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Scanning Electron Microscopy

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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Related Experiment Video

Updated: Jul 25, 2025

In Situ Characterization of Boehmite Particles in Water Using Liquid SEM

In Situ Characterization of Boehmite Particles in Water Using Liquid SEM

Published on: September 27, 2017

In Situ Inclusion Detection and Material Characterization in an Electron Beam Powder Bed Fusion Process Using

Martin Gardfjell¹, Marcel Reith¹, Martin Franke¹

¹Neue Materialien Fürth GmbH, 90762 Fürth, Germany.

Materials (Basel, Switzerland)

|June 28, 2023

Summary

Electron Optical Imaging (ELO) in Electron Beam Powder Bed Fusion (PBF-EB) can detect 100 μm foreign powder particles. ELO also accurately predicts alloy effective atomic number (Zeff) for material characterization.

Keywords:

Additive Manufacturing Backscattered Electron Detection Electron Beam Powder Bed Fusion Electron Optical Imaging Inclusion Detection Powder Contamination Process Monitoring

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Last Updated: Jul 25, 2025

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Published on: September 27, 2017

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Sample Preparation and Experimental Design for In Situ Multi-Beam Transmission Electron Microscopy Irradiation Experiments

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Area of Science:

Additive Manufacturing
Materials Science
Process Monitoring

Background:

Electron Beam Powder Bed Fusion (PBF-EB) uses an electron beam to melt metal powder.
Electron Optical Imaging (ELO) leverages backscattered electrons for process monitoring.
ELO's material contrast capabilities for PBF-EB are not well-understood.

Purpose of the Study:

Investigate the extent of material contrast using ELO in PBF-EB.
Assess ELO's ability to detect powder contamination.
Explore ELO for material characterization via effective atomic number (Zeff) prediction.

Main Methods:

Utilized ELO with a backscattered electron detector during PBF-EB.
Focused on identifying foreign powder particles based on backscattering coefficients.
Developed a mathematical model linking ELO signal intensity to Zeff.

Main Results:

Demonstrated ELO's capability to distinguish 100 μm foreign particles with higher backscattering coefficients.
Successfully predicted the effective atomic number (Zeff) of alloys within ±1 atomic number.
Verified the model with empirical data from twelve distinct materials.

Conclusions:

ELO is effective for detecting small foreign particles in PBF-EB.
ELO provides a viable method for non-destructive material characterization in PBF-EB.
The developed framework accurately relates ELO signal intensity to alloy Zeff.