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ava i l ab l e a t www.sc i enced i rec t . com

Tutorial review

Electron backscatter diffraction: Strategies for reliable dataacquisition and processing

Valerie Randle⁎

Materials Research Centre, School of Engineering, Swansea University, Swansea SA2 8PP, UK

A R T I C L E D A T A

⁎ Tel.: +44 1792 295841; fax: +44 1792 295676E-mail address: v.randle@swansea.ac.uk.

1044-5803/$ – see front matter © 2009 Elsevidoi:10.1016/j.matchar.2009.05.011

A B S T R A C T

Article history:Received 18 March 2009Received in revised form 18May 2009Accepted 20 May 2009

In electron backscatter diffraction (EBSD) software packages there are many user choicesboth in data acquisition and in data processing and display. In order to extract maximumscientific value from an inquiry, it is helpful to have some guidelines for best practice inconducting an EBSD investigation. The purpose of this article therefore is to address selectedtopics of EBSD practice, in a tutorial manner. The topics covered are a brief summary on theprinciples of EBSD, specimen preparation, calibration of an EBSD system, experimentdesign, speed of data acquisition, data clean-up, microstructure characterisation (includinggrain size) and grain boundary characterisation. This list is not meant to cover exhaustivelyall areas where EBSD is used, but rather to provide a resource consisting of some usefulstrategies for novice EBSD users.

© 2009 Elsevier Inc. All rights reserved.

Keywords:Electron backscatter diffractionMicrotextureOrientation

1. Introduction

Electron backscatter diffraction (EBSD) is a scanning electronmicroscope (SEM) based technique which has become wellknown as a powerful and versatile experimental tool formaterials scientists, physicists, geologists and other scientistsand engineers. It allows the measurement of microtexture(texture on the scale of the microstructure) [1], microstructurequantification [2], grain and phase boundary characterisation[3,4], phase identification [5] and strain determination [6] incrystalline multiphase materials of any crystal structure. Ithas now been more than twenty years since the inception ofEBSD as an add-on facility to the capabilities of an SEM.Following commercialisation of the product at an early stageEBSD has attracted increasing interest in SEM user commu-nities, and several key publications have chronicled itsdevelopment [7–11]. Nowadays, EBSD systems exist world-wide. There are two main manufacturers plus a few smallerspecialist companies.

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er Inc. All rights reserved

Fig. 1 illustrates the growth in publications relating to EBSDin the present decade. There is an exponential increase,showing particularly a take-off in papers since 2005 as EBSDgained in popularity and accessibility. The papers quoted hereare those obtained from a single database source which islikely to reflect the most significant papers in the materialsfield. The absolute number of publications relating to EBSDover this time period will be therefore higher than thenumbers quoted in Fig. 1. Further analysis of recent trendsin EBSD application has shown that, although microtexturedetermination used to be the primary application of thetechnique, nowadays it is used for a wide range of sophisti-cated microstructure characterisation, sometimes in conjunc-tion with other analyses such as finite element modelling.Furthermore originally EBSD was applied exclusively tomaterials having cubic symmetry, whereas now increasinglyit is applied to materials with more complex structures.Hexagonal materials and geological materials are examplesof such growth areas [10].

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Fig. 1 – Number of EBSD-related publications in the period2000–2008 (Source: ScienceDirect).

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Operation of an EBSD system is no more difficult thanoperating an SEM. However, in the comprehensive EBSD soft-ware therearemanyuserchoicesboth indataacquisitionand indata processing and display. In order to extract maximumscientific value from an inquiry, it is helpful to have someguidelines for best practice in conducting anEBSD investigation.The purpose of this article therefore is to address selected topicsof EBSD practice in a tutorial manner. The topics covered are abrief summary on theprinciples of EBSD, specimenpreparation,calibration of an EBSD system, experiment design, speed of dataacquisition, data clean-up, microstructure characterisation(including grain size) and grain boundary characterisation.This list is not meant to cover exhaustively all areas whereEBSD is used, but rather to provide some useful strategies fornovice EBSD users. Throughout the text some ‘golden rules’ arementioned. These are printed in italics for emphasis.

