Literature DB >> 20888125

Factors affecting the accuracy of high resolution electron backscatter diffraction when using simulated patterns.

T B Britton1, C Maurice, R Fortunier, J H Driver, A P Day, G Meaden, D J Dingley, K Mingard, A J Wilkinson.   

Abstract

High resolution EBSD directly compares electron backscattering patterns (EBSPs), generated in a scanning electron microscope, to measure relative strain and rotation to a precision of ∼ 10(-4) in strain and 10(-4)rad (0.006 °) in rotation. However the measurement of absolute strain and rotation requires reference EBSPs of known strain and orientation (or a far field region of known strain). Recent suggestions of using simulated EBSPs with known strain show much promise. However precise measurement of the experimental geometry (pattern centre) is required. Common uncertainties of 0.5% in pattern centre result in uncertainty of ∼ 10(-3) in strain state. Aberrations in the compact lenses used for EBSP capture can also result in image shifts that correspond to strains/rotations of ± 10(-3) between experimental and simulated EBSPs. Simulated EBSPs can be generated using dynamical or kinematic models (or a combination of the two). The choice in simulation model has a significant effect on the measured shifts, particularly at zone axis and high structure factor bands, due to large intensity variations, and for simple kinematic simulations can result in the measurement of rogue shifts and thus erroneous strain measurements. Calibrant samples of known strain provide a method of measuring the experimental geometry but imprecise stage movement combined with the high depth of field in the SEM could also result in uncertainties in strain of ∼ 10(-3).
Copyright © 2010 Elsevier B.V. All rights reserved.

Entities:  

Year:  2010        PMID: 20888125     DOI: 10.1016/j.ultramic.2010.08.001

Source DB:  PubMed          Journal:  Ultramicroscopy        ISSN: 0304-3991            Impact factor:   2.689


  4 in total

1.  New levels of high angular resolution EBSD performance via inverse compositional Gauss-Newton based digital image correlation.

Authors:  T J Ruggles; G F Bomarito; R L Qiu; J D Hochhalter
Journal:  Ultramicroscopy       Date:  2018-08-29       Impact factor: 2.689

2.  Efficient few-shot machine learning for classification of EBSD patterns.

Authors:  Kevin Kaufmann; Hobson Lane; Xiao Liu; Kenneth S Vecchio
Journal:  Sci Rep       Date:  2021-04-14       Impact factor: 4.379

3.  Characterization by Scanning Precession Electron Diffraction of an Aggregate of Bridgmanite and Ferropericlase Deformed at HP-HT.

Authors:  B C Nzogang; J Bouquerel; P Cordier; A Mussi; J Girard; S Karato
Journal:  Geochem Geophys Geosyst       Date:  2018-03-02       Impact factor: 3.624

4.  Simulation of kinematic Kikuchi diffraction patterns from atomistic structures.

Authors:  Adam D Herron; Shawn P Coleman; Khanh Q Dang; Douglas E Spearot; Eric R Homer
Journal:  MethodsX       Date:  2018-09-06
  4 in total

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