1. Lecture 4 - Spectroscopy
Analytical Electron Microscopy (AEM), Energy Dispersive Spectroscopy (EDS), Electron Energy Loss Spectroscopy (EELS),,
EDS-EELS Spectrum Imaging,
Energy Filtered TEM (EFTEM)

36. What we are mostly interested in measuring by EELS in the TEM is inelastic electron scattering
Elastic scattering
Phonon scattering (few meV)
Quasi-elastic
Thermal diffuse scattering
Plasmon excitation (10-30 eV)
Collective excitation of
conduction electrons
Valence electron excitation
Inner-shell ionization
Core losses
Absorption edges
Most useful for:
Composition
Bonding

37. 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

38. 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

39. Gatan parallel-collection electron energy-loss spectrometer (PEELS) curved pole piece entrance/exit faces; double-focusing 90° magnetic prism

40. Information from energy-loss spectrum

41. Nomenclature for inner-shell ionization edges

42. 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)

43. Anatomy of an electron energy-loss spectrum (TiC, 100kV, b = 4
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

44. Low-loss region Plasmons and thickness determination
Plasmons are collective excitations of valence electrons
Lifetime 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, 0 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
(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 Z where Z is average atomic number
F = {1 + (E0/1022)} / {1 + (E0/511)2}
Java script at Nestor’s web site

47. 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)}

48. 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 
Joy proposed a correction to reduce s(D,b).
Reduction factor R = [ln{1+(/)2} b] / [ln{1+(b/)2} ]

49. 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).

50. 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)

51. 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

52. 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

53. Energy-loss near-edge structure (ELNES) indicative of empty
(unfilled) density of states (DOS)

54. Additional examples of ELNES

55. 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)

56. 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

57. Spectrum imaging in STEM - Philips CM200FEG with Emispec Vision Simultaneous EDS and EELS (with GIF) Co-Cr-Pt-B developmental media
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
DF STEM
B K
Cr L23
Co L23
Cr Ka
Co Ka
Pt Ma
0-20 keV

58. Typical EDX spectrum from a B-poor region in Sample 4965B
Elemental Composition
Edge Intensity k-factor Weight% Atomic%
Cr Ka * % %
Co Ka * % %
Pt La * % %
Calculated k-factor for Pt-La may be suspect.
No k-factor for Pt Ma available.

59. 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 Intensity k-factor Weight% Atomic%
Cr Ka * % %
Co Ka * % %
Pt La * % %

60. 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
Green curve is x16 Cr B O Co C

61. B-rich PEELS background fit, regular AE-r (log-poly same)
Shape of B edge as expected
Quant: B:Co = /- 0.06
Normalized Composition
Co Cr Pt B
at%
Purple curve is x8

62. Spectrum Lines of Soft Magnetic Multilayers

63. Nine Layer FeTaN/IrMn

64. Makes Quantification Difficult
Overlapping EDS Peaks
Makes Quantification Difficult
Combining EDS and EELS
Allows for Fe, Ta, N, Ir, and Mn Quantification

66. Two types of imaging filter for EFTEM In-column omega (or variants), used by Leo (Zeiss) and JEOL Post-column Gatan imaging filter (GIF)

67. Gatan imaging filter

68. Basic EFTEM operation Images or diffraction patterns GIF magnification ~19, so MSC chip um 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.

69. 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 OK
CrL23
CoL23 1 2 3
Co Jump ratio
Co Map
Co Pre-edge 1
Co Pre-edge 2
Co Post-edge
100 nm

70. 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 OK
CrL23
CoL23 1 2 3 4
O pre-edge 1
O pre-edge 2
O post-edge
Cr post-edge
100 nm
Cr map
Cr jump ratio

71. 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 map
Co map
Cr/Co map ratio
100 nm

72. 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

73. MA 12YWT (Fe-12%Cr-3%W-0. 4%Ti-0
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)

74. 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