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Title: A physics-based model for crystal orientation dictionary indexing by directional reflectance microscopy
Authors: Zhu, Chenyang
Seita, Matteo
Keywords: Engineering::Mechanical engineering
Issue Date: 2022
Source: Zhu, C. & Seita, M. (2022). A physics-based model for crystal orientation dictionary indexing by directional reflectance microscopy. Acta Materialia, 231, 117863-.
Project: MOE2017-T2–2-119
Journal: Acta Materialia
Abstract: Directional reflectance microscopy (DRM) is a new optical technique that enables grain orientation mapping in crystalline solids by capturing and analyzing light reflectance signals generated by chemically etched surfaces. Currently, orientation indexing by DRM relies on fitting the optical signals to identify user-defined features that carry orientation information. This approach is inevitably error-prone and material-dependent. These shortcomings hinder the adoption of DRM as a universal characterization method in materials science. We propose a new indexing method to improve the robustness and versatility of DRM. Our method relies on building a dictionary of all possible reflectance signals generated by a metal, which we simulate using a physics-based forward model that takes crystal orientation as input. We then compare each measured reflectance signal acquired by DRM to all the entries in the dictionary in search of the best match, and thus the correct crystal orientation. We demonstrate our dictionary indexing DRM (DI-DRM) approach on nickel and aluminum polycrystals, which produce markedly different optical reflectance signals. We find that DI-DRM yields measurements with improved accuracy compared to those enabled by fitting the optical signal on both materials and across all crystal orientations considered. We also show that the measurement error (∼3°) is mildly sensitive to experimental variability, including noise, measurement settings, and sample surface preparation. DI-DRM represents a considerable step forward towards the implementation of DRM as a streamline materials characterization technique.
ISSN: 1359-6454
DOI: 10.1016/j.actamat.2022.117863
Rights: © 2022 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
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