untethered atom · TEM

Where is the element? Jump-ratio and three-window EFTEM maps

Dividing two images cancels what they share. Subtracting keeps it. That one fact decides which map to trust.

An energy filter records whole images at chosen energy losses. Two images before an edge and one after it give an elemental map. Here you record them from a sample you set up, build both kinds of map live, and see what a bend contour, a thickness change, drift, low counts or a badly placed window does to each one.

Try a lesson:
1Pre-edge 1
2Pre-edge 2
3Post-edge
4Check: Pre-edge 1 ÷ Pre-edge 2. Must show no sharp features.
5Truth: amount of X you put in.
6Jump-Ratio Map: Post-edge ÷ Pre-edge 2. Where X is.
7Elemental Map (three-window): Post-edge minus the power-law background fitted through Pre-edge 1 and 2. How much X.
8Elemental Map ÷ Pre-edge 2. Removes contrast shared by all images.
Click any picture to see the spectrum at that point. The dashed line on the maps is the profile below.
Spectrum at the chosen point. Pre-edge images are recorded at an energy loss just below the edge onset, where only background reaches the camera. The Post-edge image is recorded just above it, where element X adds its signal. Shaded: the three windows (Slit width 20 eV). Dots: what the images measured (5 × 5 px average; single pixels are much noisier). Dashed: the power-law background fitted through the Pre-edge 1 and Pre-edge 2 dots. The red bar at Post-edge is the elemental signal.
Profile A → B (dashed line on the maps). Each map is scaled so the clean case reads 1 in B. Grey: truth.

Specimen the truth you put in

Precipitates A (left) and B (upper right) are rich in element X, edge at 708 eV (like Fe L2,3). The matrix has none. 128 × 128 px, 1 nm per px.

Acquisition

Counts per pixel in Pre-edge 1, in the matrix (set in GMS by Exposure time and Binning). Bend contour: share of electrons it removes from all images. Slit width is 20 eV for all three images (fixed here). The edge onset is at about 702 eV.

Processing

On: the Post-edge image is lined up with Pre-edge 2 by cross-correlation and shifted back by whole pixels.

Numbers

The method in six steps

StepWhat you doKnob on this pageWhat goes wrong
1 Energy lossSet the Energy loss of Pre-edge 1 and Pre-edge 2 below the edge onset (background only), and of Post-edge just above it (background plus element). Set the Slit width; 10 to 30 eV is common.Pre-edge 1, Pre-edge 2, Post-edge energy lossA pre-edge window that touches the edge takes signal away from both maps.
2 CaptureCapture the three images, as fast as the counts allow (Exposure time, Binning). Keep the same objective aperture and focus.counts per pixelLong exposures let the specimen drift or bend between images.
3 Drift CorrectionTurn on Drift Correction, so the images are lined up (cross-correlation) before any arithmetic.Drift CorrectionA few pixels of drift give bright and dark fringes at every edge.
4 CheckDivide Pre-edge 1 by Pre-edge 2 yourself (it is not a Gatan map). The result should show no sharp features.check image (4)Lines or blobs mean the contrast changed between images. Do not trust either map there.
5 Jump-Ratio MapPost-edge divided by Pre-edge 2. Use it to find where the element is.map 6Not proportional to the amount. Falls in thick areas.
6 Elemental MapThe three-window method: Background model power law, A·E−r, fitted through Pre-edge 1 and 2 pixel by pixel, then subtracted from Post-edge.map 7, map 8Noisier. Keeps diffraction and thickness contrast unless you divide it out.

Names follow Gatan’s EFTEM software (GMS): Energy loss, Slit width, Exposure time, Binning, Pre-edge 1, Pre-edge 2, Post-edge, Drift Correction, Background model, Jump-Ratio Map, Elemental Map, and Thickness Map (from an Unfiltered and a Zero-loss image).

