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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Spectroscopic investigation of electron-beam-induced excitation and ionization of air [Abstract]

Time-dependent visible and near-ultraviolet emission spectroscopy was used to track the presence of excited and ionized states induced as an electron beam transited a cavity filled with air at low pressures. An electron beam was produced in vacuum using a Febetron pulsed-power generator modified to produce a peak voltage of 100 kV, a peak current of 4.5 kA, and a pulse width of 100 ns. The beam electrons then passed through thin anode and pressure foils and transited a cavity filled with dry air at either 0.1 Torr or 1 Torr, exciting and ionizing the air along the way. The spectral measurements were combined with information from electrical, interferometric, and imaging diagnostics to reveal different ionization dynamics for the two cases under study.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Characterization of Crystal Properties and Defects in CdZnTe Radiation Detectors

CdZnTe-based detectors are highly valued because of their high spectral resolution, which is an essential feature for nuclear medical imaging. However, this resolution is compromised when there are substantial defects in the CdZnTe crystals. In this study, we present a learning-based approach to determine the spatially dependent bulk properties and defects in semiconductor detectors. This characterization allows us to mitigate and compensate for the undesired effects caused by crystal impurities. We tested our model with computer-generated noise-free input data, where it showed excellent accuracy, achieving an average RMSE of 0.43% between the predicted and the ground truth crystal properties. In addition, a sensitivity analysis was performed to determine the effect of noisy data on the accuracy of the model.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Analysis of Hybrid Gas–Dust Outbursts Observed at 67P/Churyumov–Gerasimenko

Cometary outbursts offer a valuable window into the composition of comet nuclei with their forceful ejection of dust and volatiles in explosive events, revealing the interior components of the comet. Understanding how different types of outbursts influence the dust properties and volatile abundances, to better interpret what signatures can be attributed to primordial composition and what features are the result of processing, is an important task best undertaken with a multi-instrument approach. The European Space Agency Rosetta mission to 67P/Churyumov–Gerasimenko carried a suite of instruments capable of carrying out this task in the near-nucleus coma with unprecedented spatial and spectral resolution. In this work, we discuss two outbursts that occurred 2015 November 7 and were observed by three instruments on board: the Alice ultraviolet spectrograph, the Visual Infrared and Thermal Imaging Spectrometer, and the Optical, Spectroscopic, and Infrared Remote Imaging System. Together, the observations show that mixed gas and dust outbursts can have different spectral signatures representative of their initiating mechanisms, with the first outburst showing indicators of a cliff collapse origin and the second more representative of fresh volatiles being exposed via a deepening fracture. This analysis opens up the possibility of remote spectral classification of cometary outbursts with future work.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Imaging pyrometry for most color cameras using a triple pass filter

A simple combination of the Planck blackbody emission law, optical filters, and digital image processing is demonstrated to enable most commercial color cameras (still and video) to be used as an imaging pyrometer for flames and explosions. The hardware and data processing described take advantage of the color filter array (CFA) that is deposited on the surface of the light sensor array present in most digital color cameras. In this work, a triple-pass optical filter incorporated into the camera lens allows light in three 10-nm wide bandpass regions to reach the CFA/light sensor array. These bandpass regions are centered over the maxima in the blue, green, and red transmission regions of the CFA, minimizing the spectral overlap of these regions normally present. A computer algorithm is used to retrieve the blue, green, and red image matrices from camera memory and correct for remaining spectral overlap. A second algorithm calibrates the corrected intensities to a gray body emitter of known temperature, producing a color intensity correction factor for the camera/filter system. The Wien approximation to the Planck blackbody emission law is used to construct temperature images from the three color (blue, green, red) matrices. A short pass filter set eliminates light of wavelengths longer than 750 nm, providing reasonable accuracy (±10%) for temperatures between 1200 and 6000 K. The effectiveness of this system is demonstrated by measuring the temperature of several systems for which the temperature is known.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Artificial illumination identification from an unmanned aerial vehicle

Artificial illumination identification within images is a useful tool for many applications. Performing such identification allows for an estimation of the illumination source spectrum, which in turn can be used for additional applications ranging from spectral detection and exploitation to statistics about nighttime light usage. Illumination identification has been performed in laboratory settings but not from an unmanned aerial vehicle (UAV) platform. Here, we test the feasibility of using a UAV and commercial off-the-shelf multispectral imaging sensor to perform such artificial illumination identification through linear discriminant analysis using nighttime UAV images. The results are very promising, showing source classification accuracies of 83.3%, 92.3%, 100%, and 100% for the incandescent, light-emitting diode, high pressure sodium, and metal halide illumination sources, respectively. We show that the information gained from the source identification can be further used to inform additional analysis, such as spectral identification. The high resolution of UAV imaging techniques combined with the knowledge of the illumination source can lead to better exploitation of such nighttime data for many applications.

