A Forward Modeling Approach to High-Reliability Grain Mapping by Laboratory Diffraction Contrast Tomography (LabDCT)

Sridhar Niverty, Jun Sun, Jason Williams, Florian Bachmann, Nicolas Gueninchault, Erik Lauridsen, Nikhilesh Chawla

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Laboratory diffraction contrast tomography (LabDCT) is a laboratory-scale x-ray microtomography technique that can be used to non-destructively map grains and grain boundaries in 3D. The fidelity of grain mapping significantly depends on the quality of grain reflections obtained from the illuminated volume of the specimen. In this article, we report the application of a novel forward modeling approach to improve the reliability of grain mapping. Through this approach, a comparison between the obtained grain reflections and simulated grain reflections can be used to perform a self-fitting operation. This can be used to optimize instrumental parameters and iteratively improve the quality of reconstruction. To demonstrate the effectiveness of the forward modeling approach, LabDCT was used to map the grains in a polycrystalline specimen of the magnesium alloy AZ91E and iteratively improve reconstruction quality significantly.

Original languageEnglish (US)
Pages (from-to)2695-2704
Number of pages10
JournalJOM
Volume71
Issue number8
DOIs
StatePublished - Aug 15 2019
Externally publishedYes

ASJC Scopus subject areas

  • Materials Science(all)
  • Engineering(all)

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