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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Research Instruments

The GENETI-SCANNER, newest product of Perceptive Scientific Instruments, Inc. (PSI), rapidly scans slides, locates, digitizes, measures and classifies specific objects and events in research and diagnostic applications. Founded by former NASA employees, PSI's primary product line is based on NASA image processing technology. The instruments karyotype - a process employed in analysis and classification of chromosomes - using a video camera mounted on a microscope. Images are digitized, enabling chromosome image enhancement. The system enables karyotyping to be done significantly faster, increasing productivity and lowering costs. Product is no longer being manufactured.

Source record↗
NASA NTRS1997

Modulation of statolith mass and grouping in white clover (Trifolium repens) growth in 1-g, microgravity and on the clinostat

Current models of gravity perception in higher plants focus on the buoyant weight of starch-filled amyloplasts as the initial gravity signal susceptor (statolith). However, no tests have yet determined if statolith mass is regulated to increase or decrease gravity stimulus to the plant. To this end, the root caps of white clover (Trifolium repens) grown in three gravity environments with three different levels of gravity stimulation have been examined: (i) 1-g control with normal static gravistimulation, (ii) on a slow clinostat with constant gravistimulation, and (iii) in the stimulus-free microgravity aboard the Space Shuttle. Seedlings were germinated and grown in the BioServe Fluid Processing Apparatus and root cap structure was examined at both light and electron microscopic levels, including three-dimensional cell reconstruction from serial sections. Quantitative analysis of the electron micrographs demonstrated that the starch content of amyloplasts varied with seedling age but not gravity condition. It was also discovered that, unlike in starch storage amyloplasts, all of the starch granules of statolith amyloplasts were encompassed by a fine filamentous, ribosome-excluding matrix. From light micrographic 3-D cell reconstructions, the absolute volume, number, and positional relationships between amyloplasts showed (i) that individual amyloplast volume increased in microgravity but remained constant in seedlings grown for up to three days on the clinostat, (ii) the number of amyloplasts per cell remained unchanged in microgravity but decreased on the clinostat, and (iii) the three-dimensional positions of amyloplasts were not random. Instead amyloplasts in microgravity were grouped near the cell centers while those from the clinostat appeared more dispersed. Taken together, these observations suggest that changing gravity stimulation can elicit feedback control over statolith mass by changing the size, number, and grouping of amyloplasts. These results support the starch-statolith theory of graviperception in higher plants and add to current models with a new feedback control loop as a mechanism for modulation of statolith responsiveness to inertial acceleration.

Flight Experiment↗
NASA NTRS1978

Medical Image Analysis Facility

To improve the quality of photos sent to Earth by unmanned spacecraft. NASA's Jet Propulsion Laboratory (JPL) developed a computerized image enhancement process that brings out detail not visible in the basic photo. JPL is now applying this technology to biomedical research in its Medical lrnage Analysis Facility, which employs computer enhancement techniques to analyze x-ray films of internal organs, such as the heart and lung. A major objective is study of the effects of I stress on persons with heart disease. In animal tests, computerized image processing is being used to study coronary artery lesions and the degree to which they reduce arterial blood flow when stress is applied. The photos illustrate the enhancement process. The upper picture is an x-ray photo in which the artery (dotted line) is barely discernible; in the post-enhancement photo at right, the whole artery and the lesions along its wall are clearly visible. The Medical lrnage Analysis Facility offers a faster means of studying the effects of complex coronary lesions in humans, and the research now being conducted on animals is expected to have important application to diagnosis and treatment of human coronary disease. Other uses of the facility's image processing capability include analysis of muscle biopsy and pap smear specimens, and study of the microscopic structure of fibroprotein in the human lung. Working with JPL on experiments are NASA's Ames Research Center, the University of Southern California School of Medicine, and Rancho Los Amigos Hospital, Downey, California.

