A Denoising Autoencoder for Improved Kikuchi Pattern Quality and Indexing in Electron Backscatter Diffraction

Andrews, Caleb E.; Strantza, Maria; Calta, Nicholas P.; Matthews, Manyalibo J.; Taheri, Mitra L.

doi:10.1016/j.ultramic.2023.113810

A Denoising Autoencoder for Improved Kikuchi Pattern Quality and Indexing in Electron Backscatter Diffraction

Journal Article · Fri Jul 07 00:00:00 EDT 2023 · Ultramicroscopy

DOI:https://doi.org/10.1016/j.ultramic.2023.113810· OSTI ID:2007284

^[1]; Strantza, Maria ^[2]; Calta, Nicholas P. ^[2]; Matthews, Manyalibo J. ^[2]; ^[1]

Johns Hopkins Univ., Baltimore, MD (United States)
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

The rapid collection and indexing of electron diffraction patterns as produced via electron backscatter diffraction (EBSD) has enabled crystallographic orientation and structural determination, as well as additional property-determining strain and dislocation density information with increasing speed, resolution, and efficiency. Pattern indexing quality is reliant on the noise of the collected electron diffraction patterns, which is often convoluted by sample preparation and data collection parameters. EBSD acquisition is sensitive to many factors and thus can result in low confidence index (CI), poor image quality (IQ), and improper minimization of fit, which can result in noisy datasets and misrepresent the microstructure. In an attempt to enable both higher speed EBSD data collection and enable greater orientation fit accuracy with noisy datasets, an image denoising autoencoder was implemented to improve pattern quality. Here, we show that EBSD data processed through the autoencoder results in a higher CI, IQ, and a more accurate degree of fit. In addition, using denoised datasets in HR-EBSD cross correlative strain analysis can result in reduced phantom strain from erroneous calculations due to the increased indexing accuracy and improved correspondence between collected and simulated patterns.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); US Department of the Navy, Office of Naval Research (ONR)

Grant/Contract Number:: AC52-07NA27344

OSTI ID:: 2007284

Alternate ID(s):: OSTI ID: 1999931

Report Number(s):: LLNL--JRNL-840753; 1062335

Journal Information:: Ultramicroscopy, Journal Name: Ultramicroscopy Vol. 253; ISSN 0304-3991

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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A Denoising Autoencoder for Improved Kikuchi Pattern Quality and Indexing in Electron Backscatter Diffraction

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