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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. Ionization by fast electrons in the TEM Alternative ways of de-excitation

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Phase identification by combining local composition from EDX with information from diffraction database


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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
Composition by EDX
  • 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
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
Fluorescence yield

First problem with light element detection

cascading of x ray lines
Cascading of X-ray lines
  • Naming convention
  • Quantitative analysis uses one analytical line  weight of lines is needed
self absorption in the sample
Self-absorption in the sample
  • 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
Detection in EDS
  • , Fano factor
  • Escape peak
  • Dead-layer
  • Detector thickness
from detector to x ray analyzer
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 analyzer10
From detector to X-ray analyzer
  • Temperature  Window
  • Detection of light elements
artifacts ice
Artifacts: ice

Can be identified and removed

quantitative analysis
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
Quantitative analysis: standardless
  • Intensity:
    • For high energy electrons: NQ(E0)
  • Atomic data, Detector parameters
  • Sample thickness: absorption
  • Secondary fluorescence
  • Artifacts: escape, contamination, spectral, channelling
thin sample criterion
Thin sample criterion
  • 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
Artifacts: spectral contamination
  • Stray radiation from thick parts
  • Can be identified
  • Frequently can be corrected for
structure from art i fact alchemi
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
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
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
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
The JCPDS cards in the Pdf-2 database

As shown by the PCPDFWIN program

Name & reference

Space group, cell parameters

d-spacing, Intensity, Miller-indices

Radiation, wavelength, filter

searching for known structures in the xrd database processdiffraction
Searching for known structures in the XRD database: ProcessDiffraction

Filtering for elements

Filtering for d-values

why xrd database can only be used for qualitative phase analysis in electron diffraction
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 modeland nanocrystalline samples
conclusion
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