- •Preface
- •Imaging Microscopic Features
- •Measuring the Crystal Structure
- •References
- •Contents
- •1.4 Simulating the Effects of Elastic Scattering: Monte Carlo Calculations
- •What Are the Main Features of the Beam Electron Interaction Volume?
- •How Does the Interaction Volume Change with Composition?
- •How Does the Interaction Volume Change with Incident Beam Energy?
- •How Does the Interaction Volume Change with Specimen Tilt?
- •1.5 A Range Equation To Estimate the Size of the Interaction Volume
- •References
- •2: Backscattered Electrons
- •2.1 Origin
- •2.2.1 BSE Response to Specimen Composition (η vs. Atomic Number, Z)
- •SEM Image Contrast with BSE: “Atomic Number Contrast”
- •SEM Image Contrast: “BSE Topographic Contrast—Number Effects”
- •2.2.3 Angular Distribution of Backscattering
- •Beam Incident at an Acute Angle to the Specimen Surface (Specimen Tilt > 0°)
- •SEM Image Contrast: “BSE Topographic Contrast—Trajectory Effects”
- •2.2.4 Spatial Distribution of Backscattering
- •Depth Distribution of Backscattering
- •Radial Distribution of Backscattered Electrons
- •2.3 Summary
- •References
- •3: Secondary Electrons
- •3.1 Origin
- •3.2 Energy Distribution
- •3.3 Escape Depth of Secondary Electrons
- •3.8 Spatial Characteristics of Secondary Electrons
- •References
- •4: X-Rays
- •4.1 Overview
- •4.2 Characteristic X-Rays
- •4.2.1 Origin
- •4.2.2 Fluorescence Yield
- •4.2.3 X-Ray Families
- •4.2.4 X-Ray Nomenclature
- •4.2.6 Characteristic X-Ray Intensity
- •Isolated Atoms
- •X-Ray Production in Thin Foils
- •X-Ray Intensity Emitted from Thick, Solid Specimens
- •4.3 X-Ray Continuum (bremsstrahlung)
- •4.3.1 X-Ray Continuum Intensity
- •4.3.3 Range of X-ray Production
- •4.4 X-Ray Absorption
- •4.5 X-Ray Fluorescence
- •References
- •5.1 Electron Beam Parameters
- •5.2 Electron Optical Parameters
- •5.2.1 Beam Energy
- •Landing Energy
- •5.2.2 Beam Diameter
- •5.2.3 Beam Current
- •5.2.4 Beam Current Density
- •5.2.5 Beam Convergence Angle, α
- •5.2.6 Beam Solid Angle
- •5.2.7 Electron Optical Brightness, β
- •Brightness Equation
- •5.2.8 Focus
- •Astigmatism
- •5.3 SEM Imaging Modes
- •5.3.1 High Depth-of-Field Mode
- •5.3.2 High-Current Mode
- •5.3.3 Resolution Mode
- •5.3.4 Low-Voltage Mode
- •5.4 Electron Detectors
- •5.4.1 Important Properties of BSE and SE for Detector Design and Operation
- •Abundance
- •Angular Distribution
- •Kinetic Energy Response
- •5.4.2 Detector Characteristics
- •Angular Measures for Electron Detectors
- •Elevation (Take-Off) Angle, ψ, and Azimuthal Angle, ζ
- •Solid Angle, Ω
- •Energy Response
- •Bandwidth
- •5.4.3 Common Types of Electron Detectors
- •Backscattered Electrons
- •Passive Detectors
- •Scintillation Detectors
- •Semiconductor BSE Detectors
- •5.4.4 Secondary Electron Detectors
- •Everhart–Thornley Detector
- •Through-the-Lens (TTL) Electron Detectors
- •TTL SE Detector
- •TTL BSE Detector
- •Measuring the DQE: BSE Semiconductor Detector
- •References
- •6: Image Formation
- •6.1 Image Construction by Scanning Action
- •6.2 Magnification
- •6.3 Making Dimensional Measurements With the SEM: How Big Is That Feature?
