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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 955 records · Page 53

Plasma-enhanced chemical vapor deposition of multiwalled carbon nanofibers

Plasma-enhanced chemical vapor deposition is used to grow vertically aligned multiwalled carbon nanofibers (MWNFs). The graphite basal planes in these nanofibers are not parallel as in nanotubes; instead they exhibit a small angle resembling a stacked cone arrangement. A parametric study with varying process parameters such as growth temperature, feedstock composition, and substrate power has been conducted, and these parameters are found to influence the growth rate, diameter, and morphology. The well-aligned MWNFs are suitable for fabricating electrode systems in sensor and device development.

Nanotechnology/instrumentation/methods↗

Scanning Electron Microscopy Investigation of a Sample Depth Profile Through the Martian Meteorite Nakhla

The ongoing scientific debate as to whether or not the Martian meteorite ALH84001 contained evidence of possible biogenic activities showed the need to establish consistent methods to ascertain the origin of such evidence. To distinguish between terrestrial organic material/microbial contaminants and possible indigenous microbiota within meteorites is therefore crucial. With this in mind a depth profile consisting of four samples from a new sample allocation of Martian meteorite Nakhla was investigated using scanning electron microscopy (SEM) and energy dispersive X-ray analysis. SEM imaging of freshly broken fractured chips revealed structures strongly recent terrestrial microorganisms, in some cases showing evidence of active growth. This conclusion was supported by EDX analysis, which showed the presence of carbon associated with these structures, we concluded that these structures represent recent terrestrial contaminants rather than structures indigenous to the meteorite. Page

Toporski, Jan↗

Aerosol Sampling Experiment on the International Space Station

The International Space Station (ISS) is a unique indoor environment which serves as both home and workplace to the astronaut crew. There is currently no particulate monitoring, although particulate matter requirements exist. An experiment to collect particles in the ISS cabin was conducted recently. Two different aerosol samplers were used for redundancy and to collect particles in two size ranges spanning from 10 nm to hundreds of micrometers. The Active Sampler is a battery operated thermophoretic sampler with an internal pump which draws in air and collects particles directly on a transmission electron microscope grid. This commercial-off-the-shelf device was modified for operation in low gravity. The Passive Sampler has five sampling surfaces which were exposed to air for different durations in order to collect at least one sample with an optimal quantity of particles for microscopy. These samples were returned to Earth for analysis with a variety of techniques to obtain long-term average concentrations and identify particle emission sources. Results are compared with the inventory of ISS aerosols which was created based on sparse data and the literature. The goal of the experiment is to obtain data on indoor aerosols on ISS for future particulate monitor design and development.

Aerosol↗

Investigation of Bipropellant Plume-Induced Contamination Effects on Coverglass Materials

Contamination and degradation of external spacecraft materials by unburned and partially combusted species from bipropellant thruster plumes has long been observed as a key component of the induced space environment. Space shuttle flight experiments and returned flight hardware from the International Space Station (ISS) have both experienced microscopic impact features induced by high-velocity thruster plume droplets. Analytical results have shown that droplet impingement angle relative to a receiving surface plays a key role in the surface damage. Although impacts with normal impingement angles contribute more severely to surface degradation than highly oblique angles, surface effects at higher impingement angles should not be dismissed. Thruster plume-induced materials degradation is a complex phenomenon that depends on a variety of parameters, including but not limited to material type, system temperature and pressure, plume composition, and thruster firing specifications such as number of pulses, pulse duration, and sample distance from the thruster. For space applications, attaining the vacuum pressure and temperature conditions necessary for flight-like plume expansion and exposure conditions is not a trivial task. The German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt, DLR) is a facility uniquely capable of simulating such conditions. Test coupons were exposed to bipropellant thruster firings under high vacuum at the DLR facility. Percent area coverage (PAC) and droplet size distributions were evaluated for the uncoated and coated solar array coverglass materials over a range of impingement angles (0̊ to 75̊). A post-test imaging workflow was developed that aimed to quantify changes in sample surface morphology obtained from scanning electron microscopy (SEM) images using the Image Processing and Analysis in Java (ImageJ) tool; an opensource image processing software. The goal was to create a framework through which to evaluate the effect of bipropellant-induced PAC and droplet size distribution on solar array coverglass optical transmission losses. Understanding this relationship is important because optical transmission losses are known to lead to current reduction in solar power generation systems. In addition to the development of surface characterization workflows, valuable lessons learned as they pertain to future investigations and experiments will be discussed. The authors hope that sharing these lessons will facilitate more utilization of DLR’s unique capabilities as well as open the conversation for how best to address experimental characterization of flight-like plume expansion and its impacts on materials surface degradation effects.

