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Related Concept Videos

Scanning Electron Microscopy01:07

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A scanning electron microscope (SEM) is used to study the surface features of a sample by using an electron beam that scans the sample surface in a two-dimensional manner. Typically, areas between ~1 centimeter to 5 micrometers in width can be imaged. SEM can be used to image bacteria, viruses, tissues as well as larger samples like insects. Conventional SEM gives a magnification ranging from 20X to 30,000X and spatial resolution of 50 to 100 nanometers.
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To be visualized by an electron microscope, either transmission or scanning, biological samples need to be fixed (stabilized) so the electron beam does not destroy them and dried thoroughly (desiccated/dehydrated) so the vacuum does not affect them. Fixation needs to be done as quickly as possible because the sample properties will start changing as soon as it is removed from its natural environment. For example, in a tissue sample, the oxygen levels begin decreasing, causing an altered...
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The wavelengths of visible light ultimately limit the maximum theoretical resolution of images created by light microscopes. Most light microscopes can only magnify 1000X, and a few can magnify up to 1500X. Electrons, like electromagnetic radiation, can behave like waves, but with wavelengths of 0.005 nm, they produce significantly greater resolution up to 0.05 nm as compared to 500 nm for visible light. An electron microscope (EM) can create a sharp image that is magnified up to 2,000,000X.
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Transmission Electron Microscopy01:15

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In 1931, physicist Ernst Ruska—building on the idea that magnetic fields can direct an electron beam just as lenses can direct a beam of light in an optical microscope—developed the first prototype of the electron microscope. This development led to the development of the field of electron microscopy. In the transmission electron microscope (TEM), electrons are produced by a hot tungsten element and accelerated by a potential difference in an electron gun, which gives them up to 400...
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Immunoelectron microscopy utilizes immunogold labeling of endogenous proteins with specific antibodies to detect and localize these proteins in cells and tissues. The procedure provides insights into the distribution and quantification of protein under different stimulation conditions offering clues about their functions. Conjugating highly electron-dense gold particles with primary or secondary antibodies allow antigen detection on and within cells, with high resolution and specificity.
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Updated: Aug 17, 2025

Electron Channeling Contrast Imaging for Rapid III-V Heteroepitaxial Characterization
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Secondary electron count imaging in SEM.

Akshay Agarwal1, John Simonaitis1, Vivek K Goyal2

  • 1Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, United States of America.

Ultramicroscopy
|December 15, 2022
PubMed
Summary
This summary is machine-generated.

Scanning electron microscopy (SEM) image quality is improved by using secondary electron (SE) count imaging. This method enhances the signal-to-noise ratio by directly counting SEs, overcoming noise limitations in conventional SEM.

Keywords:
Electron countingScanning electron microscopySecondary electronsSignal-to-noise-ratio

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Area of Science:

  • Materials Science
  • Physics
  • Microscopy

Background:

  • Conventional scanning electron microscopy (SEM) relies on average signal intensity for imaging, which is susceptible to noise.
  • Detector signal variations in traditional SEM can degrade image quality, especially at low imaging doses.
  • Secondary electrons (SEs) emitted from samples are crucial for nanoscale imaging.

Purpose of the Study:

  • To introduce and implement a secondary electron (SE) count imaging scheme for enhanced SEM.
  • To overcome the limitations of conventional SEM imaging by reducing noise.
  • To improve the signal-to-noise ratio (SNR) in SEM images.

Main Methods:

  • Implemented an SE count imaging scheme by synchronizing detector and beam scan signals.
  • Utilized custom code to process detector signals and count individual SEs.
  • Compared SE count imaging with conventional average intensity imaging.

Main Results:

  • Achieved a significant increase in image signal-to-noise-ratio (SNR) of approximately 30% using SE count imaging.
  • Demonstrated that SE counting effectively reduces noise compared to conventional SEM imaging.
  • Validated the scheme's performance and its potential for improving SEM image quality.

Conclusions:

  • SE count imaging offers a substantial improvement in SEM image quality over conventional methods.
  • The proposed scheme is easily implementable on existing SEM systems with minimal external hardware (a suitable oscilloscope).
  • This technique provides a pathway to higher quality nanoscale imaging with reduced noise.