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Related Experiment Video

Updated: Aug 11, 2025

Processing of Bulk Nanocrystalline Metals at the US Army Research Laboratory

Processing of Bulk Nanocrystalline Metals at the US Army Research Laboratory

Published on: March 7, 2018

Advancing analytical electron microscopy methodologies to characterise microstructural features in superalloys.

B Schulz¹, N Haghdadi¹, T Leitner²

¹School of Materials Science & Engineering, UNSW Sydney, NSW, 2052, Australia.

Ultramicroscopy

|February 8, 2023

Summary

New automated methods enhance electron backscatter diffraction (EBSD) analysis for Ni-based superalloys. These techniques provide statistically significant insights into microstructure, aiding recrystallization mechanism identification and grain boundary characterization.

Keywords:

Electron backscatter diffraction Energy-dispersive X-ray spectroscopy Habit plane Microstructure Twin

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Last Updated: Aug 11, 2025

Processing of Bulk Nanocrystalline Metals at the US Army Research Laboratory

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Published on: March 7, 2018

Quantitative Atomic-Site Analysis of Functional Dopants/Point Defects in Crystalline Materials by Electron-Channeling-Enhanced Microanalysis

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Published on: June 2, 2017

Area of Science:

Materials Science
Crystallography
Metallurgy

Background:

Electron backscatter diffraction (EBSD) is crucial for material microstructure analysis.
Current EBSD software offers basic analysis, but advanced insights require manual, localized methods.
Lack of automated tools limits comprehensive microstructural characterization.

Purpose of the Study:

Introduce novel automated methodologies for advanced EBSD analysis.
Enable deeper understanding of microstructural features and physical phenomena in Ni-based superalloys.
Provide a tutorial-style guide for applying these advanced techniques.

Main Methods:

Developed automated algorithms for advanced EBSD data analysis.
Integrated EBSD with energy-dispersive X-ray spectroscopy (EDS) for enhanced accuracy.
Implemented methods for correcting indexing artifacts, classifying recrystallized grains, analyzing grain boundary planes, and studying twin evolution.

Main Results:

Successfully corrected interfacial artifacts in combined EBSD-EDS data.
Enabled classification of recrystallized grains for mechanism identification.
Provided detailed assessment and visualization of grain boundary planes and Σ3 twin evolution.
Achieved more accurate determination of phase fractions and grain sizes.

Conclusions:

Automated methodologies significantly advance EBSD analysis capabilities.
These methods offer statistically significant, localized insights into material microstructure.
The freely available algorithms are applicable beyond Ni-based superalloys to other crystalline systems.