scholarly journals Carbon Redistribution in Martensite in High-C Steel: Atomic-Scale Characterization and Modelling

Metals ◽  
2018 ◽  
Vol 8 (8) ◽  
pp. 577 ◽  
Author(s):  
Wenwen Song ◽  
Carsten Drouven ◽  
Enrique Galindo-Nava
Keyword(s):  
Electron Microscopy ◽  
Atom Probe Tomography ◽  
Atom Probe ◽  
Atomic Scale ◽  
Alloying Elements ◽  
Plate Martensite ◽  
Carbon Redistribution ◽  
Scale Characterization

The microstructure of the as-quenched plate martensite in a high-C steel 100Cr6 was characterized by means of electron microscopy and atom probe tomography. The carbon redistribution behavior was investigated at the atomic scale, which revealed the nature of the transformation dynamics influenced by carbon and other substitutional alloying elements. A model was proposed to predict the carbon redistribution at twins and dislocations in martensite, which was based on their spatial arrangements.

Atomic scale characterization of buried InxGa1−xAs quantum dots using pulsed laser atom probe tomography

2008 ◽  
Vol 92 (23) ◽  
pp. 233115 ◽  
Author(s):  
M. Müller ◽  
A. Cerezo ◽  
G. D. W. Smith ◽  
L. Chang ◽  
S. S. A. Gerstl
Keyword(s):  
Quantum Dots ◽  
Atom Probe Tomography ◽  
Pulsed Laser ◽  
Atom Probe ◽  
Atomic Scale ◽  
Scale Characterization

scholarly journals Characterization of Ni-base Superalloys on the Atomic Scale by Atom Probe Tomography and Spherical-Aberration Corrected Analytical Electron Microscopy Techniques

2006 ◽  
Vol 12 (S02) ◽  
pp. 534-535 ◽  
Author(s):  
M Watanabe ◽  
D Saxey ◽  
R Zheng ◽  
D Williams ◽  
S Ringer
Keyword(s):  
Electron Microscopy ◽  
Atom Probe Tomography ◽  
Spherical Aberration ◽  
Analytical Electron Microscopy ◽  
Atom Probe ◽  
Atomic Scale ◽  
Analytical Electron ◽  
Microscopy Techniques ◽  
Aberration Corrected

Extended abstract of a paper presented at Microscopy and Microanalysis 2006 in Chicago, Illinois, USA, July 30 – August 3, 2006

Atomic-Scale Tomography: A 2020 Vision

2013 ◽  
Vol 19 (3) ◽  
pp. 652-664 ◽  
Author(s):  
Thomas F. Kelly ◽  
Michael K. Miller ◽  
Krishna Rajan ◽  
Simon P. Ringer
Keyword(s):  
Electron Microscopy ◽  
Atom Probe Tomography ◽  
Atom Probe ◽  
Atomic Scale ◽  
Multidimensional Data ◽  
Materials Engineering ◽  
Transmission Electron ◽  
Integrated Computational Materials Engineering ◽  
Computational Materials ◽  
Structure Properties

AbstractAtomic-scale tomography (AST) is defined and its place in microscopy is considered. Arguments are made that AST, as defined, would be the ultimate microscopy. The available pathways for achieving AST are examined and we conclude that atom probe tomography (APT) may be a viable basis for AST on its own and that APT in conjunction with transmission electron microscopy is a likely path as well. Some possible configurations of instrumentation for achieving AST are described. The concept of metaimages is introduced where data from multiple techniques are melded to create synergies in a multidimensional data structure. When coupled with integrated computational materials engineering, structure–properties microscopy is envisioned. The implications of AST for science and technology are explored.

scholarly journals Atomic Scale Composition Profiling of Ferroelectrics via Laser-Pulsed Atom Probe Tomography and Cross-Correlative Transmission Electron Microscopy

2013 ◽  
Vol 19 (S2) ◽  
pp. 980-981 ◽  
Author(s):  
R. Kirchhofer ◽  
D.R. Diercks ◽  
B.P. Gorman ◽  
G.L. Brennecka
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
Atom Probe Tomography ◽  
Atom Probe ◽  
Atomic Scale ◽  
Transmission Electron ◽  
Scale Composition

Extended abstract of a paper presented at Microscopy and Microanalysis 2013 in Indianapolis, Indiana, USA, August 4 – August 8, 2013.

scholarly journals Phase Segmentation in Atom-Probe Tomography Using Deep Learning-Based Edge Detection

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Sandeep Madireddy ◽  
Ding-Wen Chung ◽  
Troy Loeffler ◽  
Subramanian K. R. S. Sankaranarayanan ◽  
David N. Seidman ◽  
...  
Keyword(s):  
Atom Probe Tomography ◽  
Deep Neural Networks ◽  
Interfacial Properties ◽  
Atom Probe ◽  
Atomic Scale ◽  
Precipitate Phase ◽  
Local Composition ◽  
Segmentation Approach ◽  
Scale Characterization ◽  
Traditional Approaches

AbstractAtom-probe tomography (APT) facilitates nano- and atomic-scale characterization and analysis of microstructural features. Specifically, APT is well suited to study the interfacial properties of granular or heterophase systems. Traditionally, the identification of the interface between, for precipitate and matrix phases, in APT data has been obtained either by extracting iso-concentration surfaces based on a user-supplied concentration value or by manually perturbing the concentration value until the iso-concentration surface qualitatively matches the interface. These approaches are subjective, not scalable, and may lead to inconsistencies due to local composition inhomogeneities. We introduce a digital image segmentation approach based on deep neural networks that transfer learned knowledge from natural images to automatically segment the data obtained from APT into different phases. This approach not only provides an efficient way to segment the data and extract interfacial properties but does so without the need for expensive interface labeling for training the segmentation model. We consider here a system with a precipitate phase in a matrix and with three different interface modalities—layered, isolated, and interconnected—that are obtained for different relative geometries of the precipitate phase. We demonstrate the accuracy of our segmentation approach through qualitative visualization of the interfaces, as well as through quantitative comparisons with proximity histograms obtained by using more traditional approaches.

Sign in / Sign up

Export Citation Format

Share Document