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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Three-dimensional (3D) analysis of white etching bands (WEBs) in AISI M50 bearing steel using automated serial sectioning

Dark etching regions (DER) and white etching bands (WEB) form in the subsurface stressed regions of bearing raceways and rolling elements. Also, “butterfly” formations form around non-metallic inclusions and large carbides. The formation of WEBs, DERs and butterfly are dependent on operating conditions, material alloying elements and heat treatment. The DER, WEB and butterfly formations are well studied in two dimensions (2D). The objective of this study was to analyze WEB formation in three dimensions (3D) that will allow better understanding of material transformation after stress cycling. Three rolling contact fatigue (RCF) tested vacuum induction melted vacuum arc re-melted (VIM-VAR) AISI M50 samples (from a bench test, sub-scale test and commercial gas turbine engine) were analyzed using automated serial sectioning to map WEB networks and a butterfly formation in 3D. Automated serial sectioning and 2D optical microstructural data for 3D reconstructions and analysis was done using a fully automated serial sectioning system – Robo-Met.3D®. 3D analysis was performed using Image-Pro Premier 3D. The data set allowed 3D visualization and analysis of the evolution and propagation of WEB and butterfly in M50 bearing steel, including the positive microscopic identification of a ceramic inclusion that was the source of a WEB.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Microstructural characterization of SiO2/Ni nanocomposites electrodeposited from a sulphate bath modified by PEI

Highlights: • SiO{sub 2}/Ni + PEI nanocomposites are deposited from the sulphate bath containing PEI. • PEI allows incorporation of higher SiO{sub 2} vol% in SiO{sub 2}/Ni + PEI nanocomposites. • PEI in the form of a thin layer surrounds spherical Ni nanograins and SiO{sub 2} clusters. • PEI action ensures high hardness, tribological properties and corrosion resistance. - Abstract: SiO{sub 2}/Ni nanocomposite coatings containing well-dispersed SiO{sub 2} nanoparticles were electrodeposited from a sulphate bath with and without the addition of polyethylenimine (PEI) as a cationic surfactant. The surface morphology and microstructure in the cross-sections of the deposited nanocomposites were examined by scanning electron microscopy. More detailed microstructure characterization was performed using transmission, scanning-transmission and high resolution transmission electron microscopy. It was determined that the addition of 0.05 g/L and 0.1 g/L of PEI allows the incorporation of SiO{sub 2} nanoparticles in the nickel matrix to be increased in comparison with the nanocomposite deposited without a surfactant. Based on high spatial resolution microanalysis, performed using high count rate energy dispersive spectroscopy of characteristic X-rays in the scanning-transmission mode, the distribution of SiO{sub 2} nanoparticles in the nanocomposite was visualized on elemental maps. Image analysis of the electron microscopy images enabled the mean equivalent circle diameters of grains in the nickel matrix to be determined, together with the volume fraction of SiO{sub 2} nanoparticles in the nanocomposites. The volume fraction of SiO{sub 2} clusters in the SiO{sub 2}/Ni + PEI nanocomposites with the addition of 0.05 g/L and 0.1 g/L of PEI is equal to 18.4% and 13.3%, respectively. Furthermore, the PEI addition allows the nickel grain size in the matrix to be reduced. The combination of different imaging techniques confirmed that PEI is not only present as a surfactant in the electrolytic bath, but also incorporates into the microstructure of the nanocomposite. Nanocomposites electrodeposited in the presence of 0.05 g/L of PEI exhibit higher hardness, good tribological properties and improved corrosion resistance. Although increasing the PEI concentration in the bath up to 0.1 g/L strongly promotes grain size reduction and increase of the SiO{sub 2} volume fraction, it also causes an increase in the PEI fraction embedded in the microstructure, which results in deterioration of the properties of the SiO{sub 2}/Ni + PEI nanocomposites.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Secondary carbides in high chromium cast irons: An alternative approach to their morphological and spatial distribution characterization

