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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Mineral and organic matrix interaction in normally calcifying tendon visualized in three dimensions by high-voltage electron microscopic tomography and graphic image reconstruction

To define the ultrastructural accommodation of mineral crystals by collagen fibrils and other organic matrix components during vertebrate calcification, electron microscopic 3-D reconstructions were generated from the normally mineralizing leg tendons from the domestic turkey, Meleagris gallopavo. Embedded specimens containing initial collagen mineralizing sites were cut into 0.5-micron-thick sections and viewed and photographed at 1.0 MV in the Albany AEI-EM7 high-voltage electron microscope. Tomographic 3-D reconstructions were computed from a 2 degree tilt series of micrographs taken over a minimum angular range of +/- 60 degrees. Reconstructions of longitudinal tendon profiles confirm the presence of irregularly shaped mineral platelets, whose crystallographic c-axes are oriented generally parallel to one another and directed along the collagen long axes. The reconstructions also corroborate observations of a variable crystal length (up to 170 nm measured along crystallographic c-axes), the presence of crystals initially in either the hole or overlap zones of collagen, and crystal growth in the c-axis direction beyond these zones into adjacent overlap and other hole regions. Tomography shows for the first time that crystal width varies (30-45 nm) but crystal thickness is uniform (approximately 4-6 nm at the resolution limit of tomography); more crystals are located in the collagen hole zones than in the overlap regions at the earliest stages of tendon mineralization; the crystallographic c-axes of the platelets lie within +/- 15-20 degrees of one another rather than being perfectly parallel; adjacent platelets are spatially separated by a minimum of 4.2 +/- 1.0 nm; crystals apparently fuse in coplanar alignment to form larger platelets; development of crystals in width occurs to dimensions beyond single collagen hole zones; and a thin envelope of organic origin may be present along or just beneath the surfaces of individual mineral platelets. Implicit in the results is that the formation of crystals occurs at different sites and times by independent nucleation events in local regions of collagen. These data provide the first direct visual evidence from 3-D imaging describing the size, shape, orientation, and growth of mineral crystals in association with collagen of a normally mineralizing vertebrate tissue. They support concepts that c-axial crystal growth is unhindered by collage hole zone dimensions, that crystals are organized in the tendon in a series of generally parallel platelets, and that crystal growth in width across collagen fibrils may follow channels or grooves formed by adjacent hole zones in register.

Non-NASA Center↗
NASA NTRS1976

Studies of noble-metal thermocouple stability at high temperatures

Two investigatory studies on performance characteristics of noble-metal thermocouples are described. (1) thermoelectric stability as affected by preferential oxidation of iridium in the system iridium-40% rhodium versus iridium, and (2) the effects of temperature gradients on the emf stability of the systems platinum-13% rhodium versus platinum and iridium-40% rhodium versus iridium, operating in air. The stability investigation was carried out at three temperatures - 1700, 1850, and 2000 C - by comparing the output of the test thermocouple in air with the output of an identically constructed reference thermocouple in nitrogen. The results show that no calibration shift was observed producing a change in output greater than that corresponding to a 2.0% change in the indicated temperature for all samples tested. The investigation of gradient effects was carried out by subjecting test thermocouples to both severe and mild gradients for periods up to 200 hours. For the platinum system, the operating temperature was 1500 C with gradients of 1475 and 700 C/cm; for the iridium system, 2000 C with gradients of 700, 1500, and 1975 C/cm. Exposure to temperature gradients was found to introduce significant changes in calibration for both systems. In both investigations, the thermoelements were examined by means of electron-probe analysis and by metallographic methods to detect chemical and structural changes. Data and micrographs are presented.

