Automated Crystal Orientation Mapping in py4DSTEM using Sparse Correlation Matching

Crystalline materials used in technological applications are often complex assemblies composed of multiple phases and differently oriented grains. Robust identification of the phases and orientation relationships from these samples is crucial, but the information extracted from the diffraction condi...

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Veröffentlicht in:Microscopy and microanalysis Jg. 28; H. 2; S. 390 - 403
Hauptverfasser: Ophus, Colin, Zeltmann, Steven E., Bruefach, Alexandra, Rakowski, Alexander, Savitzky, Benjamin H., Minor, Andrew M., Scott, Mary C.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, USA Cambridge University Press 01.04.2022
Oxford University Press
Microscopy Society of America (MSA)
Schlagworte:
Algorithms
automated crystal orientation mapping (ACOM)
Automation
Crystal structure
Datasets
Diffraction
Diffraction patterns
Electron beams
Electron probe
Electron probes
Experiments
four-dimensional scanning
Grains
Libraries
Machine learning
Mapping
MATERIALS SCIENCE
Methods
nanobeam electron diffraction (NBED)
Nanotechnology
Nanowires
open-source software
Orientation relationships
Point defects
Scanning electron microscopy
scanning electron nanodiffraction (SEND)
Software and Instrumentation
Source code
Transmission electron microscopy
transmission electron microscopy (4D-STEM)
automated crystal orientation mapping (ACOM)
open-source software
nanobeam electron diffraction (NBED)
scanning electron nanodiffraction (SEND)
four-dimensional scanning transmission electron microscopy (4D-STEM)
ISSN:1431-9276, 1435-8115, 1435-8115
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Zusammenfassung:Crystalline materials used in technological applications are often complex assemblies composed of multiple phases and differently oriented grains. Robust identification of the phases and orientation relationships from these samples is crucial, but the information extracted from the diffraction condition probed by an electron beam is often incomplete. We have developed an automated crystal orientation mapping (ACOM) procedure which uses a converged electron probe to collect diffraction patterns from multiple locations across a complex sample. We provide an algorithm to determine the orientation of each diffraction pattern based on a fast sparse correlation method. We demonstrate the speed and accuracy of our method by indexing diffraction patterns generated using both kinematical and dynamical simulations. We have also measured orientation maps from an experimental dataset consisting of a complex polycrystalline twisted helical AuAgPd nanowire. From these maps we identify twin planes between adjacent grains, which may be responsible for the twisted helical structure. All of our methods are made freely available as open source code, including tutorials which can be easily adapted to perform ACOM measurements on diffraction pattern datasets.
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AC02-05CH11231
USDOE Office of Science (SC), Basic Energy Sciences (BES). Chemical Sciences, Geosciences & Biosciences Division
ISSN:1431-9276
1435-8115
1435-8115
DOI:10.1017/S1431927622000101