3D-EBSD data and analysis of Ti-6Al-4V fabricated using electron powder bed fusion with a random scan strategy (R3)

Published: 9 July 2021| Version 1 | DOI: 10.17632/c5x7ckcfsp.1


This data is a companion to the manuscript '3D Electron backscatter diffraction characterization of fine α titanium microstructures: collection, reconstruction, and analysis methods', by Ryan DeMott, Nima Haghdadi, Charlie Kong, Ziba Gandomkar, Matthew Kenney, Peter Collins, and Sophie Primig, currently submitted to Ultramicroscopy. It includes the raw data and code used for analysis of a slightly truncated version of the 'random' dataset which appears in that manuscript as well as DeMott, R., Haghdadi, N., Gandomkar, Z. et al. 3D characterization of microstructural evolution and variant selection in additively manufactured Ti-6Al-4 V. J Mater Sci 56, 14763–14782 (2021). https://doi.org/10.1007/s10853-021-06216-2 and DeMott, R., Haghdadi, N., Liao, X. et al. Formation and 3D Morphology of Interconnected α Microstructures in Additively Manufactured Ti-6Al-4V. Acta mater. In Review. Please cite the above publications and acknowledge the authors if using this data or code in your own work. The files include the raw EBSD scans as a library of .ctf files, the pipeline for reconstructing and analyzing the data using the DREAM.3D software package, and the code used for performing further analysis of the data with the MTEX toolbox for MATLAB. DREAM.3D v6.5.138 , MATLAB R2019b, and MTEX v5.1.1 were the software versions used. RandomCTFFiles.zip contains the library of .ctf files The DREAM3D pipelines include ImportCTFLibrary.json, which generates an H5EBSD file from the ctf library and FullReconstruction.json, which includes all of the steps described in chapter 4 of the manuscript. A new user may find it easier to split it into several shorter pipelines with outputs at each step. The MTEX code folder includes all of the MATLAB functions and scripts used for the analyses described in chapter 5 of the manuscript. AssignBoundaryTypes.m is a function which uses a .dream3d file path and tolerance to classify intervariant boundary types as described in section 5.1 TripleJunctByNodes.m is a script which uses the functions AssignBoundaryTypes.m and TriadPlot.m to classify and plot three-variant clusters in terms of triple junctions as described in section 5.1 (figure 10a) PlotTriads.m is a script which uses the functions findTriads.m, AssignBoundarTypes.m, and TriadPlot.m to classify and plot three-variant clusters in terms of mutally neighboring grains as described in section 5.2 (figure 10b) NewAssignVariants.m is a script for assigning grains to variants as described in section 5.3