Freeze, P.↗
NASA NTRS1995

3-D Reconstruction of Macular Type II Cell Innervation Patterns in Space-Flight and Control Rats

A semiautomated method for reconstructing objects from serial thin sections has been developed in the Biocomputation Center. The method is being used to completely, for the first time, type II hair cells and their innervations. The purposes are to learn more about the fundamental circuitry of the macula on Earth and to determine whether changes in connectivities occur under space flight conditions. Data captured directly from a transmission electron microscope via a video camera are sent to a graphics workstation. There, the digitized micrographs are mosaicked into sections and contours are traced, registered and displayed by semiautomated methods. Current reconstructions are of type II cells from the medial part of rat maculas collected in-flight on the Space Life Sciences-2 mission, 4.5 hrs post-flight, and from a ground control. Results show that typical type II cells receive processes from tip to six nearby calyces or afferents. Nearly all processes are elongated and have bouton-like enlargements; some have numerous vesicles. Multiple (2 to 4) processes from a single calyx to a type II cell are common, and approximately 1/3 of the processes innervale 2 or 3 type II cells or a neighboring cluster. From 2% to 6% of the cells resemble type I cells morphologically but have demi-calyces. Thus far, increments in synaptic number in type II cells of flight rats are prominent along processes that supply two hair cells. It is clear that reconstruction methods provide insights into details of macular circuitry not obtainable by other techniques. The results demonstrate a morphological basis for interactions between adjacent receptive fields through feed back-feed forward connections, and for dynamic alterations in receptive field range and activity during preprocessing of linear acceleratory information by the maculas. The reconstruction method we have developed will find further applications in the study of the details of neuronal architecture of more complex systems, to seek out shared organizational properties or neuronal networks and to understand better localization of synaptic changes in altered environments.

Ross, Muriel Dorothy↗
DOE OSTI2023

Application of a deep learning semantic segmentation model to helium bubbles and voids in nuclear materials

Imaging nanoscale radiation-induced defects using the transmission electron microscope (TEM) is a key factor in the successful implementation of materials for nuclear energy structural applications. Analyzing each defect in a TEM micrograph is currently a manual task. To identify the defects in a single image can take anywhere from 15 min to an hour and a project can require the analysis of anywhere from tens to ≥ 100 images. Here, we use artificial intelligence (AI) models to automate this task. For simplification, we evaluated images with only a single type of defect; helium bubbles. Additionally, we performed semantic segmentation of these helium bubble defects in electron microscopy images of irradiated FeCrAl alloys using a deep learning DefectSegNet model. This model, which was previously used to classify crystal defects, is inspired by the classic DenseNet and U-Net image segmentation models. It claims high spatial resolution, but has poor performance at object boundaries. Our paper improves the DefectSegNet model’s application by adding two new features. First, the DefectSegNet model is applied not only to perform calculation pixel-wise but also object (or feature) wise. Because object-wise metrics are directly relevant to our final goal of detecting bubbles, whereas pixel-wise classification is only an intermediate step, it is an important part of our study. Second, a distance map loss (DML) function has been added to increase its performance at object boundaries. It is crucial to accurately represent defects boundaries, especially bubbles, in order to track the bubble-induced swelling caused by irradiation. The boundary-focused DML function is also compared to other loss functions like Cross-entropy, Weighted Binary Cross Entropy (WBCE), Dice and Intersection over Union (IOU). Finally, by incorporating new features, we found a marked improvement on segmentation quality and better shape preservation at the boundaries and areas of the bubbles.

42 ENGINEERING↗
NASA NTRS1998

Analysis of Phase Separation in Czochralski Grown Single Crystal Ilmenite

Ilmenite (FeTiOs) is a wide bandgap semiconductor with an energy gap of 2.58 eV. Ilmenite has properties suited for radiation tolerant applications, as well as a variety of other electronic applications. Single crystal ilmenite has been grown from the melt using the Czochralski method. Growth conditions have a profound effect on the microstructure of the samples. Here we present data from a variety of analytical techniques which indicate that some grown crystals exhibit distinct phase separation during growth. This phase separation is apparent for both post-growth annealed and unannealed samples. Under optical microscopy, there appear two distinct areas forming a matrix with an array of dots on order of 5 pm diameter. While appearing bright in the optical micrograph, atomic force microscope (AFM) shows the dots to be shallow pits on the surface. Magnetic force microscope (MFM) shows the dots to be magnetic. Phase identification via electron microprobe analysis (EMPA) indicates two major phases in the unannealed samples and four in the annealed samples, where the dots appear to be almost pure iron. This is consistent with micrographs taken with a scanning probe microscope used in the magnetic force mode. Samples that do not exhibit the phase separation have little or no discernible magnetic structure detectable by the MFM.

