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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Photoabsorption Imaging at Nanometer Scales Using Secondary Electron Analysis

Optical imaging with nanometer resolution offers fundamental insights into light–matter interactions. Traditional optical techniques are diffraction limited with a spatial resolution >100 nm. Optical super-resolution and cathodoluminescence techniques have higher spatial resolutions, but these approaches require the sample to fluoresce, which many materials lack. Here, we introduce photoabsorption microscopy using electron analysis, which involves spectrally specific photoabsorption that is locally probed using a scanning electron microscope, whereby a photoabsorption-induced surface photovoltage modulates the secondary electron emission. We demonstrate spectrally specific photoabsorption imaging with sub-20 nm spatial resolution using silicon, germanium, and gold nanoparticles. Theoretical analysis and Monte Carlo simulations are used to explain the basic trends of the photoabsorption-induced secondary electron signal. Based on our current experiments and this analysis, we expect that the spatial resolution can be further improved to a few nanometers, thereby offering a general approach for nanometer-scale optical spectroscopic imaging and material characterization.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2019

Wide-Bandgap Electronics Analysis

Electrical energy constitutes 40% of total primary energy consumption in the United States, and this is only expected to increase with broad adoption of electric vehicles and the proliferation of renewables. Building on its existing wide-bandgap (WBG) R&D and analysis activities, researchers at the National Renewable Energy Laboratory (NREL) are investigating new power electronic technologies based on WBG semiconductors, which are essential for advanced electrical energy generation, transmission, storage, and use. This work supports efforts by the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy's Advanced Manufacturing Office (AMO) to identify solutions to address the increase in electrical energy consumption through the development of more efficient power electronic devices.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Open Reproducible Electron Microscopy Data Analysis

Electron microscopy (EM) is a cornerstone technique in the materials and biological sciences capable of imaging structures at nano- to atomic-scale resolution. Advances in technologies mean that one acquires datasets at increasing data rates and sizes. These advancements present enormous opportunities for researchers to understand complex systems. However, processing the resulting large-scale, complex data in a reproducible and shareable way is a real challenge for researchers. The building, managing, and maintaining complex workflows in a reproducible manner requires extensive knowledge in several areas outside the researchers’ core skill sets, such as software engineering, data science, and high-performance computing (HPC). Our work demonstrates an innovative approach to solving these problems, enabling reproducible EM data analysis through container encapsulated pipelines. Using modern container technologies, we encapsulate processing elements and connect them using shared memory. We expose user-friendly, advanced algorithms and tools to allow end users to utilize without expert programming skills. The platform enables reproducible, scalable, shareable pipelines for the analysis and visualization of EM data. Focusing on interoperability, we leverage the DOE and other agencies’ existing investments to provide a powerful software platform for EM data analysis.

Harris, Christopher↗
DOE OSTI2018

Automated defect analysis in electron microscopic images

Electron microscopy and defect analysis are a cornerstone of materials science, as they offer detailed insights on the microstructure and performance of a wide range of materials and material systems. Building a robust and flexible platform for automated defect recognition and classification in electron microscopy will result in the completion of analysis orders of magnitude faster after images are recorded, or even online during image acquisition. Automated analysis has the potential to be significantly more efficient, accurate, and repeatable than human analysis, and it can scale with the increasingly important methods of automated data generation. Herein, an automated recognition tool is developed based on a computer vison–based approach; it sequentially applies a cascade object detector, convolutional neural network, and local image analysis methods. We demonstrate that the automated tool performs as well as or better than manual human detection in terms of recall and precision and achieves quantitative image/defect analysis metrics close to the human average. The proposed approach works for images of varying contrast, brightness, and magnification. Furthermore, these promising results suggest that this and similar approaches are worth exploring for detecting multiple defect types and have the potential to locate, classify, and measure quantitative features for a range of defect types, materials, and electron microscopic techniques.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

X-ray Emission Spectroscopy at X-ray Free Electron Lasers: Limits to Observation of the Classical Spectroscopic Response for Electronic Structure Analysis

X-ray free electron lasers (XFELs) provide ultrashort intense X-ray pulses suitable to probe electron dynamics but can also induce a multitude of nonlinear excitation processes. These affect spectroscopic measurements and interpretation, particularly for upcoming brighter XFELs. Here we identify and discuss the limits to observing classical spectroscopy, where only one photon is absorbed per atom for a Mn 2+ in a light element (O, C, H) environment. X-ray emission spectroscopy (XES) with different incident photon energies, pulse intensities, and pulse durations is presented. A rate equation model based on sequential ionization and relaxation events is used to calculate populations of multiply ionized states during a single pulse and to explain the observed X-ray induced spectral lines shifts. Furthermore this model provides easy estimation of spectral shifts, which is essential for experimental designs at XFELs and illustrates that shorter X-ray pulses will not overcome sequential ionization but can reduce electron cascade effects.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Combining variational autoencoders and physical bias for improved microscopy data analysis *