- •Using a Calibrated Structure in ImageJ-Fiji
- •6.4 Image Defects
- •6.4.1 Projection Distortion (Foreshortening)
- •6.4.2 Image Defocusing (Blurring)
- •6.5 Making Measurements on Surfaces With Arbitrary Topography: Stereomicroscopy
- •6.5.1 Qualitative Stereomicroscopy
- •Fixed beam, Specimen Position Altered
- •Fixed Specimen, Beam Incidence Angle Changed
- •6.5.2 Quantitative Stereomicroscopy
- •Measuring a Simple Vertical Displacement
- •References
- •7: SEM Image Interpretation
- •7.1 Information in SEM Images
- •7.2.2 Calculating Atomic Number Contrast
- •Establishing a Robust Light-Optical Analogy
- •Getting It Wrong: Breaking the Light-Optical Analogy of the Everhart–Thornley (Positive Bias) Detector
- •Deconstructing the SEM/E–T Image of Topography
- •SUM Mode (A + B)
- •DIFFERENCE Mode (A−B)
- •References
- •References
- •9: Image Defects
- •9.1 Charging
- •9.1.1 What Is Specimen Charging?
- •9.1.3 Techniques to Control Charging Artifacts (High Vacuum Instruments)
- •Observing Uncoated Specimens
- •Coating an Insulating Specimen for Charge Dissipation
- •Choosing the Coating for Imaging Morphology
- •9.2 Radiation Damage
- •9.3 Contamination
- •References
- •10: High Resolution Imaging
- •10.2 Instrumentation Considerations
- •10.4.1 SE Range Effects Produce Bright Edges (Isolated Edges)
- •10.4.4 Too Much of a Good Thing: The Bright Edge Effect Hinders Locating the True Position of an Edge for Critical Dimension Metrology
- •10.5.1 Beam Energy Strategies
- •Low Beam Energy Strategy
- •High Beam Energy Strategy
- •Making More SE1: Apply a Thin High-δ Metal Coating
- •Making Fewer BSEs, SE2, and SE3 by Eliminating Bulk Scattering From the Substrate
- •10.6 Factors That Hinder Achieving High Resolution
- •10.6.2 Pathological Specimen Behavior
- •Contamination
- •Instabilities
- •References
- •11: Low Beam Energy SEM
- •11.3 Selecting the Beam Energy to Control the Spatial Sampling of Imaging Signals
- •11.3.1 Low Beam Energy for High Lateral Resolution SEM
- •11.3.2 Low Beam Energy for High Depth Resolution SEM
- •11.3.3 Extremely Low Beam Energy Imaging
- •References
- •12.1.1 Stable Electron Source Operation
- •12.1.2 Maintaining Beam Integrity
- •12.1.4 Minimizing Contamination
- •12.3.1 Control of Specimen Charging
- •12.5 VPSEM Image Resolution
- •References
- •13: ImageJ and Fiji
- •13.1 The ImageJ Universe
- •13.2 Fiji
- •13.3 Plugins
- •13.4 Where to Learn More
- •References
- •14: SEM Imaging Checklist
- •14.1.1 Conducting or Semiconducting Specimens
- •14.1.2 Insulating Specimens
- •14.2 Electron Signals Available
- •14.2.1 Beam Electron Range
- •14.2.2 Backscattered Electrons
- •14.2.3 Secondary Electrons
- •14.3 Selecting the Electron Detector
- •14.3.2 Backscattered Electron Detectors
- •14.3.3 “Through-the-Lens” Detectors
- •14.4 Selecting the Beam Energy for SEM Imaging
- •14.4.4 High Resolution SEM Imaging
- •Strategy 1
- •Strategy 2
- •14.5 Selecting the Beam Current
- •14.5.1 High Resolution Imaging
- •14.5.2 Low Contrast Features Require High Beam Current and/or Long Frame Time to Establish Visibility
- •14.6 Image Presentation
- •14.6.1 “Live” Display Adjustments
- •14.6.2 Post-Collection Processing
- •14.7 Image Interpretation
- •14.7.1 Observer’s Point of View
- •14.7.3 Contrast Encoding
- •14.8.1 VPSEM Advantages
- •14.8.2 VPSEM Disadvantages
- •15: SEM Case Studies
- •15.1 Case Study: How High Is That Feature Relative to Another?
