph Neural Networks on Spatial Accelerators

Graph Neural Networks (GNNs) have garnered a lot of recent interest because of their success in learning representations from graph-structured data across several critical applications in cloud and HPC. Owing to their unique compute and memory characteristics that come from an interplay between dense and sparse phases of computations, the emergence of reconfigurable dataflow (aka spatial) accelerators offers promise for acceleration by mapping optimized dataflows (i.e., computation order and parallelism) for both phases. The goal of this work is to characterize and understand the design-space of dataflow choices for running GNNs on spatial accelerators in order for the compilers to optimize the dataflow based on the workload. Specifically, we propose a taxonomy to describe all possible choices for mapping the dense and sparse phases of GNNs spatially and temporally over a spatial accelerator, capturing both the intra-phase dataflow and the inter-phase (pipelined) dataflow. Using this taxonomy, we do deep-dives into the cost and benefits of several dataflows and perform case studies on implications of hardware parameters for dataflows and value of flexibility to support pipelined execution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Simultaneous three-dimensional elemental mapping of Hollandite and Pyrochlore material phases in ceramic waste form materials

In this study, differential X-ray absorption contrast tomography was performed on model ceramic composite systems to image the 3D spatial distributions of Ga and Nd containing phases. The model material systems were fabricated such that they contained two constituent phases. Ga–doped Ba hollandite (Ba 1.33 Ga 2.66 Ti 5.34 O 16 ), and pyrochlore (Nd 2 Ti 2 O 7 ) which are under consideration as nuclear waste immobilization matrices. Two complementary techniques have been used to characterize the 3D distribution of phases. The analysis suggests that the 3D spatial distributions of hollandite and pyrochlore can be readily identified through the distributions Ga and Nd, respectively. These results represent a critical development towards characterizing the complex microstructure inherent to practical materials such as multiphase ceramic composite waste forms. Furthermore, these methods can be applied to elucidate microstructural features that fundamentally determine the performance and properties of complex systems, which is central to the design of durable waste forms as well as many other real materials such fuel cells, batteries, ultra-high temperature ceramics.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Theoretical analysis of non‐ G aussian heterogeneity effects on subsurface flow and transport

Abstract Much of the stochastic groundwater literature is devoted to the analysis of flow and transport in Gaussian or multi‐Gaussian log hydraulic conductivity (or transmissivity) fields, ( x being a position vector), characterized by one or (less frequently) a multiplicity of spatial correlation scales. Yet Y and many other variables and their (spatial or temporal) increments, Δ Y , are known to be generally non‐Gaussian. One common manifestation of non‐Gaussianity is that whereas frequency distributions of Y often exhibit mild peaks and light tails, those of increments are generally symmetric with peaks that grow sharper, and tails that become heavier, as separation scale or lag between pairs of Y values decreases. A statistical model that captures these disparate, scale‐dependent distributions of Y and in a unified and consistent manner has been recently proposed by us. This new “generalized sub‐Gaussian (GSG)” model has the form where is (generally, but not necessarily) a multiscale Gaussian random field and is a nonnegative subordinator independent of G . The purpose of this paper is to explore analytically, in an elementary manner, lead‐order effects that non‐Gaussian heterogeneity described by the GSG model have on the stochastic description of flow and transport. Recognizing that perturbation expansion of hydraulic conductivity diverges when Y is sub‐Gaussian, we render the expansion convergent by truncating Y 's domain of definition. We then demonstrate theoretically and illustrate by way of numerical examples that, as the domain of truncation expands, (a) the variance of truncated Y (denoted by Y t ) approaches that of Y and (b) the pdf (and thereby moments) of Y t increments approach those of Y increments and, as a consequence, the variogram of approaches that of . This in turn guarantees that perturbing to second order in (the standard deviation of Y t ) yields results which approach those we obtain upon perturbing to second order in even as the corresponding series diverges. Our analysis is rendered mathematically tractable by considering mean‐uniform steady state flow in an unbounded, two‐dimensional domain of mildly heterogeneous Y with a single‐scale function G having an isotropic exponential covariance. Results consist of expressions for (a) lead‐order autocovariance and cross‐covariance functions of hydraulic head, velocity, and advective particle displacement and (b) analogues of preasymptotic as well as asymptotic Fickian dispersion coefficients. We compare these theoretically and graphically with corresponding expressions developed in the literature for Gaussian Y . We find the former to differ from the latter by a factor k = ( denoting ensemble expectation) and the GSG covariance of longitudinal velocity to contain an additional nugget term depending on this same factor. In the limit as Y becomes Gaussian, k reduces to one and the nugget term drops out.

