Multivariate statistical approach to electron backscattered diffraction

Luke N Brewer; Paul G Kotula; Joseph R Michael

doi:10.1016/j.ultramic.2007.10.013

Multivariate statistical approach to electron backscattered diffraction

Ultramicroscopy. 2008 May;108(6):567-78. doi: 10.1016/j.ultramic.2007.10.013. Epub 2007 Nov 1.

Authors

Luke N Brewer¹, Paul G Kotula, Joseph R Michael

Affiliation

¹ Sandia National Laboratories, P.O. Box 5800-MS 1411, Albuquerque, NM 87185-1411, USA. lnbrewe@sandia.gov

PMID: 18077093
DOI: 10.1016/j.ultramic.2007.10.013

Abstract

This paper assesses the potential of multivariate statistical analysis (MSA) applied to electron backscattered diffraction (EBSD) data. Instead of directly indexing EBSD patterns on an individual basis, this multivariate approach reduces a large (thousands) set of individual EBSD patterns into a core set of statistically derived component EBSD patterns which can be subsequently indexed. The following hypotheses are considered in this paper: (1) experimental EBSD patterns from a microstructure can be analytically treated as linear combinations of spatially simple components, (2) MSA has an angular resolution on par with standard EBSD, (3) MSA can discriminate between similar and dissimilar phases, and (4) the MSA approach can improve the effective spatial resolution of automated EBSD.