Source record↗
NASA NTRS2011

Macro vs. Micro: Relating the Spectral Properties of Vesta and the HED Meteorite

We present the main results obtained comparing the visible-near infrared (VIS-NIR) spectra Vesta s surface with howardites, eucrites, diogenites (HED). HEDs are commonly associated with Vesta s composition based on spectral similarities. Because of such association, much effort is being made to merge the information from HEDs as well as Vestoids - with that from Vesta to characterize the lithologic diversity of the surface of this asteroid and to infer clues regarding its thermal history. However, while the HEDs are a class of meteorites well studied in the laboratory, the only spectral data available for Vesta until now were telescopic observations which are limited in terms of observation conditions, spatial resolution and Signal to Noise Ratio. The Dawn spacecraft, orbiting around Vesta since July 2011, is performing detailed observations of this body and thus improving our knowledge of its properties. Dawn s scientific payload includes an imaging spectrometer, VIR-MS, sensitive to the VIS-NIR spectral range. VIR-MS began acquiring spectra during the approach phase started in May 2011 and will continue its observations through July 2012 when the spacecraft will depart Vesta to travel to Ceres. The VIR-MS spatial resolution depends upon the mission phase (approach, survey, high altitude, low altitude). However, spectra acquired by VIR-MS have already exceeded the spatial resolution of ground-based telescopic observations, with resolution in the approach phase ranging from 2.5 up to 0.8 km/pixel. Moreover, the observations are uniformly distributed in latitude and longitude allowing us to have a global view of Vesta s crust spectral properties. Using the information provided by VIR spectra, we studied the distribution of the spectral heterogeneities on the surface and we used our findings to perform a comparison with HEDs spectra in the VIS-NIR spectral range searching for analogies and/or incompatibilities. In our analysis, we focused on a method to compare the results obtained at microscopic scale on HEDs samples and the one obtained at macroscopic scale on the surface of Vesta. Finally, we discuss our results in the context of vestan thermal history. The intent of this study is to improve our understanding of the connection between Vesta and the HED samples, which is one of the primary Dawn scientific objectives. This work is supported by an Italian Space Agency (ASI) grant and by NASA through the Dawn project and a Dawn at Vesta Participating Scientist grant.

Ammannito, E.↗
NASA NTRS2017

Orion Exploration Flight Test Post-Flight Inspection and Analysis

The principal mechanism for developing orbital debris environment models, is to make observations of larger pieces of debris in the range of several centimeters and greater using radar and optical techniques. For particles that are smaller than this threshold, breakup and migration models of particles to returned surfaces in lower orbit are relied upon to quantify the flux. This reliance on models to derive spatial densities of particles that are of critical importance to spacecraft make the unique nature of the EFT-1's return surface a valuable metric. To this end detailed post-flight inspections have been performed of the returned EFT-1 backshell, and the inspections identified six candidate impact sites that were not present during the pre-flight inspections. This paper describes the post-flight analysis efforts to characterize the EFT-1 mission craters. This effort included ground based testing to understand small particle impact craters in the thermal protection material, the pre- and post-flight inspection, the crater analysis using optical, X-ray computed tomography (CT) and scanning electron microscope (SEM) techniques, and numerical simulations.

Miller, J. E.↗
DOE OSTI2021

Rapid and flexible segmentation of electron microscopy data using few-shot machine learning

Abstract Automatic segmentation of key microstructural features in atomic-scale electron microscope images is critical to improved understanding of structure–property relationships in many important materials and chemical systems. However, the present paradigm involves time-intensive manual analysis that is inherently biased, error-prone, and unable to accommodate the large volumes of data produced by modern instrumentation. While more automated approaches have been proposed, many are not robust to a high variety of data, and do not generalize well to diverse microstructural features and material systems. Here, we present a flexible, semi-supervised few-shot machine learning approach for segmentation of scanning transmission electron microscopy images of three oxide material systems: (1) epitaxial heterostructures of SrTiO 3 /Ge, (2) La 0.8 Sr 0.2 FeO 3 thin films, and (3) MoO 3 nanoparticles. We demonstrate that the few-shot learning method is more robust against noise, more reconfigurable, and requires less data than conventional image analysis methods. This approach can enable rapid image classification and microstructural feature mapping needed for emerging high-throughput characterization and autonomous microscope platforms.

