Presentations EBSD
Transcript of Presentations EBSD
The Business of Science®
Page 1 © Oxford Instruments 2015
Jenny Goulden
Oxford Instruments Recent Developments in EBSD
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Page 2 © Oxford Instruments 2015
• Product Updates: • 10:15-10:45 EBSD developments :
• Hardware, basic Aztec, ease of use, indexing, mapping, Synergy
• 10:50-11.30 Advanced functions: • Large area mapping, refined accuracy, updates to post processing
• More application specific talks later
Agenda
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Page 3 © Oxford Instruments 2015
Introduction • Developments driven by market / application requirements
• What are the challenges • Which solutions work / don’t work • How can we help?
• Market requirements
• Improved spatial resolution EBSD (lower kV & beam current) • Faster data acquisition (reduce SEM time, more data, better
statistics) • Improvements to data acquisition • Improvements to EDS integration • Easier to acquire better quality data
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Introduction
• Result number of development • Detector developments
• Improve sensitivity • Improve speed
• AZtec platform launched 2011
• Updates about every 6 months • Brief overview of product • Key features and functions
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• NordlysNano
• Better sensitivity
• Improved spatial resolution
• NordlysMax2
• Faster acquisition speed
• Retain sensitivity
• Forescattered Detectors
• Better orientation imaging
EBSD Hardware Developments
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Detector Developments - NordlysNano
• EBSD detector with HIGHER sensitivity
– Designed to for the requirements of ‘nano scale’ applications
• Developed in direct response to customer requests
– To work at low kV
– To work at low beam current
– Best spatial resolution
– Highest quality patterns (high pixel count)
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Higher Spatial Resolution
20kV Iron Pyrite 5kV Iron Pyrite
• The challenge for improving spatial resolution is operation at low kV
• Low signal • Weaker patterns especially at edges • Broader Bands
• Requires optimisation the signal to the sensor
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NorldysNano
• Delivers the best possible sensitivity while accurately imaging the EBSP
• 60% more sensitive than older EBSD detectors
• Sensitivity is directly related to quantum efficiency of the CCD coupled with the detector optics
– NordlysNano has 70% Quantum efficiency
– Coupled with bespoke optics specifically optimised to work with our CCD
• Eliminates distortion from the pattern (zero barrel distortion)
– Barrel distortion present in all optics
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Barrel Distortion Removal:
Old lens ~2% distortion New lens <0.5% distortion
• Best pattern quality: important in applications looking at pattern detail or subtle differences in EBSPs • For example cross correlation techniques
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NordlysNano
• Capability to work at lower beam energies, important for:
• Nano materials where low kV offers better spatial resolution
• Beam sensitive samples, where higher beam energies damage the samples
• Insulators, where lower kV can remove the need to coat the sample
• Excellent for TKD
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NordlysNano
• 5kV Ni 0.5um grain size 100Hz • Aluminia Insulator
• Alumina – NO coating
• Hit Rate 85% (porous sample) at 90Hz
10kV
5kV
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NordlysNano
• Transmission Kikuchi Diffraction
• Cu15B-strained-4nm-IPF-Z
• This is a strained nanocrystalline copper
• IPF-Z direction, high angle boundaries in black and CSL boundaries in colour. Step size 4nm.
