Semi-Automated, Object-Based Tomography of Dislocation Structures

Sills, Ryan B.; Medlin, Douglas L.

doi:10.1017/S1431927622000332

Semi-Automated, Object-Based Tomography of Dislocation Structures

Journal Article · Mon Mar 07 23:00:00 EST 2022 · Microscopy and Microanalysis

DOI:https://doi.org/10.1017/S1431927622000332· OSTI ID:1856054

; Medlin, Douglas L.

The characterization of the three-dimensional arrangement of dislocations is important for many analyses in materials science. Dislocation tomography in transmission electron microscopy is conventionally accomplished through intensity-based reconstruction algorithms. Although such methods work successfully, a disadvantage is that they require many images to be collected over a large tilt range. Here, we present an alternative, semi-automated object-based approach that reduces the data collection requirements by drawing on the prior knowledge that dislocations are line objects. Our approach consists of three steps: (1) initial extraction of dislocation line objects from the individual frames, (2) alignment and matching of these objects across the frames in the tilt series, and (3) tomographic reconstruction to determine the full three-dimensional configuration of the dislocations. Drawing on innovations in graph theory, we employ a node-line segment representation for the dislocation lines and a novel arc-length mapping scheme to relate the dislocations to each other across the images in the tilt series. We demonstrate the method for a dataset collected from a dislocation network imaged by diffraction-contrast scanning transmission electron microscopy. Based on these results and a detailed uncertainty analysis for the algorithm, we discuss opportunities for optimizing data collection and further automating the method.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: AC02-05CH11231; NA0003525

OSTI ID:: 1856054

Alternate ID(s):: OSTI ID: 1882891

Journal Information:: Microscopy and Microanalysis, Journal Name: Microscopy and Microanalysis Journal Issue: 3 Vol. 28; ISSN 1431-9276

Publisher:: Oxford University PressCopyright Statement

Country of Publication:: United States

Language:: English

References (36)