Fig. 2 – (a) Typical processed EBSD diffraction pattern from anaustenitic (face centred cubic) steel. (b) Diffraction patternfrom (a) with simulated bands added, as part of thecalibration routine.

2. Principles of EBSD

EBSD is based on acquisition and analysis of Kikuchi diffrac-tion patterns from the surface of a specimen in an SEM.Detailed accounts of EBSD hardware, software and thegeneration and indexing of diffraction patterns can be foundin several texts [9,12], and will not be repeated here. To obtainan EBSD diffraction pattern a stationary beam of electrons issited on the specimen surface. Backscattered electrons arediffracted at crystal lattice planes within the probe volume,according to Bragg's law. The fraction of diffracted back-scattered electrons which are able to escape from the speci-men surface is maximised by tilting the specimen so that itmakes a small angle, typically 20°, with the incoming electronbeam. The diffraction patterns arise therefore from typicallyup to 50 nm depth from the specimen surface. The depthresolution has been quoted as approximately 40 nm for siliconand 10 nm for nickel [13–15]. The diffracted signal is collectedand viewed via a low-light video camera interfaced to aphosphor screen.

Camera technology has improved greatly in the last fewyears, which has underpinned vastly increased data acquisi-tion speeds. The improved quality of the captured diffractionpattern is due in part to an improved dynamic range of thecamera, i.e. the number of distinguishable grey levels, whichhas increased tenfold by use of a Charge-Coupled Device (CCD)

camera compared to the older Silicon Intensified Target (SIT)camera. The improvement is also due to the recent advancewhereby groups of pixels in the diffraction pattern can begrouped together into ‘super pixels’ (binning), which has theeffect of increasing the sensitivity of the camera. For examplea block of 8×8 pixels can be grouped together to produce thesame increase in camera sensitivity, i.e. 8×8=64. In turn, thisgives the same reduction in diffraction pattern collection time.The gain in pattern collection speed brought about by binningis further enhanced by recent improvements in electronicprocessing, such as frame averaging, and amplification of thecaptured diffraction pattern as well as computer and softwareimprovements. This has led to faster and faster mappingrates, depending on the material (Section 3.4). The latestgeneration of cameras also has the advantage of distortion-free lenses and a rectangular phosphor screen, to replace theprevious circular screen, so that the whole diffraction patternis captured and used. This camera is also shaped so that it canbe moved close to the specimen, which increases both thecamera sensitivity and the spatial resolution.

The diffraction patterns provide crystallographic informa-tion that can be related back to their position of origin on thespecimen. Fig. 2a shows a typical processed EBSD diffractionpattern from an austenitic (face centred cubic) steel. Evalua-tion and indexing of the diffraction patterns is performed inmost cases automatically and the data is output in a variety of

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both statistical and pictorial formats. The most versatile andrevealing of these outputs is the ‘orientationmap’ (sometimescalled an Orientation Imaging Micrograph, OIM), which is aquantitative depiction of an area of microstructure in terms ofits crystallographic constituents. Orientation maps are dis-cussed further in Section 4.

The spatial resolution of EBSD is influenced by themicroscope parameters, the atomic number of the material,the specimen/microscope geometry, the accelerating voltageand probe current used and the diffraction pattern quality.These factors are discussed in some detail elsewhere[9,11,12]. The best spatial resolution for a material such asbrass, for example, is 25–50 nm for a tungsten filament SEMand 9–22 nm for a FEGSEM, both measured parallel to the tiltaxis [16–18].

