Lecture 4 - Spectroscopy
Analytical Electron Microscopy (AEM),
Energy Dispersive Spectroscopy (EDS),
Electron Energy Loss Spectroscopy (EELS),,
EDS-EELS Spectrum Imaging,
Energy Filtered TEM (EFTEM)
What we are mostly interested in measuring by EELS in
the TEM is inelastic electron scattering
Elastic scattering
Phonon scattering (few m
Quasi-elastic
Thermal diffuse scattering
Plasmon excitation (10-30
Collective excitation of
conduction electrons
Valence electron excitatio
Inner-shell ionization
Core losses
Absorption edges
Gatan parallel-collection electron energy-loss spectrometer
(PEELS)
Attaches to base of camera/viewing chamber of TEM
Additional ports for scintillator and PMT for on-axis STEM detector
Gatan electron energy-loss spectrometer (EELS)
Old-style serial-collection; newer parallel-collection (PEELS)
Latest PEELS (Enfina) uses a CCD detector instead of a photodiode array
Gatan parallel-collection electron energy-loss
spectrometer (PEELS)
curved pole piece entrance/exit faces; double-focusing 90°
magnetic prism
Information from energy-loss spectrum
Nomenclature for inner-shell ionization edges
L3 and L2 white lines for 3d transition metals
Transitions from 2p to unfilled 3d states
Similar M5 and M4 white lines for Lanthanides (unfilled 4f states)
Anatomy of an electron energy-loss spectrum
(TiC, 100kV, b = 4.7 mrad, a = 2.7 mrad, t/l = 0.52)
from Disko in Disko, Ahn, Fultz, Transmission EELS in Materials Science, TMS,
Warrendale PA, 1992
I0 zero loss or elastic peak
low-loss region <40eV, dominated by bulk plasmon at 23.5 eV
Carbon K edge, 285 eV, 1s shell electron excited
Titanium L23 edge, 455 eV, 2p shell
Low-loss region
Plasmons and thickness determination
Plasmons are collective excitations of valence electrons
Lifetime 10-15 s, localized to <10 nm
Ep = hwp/2p = h/2p (ne2/e0m)0.5
h is Planck’s constant, n is free-electron density,
e and m are electron charge and mass, e0 is permittivity of free space
Characteristic scattering angles are small <1 mrad
Thickness (t) determination:
t/l = ln (IT/I0)
l is inelastic scattering mean free path (average distance between scattering events)
and is inversely proportional to scattering cross section
IT is total intensity, I0 is zero-loss intensity
l(nm) = 106 F (E0/Em) / ln (2b E0/Em)
E0 is in kV, b in mrad, F is a relativistic correction factor ~1 for E0 < 300 kV,
Em is the average energy loss in eV
Em = 7.6 Z0.36 where Z is average atomic number
F = {1 + (E0/1022)} / {1 + (E0/511)2}
Java script at Nestor’s web site http://tpm.amc.anl.gov/NJZTools/NJZTools.html
Quantitative microanalysis with core-loss EELS
(TiC spectrum from Disko)
Isolation of core-loss intensities that scale with atomic concentrations
Atomic fractions or atoms/area with use of atomic scattering cross sections
Least squares fit of form AE-r to
model background ~50 eV before
each edge
Extrapolated to higher energy losses
Integrated counts above extrapolated
background give shaded core-edge
intensities in energy windows width D
IC(D,b) = NC sC(E0,D,b) I (D,b)
NC carbon atoms/area
IL(D,b) = total spectrum intensity up to
an energy loss D
sC = partial ionization cross section at
incident beam energy E0 up to a
maximum scattering angle b
(collection semiangle)
No need for I0(D,b) if use element ratios:
NC/NTi = {IC(D,b) / ITi(D,b)} {sTi(E0,D,b)
/ sC (E0,D,b)}
Quantitative microanalysis with core-loss EELS
Selection and measurement of acquisition parameters
The sample must be thin !
Typically t/l 0.3 to 0.5
The collection angle b should be set to
an appropriate value wrt the
characteristic scattering angle
 = E/2E0
(E0 should be relativistic)
