Demonstration of a quantile system for compression of data from deep space probes
Statistical probability and sampled data method for compressing data from deep space probes
DATA COMPRESSOR↗
SEARCH · Engineering Papers
Results for “sampling methods”
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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Performing In Situ Closed-Cell Gas Reactions in the Transmission Electron Microscope
Gas reactions studied by in situ electron microscopy can be used to capture the real-time morphological and microchemical transformations of materials at length scales down to the atomic level. In situ closed-cell gas reaction (CCGR) studies performed using (scanning) transmission electron microscopy (STEM) can separate and identify localized dynamic reactions, which are extremely challenging to capture using other characterization techniques. For these experiments, we used a CCGR holder that utilizes microelectromechanical systems (MEMS)-based heating microchips (hereafter referred to as "E-chips"). The experimental protocol described here details the method for performing in situ gas reactions in dry and wet gases in an aberration-corrected STEM. This method finds relevance in many different materials systems, such as catalysis and high-temperature oxidation of structural materials at atmospheric pressure and in the presence of various gases with or without water vapor. Here, several sample preparation methods are described for various material form factors. During the reaction, mass spectra obtained with a residual gas analyzer (RGA) system with and without water vapor further validates gas exposure conditions during reactions. Integrating an RGA with an in situ CCGR-STEM system can, therefore, provide critical insight to correlate gas composition with the dynamic surface evolution of materials during reactions. In situ/operando studies using this approach allow for detailed investigation of the fundamental reaction mechanisms and kinetics that occur at specific environmental conditions (time, temperature, gas, pressure), in real-time, and at high spatial resolution.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
An Examination of the Space Weathering Patina of Lunar Rock 76015
Space weathering discussions have generally centered around soils but exposed rocks will also incur the effects of weathering. Rocks have much longer surface lifetimes than an individual soil grain and thus record a longer history of exposure. By studying the weathering products which have built up on a rock surface, we can gain a deeper perspective on the weathering process and better assess the relative importance of various weathering components. The weathered coating, or patina, of the lunar rock 76015 has been previously studied under SEM and also by TEM using ultramicrotome sample preparation methods. However, to really understand the products involved in creating these coatings, it is helpful to examine the patina in cross section, something which is now possible though the use of Focused Ion Beam (FIB) sample prep techniques, which allows us to preserve intact the delicate stratigraphy of the patina coating and provides a unique cross-sectional view of the space weathering process. Several samples have been prepared from the rock and the coatings are found to be quite variable in thickness and composition from one sample to the next.
Noble, S.↗
FMX – the Frontier Microfocusing Macromolecular Crystallography Beamline at the National Synchrotron Light Source II
Two new macromolecular crystallography (MX) beamlines at the National Synchrotron Light Source II, FMX and AMX, opened for general user operation in February 2017 [Schneider et al. (2013). J. Phys. Conf. Ser. 425 , 012003; Fuchs et al. (2014). J. Phys. Conf. Ser. 493 , 012021; Fuchs et al. (2016). AIP Conf. Proc. SRI2015 , 1741 , 030006]. FMX, the micro-focusing Frontier MX beamline in sector 17-ID-2 at NSLS-II, covers a 5–30 keV photon energy range and delivers a flux of 4.0 × 10 12 photons s −1 at 1 Å into a 1 µm × 1.5 µm to 10 µm × 10 µm (V × H) variable focus, expected to reach 5 × 10 12 photons s −1 at final storage-ring current. This flux density surpasses most MX beamlines by nearly two orders of magnitude. The high brightness and microbeam