Analytical
An
Introduction to EBSD
Keith Dicks MSc
EBSD Specialist
Oxford Instruments Analytical
High Wycombe
England
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EBSD
EBSD = Electron Back Scatter Diffraction which
allows:
• Crystallographic Orientations
• Misorientations
• Texture measurement
• Grain size and boundary types
• Phases
To be characterised and quantified on a macro to submicron or nano-meter scale
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What does EBSD Contribute to Materials Analysis?
• EDS/WDS - Chemical analysis
– i.e. What the sample is made from
• EBSD - Microstructural analysis
– Polycrystalline materials
• Grain Structure - size/distribution, ASTM number etc.
• Grain Boundary Characteristics
• Macro & Micro-Crystallographic Texture
• Phase Discrimination and distribution
• Deformation
– Single Crystal materials/deposited layers
• Crystal orientation
• Epitaxy between layers
– i.e. How the sample is put together and what condition it is in
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Typical Applications
•
•
•
Metals
– Metal production i.e. sheet metal, castings, forgings - automotive,
aerospace, power generation and distribution, petrochemical and
chemical plant, nuclear i.e. extreme duty materials - high strength,
high temperature and corrosive environments. Electronics.
– Phase identification and discrimination
– Texture analysis, grain boundary characterisation
– Deformation
Geological
– Phase identification and discrimination
– Orientation & texture analysis
Ceramics
– Phase identification and discrimination
– Orientation & texture analysis
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Typical Areas of Investigation
• Production and process control
– Cost savings - reduce heat treatment times, optimise heat
treatment and phase transformation, investigate grain size,
grain boundary and texture evolution
– Improved product i.e. surface finish, forming or joining
characteristics, process optimisation & control
– Control physical properties - improve or achieve specific
properties i.e. high corrosion resistance, fatigue or cracking
(stress corrosion cracking) resistance.
• Component life-time prediction
– Characterise microstructure - identify problem phases or
microstructural feature
• Failure Analysis
– Investigate micrstructural features associated with failure and
propose failure mechanism
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Schematic Layout of EBSD System
• Schematic layout
of components
• PC and Imaging
hardware
common for
INCA Energy
and Wave
• Market leading
EBSD, EDS &
WDS all from
one vendor
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‘Nordlys’EBSD Detector
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Comparison of conventional and advanced EBSD hardware design
Conventional
‘open bracket’
design
Advanced ‘in tube’ design
Tube length
does not
affect
efficiency
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EBSD hardware - configurable collection geometry
X-Rays
Incident
beam
Backscatter
Diffracted
Electrons
Camera position control unit
• Revolutionary high efficiency, fast detector
with rectangular phosphor and multiple FSE
detectors
Forward
Scattered
Electrons
• Motorized insertion/retraction with no
constraints on working geometry
• Can be optimised for short WD or to avoid
occluding other detectors
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Forward Scattered Electron (FSE) Imaging
• FSE greatly
enhances
diffraction
contrast in
imaging
• Grains and
grain
boundaries
are clearly
revealed
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FSE Imaging using a single detector
• Nickel
• Austenitic
Stainless
Steel
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Forescatter Detector Option
• For orientation, phase
contrast imaging at high
tilt
• Two, four or six diodes –
may be retrofitted or
moved by user
• BSE, FSE or mixed
mode detection
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Multiphase rock (gabbro)
BSE Image – Density (phase)
contrast
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OC (FSD) Image – Channeling contrast
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Forescatter gallery
Calcite (Dave Prior, Liverpool)
Welded superalloy (NPL)
100µm
100µm
Zircon grain
Deformed superalloy
Plagioclase
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EBSP Formation
•
•
•
•
•
•
The electron beam strikes the
specimen
Scattering produces backscatter
electrons in all directions, most
intensely downward & outward
Electrons that travel along a
crystallographic plane trace
generate Kikuchi bands whose
widths are dictated by the Bragg
Law and specimen-to-phosphor
screen distance.
The electrons hit the imaging
phosphor and produce light
The light is detected by a CCD/SIT
camera and converted to an image
Which is indexed...
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Diffraction
λ = 12.26 ∗ Ε-1/2
E = incident
beam energy in
volts
θ
d
Extra path length
= 2d sinθ
For 20 kV and a
plane spacing of
0.2 nm, the Bragg
angle, θ,is about
1.25°.
Constructive interference occurs when the extra path length is an integral number of
wavelengths.