Gateway↗

Isothermal oxidation of zirconium using steam

Oxidation of zirconium and its alloys under any atmosphere is generally characterised by a protective and non-protective stage. During the protective stage, the kinetics of oxidation are quasi-parabolic, while the oxide scale formed on the surface of the metal is black, compact, and protective in nature. For the non-protective stage, the oxidation rate becomes linear, while the protective oxide film turns into a deteriorated white scale. Breakaway is known as the transition point from protective to non-protective stage. The actual mechanism leading to breakaway of zirconium is still a matter of controversy, however some of the most common factors affecting breakaway are the following: - Impurities on the metal (Carbon, Oxygen, Nitrogen); - Oxidizing atmosphere (Presence of H{sub 2}O (g) or N{sub 2} (g)); - Sample preparation (Chemically etched or polished); - Temperature (LWR, LOCA). This research investigates the effect of temperature on 'breakaway' when zirconium is oxidized isothermally in steam for 60 min at 800 and 900 deg. C using thermogravimetric and optical microscopic imaging techniques. 1. Steam isothermal oxidations were performed on zirconium at 800 and 900 deg. C using a Thermogravimetric Analyzer (TGA). 2. Log-log plots of mass gain vs time were obtained from thermogravimetric results to calculate the reaction orders (n) and reaction rate constants (K) during oxidation. 3. Results of the kinetics of reaction were correlated with optical microscopic images form Light Microscope (LM) and Scanning Electron Microscope (SEM). Breakaway depends very strongly on temperature. At 800 deg. C, the weight gain followed a cubic-parabolic behaviour with evidence of a protective oxide film. On the other hand, oxidation at 900 deg. C showed signs of breakaway since the oxide film was cracked and oxidation rate was almost linear throughout the reaction.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Thermal Conductivity Degradation in High Burnup U-Pu-Zr Fuel

Recent advancements in the characterization of irradiated U-Pu-Zr fuels have revealed complexities that challenge existing understanding of constituent redistribution. Traditionally, models have proposed three concentric regions within the fuel, each characterized by distinctive phases and porosity. However, through detailed analysis of high burnup U-Pu-Zr, we discovered the presence of four distinct constituent redistribution regions. Particularly novel is the observation of significant Pu redistribution, a previously unreported phenomenon that necessitates a reevaluation of current models. This work aims to delve deeper into these findings, seeking to correlate mesoscale measurements of thermal diffusivity and respective thermal conductivity with the phases present in each redistribution region. To achieve this objective, we employed mesoscale thermoreflectance methods using the unique, Idaho National Laboratory (INL) developed, Thermal Conductivity Microscope (TCM) at INL’s Irradiated Materials Characterization Laboratory. The TCM employs two tightly focused lasers: one for heating to generate periodic thermal waves in the substrate, and another spatially separated probe laser to detect changes in the optical reflectivity of the gold-coated substrate resulting from thermal wave diffusion. We conducted several thermal diffusivity measurements within each region of constituent redistribution of a U-19Pu-10Zr fuel pin cross section irradiated to 11 at. % burnup. The TCM measurement positions strategically aligned with transmission electron microscopy (TEM) lift-out locations previously collected from the fuel sample. Complementary microstructural analysis techniques such as optical and scanning electron microscopy (OM/SEM), electron probe microanalysis for chemical compositions, and TEM-based selective area electron diffraction (SAED) analysis for crystallographic insights into each phase were also utilized. This comprehensive approach allowed us to correlate local thermal diffusivity data with microstructural characteristics, enabling the computation of local thermal conductivity at each position. The significance of this contribution lies in its pioneering use of the TCM for ternary fuel mesoscale examination, shedding light on the previously overlooked effects of Pu redistribution on local thermal conductivity. By informing current models capturing constituent redistribution and heat transfer, our findings pave the way for more accurate predictions of metallic fuel performance. Moreover, this work sets the stage for future comparisons with similar TCM examinations on U-19Pu-10Zr fuels at ultra-low burnup, facilitating a comprehensive understanding of thermal property changes across different burnup levels. Ultimately, our study not only enriches our understanding of the thermophysical properties of individual redistribution regions within U-Pu-Zr fuel but also offers valuable insights for the design and operational parameters of proposed next-generation fast reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Upscaling X-ray nanoimaging to macroscopic specimens