capability of FMX are focused on solving difficult crystallographic challenges. The beamline's flexible design supports a wide range of structure determination methods – serial crystallography on micrometre-sized crystals, raster optimization of diffraction from inhomogeneous crystals, high-resolution data collection from large-unit-cell crystals, room-temperature data collection for crystals that are difficult to freeze and for studying conformational dynamics, and fully automated data collection for sample-screening and ligand-binding studies. FMX's high dose rate reduces data collection times for applications like serial crystallography to minutes rather than hours. With associated sample lifetimes as short as a few milliseconds, new rapid sample-delivery methods have been implemented, such as an ultra-high-speed high-precision piezo scanner goniometer [Gao et al. (2018). J. Synchrotron Rad. 25 , 1362–1370], new microcrystal-optimized micromesh well sample holders [Guo et al. (2018). IUCrJ , 5 , 238–246] and highly viscous media injectors [Weierstall et al. (2014). Nat. Commun. 5 , 3309]. The new beamline pushes the frontier of synchrotron crystallography and enables users to determine structures from difficult-to-crystallize targets like membrane proteins, using previously intractable crystals of a few micrometres in size, and to obtain quality structures from irregular larger crystals.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Laser Diffraction Techniques Replace Sieving for Lunar Soil Particle Size Distribution Data
Sieving was used extensively until 1999 to determine the particle size distribution of lunar samples. This method is time-consuming, and requires more than a gram of material in order to obtain a result in which one may have confidence. This is demonstrated by the difference in geometric mean and median for samples measured by [1], in which a 14-gram sample produced a geometric mean of approx.52 micrometers, whereas two other samples of ~1.5 grams resulted in gave means of approx.63 and approx.69 micrometers. Sample allocations for sieving are typically much smaller than a gram, and many of the sample allocations received by our lab are 0.5 to 0.25 grams in mass. Basu [2] has described how the finest fraction of the soil is easily lost in the sieving process, and this effect is compounded when sample sizes are small.
Cooper, Bonnie L.↗
A structured framework for predicting sustainable aviation fuel properties using liquid-phase FTIR and machine learning
Sustainable aviation fuels have the potential to improve efficiency, reduce emissions, and enhance energy security. To help identify viable sustainable aviation fuels and accelerate research, machine learning models have been developed to predict relevant physicochemical properties. However, many models have limited applicability, leverage data from complex analytical techniques with confined spectral ranges, or use feature decomposition methods that offer limited interpretability. Using liquid-phase Fourier Transform Infrared (FTIR) spectra, this study presents a structured method for creating accurate and interpretable property prediction models for neat molecules, aviation fuels, and blends. Liquid FTIR spectra can be collected quickly and consistently, offering high reliability, sensitivity, and component specificity using less than 2 ml of sample. The method first decomposes FTIR spectra into fundamental building blocks using non-negative matrix factorization (NMF) to enable scientific analysis of FTIR spectra attributes and fuel properties. The NMF features are then used to create five ensemble models for predicting final boiling point, flash point, freezing point, density at 15°C, and kinematic viscosity at -20°C. All models were trained using experimental property data from neat molecules, aviation fuels, and blends. The models accurately predict key properties across a broad range of neat molecules and representative fuels and blends, while enabling interpretation of relationships between compositional elements, such as functional groups or chemical classes, and their resulting properties. This demonstrates strong potential to support sustainable aviation fuel research and development. The models and data are available on an interactive web tool.
