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Updated: Nov 9, 2025

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Characterization of Ultra-fine Grained and Nanocrystalline Materials Using Transmission Kikuchi Diffraction
Published on: April 1, 2017
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Optimizing laboratory X-ray diffraction contrast tomography for grain structure characterization of pure iron
Adam Lindkvist1, Haixing Fang1, Dorte Juul Jensen1
1Department of Mechanical Engineering, Technical University of Denmark, Kongens Lyngby, 2800, Denmark.
Summary
Laboratory diffraction contrast tomography (LabDCT) optimizes 3D grain mapping by analyzing experimental parameters. Key findings guide improved X-ray diffraction contrast tomography for materials science.
Area of Science:
- Materials Science
- Crystallography
- X-ray Physics
Background:
- Laboratory diffraction contrast tomography (LabDCT) is an emerging technique for non-destructive 3D grain mapping.
- It utilizes a laboratory-based X-ray source and a conical polychromatic beam.
Purpose of the Study:
- To quantify the impact of experimental parameters on 3D grain structure characterization using LabDCT.
- To provide recommendations for optimizing LabDCT experiments and 3D volume reconstruction.
Main Methods:
- Experiments were performed on an iron sample using a ZEISS Xradia 520 Versa with a LabDCT module.
- Data analysis involved the GrainMapper3D software for 3D reconstruction from binarized 2D diffraction patterns.
- Forward simulations were used to assess the effect of projection numbers.
Main Results:
- Exposure time critically influences background noise and the detection of small grain diffraction spots.
- As few as 30-40 projections are sufficient for accurate crystallographic orientation indexing and grain shape resolution.
- Electron current is more influential than accelerating voltage for optimizing photon flux in the 20-60 keV range.
Conclusions:
- Optimizing exposure time and projection count enhances 3D grain mapping accuracy.
- Electron current is a key parameter for maximizing photon flux in relevant energy ranges for metals like iron and aluminum.
- The study offers practical guidance for improving LabDCT experimental design and data reconstruction.
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