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Ronan Smith1, Fabio De Marco2,3, Ludovic Broche4

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|August 29, 2022
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Summary
This summary is machine-generated.

This study introduces a new algorithm for X-ray directional dark-field imaging, enabling the visualization of hidden microstructures. The technique accurately quantifies the orientation of anisotropic materials like carbon fibre reinforced polymers.

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Area of Science:

  • Materials Science
  • Physics
  • Imaging Technology

Background:

  • Conventional X-ray imaging lacks the resolution to reveal small-scale structural properties.
  • Anisotropic structures possess directional properties that are difficult to detect with standard methods.
  • X-ray directional dark-field imaging is an emerging technique offering enhanced contrast for microstructural analysis.

Purpose of the Study:

  • To develop and present an algorithm for extracting directional dark-field signals from X-ray speckle-based imaging data.
  • To demonstrate the capability of the technique in detecting and quantifying the orientation of anisotropic structures.
  • To analyze the accuracy and resolution trade-offs of the proposed method.

Main Methods:

  • Utilizing X-ray speckle-based imaging with a simple diffuser (sandpaper) in a full-field microscope setup.
  • Developing an algorithm to extract directional dark-field signals, mean scattering width, directionality, and orientation from speckle images.
  • Acquiring and analyzing data from a carbon fibre reinforced polymer (CFRP) sample.

Main Results:

  • Successfully extracted directional dark-field signals from X-ray speckle data.
  • Demonstrated accurate detection and quantification of fibre orientation in CFRP samples, achieving within one degree of accuracy.
  • Quantified the relationship between the number of measurements and the achieved accuracy.
  • Showcased the ability to tune reconstruction parameters for accuracy versus spatial resolution.

Conclusions:

  • The presented algorithm effectively extracts directional dark-field information from X-ray speckle data.
  • The technique provides accurate orientation information for anisotropic materials, with potential applications in materials science and engineering.
  • The method's accuracy is dependent on the number of measurements and can be optimized by adjusting reconstruction parameters.