Efficient microstructure characterization of metals using light microscopy

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A material’s properties are strongly linked to its microstructure, such as grain size, porosity, phase and non-metallic inclusions. Light microscopy is a powerful tool for evaluating a material’s microstructure, but extracting meaningful results using traditional image analysis can be challenging, especially for new materials or materials with multiple phases. For instance, magnetic materials being developed for use in electric motors consist of complex structures. Segmentation of these structures in different phases can prove difficult with traditional image analysis techniques.

High Temperature Corrosion Scale on 9% Chromium Steel
High Temperature Corrosion Scale on 9% Chromium Steel.
Left side (background): Brightfield image; Right side (foreground): individual layers segmented with machine learning
Sample courtesy of TWI Ltd

In a recent SelectScience® webinar, Tim Schubert, materials scientists at the Materials Research Institute Aalen (IMFAA), Aalen University, and Torben Wulff, solutions manager light microscopy at ZEISS Research Microscopy Solutions, introduce a new comprehensive solution for microstructure analysis and present standardized techniques for metallography investigation.

Watch the webinar on demand by registering here

Discover Q&A highlights from the live event

Tags: Light Microscopy, Machine Learning

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