36 MATERIALS SCIENCE↗
NASA NTRS2008

Development and Optical Testing of the Camera, Hand Lens, and Microscope Probe with Scannable Laser Spectroscopy (CHAMP-SLS)

Conducting high resolution field microscopy with coupled laser spectroscopy that can be used to selectively analyze the surface chemistry of individual pixels in a scene is an enabling capability for next generation robotic and manned spaceflight missions, civil, and military applications. In the laboratory, we use a range of imaging and surface preparation tools that provide us with in-focus images, context imaging for identifying features that we want to investigate at high magnification, and surface-optical coupling that allows us to apply optical spectroscopic analysis techniques for analyzing surface chemistry particularly at high magnifications. The camera, hand lens, and microscope probe with scannable laser spectroscopy (CHAMP-SLS) is an imaging/spectroscopy instrument capable of imaging continuously from infinity down to high resolution microscopy (resolution of approx. 1 micron/pixel in a final camera format), the closer CHAMP-SLS is placed to a feature, the higher the resultant magnification. At hand lens to microscopic magnifications, the imaged scene can be selectively interrogated with point spectroscopic techniques such as Raman spectroscopy, microscopic Laser Induced Breakdown Spectroscopy (micro-LIBS), laser ablation mass-spectrometry, Fluorescence spectroscopy, and/or Reflectance spectroscopy. This paper summarizes the optical design, development, and testing of the CHAMP-SLS optics.

Fluorescence↗
DOE OSTI2020

Spatially Resolved Performance Analysis for Perovskite Solar Cells

This review explores the current state of the art in spatially resolved characterization of mixed-halide perovskite solar cells. As the size of perovskite cells and modules continues to grow, quantification of the spatial distribution of key cell parameters will become increasingly valuable in predicting ultimate cell-level performance and tracking process homogeneity. Here, both high resolution microscopic approaches using scanning techniques and camera-based methods for full-area cell and/or module analysis are discussed. The value of this local data in predicting performance losses at the cell level is particularly emphasized. Measurable physical parameters sensitive to losses of voltage, current, fill factor, and efficiency are discussed together with selected experimental results. It is demonstrated that a combination of spatially resolved cell parameter mapping/imaging can be used to quantitatively discriminate various loss contributions at high resolution. The impact and control of inhomogeneities become particularly important when upscaling from small devices to large formats compatible with industrial mass production.

14 SOLAR ENERGY↗
NASA NTRS2017

Failure Analysis of Heavy-Ion-Irradiated Schottky Diodes

In this paper, we use high- and low-magnification optical microscope images, thermal infrared camera images, and scanning electron microscope images to identify failure locations in heavy-ion-irradiated Schottky diodes. After failures have been identified, the parts were cross-sectioned to describe the structure of the failures and energy dispersive x-ray spectroscopy was used to characterize the materials in the failure structures.

Radiation effects↗
NASA NTRS1992

X-Ray Microanalysis and Electron Energy Loss Spectrometry in the Analytical Electron Microscope: Review and Future Directions

This paper reviews and discusses future directions in analytical electron microscopy for microchemical analysis using X-ray and Electron Energy Loss Spectroscopy (EELS). The technique of X-ray microanalysis, using the ratio method and k(sub AB) factors, is outlined. The X-ray absorption correction is the major barrier to the objective of obtaining I% accuracy and precision in analysis. Spatial resolution and Minimum Detectability Limits (MDL) are considered with present limitations of spatial resolution in the 2 to 3 microns range and of MDL in the 0.1 to 0.2 wt. % range when a Field Emission Gun (FEG) system is used. Future directions of X-ray analysis include improvement in X-ray spatial resolution to the I to 2 microns range and MDL as low as 0.01 wt. %. With these improvements the detection of single atoms in the analysis volume will be possible. Other future improvements include the use of clean room techniques for thin specimen preparation, quantification available at the I% accuracy and precision level with light element analysis quantification available at better than the 10% accuracy and precision level, the incorporation of a compact wavelength dispersive spectrometer to improve X-ray spectral resolution, light element analysis and MDL, and instrument improvements including source stability, on-line probe current measurements, stage stability, and computerized stage control. The paper reviews the EELS technique, recognizing that it has been slow to develop and still remains firmly in research laboratories rather than in applications laboratories. Consideration of microanalysis with core-loss edges is given along with a discussion of the limitations such as specimen thickness. Spatial resolution and MDL are considered, recognizing that single atom detection is already possible. Plasmon loss analysis is discussed as well as fine structure analysis. New techniques for energy-loss imaging are also summarized. Future directions in the EELS technique will be the development of new spectrometers and improvements in thin specimen preparation. The microanalysis technique needs to be simplified and software developed so that the EELS technique approaches the relative simplicity of the X-ray technique. Finally, one can expect major improvements in EELS imaging as data storage and processing improvements occur.