Wilkins, R.↗
DOE OSTI2026

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↗
DOE OSTI2024

Deep learning-enabled probing of irradiation-induced defects in time-series micrographs

Modeling time-series data with convolutional neural networks (CNNs) requires building a model to learn in batches as opposed to training sequentially. Coupling CNNs with in situ or operando techniques opens the possibility of accurately segmenting dynamic reactions and mass transport phenomena to understand how materials behave under the conditions in which they are used. In this article, in situ ion irradiation transmission electron microscopy (TEM) images are used as inputs into the CNN to assess the defect generation rate, defect cluster density, and saturation of defects. We then use the output segmentation maps to correlate with conventional TEM micrographs to assess the model’s ability to detail nanoscale interactions. Next, we discuss the implications of preprocessing and hyperparameters on model variability, accuracy when expanded to other datasets, and the role of regularization when controlling model variance. Ultimately, we eliminate human bias when extrapolating physical metrics, speed up analysis time, decouple reactions that happen at 100 ms intervals, and deploy models that are both accurate and transferable to similar experiments.

Burns, Kory (ORCID:0000000158019909)↗
NASA NTRS1977

Airborne particle monitoring by electrostatic precipitation

For qualitative analysis of atmospheric particulates by microscopy, the sampling device should preserve the particles in the state existing at the moment of capture. A collector is described that uses electrostatic precipitation to capture and disperse specimens on various substrates for direct insertion into microscopes. Sampling runs in various atmospheres are described. Micrographs are presented to show particle morphology and distribution on the substrates. Chemical identification by X-ray energy probe and electron diffraction is illustrated.

Robinson, J. C.↗
DOE OSTI2025

Quantifying dislocation-type defects in post irradiation examination via transfer learning

The quantitative analysis of dislocation-type defects in irradiated materials is critical to materials characterization in the nuclear energy industry. The conventional approach of an instrument scientist manually identifying any dislocation defects is both time-consuming and subjective, thereby potentially introducing inconsistencies in the quantification. This work approaches dislocation-type defect identification and segmentation using a standard open-source computer vision model, YOLO11, that leverages transfer learning to create a highly effective dislocation defect quantification tool while using only a minimal number of annotated micrographs for training. This model demonstrates the ability to segment both dislocation lines and loops concurrently in micrographs with high pixel noise levels and on two alloys not represented in the training set. Inference of dislocation defects using transmission electron microscopy on three different irradiated alloys relevant to the nuclear energy industry are examined in this work with widely varying pixel noise levels and with completely unrelated composition and dislocation formations for practical post irradiation examination analysis. Code and models are available at https://github.com/idaholab/PANDA.

36 MATERIALS SCIENCE↗
NASA NTRS1982

Evaluation of electrode shape and nondestructive evaluation method for welded solar cell interconnects

Resistance welds of solar cell interconnect tabs were evaluated. Both copper-silver and silver-silver welds were made with various heat inputs and weld durations. Parallel gap and annular gap weld electrode designs were used. The welds were analyzed by light microscope, electron microprobe and scanning laser acoustic microscope. These analyses showed the size and shape of the weld, the relationship between the acoustic micrographs, the visible electrode footprint, and the effect of electrode misalignment. The effect of weld heat input on weld microstructure was also shown.

Baraona, C. R.↗
NASA NTRS1977

Process sharpens micrographic images

Photomicrographs produced by bright field illumination of surface coated with carbon deposited by ion glow discharge, are considerably sharper and reveal more detail than those made without coating or produced by scanning electron microscopy.