Riva, Monica↗
DOE OSTI2018

Spatial and Temporal Variations in the Moment Tensor Solutions of the 2008 Wenchuan Earthquake Aftershocks and Their Tectonic Implications

Following the mainshock of the 2008 M8 Wenchuan Earthquake, there were more than 300 M L ≥ 4.0 aftershocks that occurred between 12 May 2008 and 8 September 2010. We analyzed here the broadband waveforms for these events and found 160 events with sufficient signal-to-noise levels to invert for seismic moment tensors. Considering the length of the activated fault and the distances to the recording stations, four velocity models were employed to account for variability in crustal structure. The moment tensor solutions show considerable variations with a mixture of mainly reverse and strike-slip mechanisms and a small number of normal events and ambiguous events. We analyzed the spatial and temporal distribution of the aftershocks and their mechanism types to characterize the structure and the deformation occurring in the Longmen Shan fold and thrust belt. Our results suggest that the stress is very complex at the Longmen Shan fault zone. The moment tensors have both a spatial segmentation with two major categories of the moment tensor of thrust and strike slip; and a temporal pattern that the majority of the aftershocks gradually migrated to thrust-type events. The variability of aftershock mechanisms is a strong indication of significant tectonic release and stress reorganization that activated numerous small faults in the system.

58 GEOSCIENCES↗
DOE OSTI2023

Comparative Analysis of Imaging and Measurements of Micrometer-Scale Fracture Aperture Fields Within a Heterogeneous Rock Using PET and X-ray CT

Knowledge of the spatial distribution of fracture apertures is essential for reliable characterization of flow and transport processes in fractured systems and for better understanding of physicochemical matrix–fracture interactions. Here, we propose and test two image-based methods, thereby extending the current experimental capabilities to characterize aperture size distribution in structurally heterogeneous geologic porous media noninvasively. The first approach utilizes an inversion method based on the dataset acquired from positron emission tomography (PET) and the second approach considers an extension of the classic missing attenuation technique that relies on clinical X-ray computed tomography (X-ray CT). Independent sets of imaging experiments are conducted on a fractured basalt core with heterogeneous matrix properties and aperture distributions to compare the two methodologies. A repeat of each experiment is conducted to verify the proposed workflows. The performance of these two imaging techniques is systematically evaluated through the analysis of signal-to-noise ratio, minimum fracture size detectability, and measurement errors. While both approaches provide a reliable estimation of fracture aperture distributions, PET yields a signal-to-noise ratio that is substantially higher than the corresponding X-ray CT measurements. Furthermore, uncertainties of the aperture values for PET are considerably lower ($\bar {\sigma}_{\text {d}} = 15\%$) compared to those obtained from X-ray CT ($\bar {\sigma}_{\text {d}} = 29\%$), allowing for the detection of minimum aperture sizes of 20 $\mu$m with 70% confidence level. Finally, these approaches provide key experimental tools for better understanding dynamic hydromechanical fracture properties in geologic systems.

58 GEOSCIENCES↗
DOE OSTI2019

Microbeam synchrotron radiation diffraction and fluorescence of oxide layers formed on zirconium alloys at different corrosion temperatures

