Transcript Phase identification by combining local composition from

Phase identification by combining
local composition from EDX with
information from diffraction database
János L. Lábár
•Introduction to EDX analysis
•Usage of the XRD database
Composition by EDX
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Ionization by fast electrons in the TEM
Alternative ways of de-excitation
Photons leaving the sample
Detection / detectors
Qualitative vs. quantitative analysis
Precision, accuracy, detection limits, spatial
resolution
• Artifacts and their elimination
• Effect of crystal structure: ALCHEMI
Excitation and de-excitation
• Primary process:
ionization  EELS
• Competing secondary
processes: XR / AE
• Single-electron
process: X-ray photon
emission
• Two-electron process:
Auger electron
emission
• Connection:
fluorescence yield
=NX/(NX+NA)
Fluorescence yield
First problem with light element detection
Cascading of X-ray lines
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Naming convention
Quantitative analysis uses one analytical line  weight of lines is needed
Qualitative analysis is based on
Moseley’s law
Self-absorption in the sample
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Absorption path length vs. thickness, ideal geometry Lt*cosec()
Thin-film approximation  No thickness is needed
Methods to determine thickness (EELS, CBED, …)
Accuracy problems with light elements, irregular samples
Detection in EDS
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, Fano factor
Escape peak
Dead-layer
Detector
thickness
From detector to X-ray analyzer
• Detector +
preamplifier
• Main amplifier, MCA,
pile-up rejection
• Spectral resolution,
• Si  Ge
FWHM2 =N + FE
• Temperature
From detector to X-ray analyzer
• Temperature
 Window
• Detection of
light elements
Artifacts: ice
Can be identified and removed
Quantitative analysis
Cliff-Lorimer:
thin film appr.
cA/cB=kAB*(IA/IB)
• kAB is dependent
on the detector
• Significant
differences in
„sensitivity”
• Standards vs.
standardless
Quantitative analysis: standardless
• Intensity:
I A,li  Vi  i  Rli  PEli 
VL3  N3  N2  f1,2  N1  f1,3  f1,2  f2,3
– For high energy electrons: NQ(E0)
• Atomic data, Detector parameters
  
 
 
 


PE     exp       tj  1  exp      t 
 j  
 
j
   d
d 

 
• Sample thickness: absorption
• Secondary fluorescence
• Artifacts: escape, contamination, spectral, channelling
Thin sample criterion
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Different condition for EDS and imaging
Thickness not needed for many samples
Depends on detector position for EDS
Depends on combination of elements
Determination of thickness: CBED, …
Artifacts: spectral contamination
•Stray
radiation
from thick
parts
•Can be
identified
•Frequently
can be
corrected for
Structure from „artifact”: ALCHEMI
• Bloch-waves in crystals
• Orientation-dependent
excitation
• Inhomogeneous within
unit cell  syst. error
• Main components at
known sites = inner
standards
• Location of minority c.
(additional information)
ALCHEMI example: garnet
• Calculations predicted
distinct variation of all
three crystallographic
sites (in a rest. range)
• Experiment proved it
for main components
• Location of minority
Ca and Mn is
unambiguously
determined
Summary: EDS analysis in the TEM
• Multi-elemental, parallel
• 5  Z (with ATW)
• Elemental compositions (not sensitive to the
chemical state)
• Detection limit  0.1 wt%
• Accuracy 2-10% (standardless vs. standards,
stray radiation)
• Spatial resolution: 1 nm (FEG), 10 nm (LaB6),
(sample thickness)
The XRD powder database
• Evolution of the ICDD database
– JCPDS cards
– Pdf-2 database
– Pdf-4 relational database, time-lock, atomic p.
• Usage of the database
– ICDD software
– Manufacturer’s software
– Other programs (ProcessDiffraction)
The JCPDS cards in the Pdf-2 database
As shown by the PCPDFWIN program
Name &
reference
Space group, cell
parameters
Radiation, wavelength, filter
d-spacing, Intensity, Miller-indices
Searching for known structures in
the XRD database
ICDD
softwares
• PcPdfWin
• PcsiWin
Searching for known structures in the XRD
database: ProcessDiffraction
Filtering for
elements
Filtering for
d-values
Usage of XRD database information in
ProcessDiffraction
Why XRD database can only be used for
qualitative phase analysis in electron
diffraction?
• X-rays are scattered on the electrons of the
sample

• Fast electrons of the TEM are scattered on total
charge (electrons + nuclei)
•  Intensities of the diffracted lines are different
•  Quantitative phase analysis needs a
calculation of intensities from a structural model
and nanocrystalline samples
Conclusion
• Unambiguous phase identification needs both
compositional and structural information.
• Composition from EDS (or EELS)
• XRD database is a useful collection of known
structures  easiest first source of information
during assessment of SAED patterns
• Quantitative phase analysis needs a calculation
of intensities from a structural model