Highlights: • Systematic characterization of second phase particles by combining a variety of techniques • Comparison of morphological parameters obtained from SEM, BSE, etching+CLSM and EBSD • Quantitative analysis and degree of distribution of secondary carbides • Particle size, distribution and morphology from image analysis of CLSM, SEM and EBS images - Abstract: Secondary carbides precipitated in high chromium cast irons during thermal treatments were characterized by means of different characterization techniques, including scanning electron microscopy, energy dispersive X-ray spectroscopy, electron backscattered diffraction and a combination of chemical etching with confocal scanning laser microscopy. This set of techniques provides a full morphological, chemical and crystallographic description of the analysed phases. This work evaluated different methods for optimizing the image acquisition for a further image analysis (IA) based on the threshold binarization. Finally, the carbide size, distribution and morphology were determined after IA of the images acquired by aforementioned characterization techniques. Although the different techniques report some dispersion in the value for the average particle size, the particle inter-spacing and aspect ratio meet within the error value. The proposed characterization methodology provides statistically reliable data for a further evaluation of related physical properties in composites.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Crystal c-axis mapping of hcp metals by conventional reflected polarized light microscopy: Application to untextured and textured cp-Titanium

Highlights: • A computer-aided methodology based on reflected PLM was developed for c-axis orientation mapping of hcp structures. • The methodology was applied to two alpha cp-Ti bulk samples with different texture characteristics. • Calibration and validation of the methodology were performed by using EBSD. - Abstract: Nowadays the crystallographic characterization of polycrystalline metals and metallic alloys is usually performed by means of the electron backscatter diffraction (EBSD) technique. However, when dealing with coarse structures presenting intrinsic optical anisotropy, polarized light microscopy (PLM) imaging might be an alternative or a complementary time-efficient technique. Accordingly, a new computer-aided methodology has been developed in the present study and successfully applied on the crystal c-axis characterization of a hexagonal close-packed (hcp) structure, alpha commercial pure-Titanium (cp-Ti). In this sense, the correlation between EBSD-based crystallographic parameters and PLM-based parameters under certain light microscope settings has been first established by direct comparison using a representative amount of random orientations. Finally, PLM-based c-axis mapping and subsequent c-axis texture plotting have been performed and validated with EBSD for untextured and textured cp-Ti.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Synthesis, particle shape characterization, magnetic properties and surface modification of superparamagnetic iron oxide nanochains

We report monodisperse, chain-like particles (nanochains) consisted of silica-coated maghemite (γ-Fe2O3) nanoparticle clusters prepared by colloidal chemistry and magnetic field-induced self-assembly of nanoparticle clusters. In order to quantify the shapes of chain-like particles, we have used the measure for shape convexity which is also called solidity. We functionalize the surface of the nanochains with amino (–NH2) and carboxyl groups (–COOH) in order to modify surface charge. These surfaces of nanochains provide better colloidal stability and their potential for practical applications in biomedicine. The enhanced colloidal stability of the surface modified nanochains is confirmed by Zeta potential (ζ-potential) analysis. Magnetic properties of the nanochains show superparamagnetic state at room temperature since the nanochains are composed of tiny nanoparticles as their building blocks. The measured M(H) data at room temperature have been successfully fitted by the Langevin function and magnetic moment μp = 20,526 μB for sphere-like nanoparticle clusters and μp = 20,767 μB for nanochains are determined. The determined magnetic parameters have revealed that the nanochains show a magnetic moment of the nanoparticles higher than the one of individual nanoparticle clusters. These differences can be attributed to the collective magnetic properties of superparamagnetic iron oxide nanoparticles (SPION) assembled in different morphologies (isotropic and anisotropic morphology). © 2018.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Sol-gel synthesis of Mn1.5Co1.5O4 spinel nano powders for coating applications

