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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Integrating Flow Imaging Analysis and Single-Particle ICP-TOFMS for Comprehensive Micro- and Nanoplastic Characterization

Flow imaging analysis (FIA), provides composition-agnostic morphological characterization. These measurements of particle size and shape are valuable to mass-based analysis, such as single particle inductively coupled plasma time-of-flight mass spectrometry (sp-ICP-TOFMS), which provides quantitative data on elements within particles. Using these two methods together enables informed use of geometric assumptions required by sp-ICP-TOFMS, as particle mass is typically converted to a particle diameter using assumed-spherical geometry. To validate this concept, parallel measurements to determine particle diameters were performed by FIA and sp-ICP-TOFMS on four particle suspensions: 300 nm polystyrene Eu-doped nanoparticles, 1 μm Fe-rich beads, 3 μm four element calibration polystyrene beads and 5 μm polystyrene beads. The Fe-particles obtained the highest percent difference from the manufacturer’s nominal diameter, as the mean diameter obtained by FIA was overestimated by 21% and sp-ICP-TOFMS underestimated the mean diameter by 20.7%. Two types of particles were selected to test the effect of varying the particle number concentrations (PNC) on sizing accuracy, and both methods accurately sized each particle population at the PNC expected. Single particle analysis of carbon has continued to be a popular research topic, with direct applications to environmental pollutants in terms of nano- and micro- plastics. Real-world plastic particles were studied, and FIA’s measured circularity values demonstrated that the particles deviated from spherical geometries, therefore sp-ICP-TOFMS data should be interpreted as mass-based rather than size-based. Combining these techniques enables improved interpretation of particle populations and evaluation of particle sizes.

Szakas, Sarah [ORNL] (ORCID:0000000241332197)↗
NASA NTRS1998

Multi-Scale Fractal Analysis of Image Texture and Pattern

Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and information content contained within these data. A software package known as the Image Characterization and Modeling System (ICAMS) was used to explore how fractal dimension is related to surface texture and pattern. The ICAMS software was verified using simulated images of ideal fractal surfaces with specified dimensions. The fractal dimension for areas of homogeneous land cover in the vicinity of Huntsville, Alabama was measured to investigate the relationship between texture and resolution for different land covers.

Emerson, Charles W.↗
NASA NTRS2004

An Initial Analysis of the Pixel-Level Uncertainties in Global MODIS Cloud Optical Thickness and Effective Particle Size Retrievals

Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of cloud optical thickness and effective particle radius employ well-known solar reflectance techniques using pre-calculated reflectance look-up tables. We evaluate the quantitative uncertainty in simultaneous retrievals of cloud optical thickness and particle size for this type of algorithm. The technique uses sensitivity calculations derived from the reflectance look-up tables, coupled with estimates for the effect of various error terms on the uncertainty in inferring the actual cloud-top reflectance. The error terms include the effects of instrument calibration, surface spectral albedo, and atmospheric corrections on both water and ice cloud retrievals. Because particle shapes in ice clouds are highly variable, the effect of particle shape is analyzed separately with a more approximate method. Results will deal exclusively with pixel-level uncertainties associated with plane-parallel clouds; real-world radiative departures from a plane-parallel model are an additional consideration. While we demonstrate the uncertainty technique with operational 1 km MODIS retrievals from the Terra and Aqua satellite platforms, the technique is applicable to any reflectance-based satellite- or air-borne sensor retrieval using similar spectral channels.

Platnick, S.↗
DOE OSTI2022

Sulphur variations in annually layered stalagmites using benchtop micro-XRF

Variation of sulphur in annually laminated stalagmites can be used to infer the impact of past volcanic activities, anthropogenic pollution, and climate change due to increased bushfire activity. The synchrotron radiation micro-X-Ray fluorescence (SR-XRF) microprobe is a powerful tool to analyse and image sulphur recorded in stalagmites with micrometre resolution. However, access to SR-XRF beamlines can be limited, so researchers must select the most promising stalagmites for imaging. Benchtop micro-XRF is an effective tool for trace elemental analysis of speleothem samples and is a candidate for routine laboratory measurement of sulphur along stalagmite laminae and screening for SR-XRF. Here, this study describes a protocol using matrix-matched standards to measure annual variations of sulphur at trace to percent level along the laminae of two Western Australian stalagmites, one of which already having been analysed using SR-XRF. Parameters that affected quantitation include X-ray tube voltage and current, spot size of the X-ray beam and stalagmite surface roughness and porosity. The use of a 20 μm X-ray spot size provides sub-annual spatial resolution that can be completed in an overnight scan. The features in a 1000 point micro-XRF analysis of sulphur along a 20 mm transect show good consistency with SR-XRF microprobe data. Micro-XRF mapping was also performed to produce chemical images on the stalagmite and compared with Raman and X-ray diffraction (XRD) to confirm that the stalagmite is exclusively calcite, with no aragonite, and that the source of sulphur in the samples was gypsum and anhydrite. Regions of very high sulphur in the micro-XRF maps were found to be artefacts due to diffraction of the incident beam but these could be efficiently removed by using a multiple point statistics approach to produce a clean image suitable for analysis of the laminae. This work shows the potential of micro-XRF for routine analysis of sulphur in stalagmites, and to streamline sample characterisation before SR-XRF imaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

