Open Matlab File in the Editor MTEX

Short EBSD Analysis Tutorial

How to detect grains in EBSD data and estimate an ODF.

Import EBSD data

The following script is automatically generated by the import wizard.

% crystal symmetry
CS = {...
  'Not Indexed',...
  crystalSymmetry('m-3m','mineral','Fe'),...
  crystalSymmetry('m-3m','mineral','Mg')};

% specify file name
fname = fullfile(mtexDataPath,'EBSD','85_829grad_07_09_06.txt');


% create an EBSD variable containing the data
ebsd = loadEBSD(fname,'CS',CS,'interface','generic' ...
  , 'ColumnNames', ...
  { 'Index' 'Phase' 'x' 'y' 'Euler1' 'Euler2' 'Euler3' 'MAD' 'BC' 'BS' 'Bands' 'Error' 'ReliabilityIndex'}, ...
  'ignorePhase', 0);

% plotting convention
plotx2east

Visualize the data

First we make a spatial plot of the orientations of the crystals of phase 1

plot(ebsd('Fe'))

The colorcoding can be interpreted by the collored (0,0,1) inverse pole figure

oM = ipdfHSVOrientationMapping(ebsd('Fe'))
plot(oM)
 
  Hint: You might want to use the point group
  "432" for colorcoding!
 
oM = 
  ipdfHSVOrientationMapping handle

  Properties:
    inversePoleFigureDirection: [1x1 vector3d]
                           CS1: [24x2 crystalSymmetry]
                           CS2: [1x1 specimenSymmetry]
             colorPostRotation: [1x1 rotation]
               colorStretching: 1
                   whiteCenter: [1x1 vector3d]
                            sR: [1x1 sphericalRegion]

Grain reconstruction

Next we reconstruct the grains within our measurements.

grains = calcGrains(ebsd)
 
grains = grain2d  
 
 Phase  Grains  Mineral  Symmetry  Crystal reference frame  Phase
     1     866       Fe      m-3m                                
     2     462       Mg      m-3m                                
 
 Properties: GOS, meanRotation
 

and plot them into our orientation plot

plot(ebsd('Fe'))
hold on
plot(grains.boundary,'linewidth',1.5)

One can also plot all the grains together with their mean orientation

plot(grains('Fe'))

ODF estimation

Next we reconstruct an ODF from the EBSD data. Therefore, we first have to fix a kenel function. This can be done by

psi = calcKernel(grains('Fe').meanOrientation)
 e 
psi = deLaValeePoussinKernel  
  bandwidth: 62
  halfwidth: 4.7°
 

Now the ODF is reconstructed by

odf = calcODF(ebsd('Fe').orientations,'kernel',psi)
 
odf = ODF  
  crystal symmetry : Fe (m-3m)
  specimen symmetry: 1
 
  Radially symmetric portion:
    kernel: de la Vallee Poussin, halfwidth 4.7°
    center: 2063 orientations, resolution: 2.4°
    weight: 1
 

Once an ODF is estimated all the functionallity MTEX offers for ODF analysis and ODF visualisation is available.

plotPDF(odf,[Miller(1,0,0,CS{2}),Miller(1,1,0,CS{2}),Miller(1,1,1,CS{2})],...
  'antipodal','silent')