Hostname: page-component-848d4c4894-75dct Total loading time: 0 Render date: 2024-05-25T12:33:52.477Z Has data issue: false hasContentIssue false

Autonomous EBSD Pattern Classification Performance with Changing Acquisition Parameters

Published online by Cambridge University Press:  30 July 2021

Kevin Kaufmann
Affiliation:
UC SAN DIEGO, La Jolla, California, United States
Kenneth Vecchio
Affiliation:
UC SAN DIEGO, La Jolla, California, United States

Abstract

Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'
Type
Diffraction Imaging Across Disciplines
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

References

Spurgeon, S.R., Ophus, C., Jones, L., Petford-Long, A., Kalinin, S. V., Olszta, M.J., Dunin-Borkowski, R.E., Salmon, N., Hattar, K., Yang, W.C.D., Sharma, R., Du, Y., Chiaramonti, A., Zheng, H., Buck, E.C., Kovarik, L., Penn, R.L., Li, D., Zhang, X., Murayama, M., Taheri, M.L., Towards data-driven next-generation transmission electron microscopy, Nat. Mater. (2020). doi:10.1038/s41563-020-00833-z.Google Scholar
Ge, M., Su, F., Zhao, Z., Su, D., Deep learning analysis on microscopic imaging in materials science, Mater. Today Nano. 11 (2020) 100087. doi:10.1016/j.mtnano.2020.100087.CrossRefGoogle Scholar
Kaufmann, K., Zhu, C., Rosengarten, A.S., Maryanovsky, D., Harrington, T.J., Marin, E., Vecchio, K.S., Crystal symmetry determination in electron diffraction using machine learning, Science (80-. ). 367 (2020) 564568. doi:10.1126/science.aay3062.CrossRefGoogle ScholarPubMed
Kaufmann, K., Zhu, C., Rosengarten, A.S., Vecchio, K.S., Deep Neural Network Enabled Space Group Identification in EBSD, Microsc. Microanal. 26 (2020) 447457. doi:10.1017/S1431927620001506.CrossRefGoogle ScholarPubMed
Kaufmann, K., Zhu, C., Rosengarten, A.S., Maryanovsky, D., Wang, H., Vecchio, K.S., Phase Mapping in EBSD Using Convolutional Neural Networks, Microsc. Microanal. 26 (2020) 458468. doi:10.1017/S1431927620001488.Google ScholarPubMed
Ding, Z., Pascal, E., De Graef, M., Indexing of electron back-scatter diffraction patterns using a convolutional neural network, Acta Mater. 199 (2020) 370382. doi:10.1016/j.actamat.2020.08.046.CrossRefGoogle Scholar
Shen, Y.F., Pokharel, R., Nizolek, T.J., Kumar, A., Lookman, T., Convolutional neural network-based method for real-time orientation indexing of measured electron backscatter diffraction patterns, Acta Mater. 170 (2019) 118131. doi:10.1016/j.actamat.2019.03.026.CrossRefGoogle Scholar
Schwartz, A.J., Kumar, M., Adams, B.L., Field, D.P., Electron backscatter diffraction in materials science, Springer Science+Business Media, LLC, New York, 2009. doi:10.1007/978-0-387-88136-2.CrossRefGoogle Scholar
Goulden, J., Trimby, P., Bewick, A., The Benefits and Applications of a CMOS-based EBSD Detector, Microsc. Microanal. 24 (2018) 11281129.CrossRefGoogle Scholar