- •15.2 Revealing Shallow Surface Relief
- •16.1.2 Minor Artifacts: The Si-Escape Peak
- •16.1.3 Minor Artifacts: Coincidence Peaks
- •16.1.4 Minor Artifacts: Si Absorption Edge and Si Internal Fluorescence Peak
- •16.2 “Best Practices” for Electron-Excited EDS Operation
- •16.2.1 Operation of the EDS System
- •Choosing the EDS Time Constant (Resolution and Throughput)
- •Choosing the Solid Angle of the EDS
- •Selecting a Beam Current for an Acceptable Level of System Dead-Time
- •16.3.1 Detector Geometry
- •16.3.2 Process Time
- •16.3.3 Optimal Working Distance
- •16.3.4 Detector Orientation
- •16.3.5 Count Rate Linearity
- •16.3.6 Energy Calibration Linearity
- •16.3.7 Other Items
- •16.3.8 Setting Up a Quality Control Program
- •Using the QC Tools Within DTSA-II
- •Creating a QC Project
- •Linearity of Output Count Rate with Live-Time Dose
- •Resolution and Peak Position Stability with Count Rate
- •Solid Angle for Low X-ray Flux
- •Maximizing Throughput at Moderate Resolution
- •References
- •17: DTSA-II EDS Software
- •17.1 Getting Started With NIST DTSA-II
- •17.1.1 Motivation
- •17.1.2 Platform
- •17.1.3 Overview
- •17.1.4 Design
- •Simulation
- •Quantification
- •Experiment Design
- •Modeled Detectors (. Fig. 17.1)
- •Window Type (. Fig. 17.2)
- •The Optimal Working Distance (. Figs. 17.3 and 17.4)
- •Elevation Angle
- •Sample-to-Detector Distance
- •Detector Area
- •Crystal Thickness
- •Number of Channels, Energy Scale, and Zero Offset
- •Resolution at Mn Kα (Approximate)
- •Azimuthal Angle
- •Gold Layer, Aluminum Layer, Nickel Layer
- •Dead Layer
- •Zero Strobe Discriminator (. Figs. 17.7 and 17.8)
- •Material Editor Dialog (. Figs. 17.9, 17.10, 17.11, 17.12, 17.13, and 17.14)
- •17.2.1 Introduction
- •17.2.2 Monte Carlo Simulation
- •17.2.4 Optional Tables
- •References
- •18: Qualitative Elemental Analysis by Energy Dispersive X-Ray Spectrometry
- •18.1 Quality Assurance Issues for Qualitative Analysis: EDS Calibration
- •18.2 Principles of Qualitative EDS Analysis
- •Exciting Characteristic X-Rays
- •Fluorescence Yield
- •X-ray Absorption
- •Si Escape Peak
- •Coincidence Peaks
- •18.3 Performing Manual Qualitative Analysis
- •Beam Energy
- •Choosing the EDS Resolution (Detector Time Constant)
- •Obtaining Adequate Counts
- •18.4.1 Employ the Available Software Tools
- •18.4.3 Lower Photon Energy Region
- •18.4.5 Checking Your Work
- •18.5 A Worked Example of Manual Peak Identification
- •References
- •19.1 What Is a k-ratio?
- •19.3 Sets of k-ratios
- •19.5 The Analytical Total
- •19.6 Normalization
- •19.7.1 Oxygen by Assumed Stoichiometry
- •19.7.3 Element by Difference
- •19.8 Ways of Reporting Composition
- •19.8.1 Mass Fraction
- •19.8.2 Atomic Fraction
- •19.8.3 Stoichiometry
- •19.8.4 Oxide Fractions
- •Example Calculations
- •19.9 The Accuracy of Quantitative Electron-Excited X-ray Microanalysis
- •19.9.1 Standards-Based k-ratio Protocol
- •19.9.2 “Standardless Analysis”
- •19.10 Appendix
- •19.10.1 The Need for Matrix Corrections To Achieve Quantitative Analysis
- •19.10.2 The Physical Origin of Matrix Effects
- •19.10.3 ZAF Factors in Microanalysis
- •X-ray Generation With Depth, φ(ρz)
- •X-ray Absorption Effect, A
- •X-ray Fluorescence, F
- •References
- •20.2 Instrumentation Requirements
- •20.2.1 Choosing the EDS Parameters
- •EDS Spectrum Channel Energy Width and Spectrum Energy Span
- •EDS Time Constant (Resolution and Throughput)
- •EDS Calibration
- •EDS Solid Angle
- •20.2.2 Choosing the Beam Energy, E0
- •20.2.3 Measuring the Beam Current
- •20.2.4 Choosing the Beam Current
- •Optimizing Analysis Strategy
- •20.3.4 Ba-Ti Interference in BaTiSi3O9
- •20.4 The Need for an Iterative Qualitative and Quantitative Analysis Strategy
- •20.4.2 Analysis of a Stainless Steel
- •20.5 Is the Specimen Homogeneous?