Acknowledgement: Saritha Samudrala (University of Sydney) and Kevin Hemker (Johns Hopkins University)
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Sensitivity vs High Resolution
• Target to deliver both high sensitivity and high resolution
• NordlysNano matches customised optics and CCD
• Without this optical design full resolution of megapixel CCDs cannot be achieved
– High resolution images not simply a matter of more pixels in the pattern
• Important in applications looking at pattern detail or subtle differences in EBSPs
• e.g Cross correlation techniques
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Faster Data Acquisition
• SEM time becoming more valuable / expensive
• Challenged with more efficient use of SEM time
• Collect more data / better statistics
• Traditionally with EBSD faster data collection has required higher beam current up to maximum speed
• Challenge was to develop hardware which could operate:
• Faster maximum speed
• Fast acquisition at lower beam energy
• Operate at lower kV and beam current
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Nordlys Max2 Detector
• 30% faster, with better sensitivity
• Fastest speed 870Hz (or patterns per second)
• 870Hz at 5nA - acquire and solve in real time
• 870Hz with simultaneous EDS data - acquire and solve
• Operation at 5kV
• Operation at lower beam current (100pA)
• Achieved by improving CCD
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NordlysMax2
• 870Hz • 99% indexed • 12nA
Ni sample
• Simultaneous EBSD & EDS
• Tungsten heavy alloy • 870pps • Real time sample
characterisation
100um
Ni X-ray Map
W X-ray Map
Phase Map
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NordlysMax2 Low kV EBSD Patterns
20kV
5kV
5kV
• Patterns from tungsten • 20kV • 5kV • But still able to solve
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• In-situ experiments are performed in the SEM chamber • Monitor change while ‘experimenting’ on the sample • Typically heating and/or tensile testing • Specialised stages are used in conjunction with EBSD
• Increasingly used to study and understand solid state events:
• Microstructure development • Recrystallisation and recovery • Failure analysis • Phase transformations and phase relationships
(Keith will talk about this later)
• Detector hardware is also important
EBSD – Dynamic Studies
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• NordlysMax2 has an integrated a IR filter • High sensitivity compared to conventional high temperature
phosphor screens
NordlysMax2 – Dynamic Studies
EBSP from Ti Transformation at 882°C from alpha to beta phase
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In Situ Heating Example: Low C steel 895oC 6 mins 880oC 945oC 895oC 0 mins
austenite ferrite
GATAN Heating stage
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• Nordlys EBSD detectors can have up to 6 diodes positioned around the phosphor
• Top – atomic number(Z) contrast images
• Lower - orientation contrast
• Side – mixed images
• FSD images useful for imaging a well prepared tilted sample (as in EBSD)
• These diodes are controlled independently within the Aztec platform
Forescatter Detector Imaging
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Forescatter Detector Control
• Up to 6 individual images can be acquired • Settings are controlled within the AZtec interface – both
manual and auto settings are available • Automatic optimisation means easy to collect excellent images • Default Z contrast or Orientation contrast settings • Or customise settings • Up to 6 individual images can be
mixed
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Automatic Image Optimisation
This automatic beam optimisation is capable of collecting images under a full range of beam current and kV.
20kV 10nA 20kV 5nA 20kV 0.5nA
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• How Aztec helps in getting better data – with ease
• Improved Indexing
• Distinguishing similar crystal structures
• High Angular Accuracy
• EDS Integration
• Analysis Tools
• Point & Linescan
• Line Large Area Mapping
• TKD
• Post Processing
AZtec Platform Developments
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Collecting Good EBSD Data.....
• Takes time and expertise: several variables will impact the result:
• Pattern quality: Background, exposure time, SEM conditions
• System Calibration: Detector position, working distance
• Band detection & Indexing: Manual band selection, choice of bands and reflectors
• The impact if ‘wrong’
• Lower hit rate, poor phase discrimination, etc...
