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Results for “BF-STEM imaging”

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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2013

Transmission Electron Microscopy of Iron Metal in Almahata Sitta Ureilite

Almahata Sitta (AS) is a polymict breccia mainly composed of variable ureilite lithologies with small amounts of chondritic lithologies [1]. Fe metal is a common accessory phase in ureilites, but our earlier study on Fe metals in one of AS fragments (#44) revealed a unique mineralogy never seen in other ureilites [2,3]. In this abstract we report detailed transmission electron microscopy (TEM) on these metal grains to better understand the thermal history of ureilites. We prepared FIB sections of AS#44 by JEOL JIB-4000 from the PTS that was well characterized by SEM-EBSD in our earlier study [2]. The sections were then observed by STEM (JEOL JEM- 2100F). One of the FIB sections shows a submicron-sized symplectic intergrown texture composed of Fe metal (kamacite), Fe carbide (cohenite), Fe phosphide (schreibersite), and Fe sulfide (troilite). Each phase has an identical SAED pattern in spite of its complex texture, suggesting co-crystallization of all phases. This is probably caused by shock re-melting of pre-existing metal + graphite to form a eutectic-looking texture. The other FIB section is mostly composed of homogeneous Fe metal (93 wt% Fe, 5 wt% Ni, and 2 wt% Si), but BF-STEM images exhibited the presence of elongated lathy grains (approx. 2 microns long) embedded in the interstitial matrix. The SAED patterns from these lath grains could be indexed by alpha-Fe (bcc) while interstitial areas are gamma-Fe (fcc). The elongated alpha-Fe grains show tweed-like structures suggesting martensite transformation. Such a texture can be formed by rapid cooling from high temperature where gamma-Fe was stable. Subsequently alpha-Fe crystallized, but gamma-Fe remained in the interstitial matrix due to quenching from high temperature. This scenario is consistent with very rapid cooling history of ureilites suggested by silicate mineralogy.

Mikouchi, T.↗
DOE OSTI2020

mpfit: a robust method for fitting atomic resolution images with multiple Gaussian peaks

The standard technique for sub-pixel estimation of atom positions from atomic resolution scanning transmission electron microscopy images relies on fitting intensity maxima or minima with a two-dimensional Gaussian function. While this is a widespread method of measurement, it can be error prone in images with non-zero aberrations, strong intensity differences between adjacent atoms or in situations where the neighboring atom positions approach the resolution limit of the microscope. Here we demonstrate mpfit, an atom finding algorithm that iteratively calculates a series of overlapping two-dimensional Gaussian functions to fit the experimental dataset and then subsequently uses a subset of the calculated Gaussian functions to perform sub-pixel refinement of atom positions. Based on both simulated and experimental datasets presented in this work, this approach gives lower errors when compared to the commonly used single Gaussian peak fitting approach and demonstrates increased robustness over a wider range of experimental conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Reducing Artifacts in BF and HAADF-STEM Images of Pt/C Fuel Cells using MBIR-ARAR

Electron tomography is a powerful tool for characterization of three-dimensional (3D) nanoscale materials and devices. Bright-field (BF) and high-angle annular dark-field (HAADF) scanning transmission electron microscopy (STEM) are two widely used imaging modes in electron tomography. These imaging modalities have proven to be useful for characterizing the structure of carbon-supported platinum (Pt/C) electrocatalysts used in fuel cells, which are an important class of clean energy conversion systems. BF and HAADF-STEM images are typically simultaneously acquired due to the complementary information they contain, as BF-STEM is more suitable for characterizing carbon due to its ability to detect lighter elements, while HAADF-STEM is more suitable for characterizing platinum due to its sensitivity to atomic number. However, the quality of BF- and HAADF-STEM images is often compromised by various artifacts, such as local blurring due to abrupt contrast changes as well as missing wedge artifacts which can severely impact the accuracy of the reconstructed 3D images. The traditional methods of reconstruction, such as Filtered Back-projection (FBP), Simultaneous Iterative Reconstruction Technique (SIRT), and Model-Based Iterative Reconstruction (MBIR), are often not suitable for removing these artifacts effectively. Here, to address this challenge, we present a novel approach called MBIR with Artifact Reduction and Adaptive Regularization (MBIR-ARAR).

25 ENERGY STORAGE↗