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Title: A graph theory based automated twin recognition technique for Electron Back-scatter Diffraction analysis

Here, 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:
 [1] ;  [2] ; ORCiD logo [3] ; ORCiD logo [3]
  1. Georgia Tech, Lorraine (France)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  3. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Publication Date:
Report Number(s):
LA-UR-17-20048
Journal ID: ISSN 2193-9764
Grant/Contract Number:
AC52-06NA25396
Type:
Accepted Manuscript
Journal Name:
Integrating Materials and Manufacturing Innovation
Additional Journal Information:
Journal Volume: 7; Journal Issue: 1; Journal ID: ISSN 2193-9764
Publisher:
Springer
Research Org:
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org:
USDOE Office of Science (SC). Basic Energy Sciences (BES) (SC-22)
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; EBSD
OSTI Identifier:
1460637

Pradalier, Cedric, Juan, Pierre Alexandre, Capolungo, Laurent, and Mccabe, Rodney James. A graph theory based automated twin recognition technique for Electron Back-scatter Diffraction analysis. United States: N. p., Web. doi:10.1007/s40192-018-0106-y.
Pradalier, Cedric, Juan, Pierre Alexandre, Capolungo, Laurent, & Mccabe, Rodney James. A graph theory based automated twin recognition technique for Electron Back-scatter Diffraction analysis. United States. doi:10.1007/s40192-018-0106-y.
Pradalier, Cedric, Juan, Pierre Alexandre, Capolungo, Laurent, and Mccabe, Rodney James. 2018. "A graph theory based automated twin recognition technique for Electron Back-scatter Diffraction analysis". United States. doi:10.1007/s40192-018-0106-y.
@article{osti_1460637,
title = {A graph theory based automated twin recognition technique for Electron Back-scatter Diffraction analysis},
author = {Pradalier, Cedric and Juan, Pierre Alexandre and Capolungo, Laurent and Mccabe, Rodney James},
abstractNote = {Here, 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 = {United States},
year = {2018},
month = {2}
}