# Slip Transmition

How to analyse slip transmission at grain boundaries

 On this page ... Import Titanium data Taylor model

## Import Titanium data

From Mercier D. - MTEX 2016 Workshop - TU Chemnitz (Germany) Calculation and plot on GBs of m' parameter Dataset from Mercier D. - cp-Ti (alpha phase - hcp)

```mtexdata csl

% compute grains
[grains, ebsd.grainId] = calcGrains(ebsd('indexed'));

% make them a bit nicer
grains = smooth(grains);

% extract inner phase grain boundaries
gB = grains.boundary('indexed');

plot(ebsd,ebsd.orientations)
hold on
plot(grains.boundary)
hold off``` ## Taylor model

```% consider Basal slip
sS = slipSystem.fcc(ebsd.CS)

% and all symmetrically equivalent variants
sS = sS.symmetrise;

% consider plane strain
q = 0.5;
eps = strainTensor(diag([-q 1 -(1-q)]));

% and compute Taylor factor as well as the active slip systems
[M,b,ori] = calcTaylor(inv(grains.meanOrientation).*eps,sS);```
```
sS = slipSystem
mineral: iron (m-3m)
size: 1 x 1
u    v    w  | h    k    l CRSS
0    1   -1    1    1    1    1
computing Taylor factor: 100%
```
```% find the maximum
[~,id] = max(b,[],2);```

The variable id contains now for each grain the id of the slip system with the largest Schmidt factor. In order to visualize it we first rotate for each grain the slip system with largest Schmid factor in specimen coordinates

```sSGrain = grains.meanOrientation .* sS(id)

% and plot then the plance normal and the Burgers vectors into the centers
% of the grains

plot(grains,M)

largeGrains = grains(grains.grainSize > 10)

hold on
quiver(grains,cross(sSGrain.n,zvector),'displayName','slip plane')
hold on
quiver(grains,sSGrain.b,'displayName','slip direction')
hold off```
```
sSGrain = slipSystem
size: 885 x 1

largeGrains = grain2d

Phase  Grains  Pixels  Mineral  Symmetry  Crystal reference frame
-1     442  153261     iron      m-3m

boundary segments: 21799
triple points: 1444

Properties: GOS, meanRotation

``` We may also analyse the distribution of the slip directions in a pole figure plot

`plot(sSGrain.b)` The same as a contour plot. We see a clear trend towards east.

`plot(sSGrain.b,'contourf')` 