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Title: Optimizing disk registration algorithms for nanobeam electron diffraction strain mapping

Journal Article · · Ultramicroscopy
 [1];  [2];  [3];  [1];  [3]
  1. Univ. of California, Berkeley, CA (United States). Dept. of Materials Science and Engineering; Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Center for Electron Microscopy, Molecular Foundry
  2. Erich Schmid Inst. of Materials Science, Leoben (Austria)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Center for Electron Microscopy, Molecular Foundry

Scanning nanobeam electron diffraction strain mapping is a technique by which the positions of diffracted disks sampled at the nanoscale over a crystalline sample can be used to reconstruct a strain map over a large area. However, it is important that the disk positions are measured accurately, as their positions relative to a reference are directly used to calculate strain. Here in this study, we compare several correlation methods using both simulated and experimental data in order to directly probe susceptibility to measurement error due to non-uniform diffracted disk illumination structure. We found that prefiltering the diffraction patterns with a Sobel filter before performing cross correlation or performing a square-root magnitude weighted phase correlation returned the best results when inner disk structure was present. Lastly, we have tested these methods both on simulated datasets, and experimental data from unstrained silicon as well as a twin grain boundary in 304 stainless steel.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Basic Energy Sciences (BES); Austrian Science Fund (FWF)
Grant/Contract Number:
AC02-05CH11231; AC02-05-CH11231
OSTI ID:
1379825
Alternate ID(s):
OSTI ID: 1416658
Journal Information:
Ultramicroscopy, Vol. 176, Issue C; ISSN 0304-3991
Publisher:
ElsevierCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 51 works
Citation information provided by
Web of Science

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