The angular resolution or accuracy of EBSD relates directlyto the precision with which the diffraction pattern can beindexed, which in turn is influenced by the calibration of thesystem (Section 3.2), the effectiveness of the software solveroutine, the diffraction pattern quality (Section 4.2) and themagnification of the diffraction pattern. The accuracy fororientationmeasurement by EBSD has been found experimen-tally to be approximately 0.5°–1.0° in a tungsten filament SEM[19]. This precision applies for patterns of optimumquality andwill reduce significantly for poor quality patterns. The speed ofdata collection has increased greatly in recent years, which isdiscussed in Section 3.4.

3. Data Acquisition

3.1. Specimen Preparation

Asmentioned in Section2, EBSDdiffractionpatterns arise fromthe top fewnanometers of specimensurface, and sodiffractionpattern quality is very sensitive to crystalline perfection in thissurface layer. Any occlusion or deformation must be removedfrom the surface by appropriate specimen preparation. Mostconducting materials are prepared by the normal metallo-graphic routes of grinding and polishing to produce a flatsurface. Diamond polishing is not a suitable final step in somematerials because of the surface deformation introduced.Electropolishing, etching and polishing with colloidal silicaare all used as final preparation steps. Ion milling, either in aDual-Beam instrument or ex-situ, or plasma etching can beused for materials not amenable to conventional metallogra-phy [20]. Non-conducting specimens can be thinly coated witha conducting medium, as for conventional SEM examination,and examined with a higher accelerating voltage to compen-sate for the extra thickness.

Optimum specimen preparation is a fundamental requirement foran EBSD experiment. Inadequate specimenpreparationwill resultin degraded diffraction patterns which feed through to loss ofdata quality. Data clean-up routines can compensate in part forunsolved patterns (Section 4.1) but clean-up procedures shouldnever be selected as an alternative to obtaining the best and mostrepresentative diffraction patterns. Furthermore real plastic strain,which results in reduceddiffractionpatternquality,mayexist inthe lattice [21]. It is important to distinguish this real andquantifiable effect from preparation-induced artefacts.

3.2. Calibration

The goal of calibrating an EBSD system is to establish thegeometry of the projection of the EBSD pattern onto thephosphor screen and to determine the geometrical relationshipbetween the specimen coordinates in the SEM chamber and thephosphor screen. The physical factors which can vary andtherefore alter thecalibrationparameters are the tilt angleof thespecimen surface with respect to the electron beam, theposition of the phosphor/camera assembly and the position ofthe specimen. Calibration is described in detail elsewhere [9,11]and in manufacturers' documentation. Two modes of calibra-tion can be classified: a full calibration which usually involves acalibrationcrystal of knownorientation, andan iterativepatternfitting routine which refines the calibration parameters and isperformed on a good quality pattern from a known material.The former mode is used in the initial commissioning of anEBSDsystemand thereafteronly approximately onceper year ormore frequently if thephysical set-uphasbeendisturbed. Fig. 2bshows an example of a diffraction pattern from an austeniticsteel, where the system has been well calibrated and so thesimulated Kikuchi bands are an excellent match to the realKikuchi bands in the EBSD pattern.Accurate calibration is essentialto obtaining reliable data. With practice a refined calibrationroutine takes only minutes and should be performed at thebeginning of every investigation.

3.3. Experiment Design

The first step in an EBSD investigation is deciding whatinformation is required. (Here we will assume that theinvestigation involves a specimen of known phases. Other-wise, EBSD can be used to identify the constituent phases andthis is described elsewhere [22].) The investigation is usuallycombinations of microtexture, interface parameters andmicrostructure. The requirements of the investigation willdetermine the sampling schedule, that is, the location of thedata points and how many are sampled [11].

For an unknown specimen some preliminary trial-and-errorexploration by the user will establish the scale of the orienta-tions and how they relate to themicrostructure,whichwill thenallow the user to select appropriate areas on the specimen.Examples of such areas include adjacent to a specimen edge, inthe vicinity of defects such as cracks, or to include a particularphaseor graindistribution.Once theparameters for the locationof the regionof interest (i.e. selectedareaplus the step size) havebeen determined by trial runs, most investigations can thenproceed automatically by orientation mapping.

