eels: introduction and new developments · 2019. 9. 4. · in multi-modal electron tomography, tilt...

TEMSpec - 4th International workshop on TEM spectroscopy in Material Science

EELS: introduction and new developments

Cécile Hébert Centre Interdisciplinaire de Microscopie Electronique

Laboratoire de Spectrométrie et Microscopie Electronique Ecole Polytechnique Fédérale de Lausanne

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Outline

•  Introduction •  Core Loss EELS •  Low losses •  Super low losses •  Conclusion


Introduction EELS in the TEM Probe = electrons

100-300 kV 80�60�30�20� Velocity: 0.55-0.77 c

Incoming e-

Auger e-

Elastically scattered e-

Inelastically scattered e-

X-rays photons


Introduction: inelastic? Incoming e-

Auger e-



X-rays photons

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Introduction: inelastic? Incoming e-

Auger e-



X-rays photons


Introduction: inelastic!

Interaction E loss Crystal Atom Electron

Phonon 10 meV inelastic elastic --

At. displacement 10 eV inelastic elastic --

interband ~ eV inelastic inelastic elastic

exciton ~ eV inelastic inelastic --

plasmon ~10 eV inelastic -- --

ionization ~100-1000eV inelastic inelastic elastic

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Introduction: excitation processes

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Introduction

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Introduction ⇒

O

→ e-

loss

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Cross over (chromatic object plane)

Filtered image or DP

Chromatic image plane (spectrum,energy selecting slit)

Achromatic image plane

Image or diff.pattern on the SEA (achromatic object plane)

Sample

Filter

Operated as energy filter

Introduction: energy filter


Cross over (chromatic object plane)

Spectrum

Chromatic image plane (spectrum,energy selecting slit)

Achromatic image plane

Image or diff.pattern on the SEA (achromatic object plane)

Sample

Filter

Two possibilites: in- or post-column

Operated as spectrometer

Introduction: energy filter


ΔE

ΔE

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3D Data cubes: EFTEM vs. (STEM)-EELS

An energy filtered image is a slice from the 3D data cube.

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Each recorded spectrum corresponds to a column in the 3D data cube.

Introduction: I want it all


Outline •  Introduction •  Core Loss EELS •  Low losses •  Super low losses •  Conclusion


Core Losses: chemical quantification

R F Egerton, Electron energy-loss spectroscopy in the TEM, Rep. Prog. Phys. 72 (2009) 016502 (25pp); Egerton R F 1996 Electron Energy-Loss Spectroscopy in the Electron Microscope 2nd edn (New York: Plenum/Springer)

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Core Losses: new developments 3D tomography using EELS and EDX

Nanoscale, 2014,6, 14563-14569


Raw EFTEM datacube. Energy loss range: 350-760 eV 10 eV slit width, 5 eV step Microscope: TEM JEOL 2200 FS 200 keV, FEG, in column Omega filter

Ti L2,3

O K

Cr L2,3

Fe L2,3

Data cleaning: 1- removal of “X-rays”, 2- drift correction, 3- PCA

Sample preparation: C- extraction

EFTEM in core loss: ODS steel

1


Principal Components Analysis applied to EFTEM data cube Energy loss range: 350-760 eV Microscope: TEM JEOL 2200 FS 200 keV, FEG, in column Omega filter

Ti L2,3

O K

Cr L2,3

Fe L2,3

EFTEM in core loss: ODS steel o.

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EELS fingerprints:

ß Y-O particles: 6 %, 16 nm

ß Ti-Cr-O particles: 4 %, 33 nm

ß Y-Ti-O particles: 90 %, 6 nm P. Unifantowicz, R. Schäublin, C. Hébert, T. Płociński, G. Lucas, N. Baluc, Journal of Nuclear Materials Volume 422, Issue 1-3, March 2012, Pages 131-136

EFTEM chemical maps

EFTEM in core loss: ODS steel

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Core Losses: challenge

In multi-modal electron tomography, tilt series of several signals such as X-ray spectra, electron energy-loss spectra, annular dark-field, or bright-field data are acquired at the same time in a transmission electron microscope and subsequently reconstructed in three dimensions. However, the acquired data are often incomplete and suffer from noise, and generally each signal is reconstructed independently of all other signals, not taking advantage of correlation between different datasets. ��In this paper, we show how image quality in multi-modal electron tomography can be greatly improved by employing variational modeling and multi-channel regularization techniques. �This favors similar interface positions for all reconstructions, thereby improving the image quality for all data, in particular, for 3D elemental maps. We demonstrate the joint multi-channel TGV reconstruction on tomographic energy-dispersive X-ray spectroscopy (EDXS) and high-angle annular dark field (HAADF) data, but the reconstruction method is generally applicable to all types of signals used in electron tomography, as well as all other types of projection-based tomographies.

Nanoscale, 2019,11, 5617-5632

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Core Losses fine structures

R F Egerton, Electron energy-loss spectroscopy in the TEM, Rep. Prog. Phys. 72 (2009) 016502 (25pp); Egerton R F 1996 Electron Energy-Loss Spectroscopy in the Electron Microscope 2nd edn (New York: Plenum/Springer)


Core losses: ELNES

Diamond Graphite

Carbon K edge


ELNES

ELNES or “Electron Energy Loss Near”

EELS

•

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ELNES of anisotropic materials

k k’

q

Core losses: ELNES


Applications: Irradiated graphite

Loïc Fave, Teresa Dennenwaldt, Duncan Alexander, Cédric Baumier, Manuel A. Pouchon, Cécile Hébert : in preparation.

-  SiC/SiC composites forseen as cladding tubed for nuclear power plants.

-  A graphitic carbon inter layer acts as mechanical improvement of the otherwise brittle ceramics


Application: Iron oxidation state in minerals

Iron content and valence state

PNAS October 4, 2016 113 (40) 11127-11130


Application: EMCD -

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Outline •  Introduction •  Core Loss EELS •  Low losses •  Super low losses •  Conclusion


Angular resolved low loss

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A. Alkauskas et al., Ultramicroscopy 110 (2010) 1081–1086

Evolution of the loss function of bulk Silver in the energy range 0-55 eV as a function of momentum transfer q in the (1 1 1) direction including local field effects.

Angular resolved EELS in Ag, calculation

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Data acquisition Standard acquisition method

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Data Acquisition

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EFTEM acquisition : NBD

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A. Alkauskas et al. Ultramicroscopy 110 (2010) 1081–1086

TEM image spectrum, Sputtered Ag

1 2

3

4

5 6

7

2 3

4

5 6 7

1

Experimentl results


Experimental results


Experimental results

Yoyo !


Outline •  Introduction •  Core Loss EELS •  Low losses •  Super low losses •  Conclusion &


Ultra-high energy resolution EELS

Ultramicroscopy 203 60–67 (2019)

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Momentum-resolved EELS Senga and Suenaga arXiv: 1812.08294

MORE-TEM project: Mtm-resolved (0.01 Å–1) Spatially-resolved 1 meV !E 4 K temperature “To compete with the synchrotron”

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Conclusion

Amazing recent developments Challenges in data handling and analysis New generation of detectors Software / open versus closed��

eels: introduction and new developments · 2019. 9. 4. · in multi-modal electron tomography, tilt...

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