Highlights: • Nano powder of Mn/Co spinel, applicable to solid oxide fuel cell, is synthesized. • The sol-gel synthesis of nanocrystalline Mn{sub 1.5}Co{sub 1.5}O{sub 4} spinel is investigated. • Sol-gel annealing temperature, time, and metal-to-citrate ratio are evaluated. • The optimum conditions for producing dual phase of Mn{sub 1.5}Co{sub 1.5}O{sub 4} are achieved. - Abstract: Mn{sub 1.5}Co{sub 1.5}O{sub 4} oxide spinels are widely used as protective coatings for stainless steel interconnects within planar solid oxide fuel cell stacks. Containing both cubic and tetragonal crystalline phases, these Mn/Co oxide spinels exhibit favorable thermal stability and electronic conductivity for the SOFC interconnect application. Slurry-based coating applications of Mn/Co oxides require precursor powders, which can benefit from being nano-structured. In this study, the sol-gel synthesis of nanocrystalline Mn{sub 1.5}Co{sub 1.5}O{sub 4} spinel is investigated. The decomposition of sol-gel precursors, as well as the crystalline phase structures and microstructures of the product Mn{sub 1.5}Co{sub 1.5}O{sub 4} are characterized by differential thermal and thermogravimetric (DTA/TG) analysis, X-ray diffraction (XRD), and transmission electron microscopy (TEM). The effects of various sol-gel annealing temperatures (T), treatment times (t), and citrate-to-metal ratios (Rc) are evaluated. Results suggest that nanocrystalline Mn{sub 1.5}Co{sub 1.5}O{sub 4} spinel can be synthesized around 1050 °C, and that T = 1050 °C, t = 6 h and Rc = 2 are optimum conditions for producing the smallest grain size. Image analysis of TEM results shows that the size of Mn{sub 1.5}Co{sub 1.5}O{sub 4} crystallites increases with increasing temperature, with average particle sizes ranging from ∼70 nm to ∼1 μm. Selected area diffraction pattern (SADP) of Mn{sub 1.5}Co{sub 1.5}O{sub 4} spinel synthesized at 800 °C confirms the dual (cubic/tetragonal) structure of Mn{sub 1.5}Co{sub 1.5}O{sub 4}.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2017

Achieving high spatial resolution using a microchannel plate detector with an economic and scalable approach

We report a second generation position-sensitive microchannel plate detector using the induced signal approach has been realized. This detector is presently capable of measuring the incident position of electrons, photons, or ions. To assess the spatial resolution, the masked detector was illuminated by electrons. The initial, measured spatial resolution of 276 μm FWHM was improved by requiring a minimum signal amplitude on the anode and by employing digital signal processing techniques. The resulting measured spatial resolution of 119 μm FWHM corresponds to an intrinsic resolution of 98 μm FWHM when the effect of the finite slit width is de-convoluted. This measurement is a substantial improvement from the last reported spatial resolution of 466 μm FWHM using the induced signal approach. To understand the factors that limit the measured resolution, the performance of the detector is simulated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Automatic recognition system for document digitization in nuclear power plants

With the increasing number of data-driven models in nuclear applications, large volumes of numerical data are required to accurately model and predict the health status of a plant component. However, many historical operation logs that contain useful information are not fully utilized due to the lack of a systematic approach of digitization. To overcome this issue, this study proposes an automatic pipeline for extracting information from handwritten tabular documents collected from nuclear power plants. In our pipeline, we first denoise scanned documents with morphological operations, and then extract relevant parts from individual pages using both traditional computer vision and neural network methods. Handwriting recognition is applied to obtain text and numbers. As the most challenging step is how to crop only relevant information, the main focus of our paper is to detect tables and cells from scanned handwritten documents. Here we evaluate the efficiency and accuracy of our proposed method on handwritten operational reports obtained from a real-world case study. The results demonstrate the high accuracy and practicality of our proposed method.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Correlating results from high resolution EBSD with TEM- and ECCI-based dislocation microscopy: Approaching single dislocation sensitivity via noise reduction

High resolution electron backscatter diffraction (HREBSD), an SEM-based diffraction technique, may be used to measure the lattice distortion of a crystalline material and to infer the geometrically necessary dislocation content. Uncertainty in the image correlation process used to compare diffraction patterns leads to an uneven distribution of measurement noise in terms of the lattice distortion, which results in erroneous identification of dislocation type and density. This work presents a method of reducing noise in HREBSD dislocation measurements by removing the effect of the most problematic components of the measured distortion. The method is then validated by comparing with TEM analysis of dislocation pile-ups near a twin boundary in austenitic stainless steel and with ECCI analysis near a nano-indentation on a tantalum oligocrystal. Finally, the HREBSD dislocation microscopy technique is able to resolve individual dislocations visible in TEM and ECCI and correctly identify their Burgers vectors.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Revealing latent pole and zone line information in atom probe detector maps using crystallographically correlated metrics