• So there are number of improvements to EBSD acquisition with AZtec
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Pattern Quality – Background Correction
• Signal across raw EBSD pattern is ‘steep’
• Typically static background collection required
• Scan speed, grain size, kV, phase (different Z), and magnification
• Potential negative impact on indexing success
• New dynamic background correction implemented in AZtec
• Compensates as conditions change
• Pattern by pattern contrast optimisation
• Works where static background was inadequate
Raw EBSP
Background corrected
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AutoExposure
• Optimises signal strength to avoid under or over exposure of the camera
• Optimum exposure time calculated for given binning and gain
• Uses ‘Signal Strength’ to optimise the pattern signal : noise
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System Calibration
• Accurate indexing requires an accurate calibration of the pattern centre
• Dependant on the geometry of acquisition (i.e. WD & DD)
• Refinement is required when conditions/ sample change
• Historically extracted from a single pattern • Using AZtec system is always calibrated
• Collect data at a full range of WD & DD without refinement
20mm wd 15mm wd 10mm wd
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Plagioclase, Typical mapping quality pattern
Weighted band (Hough peak) selection
• Bands chosen preferentially by length as well as intensity • Generally improves “fit” between detected & actual bands • Allows greater numbers of bands detected in routine use • Improved performance for low density materials demanding a
higher numbers of detected bands (e.g. low symmetry phases)
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Example pattern: Low-density silicate mineral at typical mapping speed
Non-weighted band detection Weighted band detection
Band selection comparison
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Aztec “Class” indexing
• Allows effective use of larger numbers of detected bands
• Fewer non-solutions and indexing mistakes
• Robust indexing on challenging phases
• Improves ease of use (# bands no longer critical setting)
• Better accommodates overlapping patterns, e.g. at grain boundaries
• Solution from dominant group of bands (from one side) generally supersedes any mistaken four-band combinations which include representatives from either side
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Steel
AZtec“Class” indexing
Improved indexing for overlapping patterns
“Class” indexing All-band indexing
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Aztec“Class” indexing
Improved indexing for phase discrimination
Traditional indexing method “Class” indexing method
Gabbro
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AZtec“Class” indexing
Improved indexing % for challenging phases
Traditional indexing method “Class” indexing method
Gabbro
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Traditional Indexing Challenges – No of bands
• Duplex steel sample: four phases; Iron FCC, Iron BCC, Sigma & Chi
12 bands
• Too many bands selected
8 bands
• Too few bands selected
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New AZtec Indexing
• No misindexing • No patches with no solution • Grain boundary minimised
12 bands
8 bands
• Higher accurate hit rates • Indexing is less sensitive
to user defined settings • Same result 8 or 12
bands • Analysis more robust
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Discrimination of Similar Crystal Structures • Differentiation of two phases with closely related structures and
slightly different unit cell sizes
• Pt & Ni weld from the central electrode tip of a spark plug
• Pt and Ni same crystal structure
• 9-10% difference in lattice parameter Pt Ni
cubic cubic
fcc fcc
3.924 3.52-3.57
space
group=225
space group
=225
Conventional indexing cannot distinguish between the two phases
Ni Pt
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Accurate Phase Discrimination
• Sorting solutions based on differences in band width to see detail of the two separate phases and the mixed region in the weld
Ni Map
Pt Map
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Discrimination of Similar Crystal Structures - TruPhase
• This function is applicable on integrated EBSD/ EDS systems • Applies the EDS signal collected in Real Time, simultaneously
with EBSD to assist in distinguishing phases with similar crystal structure but different chemistry
• Then re ranks EBSD solutions, but does not overrule the EBSD • Where there is more than one viable phase identified
through indexing alone the EDS is used to weight the results
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Discrimination of Similar Crystal Structures - TruPhase
• TruPhase applies the full X-ray spectrum profile not specific ‘windows integrals’
• Therefore it is robust to issues such as changes in background intensity, peak overlaps and peak pile up
• By applying the ‘spectrum profile’ it does not rely on automatic peak identification
• Reliable operation during Fast Mapping – when the X-ray spectra is likely to contain less statistics
• Can be applied in real time as data acquired or within re analysis
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FSD mixed image
Application Example - Differentiating Cu & Ni:
Phase map
Cu
Ni Hough based
indexing
Phase map
Tru-
Phase
Ni Kα1
Cu Kα1
Cu Ni
Cubic high Cubic high
a=3.61 a=3.57
b=3.61 b=3.57
c=3.61 c=3.57
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TruPhase Example Biotite and Muscovite
Fe map Al map
Na map
Biotite distribution
Muscovite distribution Albite distribution
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• Normal EBSD map
• Similarity between muscovite and biotite makes it difficult to differentiate the two phases resulting in the speckly solving in the muscovite phase
• Reanalaysed using TruPhase
• Better differentiation of the two phases, which corresponds to the element distribution seen in the X-ray maps
TruPhase Example Biotite and Muscovite
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• High Orientation Accuracy
• Refined Accuracy
• EDS Integration
• Point & Linescan
• Large Area Mapping
• TKD
More Advanced Functions
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• Many factors influence EBSD accuracy (including pattern resolution, CCD pixels, acquisition conditions, Hough resolution and band detection)
• Aztec Refined Accuracy improves the accuracy of band detection • Delivering more
accurate orientation measurement
Example shows Ni EBSP Traditional Hough based band
detection
Refined Accuracy Mode
Traditional band detection is good Refined accuracy is better
High Orientation Accuracy Mode
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• Primary band detection Apply fast, low resolution Hough to detect a set of 2D bands. High Hough resolution is used to increase angular resolution. Through PC and DD convert these to 3D plane normal vectors.