Goldstein, J. I.↗
NASA NTRSDate not supplied

Analysis of Samples from Asteroid Ryugu Returned by Hayabusa2

After returning to Earth in the winter of 2020, the samples from Cb-type asteroid Ryugu were stored under atmosphere-free conditions at the Extraterrestrial Materials Curation Center of ISAS/JAXA, and investigated for basic descriptions (sample imaging, weighing, etc.). They were distributed to six initial analysis teams in Japan in June 2021. The "Stone" team, in charge of analysis of coarse particles (>1 mm in size), conducted a series of analyses using a variety of techniques including reflectance spectra measurement, synchrotron-radiation three-dimensional elemental and mineralogical analysis, bulk elemental analysis using muon beam, Fe valence state measurement by XANES and Mössbauer spectroscopy, detailed mineralogical and petrological characterization by scanning and transmission electron microscopes. Physical and thermal properties of Ryiugu samples were measured to understand the response to shock and heating. In this talk, I would like to introduce summary of analysis results and what comes to be known about the formation and evolution of asteroid Ryugu.

Tomoki Nakamura↗
NASA NTRS2014

Coordinated Mineralogical and Isotopic Analysis of a Cosmic Symplectite Identified in a Stardust Terminal Particle

Comet Wild-2 samples returned by the Stardust spacecraft contain a chemically diverse mixture of material, underscoring the complex nature of comets. Studies of entire Stardust aerogel tracks afford the opportunity to examine the fine-grained particle fragments distributed along the length of the track as well as the terminal particles. Previous TEM characterization of a terminal particle (TP) in track #147 revealed a symplectically intergrown iron sulfide and oxide assemblage. Mineralogically similar assemblages, known as cosmic symplectites (COS, formerly termed "new-PCP"), have only been identified in the primitive carbonaceous chondrite Acfer 094. Meteoritic COS have isotopically heavy O compositions (delta (sup 17), O-18 = 180per mille) that point to interactions with early solar system primordial water. In this study we report mineralogical and O isotopic measurements of the Wild-2 COS assemblage. Experimental: Track #147 is a "bulbous"-type track (4600 microns long) containing 7 terminal particles. The TPs were removed from the track, embedded in epoxy, and ultramicrotomed. A JEOL 2500SE 200 keV field-emission scanning-transmission electron microscope was used to obtain quantitative elemental maps and detailed mineralogical characterization. Following TEM analysis, two thin sections of TP4 (12 microns) were analyzed for O isotopes by raster ion imaging with the JSC NanoSIMS 50L. All three O isotopes were measured simultaneously using electron multipliers. San Carlos olivine grains were used as isotopic standards. Results and Discussion: The COS in the Wild-2 track #147 TP4 sample consists of symplectically intergrown pentlandite and nanocrystalline maghemite which coexists with high-Ca pyroxene with Na and Cr (kosmochlor component). This kosmochlor component could have a nebular origin and be precursors to type II chondrules in ordinary chondrites. Yet pentlandite is not a stable phase in the nebula. The COS in Acfer 094 also consists of pentlandite, but contains magnetite [4] rather than the more oxidized maghemite observed in the Wild-2 COS. The Acfer 094 COS display heavy O isotopic compositions that are the result of sulfidization and oxidation of Fe, Ni-metal grains and sulfides by O-17- and O-18-rich water in the solar nebula or possibly on the parent body. The O isotopic composition of the Wild-2 COS, however, is indistinguishable from terrestrial, indicating it was not altered by the same primordial aqueous reservoir as the Acfer 094 COS. The alteration could have occurred on the parent body by isotopically equilibrated ice. The mineralogy and petrography of Wild-2 samples suggests an incomplete or nascent hydration process. In future work we will analyze S isotopes in the track #147 TP4 COS and search for additional COS in Stardust samples.