Poles and zone lines observed within atom probe field evaporation images are useful for a range of atom probe crystallography studies, including calibration of the reconstruction and crystallographic characterisation of microstructural features such as grain boundaries. However, this information is not always readily apparent. Techniques for plotting crystallographically correlated metrics contained within atom probe data to enhance pole and zone line contrast across the detector space are developed. This includes consideration of the electric field, molecular ions, lattice structure retained within the reconstruction, specific elemental species, the number of pulses between detection events, and the lateral distance between sequential detection events. These approaches are then applied to experimental atom probe tomography datasets on technically pure Al, nanocrystalline Al, highly doped Si, and additively manufactured Inconel 738, Haynes 282, and Ti–6Al–4V. The results facilitate the extension of atom probe crystallography studies to a broader range of crystalline datasets where crystallographic information is not readily apparent from existing methods, as well as a deeper understanding of field evaporation behaviour during an atom probe experiment.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Quantitative Imaging of Cobalt Phthalocyanine Distribution on Carbon Nanotubes: A Deep Learning Approach to Catalyst Characterization

Electrochemical reduction of carbon dioxide (CO 2 ) offers a pathway to valuable products, with catalysts playing a crucial role. This study investigates the distribution of cobalt tetraaminophthalocyanine (CoPc-NH 2 ) immobilized on carbon nanotubes (CNTs), utilizing high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) to characterize CoPc-NH 2 distribution. A challenge in the quantitative HAADF-STEM analysis is the introduction of bias from manual Co atom identification. To address this, we developed and trained a convolutional neural network (CNN) using a data set generated from images of CoPc-NH 2 /CNT samples with varying Co loadings. The CNN, implemented in TensorFlow and Keras, facilitated Co atom detections. Analysis of the CNN-generated data confirmed a correlation between Co loading and surface density, consistent with findings from UV–vis spectroscopy. Furthermore, the application of Ripley’s L(d) function highlighted the presence of slight Co atom clustering. Furthermore, this work demonstrates the utility of the combined HAADF-STEM and CNN approach for providing spatially resolved information about catalyst distribution on nonplanar supports, revealing structural details that are typically lost through other characterization methods.

HAADF-STEM↗
DOE OSTI2018

Electron-Beam-Induced Synthesis of Hexagonal 1 H -MoSe 2 from Square β-FeSe Decorated with Mo Adatoms

Two-dimensional (2D) materials have generated interest in the scientific community because of the advanced electronic applications they might offer. Powerful electron beam microscopes have been used not only to evaluate the structures of these materials but also to manipulate them by forming vacancies, nanofragments, and nanowires or joining nanoislands together. In this work, we show that the electron beam in a scanning transmission electron microscope (STEM) can be used in yet another way: to mediate the synthesis of 2D 1H-MoSe 2 from Mo-decorated 2D β-FeSe and simultaneously image the process on the atomic scale. This is quite remarkable given the different crystal structures of the reactant (square lattice β-FeSe) and the product (hexagonal lattice 1H-MoSe 2 ). Herein, the feasibility of the transformation was first explored by theoretical calculations that predicted that the reaction is exothermic. Furthermore, a theoretical reaction path to forming a stable 1H-MoSe 2 nucleation kernel within pure β-FeSe was found, demonstrating that the pertinent energy barriers are smaller than the energy supplied by the STEM electron beam.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2019

Dynamic imaging of crystalline defects in lithium-manganese oxide electrodes during electrochemical activation to high voltage

