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Scanning Electron Microscopy01:07

Scanning Electron Microscopy

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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Updated: May 10, 2026

Scanning-probe Single-electron Capacitance Spectroscopy
10:53

Scanning-probe Single-electron Capacitance Spectroscopy

Published on: July 30, 2013

A dynamic scanning method based on signal-statistics for scanning electron microscopy.

F Timischl1

  • 1JEOL Technics Ltd., Akishima-shi, Tokyo, Japan.

Scanning
|July 2, 2013
PubMed
Summary
This summary is machine-generated.

A new dynamic scanning method reduces noise in scanning electron microscopy (SEM) images. This technique improves image quality and acquisition speed, especially for saturated images, outperforming conventional methods.

Keywords:
noisescanning electron microscopyscanning methodsignal-statistics

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Area of Science:

  • Microscopy
  • Image Processing
  • Materials Science

Background:

  • Scanning Electron Microscopy (SEM) is crucial for high-resolution imaging.
  • Noise reduction is essential for accurate SEM image analysis.
  • Conventional scanning methods can be slow and may not handle signal variations effectively.

Purpose of the Study:

  • To introduce a novel dynamic scanning method for noise reduction in SEM.
  • To achieve uniform image quality with a predefined standard deviation.
  • To reduce image acquisition time without compromising image quality, particularly in partially saturated images.

Main Methods:

  • Developed a dynamic scanning method that adjusts electron beam speed based on detector signal statistics.
  • Implemented numerical simulations to compare the proposed method with conventional scanning and median filtering.
  • Evaluated image quality based on standard deviation and acquisition time.

Main Results:

  • The dynamic scanning method produced SEM images with uniform, predefined standard deviation.
  • Acquisition time was reduced for partially saturated images without loss of image quality.
  • Numerical simulations demonstrated the effectiveness of the proposed method over conventional techniques.

Conclusions:

  • The novel dynamic scanning method offers significant improvements in noise reduction and efficiency for SEM.
  • This technique is particularly beneficial for applications with varying signal intensities and saturation.
  • The method provides a robust approach to enhance SEM image quality and speed up data acquisition.