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3D electron backscatter diffraction characterization of fine α titanium microstructures: collection, reconstruction, and analysis methods
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1-s2.0-S0304399121001741-main.pdf | Published version | 20.43 MB | Adobe PDF | View/Open |
Title: | 3D electron backscatter diffraction characterization of fine α titanium microstructures: collection, reconstruction, and analysis methods |
Authors: | DeMott, R Haghdadi, N Kong, C Gandomkar, Z Kenney, M Collins, P Primig, S |
Item Type: | Journal Article |
Abstract: | 3D electron backscatter diffraction (3D-EBSD) is a method of obtaining 3-dimensional crystallographic data through serial sectioning. The recent advancement of using a Xe+ plasma focused ion beam for sectioning along with a complementary metal-oxide semiconductor based EBSD detector allows for an improvement in the trade-off between volume analyzed and spatial resolution over most other 3D characterization techniques. Recent publications from our team have focused on applying 3D-EBSD to understand microstructural phenomena in Ti-6Al-4V microstructures as a function of electron beam scanning strategies in electron beam powder bed fusion additive manufacturing. The microstructures resulting from this process have fine features, with α laths as small as 1 μm interwoven in a highly complex fashion, presenting a significant challenge to characterize. Over the course of these fundamental works, we have developed best-practice 3D-EBSD collection protocols and advanced methods for 3D data reconstruction and analysis of such microstructures which remain unpublished. These methods may be of interest to the 3D materials characterization community, especially considering the lack of standard commercial software tools. Thus, the current paper elaborates on the methods and analysis used to characterize fine titanium microstructures using 3D-EBSD and presents a detailed description of the new algorithms developed for probing the unique features therein. The new analyses include algorithms for identifying intervariant boundary types, classifying three-variant clusters, assigning grains to variants, and quantifying interconnectivity of branched α platelets. |
Issue Date: | Nov-2021 |
Date of Acceptance: | 20-Sep-2021 |
URI: | http://hdl.handle.net/10044/1/110814 |
DOI: | 10.1016/j.ultramic.2021.113394 |
ISSN: | 0304-3991 |
Publisher: | Elsevier BV |
Journal / Book Title: | Ultramicroscopy |
Volume: | 230 |
Copyright Statement: | © 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
Publication Status: | Published |
Article Number: | 113394 |
Online Publication Date: | 2021-09-26 |
Appears in Collections: | Materials |
This item is licensed under a Creative Commons License