Most EBSDdata is collected via an orientationmap, forwhichthe step size or grid sizemust be specified.A step size of one-tenthof the average grain size is a good starting point for generalmicrotexture, microstructure and grain misorientation measurements.A smaller step size than this or a ‘smart sampling’ optionwouldbe needed if the grain size distribution is inhomogeneous (e.g. apartially-recrystallised microstructure). Smart sampling, whichis designed to eliminate the high extent of oversamplingwithingrains that is a drawback of the standard orientation mappingapproach, is an option in some commercially available EBSDsoftware. The smart sampling option is best used on unde-formed grains, and could be used for example for the analysis of

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samples with a highly bimodal grain size distribution, so thatsmall grains can bemapped without extensive oversampling ofthe larger grains. The procedure begins by analysing a coarsegrid covering the whole area. Then the algorithm calculateswhether it needs to sample between any two of the originalpoints (i.e. whether there is a grain boundary between the twopoints). The procedure is iterated so that the sampling ends upconcentrated at grain boundaries.

It is especially important to capture all small grains if thegrain size is to be determined from the maps (Section 4.2).Fig. 3 shows an example of a large grain size spread caused bysecondary recrystallisation in a silicon iron sample. A smallstep size, relative to the grain size, is also required for highresolution definition of the interface network, e.g. for bound-ary reconstruction (Section 4.3).

Selection of appropriate sample areas and an appropriate stepsize is critical to the investigation.Unsuitable selections cannot bechanged retrospectively. The high throughput speeds avail-able with the latest generation EBSD cameras and systems(Section 3.4) facilitate data experiment design in that even ifthe smallest step sizes and large sampling areas are chosenmapping can be accomplished in reasonable time frames.

A note needs to be added on the significance of ‘micro-texture’ and ‘macrotexture’ measurements using EBSD. Micro-texture is defined as ‘a sample population of orientationmeasurements which can be linked individually to theirlocation within a specimen’ [11]. It refers essentially to theorientations in the sampled area only, and does not imply thetexture of the entire specimen. On the other handmacrotextureis defined as ‘an average texture determined frommany grainsobtainedwithout necessarily having reference to the location ofindividual grains within a specimen’ [11]. In the past macro-texture (referred to simply as ‘texture’) could only be measuredusing X-ray or neutron diffraction, in order to obtain sufficient

Fig. 3 – Orientationmap illustrating a large grain size spread, in sigreen, yellow and red respectively. (For interpretation of the refethe web version of this article.)

grain sampling. Nowadays the increased speed of data acquisi-tionmeans that it is viable to obtain macrotexture by EBSD, but onlyif due attention is paid to the sampling schedule and quantity of data.The statistical reliability of texturemeasurements by EBSDhavebeen compared to those obtained by X-rays in steel specimens[23]. The results from the two techniques were comparable.Approximately 10,000 grains were found to produce a very goodsampling in these materials. It should be emphasised that thisdata requirement refers to numbers of grains, and not simplydata points. Prior knowledge of the grain size is thereforeneeded. Texture measurements via EBSD have many advan-tages over X-ray methods, for example differentiating texturesin large and small grains.

In summary although there is a great diversity in applicationof EBSD for microtexture-related investigations, the basic stepsof experiment design and procedure are generic. These are

1. Selection of a suitable candidate material and specimensfor analysis

2. Optimum specimen preparation3. EBSD system calibration4. Manual checking of diffraction patterns for clarity and

expected phase match5. Appraisal of microstructure for grain size and phase distri-

bution, etc6. Selection of sampling area(s) on specimen7. Test runofdatacollection; checkappropriatenessof stepsize8. Data collection, usually via automated orientationmapping.

