Energy-filtered imaging of polymer microstructure

Author(s):  
K. Siangchaew ◽  
J. Bentley ◽  
M. Libera

Energy-filtered electron-spectroscopic TEM imaging provides a new way to study the microstructure of polymers without heavy-element stains. Since spectroscopic imaging exploits the signal generated directly by the electron-specimen interaction, it can produce richer and higher resolution data than possible with most staining methods. There are basically two ways to collect filtered images (fig. 1). Spectrum imaging uses a focused probe that is digitally rastered across a specimen with an entire energy-loss spectrum collected at each x-y pixel to produce a 3-D data set. Alternatively, filtering schemes such as the Zeiss Omega filter and the Gatan Imaging Filter (GIF) acquire individual 2-D images with electrons of a defined range of energy loss (δE) that typically is 5-20 eV.

2000 ◽  
Vol 6 (S2) ◽  
pp. 150-151
Author(s):  
P.J. Thomas

The energy-loss spectrum of transmitted electrons contains a wealth of information regarding the physical, chemical and electronic properties of the medium under analysis. It provides a powerful means for materials characterisation in the TEM by use of electron energy-loss spectroscopy (EELS) or its spatially parallel counterpart, energy-selective imaging (ESI). Essentially, both analyses probe the same core-loss information, recording transmitted intensity / as a function of energy-loss E and spatial position x, y, to yield a three-dimensional data set I(E, x, y). Acquisition of an extended series of energy-selected images across the energy-loss range of interest has been shown to provide useful spectral as well as spatial information, with the resolution of extracted ‘image-spectra’ being determined by the energy interval between acquisitions and the width of the energy-selecting slit, as illustrated in Figure la . This mode of analysis, termed ‘image-spectroscopy’ is directly analogous to spectrum-imaging in the STEM, and offers many advantages over conventional two- or three-window elemental mapping techniques .


2019 ◽  
Vol 11 (9) ◽  
pp. 2996-3023 ◽  
Author(s):  
Yongjiu Dai ◽  
Qinchuan Xin ◽  
Nan Wei ◽  
Yonggen Zhang ◽  
Wei Shangguan ◽  
...  

2000 ◽  
Vol 6 (S2) ◽  
pp. 162-163
Author(s):  
S.B. Andrews ◽  
J. Hongpaisan ◽  
N.B. Pivovarova ◽  
D.D. Friel ◽  
R.D. Leapman

In the context of biological specimens, it is in principle desirable to quantitatively map, rather than just point analyze, the distribution of physiologically important elements, and to do so at subcellular resolution. Presently, this can be accomplished by electron energy loss spectrum-imaging (EELSI) in both the scanning transmission electron microscope (STEM) and the energy-filtering transmission electron microscope (EFTEM). Until recently, this approach has been of limited value for mapping the particularly important element Ca, mainly because intracellular total Ca concentrations are normally quite low (<5 mmol/kg dry weight) and because the background in the vicinity of the Ca L23 edge is complex and requires precise background modeling to extract the very weak Ca signals. As a result, the Ca signal is usually not high enough to reach detection threshold during a practical EELSI acquisition time.


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