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Recent developments in X-ray diffraction/scattering computed tomography for materials science.

Naomi E Omori1, Antonia D Bobitan1,2,3, Antonis Vamvakeros1,4

  • 1Finden Limited, Merchant House, 5 East St Helens Street,Abingdon OX14 5EG, UK.

Philosophical Transactions. Series A, Mathematical, Physical, and Engineering Sciences
|September 11, 2023
PubMed
Summary
This summary is machine-generated.

X-ray diffraction/scattering computed tomography (XDS-CT) provides non-destructive chemical imaging. Recent advancements enhance its application in materials science, driven by machine learning and new XDS-CT techniques.

Keywords:
X-rayXRD-CTchemical imagingdiffractionscatteringtomography

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Area of Science:

  • Materials Science
  • Chemical Imaging
  • Analytical Chemistry

Background:

  • X-ray diffraction/scattering computed tomography (XDS-CT) offers non-destructive chemical imaging with spatial resolution.
  • X-ray diffraction CT (XRD-CT) is established, but newer methods like small angle X-ray scattering CT and pair distribution function CT are emerging.
  • Machine learning is increasingly used for XDS-CT data processing and reconstruction.

Purpose of the Study:

  • To review recent developments and applications of XDS-CT.
  • To focus on studies published within the last five years.
  • To highlight the impact of new instrumentation and machine learning on XDS-CT.

Main Methods:

  • Narrative review of XDS-CT literature.
  • Focus on advancements in instrumentation and data reconstruction.
  • Analysis of machine learning applications in tomographic reconstruction and data analysis.

Main Results:

  • Increased adoption of advanced XDS-CT techniques beyond traditional XRD-CT.
  • Significant impact of machine learning on data processing and analysis.
  • Broadening applications of XDS-CT in materials science.

Conclusions:

  • XDS-CT is a rapidly evolving field with significant potential for materials characterization.
  • Integration of machine learning is transforming XDS-CT capabilities.
  • Continued innovation in instrumentation and methods will expand XDS-CT applications.