Characterization of the glide planes of the [001] screw dislocations in olivine using electron tomography Mussi, Alexandre; Cordier, Patrick; Demouchy, Sylvie Physics and Chemistry of Minerals, Vol. 41, Issue 7 https://doi.org/10.1007/s00269-014-0665-1	journal	March 2014
Overview: Computer Vision and Machine Learning for Microstructural Characterization and Analysis Holm, Elizabeth A.; Cohn, Ryan; Gao, Nan Metallurgical and Materials Transactions A, Vol. 51, Issue 12 https://doi.org/10.1007/s11661-020-06008-4	journal	September 2020
Interrogating the Effects of Hydrogen on the Behavior of Planar Deformation Bands in Austenitic Stainless Steel Sabisch, J. E. C.; Sugar, J. D.; Ronevich, J. Metallurgical and Materials Transactions A, Vol. 52, Issue 4 https://doi.org/10.1007/s11661-021-06170-3	journal	February 2021
Dislocation link length distributions studied by stereo electron microscopy Modéer, Bengt Scripta Metallurgica, Vol. 8, Issue 10 https://doi.org/10.1016/0036-9748(74)90485-2	journal	October 1974
Quasi-four-dimensional analysis of dislocation interactions with grain boundaries in 304 stainless steel Kacher, Josh; Robertson, I. M. Acta Materialia, Vol. 60, Issue 19 https://doi.org/10.1016/j.actamat.2012.08.036	journal	November 2012
TEM-based dislocation tomography: Challenges and opportunities Feng, Zongqiang; Fu, Rui; Lin, Chengwei Current Opinion in Solid State and Materials Science, Vol. 24, Issue 3 https://doi.org/10.1016/j.cossms.2020.100833	journal	June 2020
Electron tomography: An imaging method for materials deformation dynamics Hata, S.; Honda, T.; Saito, H. Current Opinion in Solid State and Materials Science, Vol. 24, Issue 4 https://doi.org/10.1016/j.cossms.2020.100850	journal	August 2020
A comparative study on network alignment techniques Trung, Huynh Thanh; Toan, Nguyen Thanh; Vinh, Tong Van Expert Systems with Applications, Vol. 140 https://doi.org/10.1016/j.eswa.2019.112883	journal	February 2020
Fifty years of graph matching, network alignment and network comparison Emmert-Streib, Frank; Dehmer, Matthias; Shi, Yongtang Information Sciences, Vol. 346-347 https://doi.org/10.1016/j.ins.2016.01.074	journal	June 2016
Composition-dependence of stacking fault energy in austenitic stainless steels through linear regression with random intercepts Meric de Bellefon, G.; van Duysen, J. C.; Sridharan, K. Journal of Nuclear Materials, Vol. 492 https://doi.org/10.1016/j.jnucmat.2017.05.037	journal	August 2017
Electron tomography of dislocation structures Liu, G. S.; House, S. D.; Kacher, J. Materials Characterization, Vol. 87 https://doi.org/10.1016/j.matchar.2013.09.016	journal	January 2014
Crack tip dislocations revealed by electron tomography in silicon single crystal Tanaka, Masaki; Higashida, Kenji; Kaneko, Kenji Scripta Materialia, Vol. 59, Issue 8 https://doi.org/10.1016/j.scriptamat.2008.06.042	journal	October 2008
Visualization of grain boundary/dislocation interactions using tomographic reconstructions Kacher, J. P.; Liu, G. S.; Robertson, I. M. Scripta Materialia, Vol. 64, Issue 7 https://doi.org/10.1016/j.scriptamat.2010.12.020	journal	April 2011
The role of low angle grain boundary in deformation of titanium and its size effect Chen, Sijing; Yu, Qian Scripta Materialia, Vol. 163 https://doi.org/10.1016/j.scriptamat.2018.10.054	journal	April 2019
Application of electron tomography of dislocations in beam-sensitive quartz to the determination of strain components Mussi, Alexandre; Gallet, Julien; Castelnau, Olivier Tectonophysics, Vol. 803 https://doi.org/10.1016/j.tecto.2021.228754	journal	March 2021
Diffraction contrast STEM of dislocations: Imaging and simulations Phillips, P. J.; Brandes, M. C.; Mills, M. J. Ultramicroscopy, Vol. 111, Issue 9-10 https://doi.org/10.1016/j.ultramic.2011.07.001	journal	August 2011
Stereo-vision three-dimensional reconstruction of curvilinear structures imaged with a TEM Oveisi, Emad; Letouzey, Antoine; De Zanet, Sandro Ultramicroscopy, Vol. 184 https://doi.org/10.1016/j.ultramic.2017.08.010	journal	January 2018
Three-dimensional reconstruction and quantification of dislocation substructures from transmission electron microscopy stereo pairs Agudo Jácome, Leonardo; Pöthkow, Kai; Paetsch, Olaf Ultramicroscopy, Vol. 195 https://doi.org/10.1016/j.ultramic.2018.08.015	journal	December 2018
3D reconstruction of curvilinear structures with stereo matching deep convolutional neural networks Altingövde, Okan; Mishchuk, Anastasiia; Ganeeva, Gulnaz Ultramicroscopy, Vol. 234 https://doi.org/10.1016/j.ultramic.2021.113460	journal	April 2022
A Single-Tilt TEM Stereomicroscopy Technique for Crystalline Materials McCabe, Rodney J.; Misra, Amit; Mitchell, Terence E. Microscopy and Microanalysis, Vol. 9, Issue 1 https://doi.org/10.1017/S1431927603030071	journal	January 2003
Stereographic Methods for 3D Characterization of Dislocations Eftink, Ben P.; Gray, George T.; Maloy, Stuart A. Microscopy and Microanalysis, Vol. 23, Issue S1 https://doi.org/10.1017/S1431927617001738	journal	July 2017
High-Efficiency Three-Dimensional Visualization of Complex Microstructures via Multidimensional STEM Acquisition and Reconstruction Field, Kevin G.; Eftink, Benjamin P.; Parish, Chad M. Microscopy and Microanalysis, Vol. 26, Issue 2 https://doi.org/10.1017/S1431927620000173	journal	March 2020
Electron tomography and holography in materials science Midgley, Paul A.; Dunin-Borkowski, Rafal E. Nature Materials, Vol. 8, Issue 4 https://doi.org/10.1038/nmat2406	journal	April 2009
Deep Learning for Semantic Segmentation of Defects in Advanced STEM Images of Steels Roberts, Graham; Haile, Simon Y.; Sainju, Rajat Scientific Reports, Vol. 9, Issue 1 https://doi.org/10.1038/s41598-019-49105-0	journal	September 2019
Work hardening: surface effects. Dislocation distribution in deformed copper single crystals Basinski, Z. S. Discussions of the Faraday Society, Vol. 38 https://doi.org/10.1039/df9643800093	journal	January 1964
Three-dimensional analysis of dislocation networks in GaN using weak-beam dark-field electron tomography Barnard, J. S.; Sharp, J.; Tong, J. R. Philosophical Magazine, Vol. 86, Issue 29-31 https://doi.org/10.1080/14786430600798839	journal	October 2006
Dislocation electron tomography and precession electron diffraction – minimising the effects of dynamical interactions in real and reciprocal space Barnard, J. S.; Eggeman, A. S.; Sharp, J. Philosophical Magazine, Vol. 90, Issue 35-36 https://doi.org/10.1080/14786430903581338	journal	December 2010
In situ and tomographic analysis of dislocation/grain boundary interactions in α-titanium Kacher, Josh; Robertson, Ian M. Philosophical Magazine, Vol. 94, Issue 8 https://doi.org/10.1080/14786435.2013.868942	journal	January 2014
Hardening mechanisms in olivine single crystal deformed at 1090 °C: an electron tomography study Mussi, Alexandre; Cordier, Patrick; Demouchy, Sylvie Philosophical Magazine, Vol. 97, Issue 33 https://doi.org/10.1080/14786435.2017.1367858	journal	September 2017
Investigations of dislocation strain fields using weak beams Cockayne, D. J. H.; Ray, I. L. F.; Whelan, M. J. Philosophical Magazine, Vol. 20, Issue 168 https://doi.org/10.1080/14786436908228210	journal	December 1969
Adaptive Thresholding using the Integral Image Bradley, Derek; Roth, Gerhard Journal of Graphics Tools, Vol. 12, Issue 2 https://doi.org/10.1080/2151237X.2007.10129236	journal	January 2007
Electron tomography imaging methods with diffraction contrast for materials research Hata, Satoshi; Furukawa, Hiromitsu; Gondo, Takashi Microscopy, Vol. 69, Issue 3 https://doi.org/10.1093/jmicro/dfaa002	journal	March 2020
Thinning methodologies-a comprehensive survey Lam, L.; Lee, S. -W.; Suen, C. Y. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 14, Issue 9 https://doi.org/10.1109/34.161346	journal	January 1992
An unbiased detector of curvilinear structures Steger, C. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 20, Issue 2 https://doi.org/10.1109/34.659930	journal	January 1998
High-Resolution Three-Dimensional Imaging of Dislocations Barnard, J. S. Science, Vol. 313, Issue 5785 https://doi.org/10.1126/science.1125783	journal	July 2006
Frontiers in the Simulation of Dislocations Bertin, Nicolas; Sills, Ryan B.; Cai, Wei Annual Review of Materials Research, Vol. 50, Issue 1 https://doi.org/10.1146/annurev-matsci-091819-015500	journal	July 2020

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