Fourier transform infrared spectroscopy↗
Biased degenerate ground-state sampling of small Ising models with converged quantum approximate optimization algorithm
The quantum alternating operator ansatz, a generalization of the quantum approximate optimization algorithm (QAOA), is a quantum algorithm used for approximately solving combinatorial optimization problems. QAOA typically uses the transverse field mixer as the driving Hamiltonian. One of the interesting properties of the transverse field driving Hamiltonian is that it results in nonuniform sampling of degenerate ground states of optimization problems. In this study, we numerically examine the fair sampling properties of the transverse field mixer QAOA, and Grover mixer QAOA (GM-QAOA), which provides theoretical guarantees of fair sampling of degenerate optimal solutions, up to a large enough p such that the mean expectation value converges to an optimal approximation ratio of 1. This comparison is performed with high-quality heuristically computed, but not necessarily optimal, QAOA angles, which give strictly monotonically improving solution quality as p increases. These angles are computed using the Julia based numerical simulation software JuliQAOA. Fair sampling of degenerate ground states is quantified using the Shannon entropy of the ground-state amplitudes distribution. The fair sampling properties are reported on several quantum signature Hamiltonians from previous quantum annealing fair sampling studies. Small random fully connected spin glasses are shown, which exhibit exponential suppression of some degenerate ground states with transverse field mixer QAOA. The transverse field mixer QAOA simulations show that some problem instances clearly saturate the Shannon entropy of 0 with a maximally biased distribution that occurs when the learning converges to an approximation ratio of 1 while other problem instances never deviate from a maximum Shannon entropy (uniform distribution) at any p step. Published by the American Physical Society 2025
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Cross-linked polyvinyl alcohol films as alkaline battery separators
Cross-linking methods were investigated to determine their effect on the performance of polyvinyl alcohol (PVA) films as alkaline battery separators. The following types of cross-linked PVA films are discussed: (1) PVA-dialdehyde blends post-treated with an acid or acid periodate solution (two-step method) and (2) PVA-dialdehyde blends cross-linked during film formation (drying) by using a reagent with both aldehyde and acid functionality (one-step method). Laboratory samples of each cross-linked type of film were prepared and evaluated in standard separator screening tests. The pilot-plant batches of films were prepared and compared to measure differences due to the cross-linking method. The pilot-plant materials were then tested in nickel oxide - zinc cells to compare the two methods with respect to performance characteristics and cycle life. Cell test results are compared with those from tests with Celgard.
Sheibley, D. W.↗
Cross-linked polyvinyl alcohol films as alkaline battery separators
Cross-linking methods have been investigated to determine their effect on the performance of polyvinyl alcohol (PVA) films as alkaline battery separators. The following types of cross-linked PVA films are discussed: (1) PVA-dialdehyde blends post-treated with an acid or acid periodate solution (two-step method) and (2) PVA-dialdehyde blends cross-linked during film formation (drying) by using a reagent with both aldehyde and acid functionality (one-step method). Laboratory samples of each cross-linked type of film were prepared and evaluated in standard separator screening tests. Then pilot-plant batches of films were prepared and compared to measure differences due to the cross-linking method. The pilot-plant materials were then tested in nickel oxide-zinc cells to compare the two methods with respect to performance characteristics and cycle life. Cell test results are compared with those from tests with Celgard.
Sheibley, D. W.↗
Spectral Induced Polarization-Biogeochemical Relationships for Remediation Amendment Monitoring
Geophysical tools such as electrical resistivity (ER) can indirectly monitor subsurface changes in response to remedial injections. These methods exhibit relatively low spatial resolution compared to sediment core characterization but are advantageous due to the ability to collect measurements non-intrusively over time across large volumes of the subsurface. Moreover, along with confirmatory groundwater or core sampling, geophysical methods can be used during active biogeochemical remedies to monitor short-term contaminant transformations and mobility, as well as part of an overall strategy for long-term monitoring of subsurface contaminated sites. The use of alternating current spectral induced polarization (SIP) provides significantly more information than conventional geophysical methods like direct current ER. SIP