Analytical spectroscopic techniques such as electron energy loss spectroscopy (EELS) and
energy-dispersive X-ray spectroscopy (EDXS) are indispensable tools in materials science
as they reveal elemental composition of the specimen and, in case of EELS, can point out
the chemical bonding and electronic properties. Moreover, this spectroscopic information can
be acquired in tomographic fashion via tilting the specimen within the electron microscope
(EM) between recording of spectral images and be used to reconstruct 3D composition [1].
Despite some solutions being currently available for the automatization of holder tilting and
image capture during HAADF and EDXS signal acquisition (FEI Tomography, TEMology),
these are mostly commercial and tailored for specific Microscope/Detector combination. At
the same time EELS tilt series acquisition remains a laborious manual task limiting the tilt
range and exposure times available even for otherwise beam-stable materials, leading to
poor signal and missing wedge artefacts. It is additionally difficult to benefit from the
complementary nature of imaging and spectroscopic EM techniques in 3D characterization.
Often spectroscopic detectors are installed on separate microscopes or belong to different
manufacturer, excluding their parallel use for tomography.
We demonstrate two approaches to a combination of EELS, EDXS and HAADF tomographic
signals in multimodal reconstruction using GAPTOR software [2]. First includes universal
automatization of spectroscopic signal tilt series acquisition using open-source scripting
language AutoHotKey. Second allows combination of spectroscopic tomography data
acquired (e. g. on different microscopes) with different field of view, pixel size and tilt range
parameters.
Period | 4 Apr 2024 → 5 Apr 2024 |
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Event title | 14th ASEM Workshop on Advanced Electron Microscopy: ASEM 2024 |
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Event type | Workshop |
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Location | Graz, AustriaShow on map |
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Degree of Recognition | International |
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- General Materials Science
- Advanced Materials Science
- Basic - Fundamental (Grundlagenforschung)