Upscaling X-ray nanoimaging to macroscopic specimens has the potential for providing insights across multiple length scales, but its feasibility has long been an open question. By combining the imaging requirements and existing proof-of-principle examples in large-specimen preparation, data acquisition and reconstruction algorithms, the authors provide imaging time estimates for howX-ray nanoimaging can be scaled to macroscopic specimens. To arrive at this estimate, a phase contrast imaging model that includes plural scattering effects is used to calculate the required exposure and corresponding radiation dose. The coherent X-ray flux anticipated from upcoming diffraction-limited light sources is then considered. This imaging time estimation is in particular applied to the case of the connectomes of whole mouse brains. To image the connectome of the whole mouse brain, electron microscopy connectomics might require years, whereas optimized X-ray microscopy connectomics could reduce this to one week. Furthermore, this analysis points to challenges that need to be overcome (such as increased X-ray detector frame rate) and opportunities that advances in artificial-intelligence-based `smart' scanning might provide. While the technical advances required are daunting, it is shown that X-ray microscopy is indeed potentially applicable to nanoimaging of millimetre- or even centimetre-size specimens.

97 MATHEMATICS AND COMPUTING↗

A comparative analysis of YOLOv8 and U-Net image segmentation approaches for transmission electron micrographs of polycrystalline thin films

Metallic thin films offer a platform to experimentally study the dynamics of microstructural evolution, but the required transmission electron microscopy (TEM)-based imaging generates complex images that are challenging to segment and quantify. This work provides a comparative analysis of a new YOLOv8 model and an established U-Net model for bright-field TEM images of polycrystals, employing a framework leveraging physical observables to evaluate performance against two hand-traced benchmark datasets. This methodology obviates the comparison of large, diversely structured, and manually labeled datasets that are required to assess performance on a per-image/per-pixel basis. It is found that the YOLOv8 model, adapted for real-time instance segmentation, has up to 43× faster inferencing (NVIDIA GeForce RTX 4090) compared to U-Net and reconstructs hand-traced grain size distributions (GSDs) with excellent fidelity, finding mean diameter within 3% for grains near an optimal magnification; for grains that deviate from the optimal pixel-diameter, the size of small- (large)-diameter grains is systematically over- (under)-estimated. This is partially mitigated by including scale-aware augmentations during training. Moreover, when the bias is corrected post-inference by a rigid shift in distribution, the YOLOv8 model reproduces ground truth GSDs with exceptional fidelity, with statistical tests indicating <5% probability that the distributions are distinct. Based on ground truth data, calibration curves pertaining to this shift can be constructed for a given model. This issue is not present in the U-Net model’s results, indicating that for quantitative measurements where the true size of objects is of interest, special procedures must be implemented for YOLO-based models.

