A Graph Theory-Based Automated Twin Recognition Technique for Electron Backscatter Diffraction Analysis
Abstract
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.
- Authors:
- Publication Date:
- Research Org.:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Org.:
- USDOE; USDOE Office of Science (SC). Basic Energy Sciences (BES) (SC-22)
- OSTI Identifier:
- 1780344
- Alternate Identifier(s):
- OSTI ID: 1460637
- Report Number(s):
- LA-UR-17-20048
Journal ID: ISSN 2193-9764; PII: 106
- Grant/Contract Number:
- AC52-06NA25396
- Resource Type:
- Published Article
- Journal Name:
- Integrating Materials and Manufacturing Innovation
- Additional Journal Information:
- Journal Name: Integrating Materials and Manufacturing Innovation Journal Volume: 7 Journal Issue: 1; Journal ID: ISSN 2193-9764
- Publisher:
- Springer Science + Business Media
- Country of Publication:
- Germany
- Language:
- English
- Subject:
- 36 MATERIALS SCIENCE; EBSD
Citation Formats
Pradalier, Cédric, Juan, Pierre-Alexandre, McCabe, Rodney J., and Capolungo, Laurent. A Graph Theory-Based Automated Twin Recognition Technique for Electron Backscatter Diffraction Analysis. Germany: N. p., 2018.
Web. doi:10.1007/s40192-018-0106-y.
Pradalier, Cédric, Juan, Pierre-Alexandre, McCabe, Rodney J., & Capolungo, Laurent. A Graph Theory-Based Automated Twin Recognition Technique for Electron Backscatter Diffraction Analysis. Germany. https://doi.org/10.1007/s40192-018-0106-y
Pradalier, Cédric, Juan, Pierre-Alexandre, McCabe, Rodney J., and Capolungo, Laurent. Mon .
"A Graph Theory-Based Automated Twin Recognition Technique for Electron Backscatter Diffraction Analysis". Germany. https://doi.org/10.1007/s40192-018-0106-y.
@article{osti_1780344,
title = {A Graph Theory-Based Automated Twin Recognition Technique for Electron Backscatter Diffraction Analysis},
author = {Pradalier, Cédric and Juan, Pierre-Alexandre and McCabe, Rodney J. and Capolungo, Laurent},
abstractNote = {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.},
doi = {10.1007/s40192-018-0106-y},
journal = {Integrating Materials and Manufacturing Innovation},
number = 1,
volume = 7,
place = {Germany},
year = {Mon Feb 26 00:00:00 EST 2018},
month = {Mon Feb 26 00:00:00 EST 2018}
}
https://doi.org/10.1007/s40192-018-0106-y
Web of Science
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