Bragg’s Law nλ=2d sinθ
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EBSP formation
(022)
(202)
7 0°
(220)
S ilicon
Phosphor screen
Spherical
Kikuchi map
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c
a
{100}{200}
[001]
(011)
{110}
b
[100]
!
[011]
[010]
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What does an EBSP look like?
Silicon at 20kV
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Hi-res EBSP - Si 20kV
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From EBSP to Orientation
EBSP
Hough ‘space’
•
•
‘solve’
Hough Peaks found
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EBSP Bands detected
‘Matching’ algorithm
compares detected
bands with those
calculated from the
crystal structure for the
phase(s) of interest
EBSP ‘solved’ or
‘indexed’ to find
orientation of crystal
under the beam
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Analytical
!
"
Band Detection
#
Reflector Calculation
• List of angular relationships
between detected bands
For each potential phase, list of
allowed reflections, diffraction
band widths and intensity
hierarchy generated from
kinematic electron diffraction
theory or reflector list is loaded.
Also, for reflections above an
intensity cutoff, interband angles
are calculated.
• Band positions on phosphor
screen
• Other information also
extracted (e.g. band widths)
• Highest intensity bands most
likely to be detected
Match?
Yes
Phase discriminated
Orientation determined
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Indexing cycle
Position beam
Collect EBSP
Phase and
orientation
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Verify match:
Indexed EBSP
Hough transform
& band detection
Match to phase & orientation
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Mapping
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From EBSP to Crystal Orientation Map
•
•
•
•
•
•
•
COM with Inverse Pole
key for cubic material
Red = 100
Green = 110
Blue = 111 planes
parallel to the surface
Orientation obtained at every pixel
Colour derived from inverse Pole Figure
color key or Euler angles
Hough transform for every pixel stored for
post acquisition reprocessing
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Factors affecting EBSP Quality
Electron Back Scattered Patterns (EBSP’s)
vary greatly...
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EBSP ‘Background’
•
Only a small proportion of the electrons arriving at the phosphor screen are
diffracted.
•
Therefore the pattern is superimposed on a ‘background’
• Background removal
is required to enhance
pattern contrast
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Enhancing EBSP Contrast - Background
Removal
Fe 20kV raw EBSP
•
•
70% Background
subtracted
Background
Divided
EBSP contrast enhanced by background subtraction or division
Particularly useful in lighter atomic number materials or when pattern
quality (contrast) is low
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Accelerating Voltage - Effect of kV on Pattern Quality
Nickel 10kV
Nickel 20kV
Nickel 30kV
• Bands are broader and less sharp at low kV
• Band detection can be influenced by Hough parameters
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$ %
Sampling selection on fracture surface or free sediment
& Operator must search for locations where local topography &
damage level allow clear patterns to reach detector
• FIB-SEM allows precision selection of areas for sectioning &
mapping
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Examples of EBSPs
Al
alpha-Fe
Ge
W2Zr
Gamma-Fe
Ni
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Examples of EBSPs
GaSb
BaTiO3
(6kV)
GaP
InP
beta-Si3N4
YBa2Cu3O
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Examples of EBSPs
MgSiO3
Fe2SiO
Mg2SiO4
4
Pyroxene
Calcite
Ca(CO3)
Olivine
Garnet
Ca3Fe2(SiO4)3
Fe2NiP
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Analytical
Seven crystal systems
•
Cubic (Al, Fe)
& '
"(
'
#
&
")
#
& *
"
+'
#
&
"/
#
& '
",
-#
& '
".
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#
An
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Analytical
7 Crystal Symmetry Systems
Cubic
Orthorhombic
Hexagonal
Triclinic
Trigonal
Monoclinic
Tetragonal
• Examples of
all seven
crystal
systems
solved
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Summary of Factors Affecting Pattern Quality
Acquisition conditions affect the EBSP:
•
•
•
•
•
•
•
•
•
Band width varies with kV
Band contrast varies with kV
Band sharpness varies with kV
Camera Sensitivity (‘binning’
level/resolution)
Background removal
Integration time
Beam current (spot size) &
current density
Vacuum level
Microscope
resolution/aberrations
Sample conditions affect the EBSP:
•
•
•
•
•
•
•
Atomic number
Grain size
Preparation damage/residues
– surface contamination e.g.
carbon from SEM
Surface oxidation or reaction
products
Surface morphology
Surface coatings
Amorphised surface - ion milling
The Hough Transform can be configured to optimize band detection for a wide
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Basic Modes of Operation
1. Point Analysis
2. Mapping
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Phase Discrimination
01
!