36 MATERIALS SCIENCE↗

Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials: Part II Resveratrol Exemplar

This SAND report summarizes work supported by an Engineering Sciences Research Foundation (ESRF) Lab Directed Research and Development (LDRD) project entitled “Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials.” This SAND report is written in two parts with Part 1 discusses recrystallization of our explosive exemplar and Part 2 summarizing our work with recrystallization of resveratrol. We have studied resveratrol recrystallization with a multiscale approach combining experiments, modeling and simulation. At the single crystal scale, microscopy experiments illuminate crystal time-dependent growth rates using advanced image analysis. Bench scale experiments were carried out to look at growth of multiple particles in a small reactor creating thousands of particles and analyzing the results with microscopy and μCT. For the modeling we combine kinetic Monte Carlo (kMC) models with subscale information from density functional theory (DFT) or molecular dynamics. This work is discussed in Part 1 and can also be found in a paper from the project discussing a coarse-grained kMC model specifically developed for resveratrol. For well-mixed systems, we have population balance equations (PBE) linked with species mass conservation forming a set of ordinary differential equations that can be solved quickly. For more complicated geometries, such as the vat crystallization used throughout the complex, a coupled computational fluid dynamic (CFD)/PBE method was developed to account for gradients in temperature and concentration and differences in crystallization rates throughout the domain. These simulations are more complex and require high performance computing. We present results for two cases: 5% seed fast cool with parameters fit to the well-mixed case and 5% seed slow cool using the same parameters. We show reasonable agreement with experiments though are particles are significantly larger than the experiments.

36 MATERIALS SCIENCE↗

Investigating Carboxysome Morphology Dynamics with a Rotationally Invariant Variational Autoencoder

Carboxysomes are a class of bacterial microcompartments that form proteinaceous organelles within the cytoplasm of cyanobacteria and play a central role in photosynthetic metabolism by defining a cellular microenvironment permissive to CO2 fixation. Critical aspects of the assembly of the carboxysomes remain relatively unknown, especially with regard to the dynamics of this microcompartment. Progress in understanding carboxysome dynamics is impeded in part because analysis of the subtle changes in carboxysome morphology with microscopy remains a low-throughput and subjective process. Here we use deep learning techniques, specifically a Rotationally Invariant Variational Autoencoder (rVAE), to analyze fluorescence microscopy images of cyanobacteria bearing a carboxysome reporter and quantitatively evaluate how carboxysome shell remodelling impacts subtle trends in the morphology of the microcompartment over time. Toward this goal, we use a recently developed tool to control endogenous protein levels, including carboxysomal components, in the model cyanobacterium Synechococcous elongatus PCC 7942. By utilization of this system, proteins that compose the carboxysome can be tuned in real time as a method to examine carboxysome dynamics. We find that rVAEs are able to assist in the quantitative evaluation of changes in carboxysome numbers, shape, and size over time. Further, we propose that rVAEs may be a useful tool to accelerate the analysis of carboxysome assembly and dynamics in response to genetic or environmental perturbation and may be more generally useful to probe regulatory processes involving a broader array of bacterial microcompartments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Exploring the mobility of Cu in bimetallic nanocrystals to promote atomic-scale transformations under a reactive gas environment

Bimetallic nanocrystals (NCs) often show improved catalytic activities compared to their monometallic counterparts, but to optimize the performance it is crucial to understand how they behave under actual reaction conditions, i.e. in gas environments. Here, in this study, we use powder X-ray diffraction (PXRD), total scattering (TS) with pair distribution function (PDF) analysis and in situ high-resolution transmission electron microscopy (HR-TEM) to provide new insights into the atomic-scale behaviour of NC catalysts under a reactive gas environment. By investigating Au, Cu, Pd, PdCu, AuPd and AuCu NCs, we observe that the properties of bimetallic NCs differ significantly from their monometallic counterparts. While metal oxide phases formed for monometallic Pd and Cu under O 2 -exposure, bimetallic PdCu and AuCu NCs showed loss of metallic Cu in the crystalline phases after exposure to O 2 . However, upon introducing the bimetallic NCs to a reducing atmosphere, the Cu was found to reappear and reincorporate into a crystalline phase, forming the initial bimetallic structures. By combining TS, PDF analysis and in situ HR-TEM, we saw that Cu segregates to the NC surfaces or forms small CuO domains under O 2 -exposure. Our results thus indicate that the Cu mobility promotes segregation and formation of CuO along with the formation of a monometallic phase, which ultimately changes the resulting active surface sites of the nanocatalyst. Understanding the dynamical structure–property relations of nanocatalysts is key to enable rational design of efficient and robust catalysts for controlled catalytic reactions.

