ArticleJournal of applied crystallography2022
Reconstruction algorithms for grain mapping by laboratory X-ray diffraction contrast tomography.
Article in Journal of applied crystallography, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Laboratory three-dimensional X-ray micro-beam Laue diffraction.Journal of applied crystallography · 2025Article
- Forward-model-based grain reconstruction to improve the tolerance of diffraction contrast tomography for increased sample deformation.Journal of applied crystallography · 2025Article
- Taking three-dimensional x-ray diffraction (3DXRD) from the synchrotron to the laboratory scale.Nature communications · 2025Article
- A critical step toward far-field laboratory diffraction contrast tomography in Laue focusing geometry.Journal of applied crystallography · 2025Article
- Recent developments in X-ray diffraction/scattering computed tomography for materials science.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2023Review
- Implementation of grain mapping by diffraction contrast tomography on a conventional laboratory tomography setup with various detectors.Journal of applied crystallography · 2023Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
X-ray-based non-destructive 3D grain mapping techniques are well established at synchrotron facilities. To facilitate everyday access to grain mapping instruments, laboratory diffraction contrast tomography (LabDCT), using a laboratory-based conical polychromatic X-ray beam, has been developed and commercialized. Yet the currently available LabDCT grain reconstruction methods are either ill-suited for handling a large number of grains or require a commercial licence bound to a specific instrument. To promote the availability of LabDCT, grain reconstruction methods have been developed with multiple reconstruction algorithms based on both forward and back calculations. The different algorithms are presented in detail and their efficient implementation using parallel computing is described. The performance of different reconstruction methods is assessed on synthetic data. The code to implement all the described algorithms has been made publicly accessible with the intention of fostering the development of grain mapping techniques on widely available laboratory instruments.
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Registered trials
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