- •20.6 Beam-Sensitive Specimens
- •20.6.1 Alkali Element Migration
- •20.6.2 Materials Subject to Mass Loss During Electron Bombardment—the Marshall-Hall Method
- •Thin Section Analysis
- •Bulk Biological and Organic Specimens
- •References
- •21: Trace Analysis by SEM/EDS
- •21.1 Limits of Detection for SEM/EDS Microanalysis
- •21.2.1 Estimating CDL from a Trace or Minor Constituent from Measuring a Known Standard
- •21.2.2 Estimating CDL After Determination of a Minor or Trace Constituent with Severe Peak Interference from a Major Constituent
- •21.3 Measurements of Trace Constituents by Electron-Excited Energy Dispersive X-ray Spectrometry
- •The Inevitable Physics of Remote Excitation Within the Specimen: Secondary Fluorescence Beyond the Electron Interaction Volume
- •Simulation of Long-Range Secondary X-ray Fluorescence
- •NIST DTSA II Simulation: Vertical Interface Between Two Regions of Different Composition in a Flat Bulk Target
- •NIST DTSA II Simulation: Cubic Particle Embedded in a Bulk Matrix
- •21.5 Summary
- •References
- •22.1.2 Low Beam Energy Analysis Range
- •22.2 Advantage of Low Beam Energy X-Ray Microanalysis
- •22.2.1 Improved Spatial Resolution
- •22.3 Challenges and Limitations of Low Beam Energy X-Ray Microanalysis
- •22.3.1 Reduced Access to Elements
- •22.3.3 At Low Beam Energy, Almost Everything Is Found To Be Layered
- •Analysis of Surface Contamination
- •References
- •23: Analysis of Specimens with Special Geometry: Irregular Bulk Objects and Particles
- •23.2.1 No Chemical Etching
- •23.3 Consequences of Attempting Analysis of Bulk Materials With Rough Surfaces
- •23.4.1 The Raw Analytical Total
- •23.4.2 The Shape of the EDS Spectrum
- •23.5 Best Practices for Analysis of Rough Bulk Samples
- •23.6 Particle Analysis
- •Particle Sample Preparation: Bulk Substrate
- •The Importance of Beam Placement
- •Overscanning
- •“Particle Mass Effect”
- •“Particle Absorption Effect”
- •The Analytical Total Reveals the Impact of Particle Effects
- •Does Overscanning Help?
- •23.6.6 Peak-to-Background (P/B) Method
- •Specimen Geometry Severely Affects the k-ratio, but Not the P/B
- •Using the P/B Correspondence
- •23.7 Summary
- •References
- •24: Compositional Mapping
- •24.2 X-Ray Spectrum Imaging
- •24.2.1 Utilizing XSI Datacubes
- •24.2.2 Derived Spectra
- •SUM Spectrum
- •MAXIMUM PIXEL Spectrum
- •24.3 Quantitative Compositional Mapping
- •24.4 Strategy for XSI Elemental Mapping Data Collection
- •24.4.1 Choosing the EDS Dead-Time
- •24.4.2 Choosing the Pixel Density
- •24.4.3 Choosing the Pixel Dwell Time
- •“Flash Mapping”
- •High Count Mapping
- •References
- •25.1 Gas Scattering Effects in the VPSEM
- •25.1.1 Why Doesn’t the EDS Collimator Exclude the Remote Skirt X-Rays?
- •25.2 What Can Be Done To Minimize gas Scattering in VPSEM?