42 ENGINEERING↗
DOE OSTI2022

Integrating very-high-resolution UAS data and airborne imaging spectroscopy to map the fractional composition of Arctic plant functional types in Western Alaska

Widespread changes in vegetation cover and composition are driving strong impacts on Arctic ecosystem functioning and global climate feedbacks. An accurate characterization of tundra vegetation composition is required to understand how the Arctic will respond to future climate change. However, quantifying tundra vegetation composition over large areas is challenging as commonly-used satellite observations are too coarse, spatially and spectrally, to differentiate low-lying tundra vegetation types. Recent airborne and spaceborne imaging spectroscopy platforms provide better data to characterize vegetation composition. Yet, our ability to characterize vegetation composition with imaging spectroscopy remains largely unexplored in the Arctic, particularly due to a lack of ground observations needed to train and test classification models. To address this problem, we collected very-high-resolution (VHR, ~5 cm) unoccupied aerial system (UAS) imagery at three low-Arctic tundra sites located on the Seward Peninsula, western Alaska. In this paper, we examine the feasibility of integrating imagery from the UAS and the hyperspectral Airborne Visible/Infrared Imaging Spectrometer, Next Generation (AVIRIS-NG) airborne instrument to map the fractional composition of 12 key Arctic plant functional types (PFTs). To this end, we first mapped the 12 PFTs from our VHR UAS imagery using random forest classification. We then used these UAS-derived PFT maps as ground truth to develop partial least squares regression (PLSR) models to predict the fractional cover (FCover) of each PFT from AVIRIS-NG imagery. Further, we evaluated the performance of our PLSR models using reserved UAS samples, as well as by mapping PFT FCover and dominant PFT for large tundra landscapes. Our results show that 1) Arctic PFTs can be effectively mapped using VHR UAS imagery, with overall accuracy between 86% and 92%, 2) when the UAS mapped PFTs were used to inform PLSR scaling models, the FCover of the 12 PFTs could be effectively estimated from AVIRIS-NG imagery with a mean absolute error (MAE) <0.13, and 3) our PLSR models outperformed traditional, fully constrained least-squares (FCLS) linear mixture analysis and produced high-quality, spatially contiguous PFT FCover and PFT maps that captured vegetation spatial patterns with similar accuracy to those developed from UAS imagery. The developed PLSR models have the potential to be broadly applied for quantifying vegetation composition with AVIRIS-NG images to help monitor tundra vegetation dynamics and improve process-based modeling of tundra ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

New Candidates for Planetary-mass Brown Dwarfs in IC 348

We have used infrared images obtained with the Wide Field Camera 3 on board the Hubble Space Telescope to search for planetary-mass brown dwarfs in the star-forming cluster IC 348. In those images, we have identified 12 objects that have colors indicative of spectral types later than M8, corresponding to masses of ≲30 M {sub Jup} at the age of IC 348. The four brightest candidates have been observed with spectroscopy, all of which are confirmed to have late types. Two of those candidates appear to be young, and thus are likely members of the cluster, while the ages and membership of the other two candidates are uncertain. One of the former candidates is the faintest known member of IC 348 in extinction-corrected K {sub s} and is expected to have a mass of 4–5 M {sub Jup} based on evolutionary models and an assumed age of 3 Myr. Four of the remaining eight candidates have ground-based photometry that further supports their candidacy as brown dwarfs, some of which are fainter (and potentially less massive) than the known members.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Stimulated Raman Scattering Microscopy: Real-Time In-Situ Physical and Chemical Characterization of Reverse Osmosis Desalination Membrane Scaling

We introduce a stimulated Raman scattering (SRS) methodology designed for rapid, real-time, and in situ monitoring of RO membrane scaling adapted for bench-scale desalination flow cells. The methodology can provide new insights into membrane scaling dynamics by offering time-resolved reflection imaging of inorganic crystal growth, coupled with chemical identification from Raman spectral data. These capabilities allow for direct local measurement of the membrane surface area covered by different scalants as well as an approximation of the scalant volume using three-dimensional, integrated Raman intensity. The 2D and 3D SRS results obtained from CaSO 4 scaling experiments are compared to and are in reasonable agreement with those provided by confocal microscopy. The real-time physical and chemical characterization capabilities presented here could be extended to study combinations of inorganic, organic, and biological fouling. Overall, the SRS methodology represents an advancement in real-time sensing of membrane fouling that offers the potential for improved operation, lower cost, and more resilient RO membrane systems for sustainable water management.