allows for monitoring changes in both solution and surface conductivity by separation of real and imaginary conductivity, respectively, as well as surface capacitance. In principle, SIP can measure indicators of remedy progression such as precipitation reactions that sequester contaminants, potentially providing a better indication of amendment delivery and reactivity as compared to conventional ER methods. However, multiple processes and material properties have overlapping (interacting) electrical responses across a range of frequencies. Hence, the purpose of this scoping study was to evaluate if SIP can be used to monitor (a) amendment delivery and (b) precipitation and reactivity of amendments under consideration at Hanford. SIP measurements were collected in fully saturated columns packed with sand and Hanford formation sediments containing (a) amendments that were highly conductive with significant capacitance (zero valent iron – ZVI, sulfur modified iron – SMI) and (b) amendments that exhibited low electrical conductivity with a small capacitance (calcite, apatite, bismuth). The sand was a quartz material with homogenous particle size that exhibited a relatively low surface conductivity. It was used as a control for comparison with the sediments from the Hanford Site, which have a greater surface conductivity because of their complex mineralogy and heterogeneous particle size distribution and may have complex interactions with amendments. The amendment mass fraction was varied to represent the different stages and subsurface locations associated with the delivery of a remedy. The primary objective was to identify the solution and solid surface changes associated with the delivery amendments and their secondary reactions within the subsurface. The figure below summarizes results for the amendments tested through this project. The SIP phase shift or imaginary conductivity change for the high conductivity amendments was more than 10 times that of the low conductivity amendments, highlighting the relative ease of detection of ZVI and SMI independent of the background signal from sand or Hanford sediments. The ZVI phase shift and imaginary conductivity changes occur primarily at high frequency (> 100 Hz) whereas SMI changes were at low frequency (0.01 to 10 Hz). SIP signals of SMI also increased over time and the maximum shifted to lower frequencies. The low conductivity amendments (calcite, abiotic and biotic apatite, bismuth subnitrate) exhibited relatively small phase and imaginary conductivity changes when added to sediments. The changes were above minimum detection limits (0.5 mrad for phase shift, 0.03 µS/cm for imaginary conductivity) for the highest concentration except for the commercial bismuth material. The lowest amendment concentration that can be detected is likely sediment specific, as minerals in sediments (clays, magnetite, Fe-oxides) have some capacitance and, therefore, exhibit a variable phase shift.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
Identifying common stored product insects using automated deep learning methods
Monitoring stored product insect pests is a common practice for post-harvest management of stored grain and grain-based commodities, which helps ensure product quality from harvest to final consumer. Current methods of sampling and monitoring can be time-consuming, labor-intensive, expensive and require expertise in insect identification. Therefore, this study aims to develop an image-based automated identification system for common stored product insect species using deep-learning methods. Top-down images of the common stored product adult insect species of Rhyzopertha dominica, Cryptolestes ferrugineus, Tribolium castaneum, Sitophilus oryzae, and Oryzaephilus surinamensis were acquired and analyzed. Deep learning-based, state-of-the-art Convolutional Neural Networks (CNN) models (ResNet-50, MobileNet-v2, DarkNet-53, and EfficientNet-b0) were fine-tuned with a transfer learning approach to classify the insect species. All models were able to correctly identify the insect species with at least 96% accuracy and with few misclassifications. One issue with trained CNNs is that they do not explain the reasoning for the classification and are often called a “black box”. Therefore, visualization methods called Gradient-weighted Class Activation Mapping (Grad-CAM) were implemented to explore the black box network. The Grad-CAM uses heat maps to highlight the major image features that the network focused on to make insect species predictions. The Grad-CAM verifies the network's prediction and also helps improve network performance. This study contributes to the overall goal of developing a camera-based system for monitoring stored grain insects. As a result, the developed system would empower warehouse, flour mills, and other food facilities with a tool to quickly and accurately identify insect species in stored product environments and could be implemented as part of a close to real-time monitoring system.