Eaton, A. F.↗
NASA NTRSDate not supplied

Development and Application of Weld Track Thermal Analysis for the Exploration Extravehicular Mobility Unit

NASA is studying the next generation of space suit for safe operations in space, from the International Space Station to the lunar surface as part of the Exploration Extravehicular Mobility Unit project. The backplate structure of the portable life support system (PLSS) serves as the attachment point for assembly of the PLSS and contains embedded cooling channels. The thermal loop plumbing assembly and backplate are combined into a single component such that the fluid lines run through the midplane of the backplate. The manufacturing of the Ti-6Al-4V backplate consists of machining channels into a plate, welding cover plates on each channel using an electron beam, and additional machining for excess material removal and final detail. Careful control of the electron beam weld process is necessary to completely seal cover plates, produce consistent weld tracks, and produce channels with uniform cross sections free of debris and defects. The backplate contains multiple weld channels with unique geometries. The weld process parameters include choosing the beam current and focus, accelerating voltage, travel speed, pause times between weld tracks, and sequence of weld tracks. A transient finite element thermal analysis was developed to provide support for choosing and controlling the weld process parameters to maintain a consistent melt pool along each of the weld tracks. A moving distributed heat source is modeled to represent the heat input generated by the electron beam. The heat source model is a critical input to the analysis for accurate temperature predictions during the weld process. A modified conical heat source was developed to account for the change in working distance between the backplate and cover plates. The geometry of the material being welded must be accounted for by the heat source model to define the correct energy input. The weld process control is designed according to the predicted thermal history and melt pool dimensions for each of the weld channels. The analysis model, modified heat source, temperature and melt pool predictions, application of the thermal data to the weld parameters, and comparison with micrograph cross-sections from weld trials will be discussed in this presentation.

Electron Beam Welding↗
NASA NTRS1988

Growth and characterization of large YBa2Cu3O(7-x) single crystals

Centimeter-sized crystal plates of YBa2Cu3O(7-x) have been obtained using a bulk composition and method described by Schneemeyer at al. (1987) modified for growth in a pure oxygen atmosphere. A porous MgO crucible and long soak time promote large crystals. Mg was not detectable in the crystals. Electron microbeam analysis using a 60 A monochromator crystal for the oxygen determination gave the composition Y(1.05)Ba(2.02)Cu(2.94)O(6.52 + or - 0.06). As-grown crystals from the melt surface exhibit a fairly sharp Tc with zero resistance at 80 K, and show complex twinning and crack patterns. Optical micrographs of a lightly polished surface normal to the c-axis of a 3-mm crystal delineate twinning and fine scale microcracking; this crystal surface now has a zero resistance at 68 K. Microhardness measurements and microfracture observations indicate intrinsic properties that may inhibit or impede large scale manufacture of electronic ceramics.

Keester, Kenneth L.↗
DOE OSTI2022

Investigation of deformation mechanisms in an advanced FeCrAl alloy using in-situ SEM-EBSD testing

The deformation mechanisms associated with uniaxial tensile testing are observed by conducting tensile experiments of an FeCrAl alloy using scanning electron microscopy (SEM) coupled with electron backscattered diffraction (EBSD). Prior to the deformation, investigated alloy was consisting grain and precipitate size of ~63.0 μm and ~6.7 μm, respectively. The recorded SEM micrographs and EBSD data at increasing levels of strains revealed the complex phenomena of slip bands’ formation in the presence of surface grain morphology evolution and their (001), (110) and (111) crystallographic planes distortions. The grains with orientation (110)||tensile direction (TD) shows higher shape change; however, (001)||TD and (111)||TD oriented grains show higher lattice gradient formation. Extracted information from the EBSD indicates that the crystallographic rotations drive towards specific, fiber-like texture in relation to the loading direction. Postmortem analysis of the recorded microstructure during the tensile deformation explains the phenomena of crack formation in the hard-intermetallic particles before the ultimate tensile strength (UTS). However, after the UTS, pores were identified in the neck that resulted from extensive plastic deformation. In-depth analysis was carried out to identify the cause of cracks and pores formation phenomena during the tensile test.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Formation and optical properties of indium nanoparticle arrays for deep-UV plasmonics