Electron and scanning probe microscopy produce vast amounts of data in the form of images or hyperspectral data, such as electron energy loss spectroscopy or 4D scanning transmission electron microscope, that contain information on a wide range of structural, physical, and chemical properties of materials. To extract valuable insights from these data, it is crucial to identify physically separate regions in the data, such as phases, ferroic variants, and boundaries between them. In order to derive an easily interpretable feature analysis, combining with well-defined boundaries in a principled and unsupervised manner, here we present a physics augmented machine learning method which combines the capability of variational autoencoders to disentangle factors of variability within the data and the physics driven loss function that seeks to minimize the total length of the discontinuities in images corresponding to latent representations. Our method is applied to various materials, including NiO-LSMO, BiFeO 3 , and graphene. The results demonstrate the effectiveness of our approach in extracting meaningful information from large volumes of imaging data. The customized codes of the required functions and classes to develop phyVAE is available at https://github.com/arpanbiswas52/phy-VAE.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Investigation into Texture and Structure of MA2-1PCh Magnesium Alloy after Equal Channel Angular Extrusion and Annealing by Quantitative X-Ray Texture Analysis and Electron Backscatter Diffraction

This article discusses application of quantitative X-ray texture analysis (QTXA) based on measurement of direct pole figures and electron backscatter diffraction (EBSD) aimed at study of peculiarities of formation of texture and structure of MA2-1pch magnesium alloy after equal channel angular extrusion (ECAE) and subsequent annealing. Shear bands with the width of 60 μm oriented at 45°–50° to the extrusion direction are revealed, where an inclined scattered basis texture is detected, and outside of these bands, a prismatic texture. As a consequence, basic sliding is activated in the shear bands, which is confirmed by the distribution of Schmid factors. The influence of texture and orientation of shear bands on anisotropy of strength mechanical properties of alloy is discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multi defect detection and analysis of electron microscopy images with deep learning

Electron microscopy is widely used to explore defects in crystal structures, but human detecting of defects is often time-consuming, error-prone, and unreliable, and is not scalable to large numbers of images or real-time analysis. In this work, we discuss the application of machine learning approaches to find the location and geometry of different defect clusters in irradiated steels. We show that a deep learning based Faster R-CNN analysis system has a performance comparable to human analysis with relatively small training data sets. Furthermore, this study proves the promising ability to apply deep learning to assist the development of automated microscopy data analysis even when multiple features are present and paves the way for fast, scalable, and reliable analysis systems for massive amounts of modern electron microscopy data.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Numerical Analysis of Electron Runaway in the Presence of Enhanced Field in the Vicinity of a Microtip

Transition of field-emission electrons to the runaway regime in the region of enhanced electric field determined by the configuration of a microtip on a cathode is studied at several pressures of gas medium. The problem is solved using simulation of electron motion in the presence of nonuniform electric field with the aid of the Monte Carlo procedure in the 2D configuration. Nitrogen is used as a working gas. Passage through a relatively small region of the enhanced field in the vicinity of the microtip may substantially facilitate electron escape to the runaway regime, especially, at pressures of greater than 10 atm. In our opinion, the resulting runaway electrons may provide preionization of gas medium and formation of the initial stage of a 3D discharge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Electron beam analysis induces Cl vacancy defects in a NaCl thin film

This work reports on the electron-induced modification of NaCl thin film grown on Ag(110). We show using low energy electron diffraction that electron beam bombardment leads to desorption and formation of Cl vacancy defects on NaCl surface. The topographic structure of these defects is studied using scanning tunneling microscopy (STM) showing the Cl defects as depressions on the NaCl surface. Most of the observed defects are mono-atomic vacancies and are located on flat NaCl terraces. Auger electron spectroscopy confirms the effect of electron exposure on NaCl thin films showing Cl atoms desorption from the surface. Using density functional theory taken into account the van der Waals dispersion interactions, we confirm the observed experimental STM measurements with STM simulation. Furthermore, comparing the adsorption of defect free NaCl and defective NaCl monolayer on Ag(110) surfaces, we found an increase of the adhesion energy and the charge transfer between the NaCl film and the substrate due to the Cl vacancy. In details, the adhesion energy increases between the NaCl film and the metallic Ag substrate from 30.4 meV Å –2 for the NaCl film without Cl vacancy and from 39.5 meV Å –2 for NaCl film with a single Cl vacancy. The charge transfer from the NaCl film to the Ag substrate is enhanced when the vacancy is created, from 0.63e – to 1.25e – .