Nguyen, A. N.↗
DOE OSTI2026

RU-net for automatic characterization of TRISO fuel cross sections

During irradiation, phenomena such as kernel swelling and buffer densification may impact the performance of tristructural isotropic (TRISO) particle fuel. Post-irradiation microscopy is often used to identify these irradiation-induced morphologic changes. However, each fuel compact generally contains thousands of TRISO particles. Manually performing the work to get statistical information on these phenomena is cumbersome and subjective. Here, to reduce the subjectivity inherent in that process and to accelerate data analysis, we used convolutional neural networks (CNNs) to automatically segment cross-sectional images of microscopic TRISO layers. CNNs are a class of machine-learning algorithms specifically designed for processing structured grid data. They have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we generated a large irradiated TRISO layer dataset with more than 2,000 microscopic images of cross-sectional TRISO particles and the corresponding annotated images. Based on these annotated images, we used different CNNs to automatically segment different TRISO layers. These CNNs include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net performs best in terms of Intersection over Union (IoU). Using CNN models, we can expedite the analysis of TRISO particle cross sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

RU Net for Automatic Characterization of TRISO Fuel Cross Sections

TRistructural ISOtropic (TRISO) particle fuel is a type of nuclear fuel known for its high-temperature and high-burnup performance. Each sub-millimeter diameter TRISO particle consists of uranium-oxycarbide (UCO) or UO2 fuel kernel, coated with buffer, inner pyrolytic carbon (IPyC), silicon carbide (SiC), and outer pyrolytic carbon (OPyC) layers. The SiC layer acts as the main containment barrier for the TRISO particle to retain the fission products, while the IPyC and OPyC layers provide additional barriers to the release of fission products, especially fission gases. During irradiation, phenomena like kernel swelling, buffer densification, and IPyC fracture may impact fuel performance. Post-irradiation microscopy on entire compact cross sections or samples of individual particles deconsolidated from compacts is often used to identify these irradiation-induced changes in morphology. However, each fuel compact generally contains thousands of TRISO particles. To get statistical information on these phenomena, it is cumbersome work if done manually. For example, to get information about swelling/densification behaviors of different layers or kernels after irradiation, researchers previously manually measured the perimeter of each TRISO layer in hundreds of particles after four rounds of iterative grinding and polishing encompassing more than 2000 cross-section images for a total of four fuel compacts. To attempt to reduce the subjectivity inherent in that process and accelerate data analysis, we conducted a study on the automatic TRISO layer segmentation on cross-sectional microscopic images using Convolutional Neural Networks (CNNs). CNNs are a class of machine learning algorithms specifically designed for processing structured grid data that have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we have generated the large irradiated TRISO layer dataset with more than 2000 cross-section TRISO microscopic images and the corresponding annotated images. Based on these annotated images, we have employed different CNNs for automatic segmentation of different TRISO layers. These include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net has the best performance in terms of intersection-over-union (IoU). Through the aid of these CNN models, we can expedite the analysis of TRISO particle cross-sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

Convolutional Neural Networks↗
DOE OSTI2022

AtomAI framework for deep learning analysis of image and spectroscopy data in electron and scanning probe microscopy