36 MATERIALS SCIENCE↗

Oxide derived Cu nanofibril assembly for enhanced nonenzymatic glucose sensing

In this report, we have prepared copper nanofibril assembly via thermal oxidation followed by electrochemical reduction processes, exhibiting superior glucose detection ability. The morphological analysis evidenced the formation of rough islands or nanofibril structure on the Cu surface depending on initial thermal oxidation temperature. The glucose detection performance was investigated by performing cyclic voltammetry and chronoamperometry with varying glucose concentration. A high sensitivity (4131.57 μA mM – 1 cm – 2 ), low detection limit (1.41 μM), wider linear range (0–3.9 mM) and long–term stability (30 days) have been recorded for electrode thermally oxidized at 400 °C followed by electrochemical reduction process (rCu_400). The sensitivity is almost three times higher in comparison to the planner Cu surface. This significantly enhanced glucose sensing ability rCu_400 has been attributed to the nanofibril morphology, origination of Cu (111) facet and formation of a stable oxide layer evidenced by scanning electron microscopy, X-ray diffraction and energy dispersive spectroscopy analysis. Despite higher sensitivity, rCu_400 electrode does not show any response to the chloride ion, dopamine, ascorbic acid and uric acid. Finally, these results indicate that the Cu nanofibril structure prepared via simple oxidation/reduction process can be an excellent candidate to be used as an electrode for glucose sensing application.

36 MATERIALS SCIENCE↗

Quantitative analysis of three-dimensional fatigue crack path selection in Mg alloy WE43 using high-energy X-ray diffraction microscopy

Fatigue short-cracks in Mg alloys display complex growth behavior due to high plastic anisotropy and crack path dependence on local microstructural features. In this study, the three-dimensional crystallography of short-crack paths in Mg alloy WE43 was characterized by mapping near-field high-energy X-ray diffraction microscopy (HEDM) reconstructed grain maps to high-resolution X-ray CT reconstructions of the fracture surfaces in the crack initiation and short-crack growth regions of six ultrasonic fatigue specimens. Crack–grain–boundary intersections were analyzed at 81 locations across the six crack paths. The basal intragranular, non-basal intragranular, or intergranular character of short-crack growth following each boundary intersection was correlated to crystallographic and geometric parameters of the trailing and leading grains, three-dimensional grain boundary plane, and advancing crack front. The results indicate that crack paths are dependent on the combined crystallographic and geometric character of the local microstructure, and crack path prediction can be improved by use of dimensionality reduction on subsets of high-linear-correlation microstructural parameters.

36 MATERIALS SCIENCE↗

Exploring Physics of Ferroelectric Domain Walls in Real Time: Deep Learning Enabled Scanning Probe Microscopy

The functionality of ferroelastic domain walls in ferroelectric materials is explored in real-time via the in situ implementation of computer vision algorithms in scanning probe microscopy (SPM) experiment. The robust deep convolutional neural network (DCNN) is implemented based on a deep residual learning framework (Res) and holistically nested edge detection (Hed), and ensembled to minimize the out-of-distribution drift effects. The DCNN is implemented for real-time operations on SPM, converting the data stream into the semantically segmented image of domain walls and the corresponding uncertainty. Further the pre-defined experimental workflows perform piezoresponse spectroscopy measurement on thus discovered domain walls, and alternating high- and low-polarization dynamic (out-of-plane) ferroelastic domain walls in a PbTiO 3 (PTO) thin film and high polarization dynamic (out-of-plane) at short ferroelastic walls (compared with long ferroelastic walls) in a lead zirconate titanate (PZT) thin film is reported. This work establishes the framework for real-time DCNN analysis of data streams in scanning probe and other microscopies and highlights the role of out-of-distribution effects and strategies to ameliorate them in real time analytics.