Materials Science↗
DOE OSTI2018

A Graph Theory-Based Automated Twin Recognition Technique for Electron Backscatter Diffraction Analysis

Abstract The present article introduces a new software, Microstructure Evaluation Tool for Interface Statistics (METIS), that performs high-throughput microstructure statistical analysis from electron backscatter diffraction maps. Emphasis is placed on the detection of twin domains in hexagonal close-packed metals. The numerical framework on which METIS is built leverages graph theory, group structures, and associated numerical algorithms to automatically detect twins and unravel both their intrinsic characteristics features and those pertaining to their interactions. The proposed graphical interface allows for the detection and correction of unlikely twin/parent associations rendering the approach applicable to highly deformed microstructures. Twin statistics and microstructural data are classified and saved in a relational database that can be interrogated via either GUI or SQL requests to reveal a wide spectrum of features of the microstructure. Illustration of the approach is performed in the case of zirconium.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Gaussian process analysis of electron energy loss spectroscopy data: multivariate reconstruction and kernel control

Abstract Advances in hyperspectral imaging including electron energy loss spectroscopy bring forth the challenges of exploratory and physics-based analysis of multidimensional data sets. The multivariate linear unmixing methods generally explore similarities in the energy dimension, but ignore correlations in the spatial domain. At the same time, Gaussian process (GP) explicitly incorporate spatial correlations in the form of kernel functions but is computationally intensive. Here, we implement a GP method operating on the full spatial domain and reduced representations in the energy domain. In this multivariate GP, the information between the components is shared via a common spatial kernel structure, while allowing for variability in the relative noise magnitude or image morphology. We explore the role of kernel constraints on the quality of the reconstruction, and suggest an approach for estimating them from the experimental data. We further show that spatial information contained in higher-order components can be reconstructed and spatially localized.

36 MATERIALS SCIENCE↗
DOE OSTI2021

py4DSTEM: A Software Package for Four-Dimensional Scanning Transmission Electron Microscopy Data Analysis

Scanning transmission electron microscopy (STEM) allows for imaging, diffraction, and spectroscopy of materials on length scales ranging from microns to atoms. By using a high-speed, direct electron detector, it is now possible to record a full two-dimensional (2D) image of the diffracted electron beam at each probe position, typically a 2D grid of probe positions. These 4D-STEM datasets are rich in information, including signatures of the local structure, orientation, deformation, electromagnetic fields, and other sample-dependent properties. However, extracting this information requires complex analysis pipelines that include data wrangling, calibration, analysis, and visualization, all while maintaining robustness against imaging distortions and artifacts. In this paper, we present py4DSTEM, an analysis toolkit for measuring material properties from 4D-STEM datasets, written in the Python language and released with an open-source license. We describe the algorithmic steps for dataset calibration and various 4D-STEM property measurements in detail and present results from several experimental datasets. We also implement a simple and universal file format appropriate for electron microscopy data in py4DSTEM, which uses the open-source HDF5 standard. We hope this tool will benefit the research community and help improve the standards for data and computational methods in electron microscopy, and we invite the community to contribute to this ongoing project.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Electronic structure analysis and DFT benchmarking of Rydberg-type alkali-metal-crown ether, -cryptand, and -adamanzane complexes

Density functional theory (DFT) and electron propagator theory (EPT) calculations were performed to study ground and excited electronic structures of alkali-metal (M) coordinated 9-crown-3, 24-crown-8, [2.1.1]cryptand, o-Me 2 -1.1.1, and 3 6 Adamanzane complexes. Each complex bears an expanded electron in the periphery and occupies diffuse 1p-, 1d-, 1f-type molecular orbitals (or superatomic 1P, 1D, 1F orbitals) in excited electronic states. The calculated superatomic shell model of the M(9-crown-3) 2 is 1S, 1P, 1D, 1F, 2S, 2P, 2D, 1G and it is held by all other complexes up to the studied 1F level. Due to the highly diffuse nature of the electron, the ionization energies of these complexes are significantly lower (1.6–2.0 eV) and hence these complexes belong to the superalkali category. Further, the ab initio EPT ionization energy and the excitation energies of the Li(9-crown-3) 2 were used to evaluate DFT errors associated with a series of exchange correlation functionals that span multiple rungs of Jacob's ladder (i.e., GGA, meta-GGA, global GGA hybrid, meta-GGA hybrid, range-separated hybrid, double-hybrid). Among these, the best performing functional is the range-separated hybrid CAM-B3LYP and the errors are within 6% of high-level ab initio EPT results. The accuracy of CAM-B3LYP is indeed transferable to similar complexes and hence the findings are expected to accelerate the progression of studies of Rydberg-type systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Electronic Structural Analysis of Copper(II)–TEMPO/ABNO Complexes Provides Evidence for Copper(I)–Oxoammonium Character

Copper/aminoxyl species are proposed as key intermediates in aerobic alcohol oxidation. Several possible electronic structural descriptions of these species are possible, and here we probe this issue by examining four crystallographically characterized Cu/aminoxyl halide complexes by Cu K-edge, Cu L 2,3 - edge, and Cl K-edge X-ray absorption spectroscopy. The mixing coefficients between Cu, aminoxyl, and halide orbitals are determined via these techniques with support from density functional theory. The emergent electronic structure picture reveals that Cu coordination confers appreciable oxoammonium character to the aminoxyl ligand. The computational methodology is extended to one of the putative intermediates invoked in catalytic Cu/aminoxyl-driven alcohol oxidation reactions, with similar findings. On the whole, the results have important implications for the mechanism of alcohol oxidation and the underlying basis for cooperativity in this co- catalyst system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