• Indexing From the 3D inter-planar angles, identify all or a subset of the detected bands as crystallographic lattice planes.
• Secondary band detection (only in AZtec Refined Accuracy) Indexing determines the Bragg angle and thereby the band width. With this information, refine the band positions in the EBSP, and utilize the curvature of the Kikuchi bands.
• Form the crystal orientation Calculate the crystal orientation relative to the EBSD detector.
Refined Accuracy
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• Refined Accuracy provides :
• Higher angular accuracy of orientation measurement
• Smaller spread of data, better standard deviation
• Better fit pattern & solution
Refined Accuracy
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Integration of EDS & EBSD
• Collect and view all data simultaneously
• Apply full data cube to further interrogate the sample
• Phase ID
• Identify additional / unexpected phases
• Re-analyse if required
• How accurate is EDS data at high tilt?
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Accurate Integration of EDS & EBSD
• Variation in the specimen/ beam interaction causes changes in spectrum background & peak shape– compared to flat samples
• AZtec X-ray mapping uses a FLS filtering used for background removal
• This is tolerant to changes in background shape
• So we can collect accurate X-ray and EBSD maps at tilt
• But what about quant?
Pt Map
Spectra from XPE16 alloy
collected at 0° (solid) and 70° tilt
(red line ).
Wt % Al Si Ti Cr Fe Ni Mo Total
XPE16 - Flat 1.23 0.18 1.36 17.55 33.51 42.40 3.58 99.80
XPE16 - Tilted 70 deg 1.16 0.19 1.16 17.78 34.01 42.94 3.53 100.79
• Processed using AZtec: standardless, unnormalised quant routines with XPP matrix correction (Pouchou et al.)
• Comparable result at high tilt & on flat samples:
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• Collect spectrum & pattern simultaneously
• Multiple EBSP & spectra can be collected
• Metal valve used in power engines – matrix is steel, multiple secondary phase
• AutoID & quantify spectrum (or select elements manually).
• Based on composition the selected data bases are searched.
• Possible candidate phases listed.
• EBSP is searched against the candidate phases
• View pattern with solution overlay to see fit
Phase Identification
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Phase Identification EDS & EBSD
• Gneiss sample • Phases visible
on BSE image • Collect spectra
from 3 phases: quartz, plagioclase & orthoclase
• Select from Am. Min database
• Collect patterns • Collect phase
map
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Phase ID & Re-Analysis
• High temperature steel sample mapped
• Secondary phase not expected
• Therefore no solution
• Investigate the map data –extract pattern & spectrum
• Identify phases using Phase ID tool
• Two additional phases identified
• Additional phases added to phase list
• Data reanalysed offline to complete map
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Point Analysis
• EBSD Point Analysis
• Collect EBSPs and measure the orientation at a series of points
• Tabulate misorientaion between the each point and a reference
Example
shows a
nanowire
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Linescan
• EBSD (& EDS) Linescan
• Define a line in either x or y direction, collect EBSPs at defined step size or based on number of points
• Plot misorientation profile through the line
• Review phase, MAD etc over the line
• Select point on profile and highlight in table
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AZtec Large Area Mapping
• Unattended collection of high resolution electron images, EBSD and EDS maps from large specimen areas:
• Micro- and Nano- scale from a single data set • Analysis coarse grained material • Statistically valid analysis
2 cm
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How it Works
• Collect and montage (EBSD & EDS) data at high resolution and analyse the montaged image as a single data set
• Collect >1500 fields
• Automatic field alignment during acquisition using image correlation
• Keeps the sample in focus over the complete sample area, even when the sample Is not flat
• Best illustrated with some examples…
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Data Acquisition
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Coarse Grained Mantle Xenolith
1cm
Forsterite IPF
1cm
Cr Map
1cm
Acknowledge University of Otago
• Montaged data set can be interrogated as a single site of interest
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Folded Rolled Nickel Sheet
1000um
• Grain Boundary map shows: • Black = high angle grain
boundary • Red = twin boundaries • Grey low angle
boundary <2° • Indicate regions of
deformation in sheet
• Gas pipeline material, examine texture changes through fold • Link texture to corrosion
• 90 fields collected over Ni sheet • Large area mapping and montaging provides an overview of the
whole sample at a high level of detail:
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1000um
• Rolled Ni sheet, 100 fields • IPF X map, systematic texture variation associated with folding
Folded, Rolled Nickel Sheet
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AZtec LAM – Image Registration
• The montaged image is automatically registered in AZtec and can be used for relocation and navigation
• The montaged image (or other Aztec image) can be imported into AZtec at a later date, re-registered using fiducial markers - and used to relocate to regions of interest on the specimen
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MapQueue
• Individual point mapping experiments can be queued up
• Each mapping experiment (EDS or EBSD) can have different resolutions, dwell times, solver settings, Phase lists...
