Spectrum Imaging

Systematic method to generate a spatially resolved distribution of electron energy loss spectroscopy (EELS) data.

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Spectrum imaging (SI) is a technique that generates a spatially resolved distribution of electron energy loss spectroscopy (EELS) data. A typical experiment involves the creation of a data cube where two of the cube axes correspond to spatial information, while the third dimension represents the energy loss spectrum. The resultant dataset is referred to as a spectrum image (or spectrum line scan for the 1D case), which you can acquire and visualize in a number of ways. To create this data cube, you can acquire a complete spectrum at each spatial pixel during scanning transmission electron microscope mode (STEM SI) or collect a complete 2D image over a narrow band of energies at a single energy slice of the data cube during energy-filtered TEM mode (EFTEM SI).

A key advantage of spectrum imaging is the ability to process decisions after acquisition. When a complete spectrum is available at each data point, this allows creation of quantitative images and profiles to identify and correct data artifacts, understand image contrast, as well as determine dataset limitations.

During a STEM experiment, the electron beam focuses into a small probe, then scans over the sample to acquire spatial information (X,Y) in a serial manner. In the STEM SI mode, you can acquire a complete spectrum at each pixel position to build the spectrum image up on a spectrum-by-spectrum basis.

Alternatively, EFTEM SI uses a broad parallel beam (e.g., TEM) to acquire spectral data image plane-by-image plane, while changing the energy of each plane. In this mode, you acquire the image in parallel while the spectrum is built in a serial manner.

Once acquisition is complete, you can visualize the spectrum image (either EFTEM SI or STEM SI) either spectrum-by-spectrum (X,Y) or plane-by-plane (\DeltaE). The combination of spectral and spatial information in a single dataset opens up a wide range of data analysis possibilities. You can apply any single spectrum analysis method to the entire spectrum image dataset to perform a spatially resolved spectral analysis. This increase in information provides a powerful tool for material analysis and characterization.

For more information on the EELS family of techniques, please visit EELS.info, an educational site.

Research Spotlight

Crozier Research Group @ ASU

Department of Materials Science and Engineering.
School for the Engineering of Matter, Transport, and Energy. Arizona State University (ASU)





High-speed composition and chemical analysis of Si/STO/PZT with GIF Continuum
Atomic level EELS mapping using high energy edges in DualEELS™ mode
High speed EELS composition analysis, in DualEELS mode, of metal alloy ohmic contacts for the fabrication of III-V MOSFET devices
EELS: A tool for investigating biological materials
Fast simultaneous acquisition of low- and core-loss regions in the EELS spectrum from catalyst particles containing the heavy metals Au and Pd using the GIF Quantum® system
Fast STEM spectrum imaging using simultaneous EELS and EDS in Gatan Microscopy Suite® software
Review of recent advances in spectrum imaging and its extension to reciprocal space
The use of MLLS fitting approach to resolve overlapping edges in the EELS spectrum at the atomic level


Fast STEM EELS spectrum imaging analysis of Pd-Au based catalysts
The high efficiency of the latest generation EELS spectrometers allow highly detailed EELS spectra from heavy elements to be acquired in a matter of milliseconds resulting in composition maps with outstanding information content.

A quantitative investigation of biological materials using EELS
EELS has proved to be a valuable tool to obtain compositional information from biological samples. In addition to the composition, EELS also gives insight into the chemistry unveiling the nature of the chemical bonds and different oxidation states.

High-speed composition analysis of high-z metal alloys in DualEELS mode
Demonstrating that high-speed atomic EELS composition maps with high contrast and high signal-to-noise ratio can be acquired routinely from high-energy edges.

Fast atomic level EELS mapping analysis using high-energy edges in DualEELS mode
Demonstrating that atomic EELS mapping using high-energy edges is very effective. The high signal-to-background ratio of high-energy edges leads to simplified data extraction.

Atomic resolved EELS analysis across interfaces in III-V MOSFET high-k dielectric gate stacks
Demonstrating that EELS SI can reveal the elemental distribution at the gate of high-k MOSFET devices at atomic column level.

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