3.4. Speed of Data Acquisition

In recent years the speed of EBSD measurements hasincreased enormously. This is due to improvements in cameratechnology (especially the introduction of digital cameras),

licon iron. Small, medium and large sized grains are colouredrences to colour in this figure legend, the reader is referred to

Fig. 4 – Sequence of orientation maps from alpha-brass, illustrating the effect of data clean-up. The maps are shaded greyaccording to a pattern quality parameter, where darker shading corresponds to poorer quality. Unsolved pixels are black.(a) ‘Raw’mapwith no clean-up, containing 5% zero solutions. (b) Part cleanedmap containing 2% zero solutions. (c) Part cleanedmap containing 0.5% zero solutions.

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changes in the interface between the camera and thecomputer and upgrades in the EBSD pattern solve software.All these features are described in detail elsewhere [12,24].Fast EBSD has widened the scope of applications. SEM time isused more efficiently because EBSD scans are much faster,and statistically-significant quantities of data are easilyobtained so that for example grain size and macrotexturemeasurements are facilitated. Furthermore dynamic experi-ments such as in-situ tensile testing and hot stage experiments[25] would not be possible without fast EBSD.

At the time of writing the fastest pattern acquisition speedquoted is 750 points per second [26], on suitable specimens.EBSD manufacturers quote indexing rate of 400–750 patternsper second. A proviso is that error limits may have to bewidened in order to achieve such speeds, which feeds throughto lower reliability. Whether or not this can be tolerateddepends on the nature of the investigation. For example, fastmapping would probably be appropriate in order to gain animpression of the microtexture whereas to obtain grainboundary parameters often the highest accuracy is theparamount concern rather than speed. It is important to ensurethe mapping speed is appropriate to the inquiry.

4. Data Processing

4.1. Clean-up

Standard ‘clean-up’ or ‘noise reduction’ options in commercialEBSD packages allow the user to remove both points whereindexing was not possible and also isolated points that havebeen incorrectly indexed. The points that are removed arefixed by filling in using copies of neighbouring points.Incorrect indexing could occur because of incorrectly set

Fig. 5 – Uncleaned pattern qualitymap from an austenitic steel. Raboundaries and Σ27 boundaries are black, white, blue and yelloboundaries. (For interpretation of the references to colour in thisarticle.)

indexing parameters or misindexing due to pseudosymmetryin diffraction patterns. Zero solutions (indexing not possible)could occur at grain boundaries (because of double diffractionpattern sampling or etching), or if no phasematch is available,or if there is too much deformation in the specimen or if thespecimen surface is blemished or occluded.

Fig. 4 shows a sequence of orientation maps from alpha-brass which illustrates the effects of diffraction pattern quality,indexing and data clean-up. The maps are shaded greyaccording to diffraction pattern quality, with light grey shadingdepicting the best pattern quality (i.e. the sharpest Kikuchi linesin the diffraction pattern) and conversely dark grey shadingdepicting poor pattern quality (i.e. diffuse Kikuchi lines). Zerosolutions are black. Pattern quality is always more diffuse at adefect than within the lattice, and so grain boundaries aredelineated with darker shading than within grains. Fig. 4ashows the as-collected map, which contains 5% zero solutions.These unsolved pixels occur as isolated pixels within grains, atgrain boundaries, at minor surface scratches and extensivelywithin just a few grains. Fig. 4b and c illustrates the effect ofclean-up to leave 2% and 0.5% unsolved pixels respectively.Evidence of scratches remains as lines of poorer pattern quality.This series of maps illustrates the acceptable use of noisereduction routines which retain the integrity of the data.Excessive clean-up can distort the data and therefore clean-uproutines must always be used with caution.