We utilize a combined computational-experimental approach to examine the influence of indium nanoparticle (NP) array distributions on deep-ultraviolet (UV) plasmon resonances. For photon energies < 5.7 eV, analysis of ellipsometric spectra reveals an increase in silicon reflectance induced by indium NP arrays on silicon. For various energies in the range 5.7–7.0 eV, a decrease in reflectance is induced by the NP arrays. Similar trends in reflectance are predicted from finite-difference time-domain (FDTD) simulations using NP size distributions extracted from atomic-force micrographs as input. In addition, in the energy range of 7.4–9.2 eV, the FDTD simulations reveal reflectance minima, characteristic of localized surface plasmon resonances. Here, electron energy-loss spectroscopy collected from individual indium NPs reveals the presence of LSPR at ≈ 8 eV, further supporting the promise of indium NP arrays on silicon for deep-UV plasmonics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Dataset for Leveraging CryoEM and AI-Driven Morphological Feature Analysis for Insights on Bacterial Structures

This repository hosts an AI-assisted image segmentation and analysis pipeline for Pantoea sp. YR343 cryo-electron microscopy (cryoEM) datasets. The workflow automates membrane thickness measurements, flagella detection, and field-of-view (FOV) screening from low-dose, high-resolution cryoEM micrographs eliminating the need for slow manual annotation. By integrating deep-learning based segmentation (YOLOv11) with quantitative post-processing, this toolkit provides a scalable and reproducible way to study bacterial morphology under hydrated, near-native conditions. The GitHub repository for AI-based tools for cryoEM bacteria ultrastructures can be found here: https://github.com/Sireesiru/Cryo-EM-Ultrastructures/tree/main

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Machine-learning-based, online estimation of ceramic’s microstructure upon the laser spot brightness during laser sintering

The ceramic microstructure strongly influences its properties. During manufacturing, the online monitoring of microstructure is critical to ensure the desired material properties. So far, the microstructure on the relevant scale is usually characterized offline using scanning electron microscopy (SEM), which is time and cost-consuming. In this work, we demonstrate a cost-effective, machine learning (ML)-based approach to simulate the SEM micrographs in real-time from the laser spot brightness. We experimentally observed a strong correlation between the laser spot brightness and the corresponding microstructure at the exact locations. The brightness values obtained from thermal emission images and the corresponding SEM micrographs were used in the training datasets. The ML algorithm was a style-based conditional generative adversarial network (CGAN). After training, the ML model could generate high-fidelity microstructure images within 0.1 seconds based on in-situ captured brightness at the laser sintering spot. We used the average grain sizes as the metric to evaluate the accuracy of the ML-predicted micrographs. Here, the ML-predicted microstructures were in good agreement, with less than 5% in difference from the real SEM images. In conclusion, we demonstrate the cost-effective, online microstructure estimation during laser sintering with a simple setup (a camera, a regular computer, and the ML model).

08 HYDROGEN↗
DOE OSTI2023

A deep learning model for automatic analysis of cavities in irradiated materials

Transmission electron microscopy (TEM) is a commonly used technique in materials science for defect investigation. Quantitative analysis of defects is important for understanding the properties of a material, but manual analysis of TEM micrographs can be time-consuming and prone to error, especially when the defects have irregular shapes rather than spherical shapes. Many existing methods or deep learning models do not handle a wide range of sizes for the same object type within a single image. In this work, we present a framework that enables users to train an instance segmentation model called Mask R- CNN on any microstructure dataset, perform multi-detection on the same image at different scales, and obtain properties (e.g., size, area) of the objects based on the desired shape (e.g., circle, ellipse, rectangle). Additionally, we have developed a parallel detection module that uses multiple GPUs to increase the efficiency of the object detection process. We demonstrate the capabilities of our framework using a set of TEM images of cavities with different shapes, size distributions, and background contrasts. Finally, we show that the performance of our model in terms of density, size, and swelling of the cavities is comparable to the human average and that our model achieves the highest recall value compared to existing methods due to the use of image multi-rescaling.

36 MATERIALS SCIENCE↗