The Phenom Process Automation: mixing backscattered and secondary electron images using a Python script

By Karl Kersten - June 28, 2018

When the primary beam interacts with the sample, backscattered electrons (BSEs) and secondary electrons (SEs) are generated. Images of the samples obtained by detecting the emitted signals, carry information on the composition (for BSE signals) and on the topography (for SE signals). How are BSEs and SEs formed and why do they carry specific information? Moreover, is it possible to get both compositional and topographical information in one image? And how flexible is this solution? In this blog, I will answer these questions and introduce a script that allows users to mix their own images.

When the primary beam hits the sample surface, secondary electrons and backscattered electrons are emitted and can be detected to form images. Secondary electrons are generated from inelastic scattering events of the primary electrons with electrons in the atoms of the sample, as shown on the left of Figure 1. SEs are electrons with low energy (typically less than 50eV) that can be easily absorbed. This is the reason why only the secondary electrons coming from a very thin top layer of the sample can be collected by the detector.

On the other hand, backscattered electrons are formed from elastic scattering events, where the trajectories of primary electrons are deviated by the interaction with the nuclei of the atoms in the sample, as shown on the right in Figure 1. BSEs typically have high energy and can emerge from deep inside the sample.


Formation of secondary electrons (on the left) and backscattered electrons (on the right)

Figure 1: Formation of secondary electrons (on the left) and backscattered electrons (on the right). SEs are formed from inelastic scattering events, while BSEs are formed from elastic scattering events.

Secondary electrons images contain information on the topography of the sample. As shown on the left of Figure 2, the beam is scanned on top of a surface that has a protrusion. When the beam is located on the slope of this protrusion, the interaction volume touches the sidewall causing more secondary electrons to escape the surface. When the beam is located on the flat area, fewer secondary electrons can escape. This means that more secondary electrons will be emitted on edges and slopes, causing brighter contrast than on flat areas, providing information on the morphology of the sample.

On the other hand, the backscattered electrons yield depends on the material, as shown on the right of Figure 2. If the beam hits silicon atoms, which have atomic number Z=14, fewer backscattered electrons will be formed than in the case of gold, which has atomic number Z = 79. The reason for this is that gold atoms have bigger nuclei, providing a stronger effect on the primary electrons’ trajectories, which translates into a bigger deviation. Backscattered electrons images therefore provide information on the material difference of the sample.


backscattered and secondary electrons in SEM

Figure 2: On the left, more secondary electrons can escape the sample surface on edges and slopes than in flat areas. On the right, the yield of backscattered electrons depends on the atomic number of the material, more BSEs are generated in gold (Z = 79) than in silicon (Z = 14).

To collect the secondary electrons, the Everhart-Thornley detector (ETD) is typically used. Because SEs have low energy, a grid at high potential is placed in front of the detector to attract the secondary electrons. On the other hand, BSEs are often collected by a solid-state detector placed above the sample. The images obtained by the ETD detector and the BSD detector contain information on the morphology and the composition of the sample respectively.

For some applications, however, it is convenient to have information on both the topography and the composition, in one image. This can be done by simply adding the signal coming from the two detectors.

Mixing BSE and SE images 

When an image is acquired, the beam scans the sample surface pixel by pixel. In each pixel, the signal is collected by the detector and translated into a value. If images are acquired in 8 bits, the range of pixel values varies from 0 to 255. If images are acquired in 16 bits, the values of each pixel can vary from 0 to 65,535.

The value of the pixel depends on how many secondary electrons or backscattered electrons are emitted and the higher the value of the pixel, the brighter the pixel appears in the image. This means that in the case of the sample shown in Figure 2 on the left, the edges will appear brighter in the image because more SEs are emitted and therefore the pixels in that position will have a higher value.

Mixing backscattered electron and secondary electron images means that the two images are summed together. In practice, each pixel in the SE image is summed to the corresponding pixel in the BSE image, using the formula: 

mixing BSE and SE images formula

 Where ratio is the percentage of how much SE and BSE information the mixed image will carry. For equal topographic and compositional information, the ratio will be equal to 0.5.

On the left of Figure 3 you can see SE (top) and the BSE (bottom) images of a solar cell, where the white area is silver and the dark area is silicon. In the SE image, the topography of the sample is clear: the granular structure of the silver strip can be easily noticed, as well as the bumpy silicon surface. Of course the ETD detector picks up some BSE signal as well, which is the reason why there is a difference in contrast between the two materials.

In the BSE image, the topography of the sample is less visible. However, the material contrast is enhanced, and also shows some dirty particles on the silver strip. On the right of Figure 3, the mixed image is shown. In this case, we used a ratio of 0.5, meaning that each pixel value contains 50% of topographic information and 50% of compositional information. Not only are all the particles with different material contrast visible, but also the surface roughness of the strip and the silicon area.



 Figure 3: An example of mixing images. On the top left, the SE image and on the bottom, the BSE image of a solar cell, where the silver stripe (bright area) can be distinguished from the silicon (dark area). While the SE image carries information on the topography, in the BSE image the material contrast is dominant. On the right is the resulting mixed image using a ratio of 0.5.

The mixed imaging script

Being able to generate and save mixed backscattered and secondary electron images is a key value in many applications. Not only that, being able to set the SE:BSE ratio is also important for obtaining flawless images, that provide valuable information to the user.

Using the Phenom Programming Interface (PPI), we developed a script that can acquire BSE and SE images directly from the Phenom SEM and mix them together, as shown in Figure 4. It is also possible to load BSE and SE images that were previously saved with the Phenom and generate and save the mixed image offline.


Figure 4: User interface of the mixed images script, developed with PPI.

Do not miss the two videos below that show two examples of mixing images with our script:

Are you an experienced programmer interested in knowing more about the Phenom Programming Interface and its functionalities? Then download our specs sheet.

If you are not familiar with programming, but would still like an automated solution for your workflow, then we can help by developing the solution for you. Download the PPI/PPA specs sheet and discover more about all our possibilities.

Download your Phenom Programming Interface sheet



About the author

Karl Kersten is head of the Application team at Thermo Fisher Scientific, the world leader in serving science. He is passionate about the Thermo Fisher Scientific product and likes converting customer requirements into product or feature specifications so customers can achieve their goals.

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