- •25.2.2 Favorable Sample Characteristics
- •Particle Analysis
- •25.2.3 Unfavorable Sample Characteristics
- •References
- •26.1 Instrumentation
- •26.1.2 EDS Detector
- •26.1.3 Probe Current Measurement Device
- •Direct Measurement: Using a Faraday Cup and Picoammeter
- •A Faraday Cup
- •Electrically Isolated Stage
- •Indirect Measurement: Using a Calibration Spectrum
- •26.1.4 Conductive Coating
- •26.2 Sample Preparation
- •26.2.1 Standard Materials
- •26.2.2 Peak Reference Materials
- •26.3 Initial Set-Up
- •26.3.1 Calibrating the EDS Detector
- •Selecting a Pulse Process Time Constant
- •Energy Calibration
- •Quality Control
- •Sample Orientation
- •Detector Position
- •Probe Current
- •26.4 Collecting Data
- •26.4.1 Exploratory Spectrum
- •26.4.2 Experiment Optimization
- •26.4.3 Selecting Standards
- •26.4.4 Reference Spectra
- •26.4.5 Collecting Standards
- •26.4.6 Collecting Peak-Fitting References
- •26.5 Data Analysis
- •26.5.2 Quantification
- •26.6 Quality Check
- •Reference
- •27.2 Case Study: Aluminum Wire Failures in Residential Wiring
- •References
- •28: Cathodoluminescence
- •28.1 Origin
- •28.2 Measuring Cathodoluminescence
- •28.3 Applications of CL
- •28.3.1 Geology
- •Carbonado Diamond
- •Ancient Impact Zircons
- •28.3.2 Materials Science
- •Semiconductors
- •Lead-Acid Battery Plate Reactions
- •28.3.3 Organic Compounds
- •References
- •29.1.1 Single Crystals
- •29.1.2 Polycrystalline Materials
- •29.1.3 Conditions for Detecting Electron Channeling Contrast
- •Specimen Preparation
- •Instrument Conditions
- •29.2.1 Origin of EBSD Patterns
- •29.2.2 Cameras for EBSD Pattern Detection
- •29.2.3 EBSD Spatial Resolution
- •29.2.5 Steps in Typical EBSD Measurements
- •Sample Preparation for EBSD
- •Align Sample in the SEM
- •Check for EBSD Patterns
- •Adjust SEM and Select EBSD Map Parameters
- •Run the Automated Map
- •29.2.6 Display of the Acquired Data
- •29.2.7 Other Map Components
- •29.2.10 Application Example
- •Application of EBSD To Understand Meteorite Formation
- •29.2.11 Summary
- •Specimen Considerations
- •EBSD Detector
- •Selection of Candidate Crystallographic Phases
- •Microscope Operating Conditions and Pattern Optimization
- •Selection of EBSD Acquisition Parameters
- •Collect the Orientation Map
- •References
- •30.1 Introduction
- •30.2 Ion–Solid Interactions
- •30.3 Focused Ion Beam Systems
- •30.5 Preparation of Samples for SEM
- •30.5.1 Cross-Section Preparation
- •30.5.2 FIB Sample Preparation for 3D Techniques and Imaging
- •30.6 Summary
- •References
- •31: Ion Beam Microscopy
- •31.1 What Is So Useful About Ions?
- •31.2 Generating Ion Beams
- •31.3 Signal Generation in the HIM
- •31.5 Patterning with Ion Beams
- •31.7 Chemical Microanalysis with Ion Beams
- •References
- •Appendix
- •A Database of Electron–Solid Interactions
- •A Database of Electron–Solid Interactions
- •Introduction
- •Backscattered Electrons
- •Secondary Yields
- •Stopping Powers
- •X-ray Ionization Cross Sections
- •Conclusions
- •References
- •Index
- •Reference List
- •Index
419 |
24 |
24.2 · X-Ray Spectrum Imaging
Cube slices are X-ray |
AlK |
maps (images) |
|
50 µm
Y
X
|
|
|
Energy |
|
|
|
|
|
-ray |
||
|
|
||
X |
|
The X-ray spectrum image can be viewed as a card deck of X-ray images, each a 10-eV energy slice
1 keV
. Fig. 24.5 X-ray spectrum image considered as a stack of x, y images, each corresponding to a specific photon energy Ep
24.2.1\ Utilizing XSI Datacubes
In the simplest case, by capturing all possible X-ray information about an imaged region, the XSI permits the analyst to define regions-of-interest for total intensity mapping at any time after collecting the map datacube, creating elemental maps such as those in . Fig. 24.2. If additional information is required about other elements not in the initial set-up, there is no need to relocate the specimen area and repeat the map since the full spectrum has been captured in the XSI.
