scholarly journals Automated Reconstruction of Spherical Kikuchi Maps

2019 ◽  
Vol 25 (4) ◽  
pp. 912-923 ◽  
Author(s):  
Chaoyi Zhu ◽  
Kevin Kaufmann ◽  
Kenneth Vecchio
Keyword(s):  
Electron Backscatter Diffraction ◽  
Phase Identification ◽  
Threshold Values ◽  
Kikuchi Pattern ◽  
Electron Backscatter ◽  
Multiple Scan ◽  
Multiple Threshold ◽  
Diffraction Patterns ◽  
Backscatter Diffraction ◽  
Pattern Center

AbstractAn automated approach to fully reconstruct spherical Kikuchi maps from experimentally collected electron backscatter diffraction patterns and overlay each pattern onto its corresponding position on a simulated Kikuchi sphere is presented in this study. This work demonstrates the feasibility of warping any Kikuchi pattern onto its corresponding location of a simulated Kikuchi sphere and reconstructing a spherical Kikuchi map of a known phase based on any set of experimental patterns. This method consists of the following steps after pattern collection: (1) pattern selection based on multiple threshold values; (2) extraction of multiple scan parameters and phase information; (3) generation of a kinematically simulated Kikuchi sphere as the “skeleton” of the spherical Kikuchi map; and (4) overlaying the inverse gnomonic projection of multiple selected patterns after appropriate pattern center calibration and refinement. The proposed method is the first automated approach to reconstructing spherical Kikuchi maps from experimental Kikuchi patterns. It potentially enables more accurate orientation calculation, new pattern center refinement methods, improved dictionary-based pattern matching, and phase identification in the future.

Resolving pseudosymmetry in γ-TiAl using cross-correlation electron backscatter diffraction with dynamically simulated reference patterns

2018 ◽  
Vol 51 (3) ◽  
pp. 655-669 ◽  
Author(s):  
Brian Jackson ◽  
David Fullwood ◽  
Jordan Christensen ◽  
Stuart Wright
Keyword(s):  
Cross Correlation ◽  
Electron Backscatter Diffraction ◽  
Experimental Sample ◽  
Correct Orientation ◽  
Pattern Noise ◽  
Electron Backscatter ◽  
Diffraction Patterns ◽  
Backscatter Diffraction ◽  
Pattern Resolution ◽  
Pattern Center

Pseudosymmetry is a phenomenon that occurs when grains with different lattice parameters produce nearly identical diffraction patterns such that conventional electron backscatter diffraction (EBSD) techniques are unable to unambiguously differentiate the lattice orientations. This commonly occurs in materials with near-unity tetragonality, such as γ-TiAl. The current study uses cross-correlation EBSD to resolve pseudosymmetry in γ-TiAl. Three dynamically simulated reference patterns are generated for each point in the scan, one for each of the three potential pseudosymmetric orientations, which are subsequently correlated with the original pattern using six different methods in order to identify the correct orientation. The methods are first applied to a scan of dynamically simulated patterns, which is used to evaluate the sensitivity of the method to pattern resolution, pattern noise and pattern center error. It was determined that all six methods were 100% successful up to about 13 µm of pattern center error and pattern resolutions of about 80 × 80 pixels, and hence the methods were applied to an experimental sample of lamellar γ-TiAl. A hybrid combination of two of the methods was shown to successfully select the correct pseudosymmetry for about 96% of the points in the scan, improving upon the 70% accuracy of the Hough-based methods for the current study and 90% accuracy for previous studies resolving pseudosymmetry in lamellar γ-TiAl.

scholarly journals Crystal symmetry determination in electron diffraction using machine learning

Science ◽  
2020 ◽  
Vol 367 (6477) ◽  
pp. 564-568 ◽  
Author(s):  
Kevin Kaufmann ◽  
Chaoyi Zhu ◽  
Alexander S. Rosengarten ◽  
Daniel Maryanovsky ◽  
Tyler J. Harrington ◽  
...  
Keyword(s):  
Machine Learning ◽  
Electron Backscatter Diffraction ◽  
Crystal Symmetry ◽  
Structure Identification ◽  
Phase Identification ◽  
Training Set ◽  
The Neural Network ◽  
Electron Backscatter ◽  
Diffraction Patterns ◽  
Backscatter Diffraction