• Each point acquisition can be EDS, EBSD or both
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• Powerful variation of EBSD
• Lots of interest
• Many papers / conference talks
• Applies standard EBSD system to an electron transparent sample
• Sample close to horizontal with short working distance
• Optimise spatial resolution
Transmission Kikuchi Diffraction
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• Al sample
• Pattern distortion resulting from TKD geometry causes wider bands in the lower pattern
• Non symmetric intensity seen in the broad bands
• This results in inaccuracy in the band detection
Challenges with Transmission Kikuchi Diffraction
Typical TKD pattern
• TKD Optimised Mode
• With new band detection bands are correctly detected
MAD = 1.1
MAD = 0.13
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• In this mode a new band detection routine is applied which is more accurate
• It takes into account the band position relative to the pattern centre and detector position
• As a result can work with the sample close to horizontal at short working distance
• Optimising spatial resolution
TKD Optimised Mode
2um
Strained nanocrystalline copper sample showing IPF-Z
direction, high angle boundaries in black and CSL boundaries in colour. Step size 4nm.
Credit: Saritha Samudrala (University of Sydney) and Kevin Hemker (Johns Hopkins University)
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• All data can be exported to the post processing packages
• 64bit so can handle large data sets
• Large number of processing and display options
• Include clean up functionality
• Capability to create subsets
• Creation of crystallographic data files
Data Analysis Improvements
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• The map data values for grain and grid maps created in Tango can now be exported as a text file
• This means the map calculations can be used as input into other third party software
• The calculated (M)ODF values can also be exported as a text file
Data Analysis Improvements
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• New grain sizing filters introduced which follow the ISO DIS13067
• Easier to filter the data so that clusters which are too small to be considered as a grain can be removed from the grain statistics.
Data Analysis Improvements
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• Export of the Grain ID together with the orientation data – added to the Record Browser
• Texture components modified so if multiple components are used at the same time then the data pixels can only contribute to one component, easing calculation of area fractions
• Axis alignment component to get boundary fraction fulfilling a given criteria
Data Analysis Improvements
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•Visualises substructures in the sample.
• The average orientation is determined for each grain. The deviation from this mean orientation is then plotted for each pixel – within that grain.
Data Analysis Improvements – New Maps • GROD Grain Reference Orientation Deviation (GROD) Angle
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• The average orientation is determined per grain.
• The axis around which the orientation is rotated is calculated and displayed as a colour
• Those grains which are ‘speckled’ have an orientation which is close to the mean
Data Analysis Improvements – New Maps
Grain Reference Orientation Deviation (GROD) Axis
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• The GROD Hyper combines both the axis and angle, relative to the mean orientation of the grain
• This map combines 4 coordinates (from the axis, x,y & z, and the angle) in a 3D colour space to display subtle internal grain structures.
• This map is a visual representation but is not a quantification of the data.
Data Analysis Improvements – New Maps • Grain Reference Orientation Deviation (GROD) Hyper
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• Range of applications for EBSD is growing
• Increasing requirements to understand how microstructure influences materials behaviour
• Manufacture higher performing materials
• Interest in technique is growing
• Faster acquisition
• Smaller features
• Larger Samples
• Higher accuracy
• More challenging applications
• AZtec is solution for all applications
Summary