42 ENGINEERING↗
DOE OSTI2022

Probing plasma physics with spectral index maps of accreting black holes on event horizon scales

The Event Horizon Telescope (EHT) collaboration has produced the first resolved images of the supermassive black holes at the centre of our galaxy and at the centre of the elliptical galaxy M87. As both technology and analysis pipelines improve, it will soon become possible to produce spectral index maps of black hole accretion flows on event horizon scales. Here, in this work, we predict spectral index maps of both M87* and Sgr A* by applying the general relativistic radiative transfer (GRRT) code IPOLE to a suite of general relativistic magnetohydrodynamic (GRMHD) simulations. We analytically show that the spectral index increases with increasing magnetic field strength, electron temperature, and optical depth. Consequently, spectral index maps grow more negative with increasing radius in almost all models, since all of these quantities tend to be maximized near the event horizon. Additionally, photon ring geodesics exhibit more positive spectral indices, since they sample the innermost regions of the accretion flow with the most extreme plasma conditions. Spectral index maps are sensitive to highly uncertain plasma heating prescriptions (the electron temperature and distribution function). However, if our understanding of these aspects of plasma physics can be tightened, even the spatially unresolved spectral index around 230 GHz can be used to discriminate between models. In particular, Standard and Normal Evolution (SANE) flows tend to exhibit more negative spectral indices than Magnetically Arrested Disc (MAD) flows due to differences in the characteristic magnetic field strength and temperature of emitting plasma.

(magnetohydrodynamics) MHD↗
DOE OSTI2021

Mid-infrared Pulsed Upconversion Imaging in a Rotating Detonation Combustor

To meet the challenges associated with performing mid-InfraRed (IR) imaging in Rotating Detonation Combustors (RDCs), a novel pulsed mid-IR UpConversion Imaging (UCI) diagnostic has been implemented. UCI is an alternative to direct mid-IR detection that uses nonlinear optical frequency mixing to shift mid-IR wavelengths carrying a target image to shorter wavelengths that can be imaged with high-performance silicon-based CCD/CMOS cameras. This approach offers several favorable properties including high spectral selectivity, high temporal resolution, and superior low-light detectivity. A hydrogen-air research RDC was operated with carbon dioxide addition to allow pulsed UCI imaging of mid-IR luminosity within the combustion channel from spontaneous thermal emissions. The resulting measurements demonstrate high spatiotemporal resolution capable of imaging small structures near the supersonically propagating detonation wave front. The results show how this technique can be used to observe sharp gradients and millimeter-scale structures in the high-temperature, high-pressure zones RDC flow fields.

White, Logan W.↗
DOE OSTI2022

Predicting Switchgrass Biomass Yields Using a Spectral Vegetation Index Derived from Multispectral Satellite Imagery

Successful scaling of perennial bioenergy crop production requires a landscape design that optimizes the benefits of finite lands for people, communities, and environments. Utilizing marginal areas is the key to sustainable bioenergy crop production (Ssegane et al., 2015, 2016). Marginal areas are often small-sized lands and unevenly distributed across the agricultural landscape (Ssegane et al., 2016); thus, a systematic, semi-automated remote sensing method is needed as an effective means of estimating bioenergy crop yields across landscapes. Argonne National Laboratory (Argonne) is currently developing a tool, Scaling Up Perennial Bioenergy Economics and Ecosystem Services Tool (SUPERBEEST), to identify marginal agricultural lands and quantify environmental and economic effects of perennial bioenergy crop production systems. The tool aims to provide users a path to foster the sustainable and productive integration of bioenergy crops in the Midwestern agricultural landscape. Reliable, cost-effective, and timely estimation of bioenergy crop yields using remote sensing would help calculate and track the success of integrated bioenergy crops in the landscape for those communities. Argonne previously conducted feasibility studies for estimating biomass yields for bioenergy feedstock, corn and perennial grass using spectral vegetation indices (SVIs)1 derived from optical imagery (Hamada et al., 2015, 2021). In both studies, SVIs, more specifically those sensitive to plant chlorophyll or nitrogen contents, showed potential for estimating or predicting biomass yields with a correlation of determination (R2) ranging from 0.54 to 0.96, indicating a value for further investigation as a viable means of quantifying bioenergy feedstock production across large landscapes. Thus, the goal of this study is to evaluate the feasibility of use of SVIs as a means of estimating or predicting switchgrass biomass yields at harvest using publicly available multispectral satellite imagery. The feasibility analysis was performed using four study areas of mature switchgrass located in Virginia. Objectives are to (1) examine the SVIs and establish their relationships with switchgrass biomass yields at harvest, (2) develop a parsimonious image processing model for predicting at-harvest yields by applying the relationships with the most promising spectral index and (3) map switchgrass yields predicted by the image processing model across the study sites. The calibration to field data will rely on switchgrass biomass yields determined by the baling method, representing a potential challenge to the analysis but an important practical aspect for future applications. With this research design, the study aimed to gain insights into enabling remote sensing-based estimation of bioenergy crop yields in a reliable, cost- effective, and timely manner across large, heterogeneous landscapes.