Electron backscatter diffraction (EBSD) is one of the primary tools for crystal structure determination. However, this method requires human input to select potential phases for Hough-based or dictionary pattern matching and is not well suited for phase identification. Automated phase identification is the first step in making EBSD into a high-throughput technique. We used a machine learning–based approach and developed a general methodology for rapid and autonomous identification of the crystal symmetry from EBSD patterns. We evaluated our algorithm with diffraction patterns from materials outside the training set. The neural network assigned importance to the same symmetry features that a crystallographer would use for structure identification.

scholarly journals On the Use of EBSD and Microhardness to Study the Microstructure Properties of Tungsten Samples Prepared by Selective Laser Melting

Materials ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1215
Author(s):  
Mirza Atif Abbas ◽  
Yan Anru ◽  
Zhi Yong Wang
Keyword(s):  
Selective Laser Melting ◽  
Electron Backscatter Diffraction ◽  
Fusion Reactors ◽  
Laser Melting ◽  
Kikuchi Pattern ◽  
Plasma Facing Components ◽  
Electron Backscatter ◽  
Ebsd Technique ◽  
Temperature Exposure ◽  
Backscatter Diffraction

Additively manufactured tungsten and its alloys have been widely used for plasma facing components (PFCs) in future nuclear fusion reactors. Under the fusion process, PFCs experience a high-temperature exposure, which will ultimately affect the microstructural features, keeping in mind the importance of microstructures. In this study, microhardness and electron backscatter diffraction (EBSD) techniques were used to study the specimens. Vickers hardness method was used to study tungsten under different parameters. EBSD technique was used to study the microstructure and Kikuchi pattern of samples under different orientations. We mainly focused on selective laser melting (SLM) parameters and the effects of these parameters on the results of different techniques used to study the behavior of samples.

scholarly journals Deep Neural Network Enabled Space Group Identification in EBSD

2020 ◽  
Vol 26 (3) ◽  
pp. 447-457 ◽  
Author(s):  
Kevin Kaufmann ◽  
Chaoyi Zhu ◽  
Alexander S. Rosengarten ◽  
Kenneth S. Vecchio
Keyword(s):  
Machine Learning ◽  
Electron Backscatter Diffraction ◽  
Group Identification ◽  
Point Group ◽  
Phase Identification ◽  
Space Group ◽  
Multiple Length Scales ◽  
Analysis Technique ◽  
Diffraction Patterns ◽  
Backscatter Diffraction

AbstractElectron backscatter diffraction (EBSD) is one of the primary tools in materials development and analysis. The technique can perform simultaneous analyses at multiple length scales, providing local sub-micron information mapped globally to centimeter scale. Recently, a series of technological revolutions simultaneously increased diffraction pattern quality and collection rate. After collection, current EBSD pattern indexing techniques (whether Hough-based or dictionary pattern matching based) are capable of reliably differentiating between a “user selected” set of phases, if those phases contain sufficiently different crystal structures. EBSD is currently less well suited for the problem of phase identification where the phases in the sample are unknown. A pattern analysis technique capable of phase identification, utilizing the information-rich diffraction patterns potentially coupled with other data, such as EDS-derived chemistry, would enable EBSD to become a high-throughput technique replacing many slower (X-ray diffraction) or more expensive (neutron diffraction) methods. We utilize a machine learning technique to develop a general methodology for the space group classification of diffraction patterns; this is demonstrated within the $\lpar 4/m\comma \;\bar{3}\comma \;\;2/m\rpar$ point group. We evaluate the machine learning algorithm's performance in real-world situations using materials outside the training set, simultaneously elucidating the role of atomic scattering factors, orientation, and pattern quality on classification accuracy.