The challenge to the analyst is to make efficient use of the XSI datacube by discovering (“mining”) the useful information that it contains. Software for aiding the analyst in the interpretation of XSI datacubes ranges from simple tools in open source software to highly sophisticated, proprietary vendor software that utilizes statistical comparisons to automatically recognize spatial correlations among elements present in the specimen region that was mapped (Kotula et al. 2003).
24.2.2\ Derived Spectra
SUM Spectrum
Simple but highly effective software tools that are present in nearly all vendor XSI platforms as well as the open source software (NIH ImageJ-Fiji and NIST Lispix) include those that calculate “derived spectra.” Derived spectra are constructed by systematically applying an algorithm to the datacube to extract carefully defined information. The most basic derived spectrum is the “SUM” spectrum, illustrated schematically in
. Fig. 24.6. Conceptually, each energy “card” in the XSI datacube is selected and the counts in all pixels on that card are added together, as indicated by the systematic route through all pixels shown in . Fig. 24.6. This summed count value is then placed in the corresponding energy bin of the SUM spectrum under construction, and the process is then repeated for the next energy card until all energies have been considered. The resulting SUM spectrum has the familiar features of a conventional spectrum: characteristic X-ray peaks and the
\420 Chapter 24 · Compositional Mapping
Sum Spectrum:
Add the counts from every pixel in each energy plane; the SUM from a plane becomes the intensity in the corresponding energy channel of the derived spectrum.
Y
-ray |
Energy |
|
|
X |
|
X
Counts
3000000
2000000
1000000
0
|
Al K-L2,3 |
|
|
|
|
|
|
|
|
|
Ni L-M |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Ni |
K-L2,3 |
|
|
|
|
|
|
|
|
|
|
Ni K-M2,3 |
|
|
100 |
200 |
300 |
400 |
500 |
600 |
700 |
800 |
900 |
1000 |
|
|
|
|
Channel (X-ray Energy) |
|
|
|
|
|
. Fig. 24.6 Concept of the SUM spectrum derived from an X-ray spectrum image by adding the counts from all pixels on an individual image at a specific photon energy, Ep
X-ray continuum background, as well as artifacts such as coincidence peaks and Si-escape peaks. The SUM spectrum in
. Fig. 24.6 was calculated from the same Raney nickel XSI datacube used for . Fig. 24.4. Note that the count axis now extends to more than 3 million counts, much higher than the count axes of the individual pixel spectra in . Fig. 24.4 because of the large number of pixels that have been added together to construct the SUM spectrum. The characteristic peaks that can be recognized in the SUM spectrum (scaled to the highest intensity) represent the dominant, most abundant elemental features contained in the XSI. The analyst can select a peak
channel and view the corresponding energy card to reveal the elemental map for that peak, as shown in . Fig. 24.7. By selecting a band of adjacent channels that spans the peak and averaging the counts for each x-y pixel in the set of energy cards, an elemental image with reduced noise is obtained, as also shown in . Fig. 24.7. Systematically selecting each of the prominent characteristic X-ray peaks, total intensity maps for all of the major elemental constituents can be obtained. The SUM spectrum can be treated just like a normally recorded spectrum. By expanding the vertical scale or changing from a linear display to a logarithmic display, lower relative intensity
24
24.2 · X-Ray Spectrum Imaging
Counts |
3000000 |
|
2000000 |
||
|
1000000 |
NiLaa |
|
|
0 |
|
|
100 |
421 |
|
24 |
|
|
|
AIKa |
NiKa CuKa |
|
|
|
NiKh |
CuKh |
|
600 |
800 |
900 |
1000 |
Channel (X-ray Energy) |
|
|
|
730 |
766 |
|
|
Single ‘slice’ or X-ray channel at the NiKα peak
Multichannel image for Ni peak.
. Fig. 24.7 Using the SUM spectrum to interrogate an X-ray spectrum image to find the dominant elemental peaks for the region being mapped
peaks corresponding to minor and trace constituents can be recognized, and the corresponding total-intensity region-of- interest images can be constructed, subject to the increasing influence of the continuum background incorporated in the window. For these lower abundance constituents, it is necessary to use a band of energy channels to reduce the noise in the resulting elemental image, and such images are subject to the artifacts that arise from the atomic number dependence of the X-ray continuum noted above.