Over the past several decades, electron and scanning probe microscopes have become critical components of condensed matter physics, materials science and chemistry research. At the same time, the infrastructure for establishing a connection between microscopy observations and materials behaviour over a broader parameter space is lacking. In this work, we introduce AtomAI, an open-source software package bridging instrument-specific Python libraries, deep learning and simulation tools into a single ecosystem. AtomAI allows direct applications of deep neural networks for atomic and mesoscopic image segmentation converting image and spectroscopy data into class-based local descriptors for downstream tasks such as statistical and graph analysis. For atomically resolved imaging data, the output is types and positions of atomic species, with an option for subsequent refinement. AtomAI further allows the implementation of a broad range of image and spectrum analysis functions, including invariant variational autoencoders for disentangling structural factors of variation and im2spec type of encoder–decoder models for mapping structure–property relationships. Finally, our framework allows seamless connection to the first principles modelling with a Python interface on the inferred atomic positions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Stochastic nonlinear analysis of unidirectional fiber composites using image-based microstructural uncertainty quantification

Here, we present a data-driven nonlinear uncertainty quantification and propagation framework to study the microstructure-induced stochastic performance of unidirectional (UD) carbon fiber reinforced polymer (CFRP) composites. The proposed approach integrates (1) microscopic image characterization, (2) stochastic microstructure reconstruction, and (3) efficient multiscale finite element simulations enabled by self-consistent clustering (SCA) analysis. To model the complex microstructural variability, the proposed UQ methods take the non-Gaussian uncertainty sources into account through a distribution-free sampling approach leveraging nonparametric and asymptotic statistical tools. A hierarchical conditional sampling strategy enables the simultaneous sampling of multiple sources of uncertainties. Our approach provides insights into the impact of microstructural variabilities, which are shown to have an increasing impact on the nonlinear responses of UD CFRP parts under progressive compression loading and ultimately on the failure rate over time. We discover that before CFRP parts start to fail, a characteristic time period emerges with distinctive uncertainty distributions specific to the microstructure variability and the probability of failure. Identifying the failure time period is crucial to the reliability prediction, which is an essential component of CFRP design.

36 MATERIALS SCIENCE↗
DOE OSTI2020

1D to 2D Transition in Tellurium Observed by 4D Electron Microscopy

A new microwave-enhanced synthesis method for the production of tellurium nanostructures is reported here—with control over products from the 1D regime (sub-5 nm diameter nanowires), to nanoribbons, to the 2D tellurene regime—along with a new methodology for local statistical quantification of the crystallographic parameters of these materials at the nanometer scale. Using a direct electron detector and image-corrected microscope, large and robust 4D scanning transmission electron microscopy datasets for accurate structural analysis are obtained. These datasets allow the adaptation of quantitative techniques originally developed for X-ray diffraction (XRD) refinement analyses to transmission electron microscopy, enabling the first demonstration of sub-picometer accuracy lattice parameter extraction while also obtaining both the size of the coherent crystallite domains and the nanostrain, which is observed to decrease as nanowires transition to tellurene. This new local analysis is commensurate with global powder XRD results, indicating the robustness of both the new synthesis approach and new structural analysis methodology for future scalable production of 2D tellurene and characterization of nanomaterials.

2D materials↗
DOE OSTI2024

In Situ Characterization of Interface Evolution in Argyrodite‐Based All‐Solid‐State Li Batteries

Interfacial stability is one of the critical challenges in all-solid-state Li metal batteries. Multiple processes such as solid electrolyte (SE) decomposition and lithium dendrite growth take place at the solid interfaces during cycling, leading to the overall cell failure. To deconvolute these complex processes, in situ characterization is of paramount importance to elucidate the interfacial evolution on the SE upon Li plating/stripping. Herein, an all-solid-state asymmetric in situ cell is developed that allows the direct visualization of the highly localized Li plating/stripping processes under the optical microscope. Moreover, this cell configuration enables reliable post-mortem chemical and morphological analysis of the intact SE/Li interface. Using combined scanning electron microscopy and energy-dispersive X-ray spectroscopy, the study reveals that the evolution of the Li argyrodite interface is strongly influenced by the current density, particularly in terms of chemical distribution and Li plating morphology. More specifically, the solid interface is LiCl-rich with the formation of Li cubes at low current densities, while high currents result in more uniform elemental distribution and filament morphology. These findings elucidate the dynamic evolution mechanism at solid interfaces and offer valuable guidance for developing stable solid interfaces in all-solid-state Li metal batteries.

Huang, Di↗