Typically b ~ few times  (few mrad)
If b is too large:
S/B decreases (just extra background)
Include diffracted beams
But b should be larger than the incident beam convergence semi-angle a
Joy proposed a correction to reduce s(D,b).
Reduction factor R = [ln{1+(a/ )2} b ] / [ln{1+(b/ )2} a ]
Background fitting
Background comes from tails of (multiple) plasmons and core edges at lower
energy losses (especially outer-shells)
Inverse power law, IB = AE-r
Least squares fit to ln(I) versus ln(E)
A and r valid over a limited energy range
r is typically between 2 and 5, and decreases for increases in t, b, and E
For E < ~200 eV, AE-r commonly fails to give a good fit and extrapolation
Working with 3dTM borides in the early 80’s we developed the log-poly
background fitting for B. It is the most useful and reliable alternative to AE-r.
Polynomials do not extrapolate sensibly - do not use them.
Usually a quadratic, sometimes a third order polynomial, will cope with the small
curvature in ln(I) versus ln(E)
Mike Kundmann wrote a log-poly function for Gatan’s EL/P software.
JK Weiss included it in ESVision as nth order power law fit (select n).
Cross sections
Calculated (Egerton, Rez), parameterized (Joy)
Measured from standards, similar to k-factors in EDS
Egerton’s SIGMAK and SIGMAL used in EL/P
(Fortran) code listed in Egerton’s book
Hydrogenic model but works well
A white-line correction is also selectable in
EL/P, but best to define D beyond WLs
EL/P v3 also has Rez’s Hartree-Slater models
(includes M edges)
Plural scattering
Spectral components near core edge for “real” spectrum
1 detector noise and spurious
scattering in the spectrometer
2 single scattering tails of valence
Or lower-energy core excitations
3 plural inelastic scattering involving
(2) Combined with one or more
“plasmon” excitations
4 single scattering core edge intensity
5 plural inelastic scattering involving
Core excitation combined with one or
More “plasmon” excitations
If component 1 is small, AE-r inverse power law background fitting still works
Plural scattering - effect of increasing thickness
BN at 100 kV (Leapman in Disko et al)
S/B for boron decreases by a factor of 15
Energy-loss near-edge structure (ELNES) indicative of empty
(unfilled) density of states (DOS)
Additional examples of ELNES
Radial distribution functions by EXELFS analysis
Extended energy-loss fine structure (cf EXAFS extended x-ray absorption fine
structure)
EXELFS good for low-Z major constituents at high spatial resolution
(EXAFS advantageous for higher-Z and low concentrations)
Spectrum images and lines
A complete spectrum acquired and stored for each pixel in an image
terminology from Jeanguillaume and Colliex
spectral images/profiles also used
Acquisition of spectra one at a time is still useful in many investigations, e.g. phase
Identification, in-situ changes in composition or bonding
For composition gradients, repetitively re-positioning a small probe manually to
measure spectra is inaccurate, inefficient and time consuming
Modern integrated acquisition systems are available to automate the set-up,
acquisition, and processing of spectral series
Post processing with user interaction is usual, but can be done on-the-fly (e.g., to
create elemental maps)
Gatan - EELS only but have tried simultaneous EDS
Emispec Vision (Cynapse), TIA on FEI Tecnai - multiple simultaneous
spectroscopies, including EELS and EDS (any manufacturer) - less comprehensive
processing for EELS
Spectrum imaging in STEM - Philips CM200FEG with Emispec Vision
Simultaneous EDS and EELS (with GIF)
Co-Cr-Pt-B developmental media
DF STEM
BK
Cr L23
Co L23