MAXIMUM PIXEL Spectrum
The SUM spectrum reveals dominant elemental features in the mapped region. Rare, unexpected elemental features, which in the extreme case may occur at only a single pixel (i.e., looking for a “needle-in-a-haystack” when you don’t even know that it
is a needle you are looking for!) can be recognized with the “MAXIMUM PIXEL” derived spectrum (Bright and Newbury 2004). As shown in . Fig. 24.8, the MAXIMUM PIXEL derived spectrum is calculated by making the same tour through all of the pixels on each energy card as is done for the SUM spectrum, but rather than adding the pixel contents, the algorithm now locates the maximum intensity within a card regardless of what pixel it comes from to represent that energy value in the constructed MAXIMUM PIXEL spectrum. An example of the application of the MAXIMUM PIXEL spectrum to an XSI is shown in . Fig. 24.9, where an unanticipated Cr peak is recognized. When the Cr image is selected from the XSI, the Cr is seen to be localized in a small cluster of pixels. Note that in the plot of the SUM, LOG10SUM, and MAXIMUM PIXEL spectra in . Fig. 24.9, the Cr peak is only visible in the MAXIMUM
422\ Chapter 24 · Compositional Mapping
. Fig. 24.8 Concept of the MAXIMUM PIXEL spectrum derived from an X-ray spectrum image by finding the highest count among all the pixels on an individual image at a specific photon energy, Ep
Counts
Maximum Pixel Spectrum
Y |
|
-ray |
Energy |
|
|
X |
|
X |
|
Test every pixel in an energy plane to find the MAXIMUM value. This maximum value
becomes the intensity in the corresponding energy channel of the derived Maximum Pixel Spectrum.
200 |
|
AlK |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|||
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
150 |
|
|
|
|
|
|
|
|
|
|
|
100 |
NiL |
SiK |
|
|
|
|
|
|
|
|
|
|
|
ClKα CaKα |
|
|
CrKα |
|
NiKα CuKα |
|
|
||
50 |
|
|
|
|
|
|
|
|
|||
0 |
|
|
|
|
|
|
|
|
NiKβ |
|
|
|
100 |
200 |
300 |
400 |
500 |
600 |
700 |
800 |
900 |
1000 |
Channel (X-ray Energy)
PIXEL spectrum. Because Cr is represented at only a few pixels, in the SUM spectrum the Cr intensity is overwhelmed by the continuum intensity at all of the other pixels, so that the Cr peak is not visible even in the logarithmic expansion shown in the LOG10SUM plot.
After the elemental maps have been created from the XSI, additional image processing tools can be brought to bear. Spatial regions-of-interest can be defined in the elemental maps or in corresponding BSE or SE images recorded simultaneously with the XSI. These spatial regions can be selected by simple image processing tools that define a group of contiguous pixels that fall within a particular shape (square, rectangle, circle, ellipsoid, or closed free
form are typical choices). Another approach is the creation of a pixel mask by selecting all pixels within a particular elemental map (or BSE or SE image) whose intensities fall within a defined range above a specified gray level threshold. Pixels that satisfy this intensity criterion can occur anywhere in the x–y plane of the XSI and do not have to be contiguous. Selections can range down to an individual pixel. An example of this process is shown in . Figure 24.10, where the Fe-rich phase has been selected from the Fe total intensity map (shown in color overlay with Al and Ni) to create a mask (shown as a binary image in the inset) from which the SUM spectrum representing the Fe-rich phase is constructed.
24
423 |
24 |
24.2 · X-Ray Spectrum Imaging
Cr
10 m |
Al Cr Ni |
|
AlK
1.0
Relative intensity
0.9NiL
0.8 |
|
NiKα |
|
|
|
0.7 |
CrKα |
NiKβ |
0.6 |
|
FeKα |
0.5 |
|
Log10 SUM |
|
|
|
0.4 |
|
|
0.3 |
|
MAXIMUM PIXEL |
0.2
0.1SUM
0.0
500 |
1000 |
1500 |
Sum Log sum Max |
running sum |
log running sum |
running max |
. Fig. 24.9 Use of the MAXIMUM PIXEL spectrum to identify and locate an unexpected Cr-rich inclusion in Raney nickel alloy