Do it on your own images

  1. Record a Thickness Map first (an Unfiltered and a Zero-loss image give t/λ). Work where t/λ is below about 0.5.
  2. Tilt away from strong diffraction conditions if you can. Bend contours are the most common false feature.
  3. Keep the whole Pre-edge 2 window at least 5 eV below the edge onset: its Energy loss plus half the Slit width. Keep Pre-edge 1 and Pre-edge 2 about one Slit width apart.
  4. Turn on Drift Correction before dividing or subtracting.
  5. Look at the check image (Pre-edge 1 ÷ Pre-edge 2) before you look at the maps.
  6. Use the Jump-Ratio Map to say where. Use the Elemental Map, divided by Pre-edge 2 or by the Unfiltered image, for how much, and state the thickness.
  7. Sum several short exposures instead of one long one, and align them first.

Why the two maps disagree

A bend contour removes electrons by elastic scattering outside the objective aperture. It takes the same share from every image, background and edge alike. A division cancels that share, so the Jump-Ratio Map does not see the contour. A subtraction keeps it, so the Elemental Map shows the contour as a false drop. The trap for the Jump-Ratio Map is contrast that is not shared: a contour that moves between exposures, or drift. The check image catches both.

Scope and limits

The scene is made up: two round precipitates of one element in a matrix with none, an edge at 708 eV shaped like an L2,3 edge, and a pure power-law background whose exponent falls a little in thick areas. Plural scattering is a simple extra factor on the background, not a full calculation. The bend contour is a smooth band that removes a fixed share of electrons; real diffraction contrast also depends on energy loss through the objective aperture, which this page does not model. Chromatic blurring, the point-spread of inelastic scattering (delocalization), detector gain and readout noise are left out. Alignment here moves the image by whole pixels only. The areal density in the Elemental Map would need the edge cross-section and the incident intensity to become a number of atoms per nm2.

On this site: Reading the EELS spectrum · EELS core-loss quantification · EELS thickness calculator · Bend contours · EELS fine structure and oxidation state

Questions people ask

Which map should I publish?

Usually both, with the check image in the supplement. The Jump-Ratio Map shows where the element is with less noise. The Elemental Map is the one that scales with the amount, so it is the one to quantify, after dividing out shared contrast and stating the thickness.

My Jump-Ratio Map shows a stripe across the whole field. Is it real?

If the check image (Pre-edge 1 divided by Pre-edge 2) shows the same stripe, no. The contrast changed between exposures, most often a bend contour that moved (lesson 3). Re-record faster or at a different tilt.

Why is the Elemental Map so much noisier?

The background under the edge is extrapolated from two images. Any noise in them changes the fitted exponent r, and the extrapolation magnifies that change (lesson 6). More counts, wider windows, or pre-edge windows closer to the edge all help.

Why does my element look weaker in thick areas?

In the Jump-Ratio Map, plural scattering adds background under the edge, so the ratio falls. In the Elemental Map, more atoms under the beam push it up. Neither is a concentration (lesson 4). Keep t/λ low and record a thickness map.

References

  1. D. B. Williams and C. B. Carter, Transmission Electron Microscopy, 2nd ed., Springer (2009): chapter 37 (electron energy-loss spectrometers and filters) and chapter 39 (high energy-loss spectra and images).
  2. C. B. Carter and D. B. Williams (eds.), Transmission Electron Microscopy: Diffraction, Imaging, and Spectrometry, Springer (2016): the energy-filtered TEM chapter.
  3. R. F. Egerton, Electron Energy-Loss Spectroscopy in the Electron Microscope, 3rd ed., Springer (2011): energy-selected imaging and background fitting.
  4. O. L. Krivanek, M. K. Kundmann and K. Kimoto, Spatial resolution in EFTEM elemental maps, Journal of Microscopy 180, 277 (1995).
  5. T. Malis, S. C. Cheng and R. F. Egerton, EELS log-ratio technique for specimen-thickness measurement in the TEM, Journal of Electron Microscopy Technique 8, 193 (1988).
Cite this page: Tripathy, Manisha. “EFTEM Elemental Mapping.” untethered atom, 2026, https://untetheredatom.com/tem/eftem-elemental-mapping.
BibTeX
@misc{tripathy2026eftemelementalmapping,
  author = {Tripathy, Manisha},
  title  = {EFTEM Elemental Mapping},
  year   = {2026},
  howpublished = {\url{https://untetheredatom.com/tem/eftem-elemental-mapping}},
  note   = {Interactive web tool}
}
Last updated 23 September 2026.