60 APPLIED LIFE SCIENCES↗
Immiscible phase incorporation during directional solidification of hypermonotectics
Solidification processes in immiscible samples were investigated by directly observing the events taking place at the solid-liquid interface during directional solidification. Visualization of these events was made possible through the use of a transparent metal analog system and a temperature gradient stage assembly fitted to an optical microscope. The immiscible transparent analog system utilized was the succinonitrile-glycerol system. This system has been shown to exhibit the same morphological transitions as observed in metallic alloys of monotectic composition. Both monotectic and hypermonotectic composition samples were directionally solidified in order to gain an improved understanding of the manner in which the excess hypermonotectic liquid is incorporated into the solidifying structure. The processing conditions utilized prevented sedimentation of the excess hypermonotectic liquid by directionally solidifying the samples in very thin (13 microns), horizontally oriented cells. High thermal gradient to growth rate ratios (G/R) were used in an effort to prevent constitutional supercooling and the subsequent formation of L(sub 2) droplets in advance of the solidification front during the growth of fibrous composite structures. Results demonstrated that hypermonotectic composites could be produced in samples up to two weight percent off of the monotectic composition by using a G/R ratio greater than or equal to 4.6 x 10(exp 4) C(s)/mm(sup 2) to avoid constitutional supercooling. For hypermonotectic samples processed with G/R ratios below 4.6 x 10(exp 4) C(s)/mm(sup 2), constitutional supercooling occurred and resulted in slight interfacial instability. For these samples, two methods of incorporation of the hypermonotectic liquid were observed and are reported. The correlation between the phase spacing, lambda, and the growth rate, R, was examined and was found to obey a relationship generally associated with a diffusion controlled coupled growth process. For samples with compositions ranging from the monotectic composition up to 2 percent off of the monotectic composition, data indicated that the square of the phase spacing (lambda) varied linearly with the inverse of the growth rate (R).
Andrews, J. Barry↗
ISO 15859 Propellant and Fluid Specifications: A Review and Comparison with Military and NASA Specifications
This work presents an overview of the International Organization for Standardization (ISO) 15859 International Standard for Space Systems Fluid Characteristics, Sampling and Test Methods Parts 1 through 13 issued in June 2004. These standards establish requirements for fluid characteristics, sampling, and test methods for 13 fluids of concern to the propellant community and propellant characterization laboratories: oxygen, hydrogen, nitrogen, helium, nitrogen tetroxide, monomethylhydrazine, hydrazine, kerosene, argon, water, ammonia, carbon dioxide, and breathing air. A comparison of the fluid characteristics, sampling, and test methods required by the ISO standards to the current military and NASA specifications, which are in use at NASA facilities and elsewhere, is presented. Many ISO standards composition limits and other content agree with those found in the applicable parts of NASA SE-S-0073, NASA SSP 30573, military performance standards and details, and Compressed Gas Association (CGA) commodity specifications. The status of a current project managed at NASA Johnson Space Center White Sands Test Facility (WSTF) to rewrite these documents is discussed.
Greene, Ben↗
Dynamic Model Agnostic Reliability Evaluation of Machine-Learning Models Integrated in Instrumentation & Control Systems
In recent years, the field of data-driven neural network-based machine learning (ML) algorithms has grown significantly and spurred research in its applicability to instrumentation and control systems. While they are promising in operational contexts, the trustworthiness of such algorithms is not adequately assessed. Failures of ML-integrated systems are poorly understood; the lack of comprehensive risk modeling can degrade the trustworthiness of these systems. In recent reports by the National Institute for Standards and Technology, trustworthiness in ML is a critical barrier to adoption and will play a vital role in intelligent systems' safe and accountable operation. Thus, in this work, we demonstrate a real-time model-agnostic method to evaluate the relative reliability of ML predictions by incorporating out-of-distribution detection on the training dataset. It is well documented that ML algorithms excel at interpolation (or near-interpolation) tasks but significantly degrade at extrapolation. This occurs when new samples are "far" from training samples. The method, referred to as the Laplacian distributed decay for reliability (LADDR), determines the difference between the operational and training datasets, which is used to calculate a prediction's relative reliability. LADDR is demonstrated on a feedforward neural network-based model used to predict safety significant factors during different loss-of-flow transients. LADDR is intended as a "data supervisor" and determines the appropriateness of well-trained ML models in the context of operational conditions. Ultimately, LADDR illustrates how training data can be used as evidence to support the trustworthiness of ML predictions when utilized for conventional interpolation tasks.