The map in Fig. 5, which is from an austenitic steel,consists of the pattern quality parameter and has not under-gone any clean-up. Only 0.6% of pixels are zero solutions, andthese are virtually all sited at random grain boundaries. Thismap illustrates that in this instance specimen preparation hasbeen carried out to the highest standard and there is virtuallyno clean-up required, except at grain boundaries where someunsolved pixels are inevitable. It is also interesting to note that

ndom boundaries, annealing twins, otherΣ3 boundaries,Σ9w respectively. Zero solutions are sited mainly at randomfigure legend, the reader is referred to the web version of this

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unsolved pixels are sited at random grain boundaries but notat annealing twins [27].

4.2. Microstructure Characterisation

By far the greatest use of EBSD is to depict either micro-structure or microtexture, or frequently both. The nature oforientation mapping means that quantitative microstructuraldescriptors are generated in addition to the general portrayalof the microstructure. Whereas use of EBSD for texturedetermination is still a widely used area [11], a higher fractionof reported EBSD investigations related to general microstruc-ture characterisation than microtexture in 2006 than in 2003

Fig. 6 – Orientation maps from an electroplated nickel composite(a) Pattern quality map. The rutile particles are large and recogni(normal direction) map of the nickel phase from the same area aangle boundaries are coloured black and grey respectively (mapsreferences to colour in this figure legend, the reader is referred t

[10]. This trend is continuing. Strategies for the application ofEBSD to texture determination will not be expounded here,although they are discussed elsewhere [11].

The pattern quality map is often the best choice for the depiction ofmicrostructure.Themain advantage of the pattern qualitymap isthat the map is derived solely from contrast in the diffractionpattern, i.e. its diffuseness, rather than any indexing para-meters. As seen in Figs. 4 and 5, grain boundaries are renderedvisible and hence the grain structure is portrayed. There arevariouspattern qualitymetrics that can be employed,which arediscussed elsewhere [28]. A second advantage of pattern qualitymaps is that the viewing of different phases may be facilitated,as illustrated in Fig. 6. Fig. 6a is pattern quality map from an

coating co-deposited with titanium oxide (rutile) particles.sed by their pattern quality parameter. (b) Inverse pole figures in (a). The rutile phase is coloured green, and high and lowcourtesy of Lampke and Dietrich). (For interpretation of the

o the web version of this article.)

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electroplated nickel composite coating co-deposited with tita-niumoxide (rutile) particles [29]. Here the grain structure of bothphases is very clearly visible. Fig. 6b is an inverse pole figure(normal direction) map of the nickel phase from the same areaas in Fig. 6a. The rutile phase is coloured green.

Pattern quality maps are particularly useful for the discri-mination of phases that are difficult to distinguish by othermeans. For example pattern quality maps have been usedsuccessfully to determine the volume fraction of the micro-structural constituents bainite, ferrite and austenite, in a TRIPsteel [30]. Similarly, volume fractions of recrystallised andunrecrystallised microstructure can be determined. This taskhas been carried out automatically in aluminium [31].

Increasingly EBSD is the tool of choice for the determina-tion of grain size distribution and furthermore gives access toaccompanying derivative analyses such as grain axis ratio andmicrotexture according to grain size class. For example, grainsize and microtexture distributions have been determined for

Fig. 7 – (a) Orientation map from annealed nickel wherein grains(b) Grain size histogram from the map in (a).

nanostructured electrodeposited NiCo at both the deposit–bath interface and at the deposit–substrate interface [2]. It isimportant for grain size determination that small grains arerecognised unambiguously in maps, and that an appropriate choiceis made for the lower limit of grain boundary misorientation to definea grain. The topics of map step size selection (Section 3.3) andmap clean-up (Section 4.1) have direct bearing on accurategrain size determination. These topics are discussed andillustrated in detail elsewhere [32].

Fig. 7a shows a simple example of grain size determinationin nickel. Grains are displayed in random colours andinterfaces, including annealing twins, are black lines. Thisexample illustrates the point, from observation of the graincolours, that in this case annealing twins have been ignoredfor grain size determination. The grain size statistics areshown in Fig. 7b. Grains with two sides or less have beenomitted from the sample population. The average grain size is141 µm.

are depicted in random colours and all interfaces are black.