In Situ 4D‐STEM Imaging of the Orientation of Lamellar Clusters in Polymer Crystallization

In semi‐crystalline polymeric materials, the initial stages of nucleation and the growth path of crystalline domains can determine the final performance. Here, in this work, we used four‐dimensional scanning transmission electron microscopy (4D‐STEM) imaging to analyze the changes in lamellar orientation in high‐density polyethylene (HDPE) during heating and cooling. This method allowed us to quantitatively detect the formation of lamellae clusters with different in‐plane orientations, which are not visible with traditional methods. Our analysis provided detailed insights into the orientation and size changes of crystalline domains. Additionally, this technique enabled direct observation of lattice structures in hierarchical lamellae and the growth of crystals, confirming the local variability in lamellar orientation. This innovative approach significantly improves our understanding of polymer crystallization, linking changes in morphology and lattice structures at different length scales.

4D-STEM↗
DOE OSTI2024

Focused‐beam X‐ray fluorescence and diffraction microtomographies for mineralogical and chemical characterization of unsectioned extraterrestrial samples

Abstract This study describes the application of new synchrotron X‐ray fluorescence (XRF) and diffraction (XRD) microtomographies for the 3‐D visualization of chemical and mineralogical variations in unsectioned extraterrestrial samples. These improved methods have been applied to three compositionally diverse chondritic meteorite samples that were between 300 and 400 μm in diameter, including samples prepared from fragments of the CR2 chondrite LaPaz Icefield (LAP) 02342, H5 chondrite MacAlpine Hills (MAC) 88203, and the CM2 chondrite Murchison. The synchrotron‐based XRF and XRD tomographies used are focused‐beam techniques that measure the intensities of fluorescent and diffracted X‐rays in a sample simultaneously during irradiation by a high‐energy microfocused incident X‐ray beam. Measured sinograms of the emitted and diffracted intensities were then tomographically reconstructed to generate 2‐D slices of XRF and XRD intensity through the sample, with reconstructed pixel resolution of 1–2 μm, defined by the resolution of the focused incident X‐ray beam. For sample LAP 02342, primary mineral phases that were visualized in reconstructed slices using these techniques included isolated grains of α‐Fe, orthopyroxene, and olivine. For our sample of MAC 88203, XRF/XRD tomography allowed visualization of forsteritic olivine as a primary mineral phase, a vitrified fusion crust at the sample surface, identification of localized Cr‐rich spinels at spatial resolutions of several micrometers, and imaging of a plagioclase‐rich glassy matrix. In the sample of Murchison, major identifiable phases include clinoenstatite‐ and olivine‐rich chondrules, variable serpentine matrix minerals and small Cr‐rich spinels. Most notable in the tomographic analysis of Murchison is the ability to quantitatively distinguish and visualize the complex mixture of serpentine‐group minerals and associated tochilinite–cronstedtite intergrowths. These methods provide new opportunities for spatially resolved characterization of sample texture, mineralogy, crystal structure, and chemical state in unsectioned samples. This provides researchers an ability to characterize such samples internally with minimal disruption of sample micro‐structures and chemistry, possibly without the need for sample extraction from some types of sampling and capture media.