97 MATHEMATICS AND COMPUTING↗
The Affect of the Space Environment on the Survival of Halorubrum Chaoviator and Synechococcus (Nageli): Data from the Space Experiment OSMO on EXPOSE-R
We have shown using ESA's Biopan facility flown in Earth orbit that when exposed to the space environment for 2 weeks the survival rate of Synechococcus (Nageli), a halophilic cyanobacterium isolated from the evaporitic gypsum-halite crusts that form along the marine intertidal, and Halorubrum chaoviator a member of the Halobacteriaceae isolated from an evaporitic NaCl crystal obtained from a salt evaporation pond, were higher than all other test organisms except Bacillus spores. These results led to the EXPOSE-R mission to extend and refine these experiments as part of the experimental package for the external platform space exposure facility on the ISS. The experiment was flown in February 2009 and the organisms were exposed to low-Earth orbit for nearly 2 years. Samples were either exposed to solar ultraviolet (UV)-radiation (lambda is greater than 110 nm or lambda is greater than 200 nm, cosmic radiation (dosage range 225-320 mGy), or kept in darkness shielded from solar UV-radiation. Half of each of the UV-radiation exposed samples and dark samples were exposed to space vacuum and half kept at 105 pascals in argon. Duplicate samples were kept in the laboratory to serve as unexposed controls. Ground simulation control experiments were also performed. After retrieval, organism viability was tested using Molecular Probes Live-Dead Bac-Lite stain and by their reproduction capability. Samples kept in the dark, but exposed to space vacuum had a 90 +/- 5% survival rate compared to the ground controls. Samples exposed to full UV-radiation for over a year were bleached and although results from Molecular Probes Live-Dead stain suggested approximately 10% survival, the data indicate that no survival was detected using cell growth and division using the most probable number method. Those samples exposed to attenuated UV-radiation exhibited limited survival. Results from of this study are relevant to understanding adaptation and evolution of life, the future of life beyond earth, the potential for interplanetary transfer of viable microbes via meteorites and dust particles as well as spacecraft, and the physiology of halophiles.
space flight↗
Metadata Entry Optimization for NASA's Biological Institutional Scientific Collection (NBISC)
The NASA Biological Institutional Sample Collection (NBISC) at NASA’s Ames Research Center is a critical resource housing non-human samples collected from spaceflight missions and ground analog studies, primarily consisting of specimens from rats, mice, and select microbes. The primary objective of NBISC is to systematically receive, document, preserve, and facilitate access to these samples for the global scientific community. NBISC promotes international collaboration and maximizes the return on investment for precious tissues from spaceflight and analog experiments. Researchers can request physical samples through an online request form and subsequent written proposal review process. This study addresses two core research objectives: streamlining the NBISC sample lifecycle processes and strategizing for managing an influx of 50,000 tissue samples from a series of cosmic radiation analog experiments carried out at the NASA Space Radiation Laboratory (NSRL) by Drs. Eleanor Chang (Lawrence Berkeley Laboratory) and Polly Blakely (SRI). The Chang/Blakely studies investigated Harderian gland (HG) tumorigenesis in mice exposed to low dose and LET radiation comprising 8 different exposure protocols in over 4000 mice. NBISC sample metadata is stored in a Laboratory Information Management System (SLIMS). To streamline sample data entry, we customize python scripts using information extracted from the individual experimental protocols. The scripts automate entry into multiple SLIMS data fields including protocol name, unique sample barcode, tissue and sub-tissue information, freezer location, sample preservation method, etc. The semi-automated procedure significantly decreases the time spent on data entry by several orders of magnitude. Automation and data organization are essential, as they free up time for curation and promotion of the collection which, in turn, increase the accessibility of samples to the broader research community. NBISC benefits from streamlined data ingestion, and the methodologies developed here are applicable to other projects which use SLIMS including the NASA Biospecimen Sharing Program and GeneLab. As of Fall 2023, plans include transferring sample data from SLIMS to public facing repositories (OSDR and NLSP), expanding the reach of the Chang/Blakely sample collection. The Human Research Program Space Radiation Element plans to transfer non-human tissues from many more investigations to NBISC in the coming year.