Crystalline defects are commonly generated in lithium-metal-oxide electrodes during cycling of lithium-ion batteries. Their role in electrochemical reactions is not yet fully understood because, until recently, there has not been an effective operando technique to image dynamic processes at the atomic level. In this study, two types of defects were monitored dynamically during delithiation and concomitant oxidation of oxygen ions by using in situ high-resolution transmission electron microscopy supported by density functional theory calculations. One stacking fault with a fault vector b/6[110] and low mobility contributes minimally to oxygen release from the structure. In contrast, dissociated dislocations with Burgers vector of c/2[001] have high gliding and transverse mobility; they lead to the formation, transport and release subsequently of oxygen related species at the surface of the electrode particles. This work advances the scientific understanding of how oxygen participates and the structural response during the activation process at high potentials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Enabling reactive microscopy with MicroMator

Microscopy image analysis has recently made enormous progress both in terms of accuracy and speed thanks to machine learning methods and improved computational resources. This greatly facilitates the online adaptation of microscopy experimental plans using real-time information of the observed systems and their environments. Applications in which reactiveness is needed are multifarious. Here we report MicroMator, an open and flexible software for defining and driving reactive microscopy experiments. It provides a Python software environment and an extensible set of modules that greatly facilitate the definition of events with triggers and effects interacting with the experiment. We provide a pedagogic example performing dynamic adaptation of fluorescence illumination on bacteria, and demonstrate MicroMator’s potential via two challenging case studies in yeast to single-cell control and single-cell recombination, both requiring real-time tracking and light targeting at the single-cell level.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Demonstration of an AI-driven workflow for autonomous high-resolution scanning microscopy

Abstract Modern scanning microscopes can image materials with up to sub-atomic spatial and sub-picosecond time resolutions, but these capabilities come with large volumes of data, which can be difficult to store and analyze. We report the Fast Autonomous Scanning Toolkit (FAST) that addresses this challenge by combining a neural network, route optimization, and efficient hardware controls to enable a self-driving experiment that actively identifies and measures a sparse but representative data subset in lieu of the full dataset. FAST requires no prior information about the sample, is computationally efficient, and uses generic hardware controls with minimal experiment-specific wrapping. We test FAST in simulations and a dark-field X-ray microscopy experiment of a WSe 2 film. Our studies show that a FAST scan of <25% is sufficient to accurately image and analyze the sample. FAST is easy to adapt for any scanning microscope; its broad adoption will empower general multi-level studies of materials evolution with respect to time, temperature, or other parameters.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Deep generative learning of magnetic frustration in artificial spin ice from magnetic force microscopy images

Increasingly large datasets of microscopic images with nanoscale resolution facilitate the development of machine learning methods to identify and analyze subtle physical phenomena embedded within the images. In this work, microscopic images of honeycomb lattice spin-ice samples serve as datasets from which we automate the calculation of net magnetic moments and directional orientations of spin-ice configurations. In the first stage of our workflow, machine learning models are trained to accurately predict magnetic moments and directions within spin-ice structures. Variational Autoencoders (VAEs), an emergent unsupervised deep learning technique, are employed to generate high-quality synthetic magnetic force microscopy (MFM) images and extract latent feature representations, thereby reducing experimental and segmentation errors. The second stage of proposed methodology enables precise identification and prediction of frustrated vertices and nanomagnetic segments, effectively correlating structural and functional aspects of microscopic images. This facilitates the design of optimized spin-ice configurations with controlled frustration patterns, enabling potential on-demand synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Improving resolution and resolvability of single-particle cryoEM structures using Gaussian mixture models

Cryogenic electron microscopy is widely used in structural biology, but its resolution is often limited by the dynamics of the macromolecule. Here, we developed a refinement protocol based on Gaussian mixture models that integrates particle orientation and conformation estimation, and improves the alignment for flexible domains of protein structures. We demonstrated this protocol on multiple datasets, resulting in improved resolution and resolvability, locally and globally, by visual and quantitative measures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Rapid alignment of nanotomography data using joint iterative reconstruction and reprojection

As x-ray and electron tomography is pushed farther into the nanoscale, the limitations of rotation stages become more apparent leading to challenges in the alignment of the acquired projection images. Here we present an approach for rapid post-acquisition alignment of these projections to obtain high quality 3D images. Our approach is based on a joint estimation of alignment errors, and the object, using an iterative refinement procedure. We characterize convergence in simulations, and show its application in x-ray and electron nanotomography.

47 OTHER INSTRUMENTATION↗