36 MATERIALS SCIENCE↗

Automated Bacterial Identification and Morphological Feature Analysis in Low‐Dose Cryo‐EM Using YOLOv11

Bacteria rapidly adapt to environmental cues through morphological and ultrastructural changes that correlate with physiology and behavior. Cryogenic transmission electron microscopy (cryo‐TEM) can capture these phenotypic changes in near‐native, vitrified states, but manual analysis of low‐dose micrographs is labor intensive and limits throughput. Here, we present an end‐to‐end workflow that combines low‐dose cryo‐TEM imaging with a YOLOv11‐based instance‐segmentation model to automatically identify bacteria and quantify key structural features directly from the micrographs. This workflow enables (i) robust bacterial localization and counting from low‐magnification atlas/montage images, (ii) automated measurements of cell‐envelope (outer–inner membrane) thickness and anisotropy from higher‐magnification views, and (iii) detection and quantification of bacteria–flagella interactions, including overlap length and curvature metrics for interacting versus noninteracting flagella. Using Pantoea sp. YR343 grown under distinct media conditions, we show that the automated measurements agree with manual annotations while substantially reducing analysis time. Together, these tools provide a practical framework for scalable bacterial identification and quantitative phenotyping in low‐dose cryo‐TEM datasets and establish a foundation for extending cryo‐TEM image analysis toward higher‐throughput studies of microbial heterogeneity and biointerfaces.

YOLOv11↗

Quantitative Particle Analysis of Neptunium-237 Oxides: Optimization of MAMA Analysis for Modified Direct Denitration Products

The production of plutonium-238 through irradiation of neptunium-237 ( 237 Np) target materials for the use in radioisotope thermoelectric generators is paramount for continued deep space exploration. This work employs scanning electron microscopy to analyze 237 Np materials coupled with a well-developed image analysis framework (Morphological Analysis for Material Attribution, or MAMA) to determine the degree of micron-scale homogeneity in the materials. This work demonstrated how the quantification of particle characteristics can validate production materials and affirm the qualitative similarities observed in micrographs. The 237 Np oxide particle analysis determined that the materials from five production runs were quantitatively homogenous (significant at α = 0.05) in particle area, circularity, equivalent circular diameter, and ellipse aspect ratio, with two of the sampling dates having statistically significant different means for one of the four characteristics. Furthermore, these metrics not only confirm general homogeneity of the material but also expand the application of MAMA workflows to 237 Np materials, demonstrating the utility of MAMA analysis for a wider breadth of nuclear materials than previously reported. In the open literature, this study is the first time that these microanalytical techniques were applied to 237 Np materials to this degree.

MAMA↗

Combinatorial Cu-Ni Alloy Thin-Film Catalysts for Layer Number Control in Chemical Vapor-Deposited Graphene

We synthesized a combinatorial library of CuxNi1−x alloy thin films via co-sputtering from Cu and Ni targets to catalyze graphene chemical vapor deposition. The alloy morphology, composition, and microstructure were characterized via scanning electron microscopy (SEM), energy dispersive x-ray spectroscopy (EDS), and X-ray diffraction (XRD), respectively. Subsequently, the CuxNi1−x alloy thin films were used to grow graphene in a CH4-Ar-H2 ambient at atmospheric pressure. The underlying rationale is to adjust the CuxNi1−x composition to control the graphene. Energy dispersive x-ray spectroscopy (EDS) analysis revealed that a continuous gradient of CuxNi1−x (25 at. % < x < 83 at.%) was initially achieved across the 100 mm diameter substrate (~0.9%/mm composition gradient). The XRD spectra confirmed a solid solution was realized and the face-centered cubic lattice parameter varied from ~3.52 to 3.58 A˙, consistent with the measured composition gradient, assuming Vegard’s law. Optical microscopy and Raman analysis of the graphene layers suggest single layer growth occurs with x > 69 at.%, bilayer growth dominates from 48 at.% < x < 69 at.%, and multilayer (≥3) growth occurs for x < 48 at.%, where x is the Cu concentration. Finally, a large area of bi-layer graphene was grown via a CuxNi1−x catalyst with optimized catalyst composition and growth temperature.

2D materials↗