scholarly journals Crystal orientation and detector distance effects on resolving pseudosymmetry by electron backscatter diffraction

2021 ◽  
Vol 54 (2) ◽  
pp. 513-522
Author(s):  
Edward L. Pang ◽  
Christopher A. Schuh
Keyword(s):  
Crystal Orientation ◽  
Electron Backscatter Diffraction ◽  
Detector Distance ◽  
Recent Emergence ◽  
Distance Effects ◽  
Electron Backscatter ◽  
Sample Position ◽  
Position And Orientation ◽  
Diffraction Patterns ◽  
Backscatter Diffraction

Accurately indexing pseudosymmetric materials has long proven challenging for electron backscatter diffraction. The recent emergence of intensity-based indexing approaches promises an enhanced ability to resolve pseudosymmetry compared with traditional Hough-based indexing approaches. However, little work has been done to understand the effects of sample position and orientation on the ability to resolve pseudosymmetry, especially for intensity-based indexing approaches. Thus, in this work the effects of crystal orientation and detector distance in a model tetragonal ZrO2 (c/a = 1.0185) material are quantitatively investigated. The orientations that are easiest and most difficult to correctly index are identified, the effect of detector distance on indexing confidence is characterized, and these trends are analyzed on the basis of the appearance of specific zone axes in the diffraction patterns. The findings also point to the clear benefit of shorter detector distances for resolving pseudosymmetry using intensity-based indexing approaches.

Error analysis of the crystal orientations and disorientations obtained by the classical electron backscatter diffraction technique

2015 ◽  
Vol 48 (3) ◽  
pp. 797-813 ◽  
Author(s):  
Farangis Ram ◽  
Stefan Zaefferer ◽  
Tom Jäpel ◽  
Dierk Raabe
Keyword(s):  
Electron Diffraction ◽  
Electron Backscatter Diffraction ◽  
Diffraction Theory ◽  
Classical Electron ◽  
Accuracy Measure ◽  
Electron Backscatter ◽  
Analytical Accuracy ◽  
Precision And Accuracy ◽  
Diffraction Patterns ◽  
Backscatter Diffraction

The fidelity – that is, the error, precision and accuracy – of the crystallographic orientations and disorientations obtained by the classical two-dimensional Hough-transform-based analysis of electron backscatter diffraction patterns (EBSPs) is studied. Using EBSPs simulated based on the dynamical electron diffraction theory, the fidelity analysis that has been previously performed using the patterns simulated based on the theory of kinematic electron diffraction is improved. Using the same patterns, the efficacy of a Fisher-distribution-based analytical accuracy measure for orientation and disorientation is verified.

All You Need to Know About Electron Backscatter Diffraction: Orientation is Only the Tip of the Iceberg

1997 ◽  
Vol 3 (S2) ◽  
pp. 387-388 ◽  
Author(s):  
J. R. Michael
Keyword(s):  
Electron Backscatter Diffraction ◽  
Photographic Film ◽  
Phase Identification ◽  
Electron Backscattered Diffraction ◽  
Bulk Specimen ◽  
Electron Backscatter ◽  
Backscatter Diffraction ◽  
Over 40 Years ◽  
Orientation Determination ◽  
Scanning Electron

This tutorial will describe the technique of electron backscattered diffraction (EBSD) in the scanning electron microscope (SEM). To properly exploit EBSD in the SEM it is important to understand how these patterns are formed. This discussion will be followed by a description of the hardware required for the collection of electron backscatter patterns (EBSP). We will then discuss the methods used to extract the appropriate crystallographic information from the patterns for orientation determination and phase identification and how these operations can be automated. Following this, a number of applications of the technique for both orientation studies and phase identification will be discussed.EBSD in the SEM is a phenomenon that has been known for many years. EBSD in the SEM is a technique that permits the crystallography of sub-micron sized regions to be studied from a bulk specimen. These patterns were first observed over 40 years ago, before the development of the SEM and were recorded using a special chamber and photographic film.

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