Geochemistry & Geophysics↗
NASA NTRS2017

Multispectral Snapshot Imagers Onboard Small Satellite Formations for Multi-Angular Remote Sensing

Multispectral snapshot imagers are capable of producing 2D spatial images with a single exposure at selected, numerous wavelengths using the same camera, therefore operate differently from push broom or whiskbroom imagers. They are payloads of choice in multi-angular, multi-spectral imaging missions that use small satellites flying in controlled formation, to retrieve Earth science measurements dependent on the targets Bidirectional Reflectance-Distribution Function (BRDF). Narrow fields of view are needed to capture images with moderate spatial resolution. This paper quantifies the dependencies of the imagers optical system, spectral elements and camera on the requirements of the formation mission and their impact on performance metrics such as spectral range, swath and signal to noise ratio (SNR). All variables and metrics have been generated from a comprehensive, payload design tool. The baseline optical parameters selected (diameter 7 cm, focal length 10.5 cm, pixel size 20 micron, field of view 1.15 deg) and snapshot imaging technologies are available. The spectral components shortlisted were waveguide spectrometers, acousto-optic tunable filters (AOTF), electronically actuated Fabry-Perot interferometers, and integral field spectrographs. Qualitative evaluation favored AOTFs because of their low weight, small size, and flight heritage. Quantitative analysis showed that waveguide spectrometers perform better in terms of achievable swath (10-90 km) and SNR (greater than 20) for 86 wavebands, but the data volume generated will need very high bandwidth communication to downlink. AOTFs meet the external data volume caps well as the minimum spectral (wavebands) and radiometric (SNR) requirements, therefore are found to be currently feasible in spite of lower swath and SNR.

Nag, Sreeja↗
NASA NTRSDate not supplied

Aerothermodynamic Measurements in Hypersonic Non-Equilibrium Flows

High enthalpy arc-jets are unique facilities particularly suited for simulating complex flows in the aerospace field, such as the aerothermodynamics of a re-entry vehicle. Arc-jets are often used to evaluate important design factors such as heat shield materials and vehicle design. Characterization of these facilities is important, as studies often match specific in-flight environments during experiments. Due to the complex environment produced by an arc-jet, with effects such as thermodynamic and chemical non-equilibrium occurring in the flow, characterization experiments are significantly more difficult than in traditional blow-down wind tunnels. The current work aims to characterize an arc-jet facility in terms of flow temperature, velocity and unsteadiness, in a spatially-resolved analysis. To achieve this goal, a non-intrusive imaging technique called “planar laser-induced fluorescence” was performed in the NASA Langley Hypersonic Materials Environ-mental Test System arc-jet facility. The experimental data was analyzed to produce the quantitative measurements in multiple regions of the flow around a blunt body sample. A quasi-1D low fidelity solver was created to numerically simulate the flow to investigate non-equilibrium effects occur-ring outside the imaging region in the arc-jet nozzle. Unsteadiness in the test section was minimized by analyzing a subset of data assessing the gas injection location. Radial velocity, rotational temperature and translational temperature measurements are provided that can be used to validate future high-fidelity computational studies. The temperature measurements revealed rotational non-equilibrium potentially occurring in the flow. This work provides a methodology for characterizing arc-jet facilities, identifying and correcting sources of systematic error, and estimating the uncertainty associated with the quantitative measurements.

laser induced fluorescence↗
NASA NTRS1998

Analytical Tools for Cloudscope Ice Measurement

The cloudscope is a ground or aircraft instrument for viewing ice crystals impacted on a sapphire window. It is essentially a simple optical microscope with an attached compact CCD video camera whose output is recorded on a Hi-8 mm video cassette recorder equipped with digital time and date recording capability. In aircraft operation the window is at a stagnation point of the flow so adiabatic compression heats the window to sublimate the ice crystals so that later impacting crystals can be imaged as well. A film heater is used for ground based operation to provide sublimation, and it can also be used to provide extra heat for aircraft operation. The compact video camera can be focused manually by the operator, and a beam splitter - miniature bulb combination provide illumination for night operation. Several shutter speeds are available to accommodate daytime illumination conditions by direct sunlight. The video images can be directly used to qualitatively assess the crystal content of cirrus clouds and contrails. Quantitative size spectra are obtained with the tools described in this report. Selected portions of the video images are digitized using a PCI bus frame grabber to form a short movie segment or stack using NIH (National Institute of Health) Image software with custom macros developed at DRI. The stack can be Fourier transform filtered with custom, easy to design filters to reduce most objectionable video artifacts. Particle quantification of each slice of the stack is performed using digital image analysis. Data recorded for each particle include particle number and centroid, frame number in the stack, particle area, perimeter, equivalent ellipse maximum and minimum radii, ellipse angle, and pixel number. Each valid particle in the stack is stamped with a unique number. This output can be used to obtain a semiquantitative appreciation of the crystal content. The particle information becomes the raw input for a subsequent program (FORTRAN) that synthesizes each slice and separates the new from the sublimating particles. The new particle information is used to generate quantitative particle concentration, area, and mass size spectra along with total concentration, solar extinction coefficient, and ice water content. This program directly creates output in html format for viewing with a web browser.