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4.3. Grain Boundary Characterisation

Formany years data fromEBSDorientationmapshas beenusedto characterise grain boundary misorientation distributions,especially in cubic materials. Typically grain boundaries areclassified according to low/high angle type and often by thepopular ‘coincidence site lattice’ (CSL) notation. Such analysesprovide partial information on the possible properties of theboundary [33].

Proportions of grain boundary types can be calculated as afraction of either total grainboundary lengthor total numbers of

Fig. 8 – (a) Pattern quality orientation map from lightlydeformed rocksalt. Low angle boundaries are red lines. Oneof several square-shaped grains is depicted with a cross.(b) Reconstructed microstructure corresponding to (a). Eachgrain is assigned a single average orientation value andrepresented as a random colour. Grain boundary linesegments used in the analysis are shown as black lines.(c) Density distribution of grain boundary planes in therocksalt specimen expressed as ‘multiples of a randomdistribution’, MRD in stereographic projection. (Forinterpretation of the references to colour in this figure legend,the reader is referred to the web version of this article.)

grainboundaries. The latter statistic requires that all grains (andhence grain boundaries) have been explicitly detected, usuallyas part of the grain size determination routine. The number andlength fraction statistics derived from grain boundary classes inthe map in Fig. 7a are 30.4% length fraction Σ3, 20.8% numberfraction Σ3, 0.9% length fraction Σ9, 1.7% number fraction Σ9. Itis clear that there are differences between the length andnumber statistics, which has been discussed indetail elsewhere[34]. This fact is not always acknowledged in publications. It istherefore vital that when quoting grain boundary proportions, itshould be clearly stated if they refer to a number or a length fraction.

Like other areas of EBSD application, in recent years thearea of interface studies has evolved. Examples of this moresophisticated usage include application to grain boundarynetworks rather than individual boundaries [35], phaseboundaries and orientation relationships [4] non-cubic mate-rials [36] and measurement of the grain boundary plane inaddition to the misorientation [3,37]. The distribution of grainboundary planes can be measured using the so-called ‘five-parameter analysis’, which is described in detail elsewhere[38,39]. The boundary plane distribution is derived either by astatistical method or by serial sectioning.

The first step in determination of the boundary planedistribution is to apply a grain boundary reconstructionalgorithm to reproduce faithfully the outline of grain bound-ary segments. Fig. 8 shows an example from lightly deformedrocksalt [40]. Fig. 8a is an orientation map from the saltspecimen. Low angle boundaries are red lines. Fig. 8b showsthe corresponding reconstructed microstructure whereineach grain is assigned a single average orientation valueand represented as a random colour. Grain boundary linesegments used in the analysis are shown as black lines. It isclear that the reconstructed boundary network is a goodmatch to the real boundary network. Fig. 8c shows, in stereo-graphic projection, the overall grain boundary plane distribu-tion recorded from this specimen. The density units are‘multiples of a random distribution’, MRD. It can be seen thatthere are well-defined maxima at {100} planes. The square-shaped grains seen in Fig. 8a and b (one is depicted with across) also have been shown by manual measurements tohave planes close to {100} [41].

The five-parameter analysis and analysis of boundaryplanes is a relatively new extension of EBSD characterisation,and already is extending knowledge of the relationshipbetween grain boundary crystallography and properties [3].The recent development of a Dual-Beam EBSD and focused ionbeam microscope (FIB) allows in-situ serial sectioning of smallregions hence facilitating the characterisation of grain bound-ary planes and other three-dimensional aspects of micro-structure characterisation [42].

5. Concluding Remarks

EBSD has matured into a powerful experimental tool, encom-passing many strands of microstructure characterisation. Thispaper has sought both to illustrate the richness of data availablefrom modern EBSD analysis and to provide, via selectedexamples, a resource for novice users on how to get the bestout of an EBSD inquiry.

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