Autoclave corrosion tests of Zircaloy-4 were performed at temperatures ranging from 274°C to 427 °C to determine how the characteristics of the oxide layer changed with corrosion temperature. Corroded samples were prepared in cross-section and examined at the Advanced Photon Source using x-ray diffraction and fluorescence with sub-micron spatial resolution. These measurements provide high fidelity data for characterization of the oxide layer grown on zirconium alloys over a range of temperatures to better understand the fundamental mechanisms of corrosion. It was found that the size of the monoclinic oxide grains increases with distance from the metal-oxide interface, while the average grain size of the tetragonal oxide phase decreases. This is consistent with the continuous nucleation of a mixture of equiaxed tetragonal and monoclinic grains at the metal-oxide interface, of which only the monoclinic oxide grains that are properly aligned to minimize stresses grow into long columnar oxide grains. The tetragonal phase oxide grains transform to monoclinic oxide once a critical size is reached. While the monoclinic oxide grain size increases with corrosion temperature, the tetragonal phase grain size remains below a maximum value. Evolution of the tetragonal fraction, calculated with the Garvie-Nicholson formula, was observed, with local maxima seen just before transition and local minima seen at oxide locations corresponding to the oxide kinetic transition. No difference was observed in the tetragonal phase fraction in the oxide layers formed at different corrosion temperatures. Detailed fluorescence and diffraction mapping of one sample showed the evolution of the diffraction intensity over a short range in the oxide. In conclusion, this work provides a systematic study revealing fundamental characteristics of the microstructure of Zircaloy-4 oxide layers to further understanding of corrosion resistance of these materials.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Systematic mapping of the conformational landscape and dynamism of soluble fibrinogen

Background: Fibrinogen is a soluble, multisubunit, and multidomain dimeric protein, which, upon its proteolytic cleavage by thrombin, is converted to insoluble fibrin, initiating polymerization that substantially contributes to clot growth. Fibrinogen contains numerous, transiently accessible “cryptic” epitopes for hemostatic and immunologic proteins, suggesting that fibrinogen exhibits conformational flexibility, which may play functional roles in its temporal and spatial interactions. Hitherto, there have been limited integrative approaches characterizing the solution structure and internal flexibility of fibrinogen. Methods: Here, utilizing a multipronged, biophysical approach involving 2 solution-based techniques, temperature-dependent hydrogen-deuterium exchange mass spectrometry and small angle X-ray scattering, corroborated by negative stain electron microscopy, we present a holistic, conformationally dynamic model of human fibrinogen in solution. Results: Our data reveal 4 major and distinct conformations of fibrinogen accommodated by a high degree of internal protein flexibility along its central scaffold. We propose that the fibrinogen structure in the solution consists of a complex, conformational landscape with multiple local minima. This is further supported by the location of numerous point mutations that are linked to dysfibrinogenemia and posttranslational modifications, residing near the identified fibrinogen flexions. Conclusion: Further, this work provides a molecular basis for the structural “dynamism” of fibrinogen that is expected to influence the broad swath of its functionally diverse macromolecular interactions and fine-tune the structural and mechanical properties of blood clots.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Crystallization kinetics and nanoparticle ordering in semicrystalline polymer nanocomposites

There has been considerable interest in the nucleation and crystallization of polymers in the presence of nanoparticles (NPs, or nanofillers in general, NFs). Most of the extensive work in this area has focused on anisotropic, non-Brownian NFs (e.g., clay sheets, carbon nanotubes) whose spatial dispersion state in these nanocomposites is controlled by the process by which they are formed. Hence, NF spatial dispersion is generally limited and often remains poorly characterized. Thermodynamic handles that can be used to control NF dispersion state in the polymer melt include (a) favorable interactions between the polymer chains and the bare NP surfaces, or (b) the density and length of the chains, with the same chemistry as the matrix, grafted to the NP surface. These relatively large NFs merely act as stationary objects that affect the kinetics of nucleation by providing heterogeneous sites, and the crystallization rate by confining the polymer in the melt state. The dispersion state of the NFs can dramatically affect the nucleation and crystallization of the matrix, but in most cases reported, the NFs increase nucleation efficiency relative to the neat polymer. At higher NF loadings, the effect of polymer confinement by the NFs dominates, leading to a decrease in crystal growth rates. This review describes the most important lessons learned from these commonly studied systems and then extends to polymer composite systems containing small, mobile spherical NPs (typically smaller than 100 nm in size). The role of NP mobility, which provides for dynamic confinement of the polymer melt, on the kinetics of polymer crystallization (nucleation, growth, and overall crystallization) and how this behavior is mostly consistent with the case of immobile NF is a second important focus of this review. In addition to the role of NFs on crystallization kinetics, recently reported nanoparticle ordering phenomena such as the effect of matrix crystallization on the organization of small spherical NPs within the amorphous regions of the semicrystalline morphology are discussed. In conclusion, such phenomena are clearly not observed for large NFs and hence provide a point of departure from past works in this area.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