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Phase Discrimination by
EBSD
Kyanite
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Ilmenite
Muscovite
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Mapping
General Examples
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Visualisation of data - general microstructure
Quartzite
=100 µm; BC+E1-3; Step=1 µm; Grid298x216
3
1
3
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Ni Superalloy
=100 µm; GB10; Step=1 µm; Grid389x286
Band Contrast + Grain Boundaries (high angle – general)
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$
=100 µm; BC+GB10+SB; Step=1 µm; Grid389x286
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Band Contrast + Grain Boundaries + Twins/CSLs
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Cu thin film
0
3
1
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Cu thin film
34
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4
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Ta sputter target
IPF-based orientation + pattern quality map
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5
4
-
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0
Duplex Steel
=100 µm; Ma p4; Ste p=0.75 µm; Grid600x450
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0
5
Non-preheated
Preheated
Phase maps (+ GBs): red = ferrite, blue = austenite
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4
- 0
Unlike optical line-intercept GS analysis,
twin boundaries and low-angle grain boundaries
are positively identified and filtered from the data (if
desired); tricky GB etch techniques not necessary;
weaknesses of relying on reflected light orientation
contrast are avoided
(
!
Data available as text and in graphical format
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4
0
Aspect Ratios
Major Axis Orientation
=25 µm; BC+GB+DT+E1-3; Ste p=0.7 µm; Grid200x200
=25 µm; Map4; Step=0.7 µm; Grid200x200
=25 µm; Ma p5; Ste p=0.7 µm; Grid200x200
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0
6
-
%
5
7'
8
9
76
1
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(7
$7
5 + 7
07
"4 46 #
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0
%!
4
6
B
A
*
5
Misorientations
relative to 1st
data point
Misorientation / degrees
A
4
3
Misorientations
between adjacent
data points
2
B
1
0
0
100
200
300
400
500
Distance / microns
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0
%
5
$%
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0
• Isolate
grains by
strain
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Rolled Mo
Sheet
Strain (grain average misorientation) distribution map
Red = deformed
Blue = Recrystallized
Strain (grain average misorientation) classification map
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Rolling & heat
treatment of Fe-Al
binary alloy resulted
in a partly deformed,
partly recrystallized
microstructure
Grains subgrouped
by residual strain
state:
Red deformed,
blue recrystalllized
6
-
Texture
‘partitioning’
revealed
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:
=500 µm; BC; S te p=1 µm; Grid1196x198
=500 µm; BC+MIS -5; S te p=1 µm; Grid1196x198
Disorientation angle (degrees)
Each orientation is surrounded by 8 nearest neighbors.
The disorientation is calculated through all of the 8
nearest neighbors to get an averaged value.
gij = gi
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gj-1
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:
Cu
Relative to selected
reference point
(cumulative rotation)
For each pixel, relative to
surrounding pixels
(local rotation)
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:
Ta sputter target
Strain localization + GB map
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Texture Analysis
Pole Figures
Inverse Pole Figures
ODF
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'
0
Quartzite
=100 µm; BC+GB+DT+E1-3; Ste p=1 µm; Grid297x227
8
9
;<<<=>
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'
0
!?
001
6
X0
0
111
101
Y0
Inverse Pole X0
Figure s
001
(Folded)
Inve rse Pole Figure s
(Folde d)
[Alumin.cpr]
Aluminium (m3m)
Complete data set
40000 data points
Equa l Are a proje ction
Upper he mispheres 111
[Alumin.cpr]
Aluminium (m3m)
Complete data set
40000 data points
Equal Area proje ction
Uppe r hemisphere s
101
Y0
Half width:10°
Cluste r size:5°
Exp. densitie s (mud):
Min= 0.00, Ma x= 5.99
1
2
3
4
5
Z0
Z0
1
2
=25 µm; E1-3; Ste p=0.7 µm; Grid200x200
3
4
5
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'
0
"
φ2 =0 °
φ2 =5 °
φ2 =1 0 °
φ2 =1 5 °
φ2 =2 0 °
φ2 =2 5 °
φ2 =3 0 °
φ2 =3 5 °
φ2 =4 0 °
φ2 =4 5 °
φ2 =5 0 °
φ2 =5 5 °
φ2 =6 0 °
φ2 =6 5 °
φ2 =7 0 °
φ2 =7 5 °
#
=100 µm; BC+GB+DT+E1-3; Ste p=1 µm; Grid297x227
φ1 =9 0 °
1
1 .5
2
2 .5
Φ =9 0 °
φ2 =8 0 °
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φ2 =8 5 °
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Thank you
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