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Determining Grain Boundary Position and Geometry from EBSD Data: Limits of Accuracy

Published online by Cambridge University Press:  15 November 2021

David T. Fullwood*
Affiliation:
Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USA
Sarah Sanderson
Affiliation:
Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USA
Sterling Baird
Affiliation:
Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USA
Jordan Christensen
Affiliation:
Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USA
Eric R. Homer
Affiliation:
Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USA
Oliver K. Johnson
Affiliation:
Department of Mechanical Engineering, Brigham Young University, Provo, UT 84602, USA
*
*Corresponding author: David T. Fullwood, E-mail: dfullwood@byu.edu
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Abstract

As the feature size of crystalline materials gets smaller, the ability to correctly interpret geometrical sample information from electron backscatter diffraction (EBSD) data becomes more important. This paper uses the notion of transition curves, associated with line scans across grain boundaries (GBs), to correctly account for the finite size of the excitation volume (EV) in the determination of the geometry of the boundary. Various metrics arising from the EBSD data are compared to determine the best experimental proxy for actual numbers of backscattered electrons that are tracked in a Monte Carlo simulation. Consideration of the resultant curves provides an accurate method of determining GB position (at the sample surface) and indicates a significant potential for error in determining GB position using standard EBSD software. Subsequently, simple criteria for comparing experimental and simulated transition curves are derived. Finally, it is shown that the EV is too shallow for the curves to reveal subsurface geometry of the GB (i.e., GB inclination angle) for most values of GB inclination.

Type
Software and Instrumentation
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of the Microscopy Society of America