0-20 keV
Pt Ma
Cr Ka
Co Ka



1 nA in 1.6 nm probe
1 s dwell/pixel
64 x 64 pixels
All elements accessible
with combined EDS
and EELS
Clear intergranular
boron segregation
Log-polynomial
background fitting
insufficient for reliable
boron intensities
Compositions from
ratios of maps with k
factors
Typical EDX spectrum from a B-poor region in
Sample 4965B
Elemental Composition
Edge Intensity
Weight% Atomic%
Cr Ka
11.68%
29
17.93%
Co Ka
48.60%
106
65.82%
Pt La
39.72%
25
16.25%
k-factor
1.308*
1.493*
5.279*
Calculated kfactor for PtLa may be
suspect.
No k-factor
for Pt Ma
available.
Typical EDX spectrum from a B-rich region in
Sample 4965B
Similar Pt, higher Cr, and lower Co compared to B-poor region
Elemental Composition
Edge
Atomic%
Intensity
k-factor
Weight%
Cr Ka
29.75%
33
1.308*
19.33%
Co Ka
53.25%
58
1.493*
39.22%
Pt La
41.45%
17
17.00%
5.279*
B-rich PEELS (from single pixel in Emspec Vision,
transferred to Gatan EL/P)
Low S/B for B, C is largest peak (overcoat + contamination?), O-K in front of Cr
L23, low Co L23
Cr
B
Green curve is x16
O
Co
C
B-rich PEELS background fit, regular AE-r (log-poly same)
Shape of B edge as expected
Quant: B:Co = 0.37 +/- 0.06
Normalized Composition
Co Cr Pt B
44 25 14 17 at%
Purple curve is x8
Spectrum Lines of Soft Magnetic Multilayers
Nine Layer FeTaN/IrMn
2500
Ir Lb
Ta La
Fe Kb
Mn Ka
2000
Counts
1500
1000
500
0
0
50 nm
400
5
10
15
20
Position (nm)
25
30
Mn
Ir
Counts
300
200
Ir
Ir
100
Mn
Fe
Fe
Ir
Mn
Ta
Ir
Ta
Ir
0
0
5
10
Energy (keV)
15
Overlapping EDS Peaks
Makes Quantification Difficult
400
Mn
Counts
300
Ir
Fe
200
Mn
Fe
Ir
Ir
100
Ta
Mn
Ir
Fe
Ir
Ta
0
0
5
10
Energy (keV)
Combining EDS and EELS
Allows for Fe, Ta, N, Ir, and Mn Quantification
15
1.00
0.90
0.80
atom fraction
0.70
Ta
Ir
N
Fe
Mn
0.60
0.50
0.40
0.30
0.20
0.10
0.00
-0.10
-10.00
0.00
10.00
20.00
30.00
40.00
distance nm
50.00
60.00
70.00
Two types of imaging filter for EFTEM
In-column omega (or variants), used by Leo (Zeiss) and JEOL
Post-column Gatan imaging filter (GIF)
Gatan imaging filter
Basic EFTEM operation
Images or diffraction patterns
GIF magnification ~19, so MSC chip 10242 24um pixels equivalent to ~1mm on
TEM screen
Select pass band of energies (energy-losses) with slits.
Lower slit edge is fixed, upper slit edge is movable to adjust slit width.
Instead of displacing the slit or changing the magnet current to select different
energy losses, the accelerating voltage is increased by the energy loss desired. The
initial nominal accelerating voltage is reduced by 3kV to avoid exceeding the
manufacturers specifications.
Electrons are always the same energy after passing through sample.
No chromatic shifts or changes in magnification.
Do not have to change the excitation of the imaging lenses or imaging filter
multipoles.
The probe-forming (condenser) lenses must track with the accelerating voltage to
keep illumination “constant;” in practice there is a lot of hysteresis.
Co80Cr16Ta4 Generation of Co map and jump ratio images
Map: subtraction from post-edge image AE-r extrapolation of pre-edge 1 and 2
Jump ratio: post-edge image divided by pre-edge image
Co Pre-edge 1
Co Pre-edge 2
Co Post-edge
100 nm
Co Jump ratio
OK CrL23
CoL23
12 3
Co Map
Generation of Cr map and jump ratio images
Map: 4-window (DM custom script) to account for O edge from surface oxide
(AE-r fit: Two O pre-edge images define exponent r, O post-edge to define A)
Jump ratio: Cr post-edge image divided by O post-edge image
O pre-edge 2
O pre-edge 1
O post-edge
Cr post-edge
100 nm
CrL23
OK
12 3 4
CoL23
Cr jump ratio
Cr map
Quantitative compositions from EFTEM elemental map ratios
Compensates for diffraction contrast, and variations in thickness and illumination
Use k-factors or calculated cross sections to convert to concentration ratios
Cr/Co map ratio
Cr map
=
Co map
100 nm
Si3N4-SiCw composite sintered with Y2O3 and Al2O3
Composition differences between intergranular films and pockets
~30 at.% N in intergranular films (<5% N in triple-point pockets)
S/N for oxygen suggests fractional monolayer detectability
N signal
O signal
low loss
100 nm
1.3 nm
1.5 nm
2.0 nm
MA 12YWT (Fe-12%Cr-3%W-0.4%Ti-0.25%Y2O3) ferritic steel crept at 800°C
EFTEM Fe-M and Ti-L jump ratio images reveal nano-clusters
t/l = 0.22 (31nm), cluster concentration = 2.5 x 1023 m-3 (c.f. APT 1 x 1024 m-3)
Fe M jump ratio
100 nm
Ti L jump ratio

Electron energy-loss spectroscopy (EELS) and
energy-filtered transmission electron microscopy
(EFTEM)
Summary
and
resources
More difficult to perform
and interpret
than
EDS

Plasmons - not elementally specific but large signal

Core losses - integrated intensities yield compositions - not all elements have
edges that can be used in practice

ELNES - information on chemistry - bonding and valence

EXELFS - radial distribution functions for low-Z major constituents

EFTEM - quantitative elemental mapping at 1 nm resolution

“EELS in the Electron Microscope,” R F Egerton, Plenum 1986, 1995

“Transmission EELS in Materials Science,” M M Disko et al eds, TMS 1992
(second edition in preparation, Cambridge University Press)

Gatan EELS software (EL/P for Mac now obsolete)

“EELS Atlas,” C C Ahn and O L Krivanek, Gatan Inc and ASU 1983