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 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

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

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 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

Typical EDX spectrum from a B-poor region in Sample 4965B Elemental Composition Edge Intensity k-factor Weight% Atomic% Cr Ka 29 1.308* 11.68% 17.93% Co Ka 106 1.493* 48.60% 65.82% Pt La 25 5.279* 39.72% 16.25% Calculated k-factor for Pt-La 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 Intensity k-factor Weight% Atomic% Cr Ka 33 1.308* 19.33% 29.75% Co Ka 58 1.493* 39.22% 53.25% Pt La 17 5.279* 41.45% 17.00%

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

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

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

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

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

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

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

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)

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