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The data collected with EBSD contains a wealth of sample information which can be processed using a suite of analytical tools to visualise and represent microstructure at the micro and nano scale.

Interrogating the crystallographic orientation and phase information acquired with EBSD can then be processed to deliver information about the sample, which can be linked to the materials processing history and likely performance. Examples include

Grain Size

The mechanical and physical properties of metallic materials are closely related to grain size e.g. through the Hall- Petch relationship, where strength is inversely dependent to the square root of grain size [1]. Electron backscatter diffraction (EBSD) on a Scanning Electron Microscope (SEM) is the ideal technique for determining grain size. 

A grain is a three-dimensional crystalline volume within a sample that differs in crystallographic orientation from its surroundings but internally has little variation. Grains are identified by defining a critical misorientation angle and grain boundaries are ‘pixel pairs’ which have a misorientation higher than the critical angle. Once individual grains are detected a statistical overview of the grains in the sample can be presented, coupled with a grain map illustrating the individual grains. This data can be linked to the phases present in the map. 

Figure 1 EBSD data from a single phase steel sample.

figure 1a

(a) Grain map showing grains in random colour. Grains were detected using grain detection angle of 10 degree and minimum 100 pixels within a grain. 1378 grains are detected with mean grain diameter of 25.5μm.

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(b) Grain details and statistical summary.

In addition, grain measurement parameters can be used to visualise microstructure in a grain measurement map. This representation will highlight, for example, larger grains, or those of a specific size or shape.

Figure 2 EBSD data from a steel sample. The microstructure is not homogeneous, with a range of grain  size and shape.. The grain aspect ratio varies between 1 to 34.

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(a) A grain map shows the grain structure in the entire sample;

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(b) A grain map highlights those grains with grain aspect ratio higher than 6.

Grain Boundary Characterisation

The interface between two grains in a polycrystalline material creates a grain boundary. Grain boundaries will influence the properties of the material: typically grain boundaries are a site for the initiation of corrosion and also for the precipitation of new phases from the solid. They are also important in the mechanisms of creep. Grain boundaries can also be beneficial, and disrupt the movement of dislocations through a material, so reducing grain size, and increasing boundaries, is a way to improve mechanical strength. Techniques such as grain boundary engineering (GBE) are applied to improve material properties. As such it is important to identify and characterise different boundary types, and to understand the impact on material behaviour.

Generating a map representation of grain boundaries is powerful when visualising microstructure. Different boundary types are identified by misorientation between the two grains. Typically low angle boundaries or subgrain boundaries are those with a misorientation less than 5 degrees. High angle grain boundaries have a larger misorientation generally greater than 10 degrees. In addition, special boundaries or twin boundaries occur where the crystal lattices share a fraction of the sites on either side of the boundary. These boundaries are called coincident site lattices (CSL), and are denoted by Σ, where Σ is the ratio of the size of the CSL unit cell to the standard unit cell.  

A ‘twin limited’ microstructure, i.e. a microstructure composed entirely of special grain boundaries and triple junctions is highly resistant to intergranular degradation. These different grain boundary types are readily identified and displayed with using EBSD.

Figure 3 EBSD data from a coarse grain solar cell, area of 2.7cm by 8.2cm. The aim here is to correlate grain boundary type and distribution with sample carrier life.

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(a) EBSD IPF Z map denoting the grain orientation.

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(b) Grain boundary map illustrates the large grain size and dominance of CSL boundaries.  High angle (>10°) boundaries are in black,  Σ3 boundaries are in red, Σ9 boundaries are in blue, Σ27 boundaries are in green.

Phase Distribution and Fraction

The identification and distribution of different phases is another important application of EBSD. Phase distribution is   represented on a map, with a measure of phase fraction. A phase map is powerful in representing the spatial distribution of phases, for example useful in determining precipitates formation at grain boundaries.

Figure 4 EBSD data of a duplex steel sample showing phase distribution and fraction.

figure 4a

(a) EBSD phase map of a duplex steel sample. The microstructure contains austenite (red) and ferrite (blue) phases; it also includes intermetallic precipitation of both sigma (yellow) and chi (green) phases. These intermetallics are significant as they will degrade mechanical and corrosion properties of the material. Therefore it is important to identify them, determine their distribution and phase fraction.

figure 4b

(b) The corresponding phase fraction quantified from EBSD data.

EBSD Pattern Quality

The EBSD pattern quality parameter assigns a number to the degree of sharpness or band definition in the EBSP. Therefore the pattern quality is influenced by several factors: phase, orientation, contamination, sample preparation and the local crystalline perfection.

Figure 5 A pattern quality map for a Titanium (Ti6Al4V) sample.
Dark areas are indicative of poorer pattern quality and light areas of higher pattern quality.

figure 5a

Pattern quality maps will often reveal features invisible in the electron image such as grains, grain boundaries, internal grain structure and surface damage such as scratches. The pattern quality map is therefore very useful both during the analysis of the data and as a simple tool for checking the sample before and during analysis – in terms of focus and drift.

Orientation Data

In many materials grains do not have a completely random orientation distribution. When orientation is not random the material is said to have preferred orientation or texture. The individual crystal orientation measurements collected by EBSD can be used to show the crystallographic textures developed in the sample. The orientation information acquired from multiple points within each phase enables a statistical check whether that phase has a preferred orientation. This can be achieved by studying orientation maps or by creating pole figures.

Orientation Maps

The orientation data collected with an EBSD system is spatially displayed in either an Euler Map or a series or inverse pole figure (IPF) maps. The Euler maps give a basic presentation of microstructure. The IPF maps uses the colour from the IPF colour key, in this case the colour assigned is based on the measured orientation and the selected viewing direction. This map is good at representing preferred orientation (or texture), seen as similar or single colours in the map. The orientation data displayed in a map makes it easy to visualise and extract information about how a specific texture is spatially distributed.

Figure 6 A leaded brass sample continaing three phases: lead, α brass and β brass. EBSD illustrates phase distribution and associated texture development following thermal recovery.

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(a) Phase map. α brass in yellow, β brass in blue and lead in red.

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(b) IPF-Z map of all phases.

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(c) IPF- Z map of β brass, dominant green colour illustrates a preferred orientation present in β brass.

In addition those points in the material which have a specific texture in an EBSD map can be identified. This is a useful tool in identifying reference or ideal textures in a sample, such as Cube, GOSS or Fibre.

Figure 7 A texture map from the β brass phase shown in figure 6. A colour scheme reflects how close the data is to the ideal orientation of <110> parallel to Z direction.

figure 7a
figure 7b

Pole Figures

Pole figures are also applied for displaying texture. They enable 3D orientation data to be plotted in 2D, by converting crystallographic directions into points. This is done automatically with modern EBSD systems, with the pole figure being created being determined by the crystal structure of the phase being displayed.

Figure 8 Pole figures of β brass phase shown in figure 6 & 7.
The clustering of the data illustrates a strong <110> fibre parallel to Z direction.

figure 8a

Internal Microstructure

The orientation data measured by EBSD can be processed to illustrate different aspects of material microstructure. There are many examples of this; probably one of the most frequently used in literature is the Kernel Average Misorientation map (KAM). This is a calculation of the average misorientation between each pixel and its nearest neighbours. This map is used to study subgrain structures, which are an indication of strain which has occurred. 

Figure 9 A Ni sheet used in the manufacture of gas pipelines is bent as part of the manufacturing process.  
The KAM Map indicates where there is a high level of misorientation in the sample, shown by the green / yellow colour.
It illustrates the areas of tensile and compressive strain.

figure 9a
figure 9b
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