09 BIOMASS FUELS↗
DOE OSTI2021

Near-field infrared microscopy: A novel analytic mapping technique to nanocharacterize calcium silicate-based cement materials

Infrared imaging via scattering-type scanning near-field optical microscopy (s-SNOM) allows chemical mapping of organic and inorganic materials with nanoscale spatial resolution. However, its potential adaptation to the complex multiphase structure of Portland cement is yet to be explored. Here we demonstrate the successful implementation of s-SNOM to spatially resolve coexisting chemical phases in tricalcium silicate, Portland cement's main compound, with 20-nm resolution. We found that s-SNOM is sensitive to different anhydrous polymorphic phases, revealing nanoscale domains that are ‘invisible’ to other microscopic techniques. Furthermore, s-SNOM's ability to distinguish the unhydrated and hydrated phases signifies its great promise as an analytical tool to study the complex hydration process of cement. The key to s-SNOM's application was nano-modifying the surface roughness of the cement samples, allowing nanoscale infrared imaging without topographical artifacts. Our study opens a window for infrared spectral microscopy in cement and other porous inorganic materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Flux and estimated spectra from a low-intensity laser-driven X-ray source

Laser-driven X-rays as probes for high-energy-density physics spans an extremely large parameter space with laser intensities varying by 8 orders of magnitude. We have built and characterized a soft X-ray source driven by a modest intensity laser of 4 × 10 13 W/cm 2 . Emitted X-rays were measured by diamond radiation detectors and a filtered soft X-ray camera. A material-dependence study on Al, Ti, stainless steel alloy 304, Fe, Cu and Sn targets indicated 5-μm-thick Cu foils produced the highest X-ray yield. X-ray emission in the laser direction and emission in the reverse direction depend strongly on the foil material and the thickness due to the opacity and hydrodynamic disassembly time. The time-varying X-ray signals are used to measure the material thinning rate and is found to be ~1.5 μm/ns for the materials tested implying thermal temperature around 0.6 eV. The X-ray spectra from Cu targets peaks at ~2 keV with no emission >4 keV and was estimated using images with eight different foil filters. One-dimensional hydrodynamic and spectral calculations using HELIOS-CR provide qualitative agreement with experimental results. Modest intensity lasers can be an excellent source for nanosecond bursts of soft X-rays.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Label-free X-ray estimation of brain amyloid burden

Amyloid plaque deposits in the brain are indicative of Alzheimer’s and other diseases. Measurements of brain amyloid burden in small animals require laborious post-mortem histological analysis or resource-intensive, contrast-enhanced imaging techniques. We describe a label-free method based on spectral small-angle X-ray scattering with a polychromatic beam for in vivo estimation of brain amyloid burden. Our findings comparing 5XFAD versus wild-type mice correlate well with histology, showing promise for a fast and practical in vivo technique.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Python catemis package for DARHT Axis-II Dispenser-Cathode Emissivity and Temperature Analysis

The catemis python package includes the analysis methods used in paper "DARHT Axis-II Dispenser-Cathode Emissivity and Temperature", which was presented at the 2021 Weapons Engineering Symposium and Journal (WESJ) hosted by Los Alamos National Laboratory. The paper (LA-UR-21-25647) and presentation (LA-UR-21-28231) report on a temperature and emissivity model that has been developed and applied to data from diagnostics used to measure the surface temperature of the DARHT Axis-II hot dispenser cathode over more than a decade of operation. The catemis package provides all the methods used in reporting these results along with the data files used to create the plots and tables in the paper. This includes methods for loading and processing FAR spectral pyrometer data along with methods for temperature calibration of cathode images.