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References

Basinger, J (2011). Detail Extraction from Electron Backscatter Diffraction Patterns. Provo: Mechanical Engineering Department, Brigham Young University.Google Scholar
Basinger, J, Fullwood, D, Adams, B & Kacher, J (2009). Improving spatial and grain boundary inclination resolution through EBSD pattern separation and deconvolution. Pittsburgh: MS&T.Google Scholar
Chen, D & Kuo, J-C (2013). The effect of atomic mass on the physical spatial resolution in EBSD. Microsc Microanal 19(S5), 47. doi:10.1017/S143192761301221XCrossRefGoogle ScholarPubMed
Chen, D, Kuo, JC & Wu, WT (2011). Effect of microscopic parameters on EBSD spatial resolution. Ultramicroscopy 111(9–10), 14881494. doi:10.1016/j.ultramic.2011.06.007CrossRefGoogle ScholarPubMed
Dingley, D (2004). Progressive steps in the development of electron backscatter diffraction and orientation imaging microscopy. J Microsc 213(3), 214224. doi:10.1111/j.0022-2720.2004.01321.xCrossRefGoogle ScholarPubMed
Gulsoy, E, Simmons, J & Graef, MD (2009). Application of joint histogram and mutual information to registration and data fusion problems in serial sectioning microstructure studies. Scr Mater 60, 381384. doi:10.1016/j.scriptamat.2008.11.004CrossRefGoogle Scholar
Hall, EO (1954). Twinning and Diffusionless Transformations in Metals. London: Butterworth & Co.Google Scholar
Hjelen, J & Nes, E (1990). Spatial resolution measurements of electron backscatter diffraction patterns (EBSPs) in the scanning electron microscope. In Proceedings of the XIIth International Congress for Electron Microscopy, Peachey LD & Williams DB (Eds.), pp. 404–405. San Francisco Press.CrossRefGoogle Scholar
Humphreys, FJ (2004). Characterisation of fine-scale microstructures by electron backscatter diffraction (EBSD). Scr Mater 51, 771776. doi:10.1016/j.scriptamat.2004.05.016CrossRefGoogle Scholar
Humphreys, FJ, Huang, Y, Brough, I & Harris, C (1999). Electron backscatter diffraction of grain and subgrain structures - Resolution considerations. J Microsc 195(3), 212216. doi:10.1046/j.1365-2818.1999.00579.xCrossRefGoogle ScholarPubMed
Isabell, TC & Dravid, VP (1997). Resolution and sensitivity of electron backscattered diffraction in a cold field emission gun SEM. Ultramicroscopy 67, 5968. doi:10.1016/S0304-3991(97)00003-XCrossRefGoogle Scholar
Joy, DC (1991). Contrast in high-resolution scanning electron microscope images. J Microsc 161(2), 343355. doi:10.1111/j.1365-2818.1991.tb03095.xCrossRefGoogle Scholar
Joy, DC (1995). Monte Carlo Modeling for Electron Microscopy and Microanalysis. Oxford: Oxford University Press.Google Scholar
Joy, DC & Pawley, JB (1992). High-resolution scanning electron microscopy. Ultramicroscopy 47, 80100. doi:10.1016/0304-3991(92)90186-NCrossRefGoogle ScholarPubMed
Kacher, J, Landon, C, Adams, BL & Fullwood, D (2009). Bragg's law diffraction simulations for electron backscatter diffraction analysis. Ultramicroscopy 109(9), 11481156. doi:10.1016/j.ultramic.2009.04.007CrossRefGoogle ScholarPubMed
Krieger-Lassen, NC, Conradsen, K & Jensen, DJ (1992). Image processing procedures for analysis of electron back scattering patterns. Scanning Microsc 6, 115121.Google Scholar
Leavers, VF (1992). Shape Detection in Computer Vision Using the Hough Transform. New York: Springer-Verlag.CrossRefGoogle Scholar
Nolze, G (2016). Geometrically caused image distortion effects and their influence on interpretation of EBSD measurements. Mater Sci Technol 22(11), 13431351. doi:10.1179/174328406X130894CrossRefGoogle Scholar
Nowell, M, Anderhalt, R, Nylese, T, Eggert, F, De Kloe, R, Schleifer, M & Wright, S (2011). Improved EDS performance at EBSD geometry. Microsc Microanal 17(S2), 398399. doi:10.1017/S1431927611002868CrossRefGoogle Scholar
Reimer, L (1985). Scanning Electron Microscopy, Physics of Image Formation and Microanalysis. Berlin: Springer-Verlag.CrossRefGoogle Scholar
Ren, SX, Kenik, EA, Alexander, KB & Goyal, A (1998). Exploring spatial resolution in electron back-scattered diffraction experiments via Monte Carlo simulation. Microsc Microanal 4, 1522. doi:10.1017/S1431927698980011CrossRefGoogle ScholarPubMed
Sorensen, C, Basinger, JA, Fullwood, DT & Nowell, MM (2014). Full grain boundary character recovery from 2D EBSD data. Met Trans A 45(9), 41654172. doi:10.1007/s11661-014-2345-7Google Scholar
Steinmetz, D & Zaefferer, S (2010). Towards ultra-high resolution EBSD by low accelerating voltage. Mater Sci Technol 26, 640645. doi:10.1179/026708309X12506933873828CrossRefGoogle Scholar
Tong, V, Jiang, J, Wilkinson, AJ & Britton, TB (2015). The effect of pattern overlap on the accuracy of high resolution electron backscatter diffraction measurements. Ultramicroscopy 155, 6273. doi:10.1016/j.ultramic.2015.04.019CrossRefGoogle ScholarPubMed
Tripathi, A & Zaefferer, S (2019). On the resolution of EBSD across atomic density and accelerating voltage with a particular focus on the light metal magnesium. Ultramicroscopy 207, 112828. doi:10.1016/j.ultramic.2019.112828CrossRefGoogle ScholarPubMed
Winkelmann, A (2010). Principles of depth-resolved Kikuchi pattern simulation for electron backscatter diffraction. J Microsc 239(1), 3245. doi:10.1111/j.1365-2818.2009.03353.xCrossRefGoogle ScholarPubMed
Wright, S, Nowell, M, De Kloe, R & Chan, L (2014). Orientation precision of electron backscatter diffraction measurements near grain boundaries. Microsc Microanal 20(3), 852863. doi:10.1017/S143192761400035XCrossRefGoogle ScholarPubMed