Sample Repository↗
Metadata Entry Optimization For NASA's Biological Institutional Scientific Collection (NBISC)
The NASA Biological Institutional Sample Collection (NBISC) at NASA’s Ames Research Center is a critical resource housing non-human samples collected from spaceflight missions and ground analog studies, primarily consisting of specimens from rats, mice, and select microbes. The primary objective of NBISC is to systematically receive, document, preserve, and facilitate access to these samples for the global scientific community. NBISC promotes international collaboration and maximizes the return on investment for precious tissues from spaceflight and analog experiments. Researchers can request physical samples through an online request form and subsequent written proposal review process. This study addresses two core research objectives: streamlining the NBISC sample lifecycle processes and strategizing for managing an influx of 50,000 tissue samples from a series of cosmic radiation analog experiments carried out at the NASA Space Radiation Laboratory (NSRL) by Drs. Eleanor Chang (Lawrence Berkeley Laboratory) and Polly Blakely (SRI). The Chang/Blakely studies investigated Harderian gland (HG) tumorigenesis in mice exposed to low dose and LET radiation comprising 8 different exposure protocols in over 4000 mice. NBISC sample metadata is stored in a Laboratory Information Management System (SLIMS). To streamline sample data entry, we customize python scripts using information extracted from the individual experimental protocols. The scripts automate entry into multiple SLIMS data fields including protocol name, unique sample barcode, tissue and sub-tissue information, freezer location, sample preservation method, etc. The semi-automated procedure significantly decreases the time spent on data entry by several orders of magnitude. Automation and data organization are essential, as they free up time for curation and promotion of the collection which, in turn, increase the accessibility of samples to the broader research community. NBISC benefits from streamlined data ingestion, and the methodologies developed here are applicable to other projects which use SLIMS including the NASA Biospecimen Sharing Program and GeneLab. As of Fall 2023, plans include transferring sample data from SLIMS to public facing repositories (OSDR and NLSP), expanding the reach of the Chang/Blakely sample collection. The Human Research Program Space Radiation Element plans to transfer non-human tissues from many more investigations to NBISC in the coming year.
Biospecimen↗
NSUF Report EBSD analyses on metallic fuel samples: Tips and improvements in sample preparation
EBSD (Electron Backscatter Diffraction) is an analytic technique used to evaluate the microstructure of a specimen. It can be used to evaluate interesting crystallographic data ranging from grains size to grain orientation, from grain boundaries to stresses. Moreover, in the field of nuclear materials EBSD can aid in estimating properties important for reactor performance, such as dislocation and residual strain [1]. EBSD patterns are generated by focusing a stationary electron gun on the specimen and detecting the backscatter electrons that satisfy Bragg conditions, and thus are diffracted by the crystal planes forming the so called Kikuchi bands. These bands correspond to each of the lattice diffracting crystal planes and are detected on a phosphor screen via a low-light CCD camera [2]. The patterns are generated within a small interaction volume located at a depth of less than 50-100 nm. Because of this, the data quality is extremely sensitive to the integrity of the crystallographic lattice order at the surface of the sample and thus to sample preparation and to oxidation [3]. While conventional sample preparation methods are widely used in materials science, they often do not lead to quality electron backscatter patterns needed for the characterization of nuclear materials [4]. This has been related by many authors to the challenges associated with handling radiological specimens, their rapid oxidation, and artifacts in such samples (e.g. high number of defects, precipitates and/or porosities) [4-8]. EBSD, however, can be an invaluable technique to evaluate microstructural evolution during fabrication and after irradiation at the required mesoscale for model and simulation. It also provides important information on grain structure necessary to understand irradiation effect, such as grain subdivision. Thus, it is of paramount importance to further the application of this technique to nuclear materials and especially irradiated fuels.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