Koglin, Jason↗
DOE OSTI2020

System-Independent X-Ray Characterization

We have developed a method for image reconstruction and analysis of dual-energy X-ray scans that has been demonstrated to yield a physically intuitive characterization of materials (by electron density and effective atomic number) in a system-independent way. Our methodology stands in contrast to common practice of reconstructing images to yield linear attenuation coefficients, which depend strongly on system spectral response. At the core of our method, a technique called dual-energy decomposition is used to generate spectral energy-independent characterizations of the attenuation properties of a material. Inputs to this decomposition include system spectral response estimates and dual-energy X-ray projection data. X-ray cross-section tables are used to convert decomposition results to physical feature estimates (electron density, effective atomic number). Our method currently works best for materials with atomic numbers below 22 (titanium). In prior work for DHS, we demonstrated in a controlled, no-clutter environment that the decomposition technique could be applied to scans of a well-characterized materials on multiple systems with different X-ray spectral responses. In cases where LAC values showed a standard deviation of as much as 20% of mean value, application of our method yielded results with standard deviations as low as 1–3% of mean value.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Petrographic and spectral study of hydrothermal mineralization in drill core from Hawaii: A potential analog to alteration in the martian subsurface

Abstract Continuous rock core was collected for 1764 m (5786’) on the Pohakuloa Army Training base near the center of the big island of Hawaii. The core traverses basaltic lava flows from the volcano's shield-building phase, and perched aquifers and higher temperature groundwaters were encountered. The collected samples record water-rock interactions of basaltic materials in a setting that may be a model for groundwater interactions on Mars. We collected visible and infrared point spectra of materials in the lowest portion of the core, where alteration was noted to become more prominent. We identified three types of phyllosilicate spectral signatures and three types of zeolites. The phyllosilicates show similarity to those identified on Mars using data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM). Based on the field survey, 25 depths were selected for sampling and petrographic analysis of thin sections. The spectral data and thin section work have a strong agreement in the types of materials identified by the two different techniques. Both the spectral and petrographic data indicate low to moderate temperature geothermal alteration occurred in the lower half of the core. The field spectra are a useful reconnaissance tool for selecting mineralogic diversity for subsequent higher resolution and more time-consuming laboratory analysis.

Geochemistry & Geophysics↗
DOE OSTI2023

Single-Filament Imaging Mass Spectrometry Lipidomics in Arthrospira platensis

Elucidating intra-organismal biochemical and lipid organization in photosynthetic biological cell factories of filamentous cyanobacteria, i.e., Arthrospira platensis (Spirulina), is important to track physiological response mechanisms during growth. Little is known about the filaments' biochemical organization and cellular structure and no label-free imaging techniques exist that provide molecular mapping. We applied ultra-high resolution mass spectrometry (7T FT-ICR-MS) matrix-assisted laser desorption ionization (MALDI) imaging to immobilized Spirulina filaments to investigate the localization of lipids across distinct physiological regions. We optimized matrix selection and deposition methods with the goal of facilitating high spatial, and intra-filament, resolution using untargeted multivariate statistical spectral deconvolution across MS pixels. Our results demonstrate an improved two step application with an optimized procedure for intra-organismal lipid profiling to improve analyte sensitivity and achieve higher spatial resolution, whereby we evaluate three conventional matrices 2,5-dihydroxybenzoic acid (DHB), a 9:1 ratio of DHB:superDHB (sDHB), 1,5- diaminonaphthalene (DAN) and a 50:50 mix of DHB:sDHB and compare delineation and pixel-based elucidation of intra-filament lipidomics. We identified a total of 1,626 features that could be putatively assigned a lipid-like formula based on database query and 46 unique features, with associated lipid assignments that were significantly distinct in their intra-filament location. MALDI- imaging MS with untargeted statistical spectral deconvolution was used to visualize intra-filament lipidomics organization in Spirulina filaments. Improvements in matrix deposition, including sequential sublimation and pneumatic spraying, increased signal abundance at high spatial resolution and allowed for identification of distinct lipid composition regions. Here in this work outlines a methodology that may be used for micro-ecological untargeted molecular phenotyping.

09 BIOMASS FUELS↗