Arnott, W. Patrick↗
NASA NTRS1985

Quantitative analysis of hard X-ray 'footpoint' flares observed by the solar maximum mission

Amplifier gain and collimator hole size variations across the field of view, amplifier/filter efficiency, variations in effective collimator hole size and angular response with photon energy, dead-time, and hard X-ray plate transmission, are among the factors for which instrumental corrections have to be incorporated to effect reliable correction and deconvolution of images from the SMM satellite's Hard X-ray Imaging Spectrometer (HXIS). Attention is given to the substantial Poisson noise in these energy bands. The maximum entropy deconvolution/correction routine developed for establishing the spatial structure reliably inferrable from HXIS data is presented, together with the results of the application of this routine to the three impulsive flares reported by Duijemian et al. (1982) from April 10, May 21, and November 5, 1980.

Mackinnon, A. L.↗
DOE OSTI2022

Nanoscale Compositional Mapping of Commercial LiNi 0.8 Co 0.15 Al 0.05 O 2 Cathodes Using Atom Probe Tomography

Nickel-rich cathodes provide improved specific capacity that lead to higher gravimetric energy density, critical for electric vehicles. However, poor long-term capacity retention at elevated temperatures/high C-rates (the rate of charge and discharge on a battery) stem from material issues: surface phase changes, corrosive side reactions with the electrolyte, ion dissolution and propagation of cracks. Introducing dopants, developing nanoscale surface coatings and graded core-shell structures have all improved the electrochemical performance of nickel-rich cathodes. However, a material level understanding on the effect of Li composition and distribution in Ni-rich cathodes is limited, due to a lack of characterization methods available that can directly image Li at the nanoscale. Hence, it is critical to establish methods such as atom probe tomography (APT), having both nanometer scale spatial resolution and high compositional sensitivity to quantitatively analyze battery cathodes. To fully realize its potential as a method for quantitative compositional analysis of commercial Li-ion batteries, we provide a comprehensive description of the challenges in sample preparation and analyze the dependency of the analysis parameters, specifically laser pulse energy on the measured stoichiometry of elements in a high Ni content cathode material; LiNi 0.8 Co 0.15 Al 0.05 O 2 (NCA). In this work, our findings show the stoichiometry variations cannot be explained by charge state ratios or Ga implantation damage alone during FIB preparation, indicating that additional factors such as crystallographic orientation may need to be considered to achieve quantitative nanoscale compositional analysis of such battery cathodes using APT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1983

Analysis of the quality of image data acquired by the LANDSAT-4 thematic mapper and multispectral scanners

The geometric quality of the TM and MSS film products were evaluated by making selective photo measurements such as scale, linear and area determinations; and by measuring the coordinates of known features on both the film products and map products and then relating these paired observations using a standard linear least squares regression approach. Quantitative interpretation tests are described which evaluate the quality and utility of the TM film products and various band combinations for detecting and identifying important forest and agricultural features.

Colwell, R. N.↗
NASA NTRS1988

Mapping of Landsat satellite and gravity lineaments in west Tennessee

The analysis of earthquake fault lineament patterns within the alluvial valley of west Tennessee, which is often made difficult by the presence of unconsolidated sediments, is presently undertaken through a synergistic use of Landsat satellite images in conjunction with gravity anomaly data, which were quantitatively analyzed and compared by means of two-dimensional histograms and rose diagrams. The northeastern trend revealed for the lineaments corresponds to faults and is in keeping with reactivation of the Reelfoot rift near the Mississippi River; this suggests that deeper features, perhaps at earthquake focal depth, may extend to the land surface as Landsat-detectable lineaments.

Argialas, Demetre P.↗
NASA NTRS2004

General-Purpose Stereo Imaging Velocimetry Technique Developed for Space and Industrial Applications

A new three-dimensional, full-field analysis technique has been developed for industrial and space applications. Stereo Imaging Velocimetry (SIV) will provide full-field analysis for three-dimensional flow data from any optically transparent fluid that can be seeded with tracer particles. The goal of SIV is to provide a means to measure three-dimensional fluid velocities quantitatively and qualitatively at many points. SIV is applicable to any optically transparent fluid experiment. Except for the tracer particles, this measurement technique is nonintrusive. Velocity accuracies are on the order of 95 to 99 percent of fullfield. The system components of SIV include camera calibration, centroid determination, overlap decomposition, particle tracking, stereo matching, and three-dimensional velocity analysis. SIV has been used successfully for space shuttle experiments as well as for fluid flow applications for business and industry.

McDowell, Mark↗
DOE OSTI2025

X-Ray Microtomography Measurements of Coevolving Particle Size and Shape

This study measures simultaneous changes in particle size and shape during grain crushing and proposes quantitative metrics to track their coevolving statistical distribution. Idealized granular materials with widely different initial particle shapes (i.e., spheres, quasi-ellipsoids, plates, and rods) are compressed oedometrically at vertical stress levels sufficient to induce particle breakage. X-ray microtomography and digital image analysis are then used to track changes in particle-scale characteristics. The observations indicate that more irregular particles tend to exhibit a higher degree of breakage compared to more spherical grains subjected to an equivalent stress level. Despite these differences, the measurements also indicate that all the tested particle sets approach a common attractor (expressed in terms of aspect ratio, flatness, and elongation), regardless of their initial morphology. A new shape evolution index is proposed to quantify such trends. With this new metric, it is shown that in all the tested materials, the particle shape evolves faster than size, especially for the more regular morphologies, thus implying that the shape tends to reach its attractor point before the grading reaches its ultimate particle size distribution. Furthermore, this finding underpins an ultimate stage of crushing-driven compression that occurs with particle size reduction but minimal shape changes (i.e., self-replicating shapes due to fractures).

Oedometric compression↗
DOE OSTI2022

Multimodal imaging of hemorrhagic transformation biomarkers in an ischemic stroke model.

Abstract Hemorrhagic transformation of ischemic stroke has devastating consequences, with high mortality and poor functional outcomes. Animal models of ischemic stroke also demonstrate the potential for hemorrhagic transformation, which complicates biochemical characterization, treatment studies, and hinders poststroke functional outcomes in affected subjects. The incidence of hemorrhagic transformation of ischemic stroke in animal model research is not commonly reported. The postmortem brain of such cases presents a complex milieu of biomarkers due to the presence of healthy cells, regions of varying degrees of ischemia, dead and dying cells, dysregulated metabolites, and blood components (especially reactive Fe species released from lysed erythrocytes). To improve the characterization of hemorrhage biomarkers on an ischemic stroke background, we have employed a combination of histology, X-ray fluorescence imaging (XFI), and Fourier transform infrared (FTIR) spectroscopic imaging to assess 122 photothrombotic (ischemic) stroke brains. Rapid freezing preserves brain biomarkers in situ and minimizes metabolic artifacts due to postmortem ischemia. Analysis revealed that 25% of the photothrombotic models had clear signs of hemorrhagic transformation. The XFI and FTIR metabolites provided a quantitative method to differentiate key metabolic regions in these models. Across all hemorrhage cases, it was possible to consistently differentiate otherwise healthy tissue from other metabolically distinct regions, including the ischemic infarct, the ischemic penumbra, blood vessels, sites of hemorrhage, and a region surrounding the hemorrhage core that contained elevated lipid oxidation. Chemical speciation of deposited Fe demonstrates the presence of heme-Fe and accumulation of ferritin.

Pushie, M. J. (ORCID:0000000174945427)↗
DOE OSTI2020

Quantifying the generalization error in deep learning in terms of data distribution and neural network smoothness

We report the accuracy of deep learning, i.e., deep neural networks, can be characterized by dividing the total error into three main types: approximation error, optimization error, and generalization error. Whereas there are some satisfactory answers to the problems of approximation and optimization, much less is known about the theory of generalization. Most existing theoretical works for generalization fail to explain the performance of neural networks in practice. To derive a meaningful bound, we study the generalization error of neural networks for classification problems in terms of data distribution and neural network smoothness. We introduce the cover complexity (CC) to measure the difficulty of learning a data set and the inverse of the modulus of continuity to quantify neural network smoothness. A quantitative bound for expected accuracy/error is derived by considering both the CC and neural network smoothness. Although most of the analysis is general and not specific to neural networks, we validate our theoretical assumptions and results numerically for neural networks by several data sets of images. The numerical results confirm that the expected error of trained networks scaled with the square root of the number of classes has a linear relationship with respect to the CC. We also observe a clear consistency between test loss and neural network smoothness during the training process. In addition, we demonstrate empirically that the neural network smoothness decreases when the network size increases whereas the smoothness is insensitive to training dataset size.

97 MATHEMATICS AND COMPUTING↗