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Related Experiment Video

Updated: Dec 7, 2025

Dynamic Pore-scale Reservoir-condition Imaging of Reaction in Carbonates Using Synchrotron Fast Tomography
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Dynamic Pore-scale Reservoir-condition Imaging of Reaction in Carbonates Using Synchrotron Fast Tomography

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Unveiling water dynamics in fuel cells from time-resolved tomographic microscopy data.

Minna Bührer1,2, Hong Xu3, Jens Eller3

  • 1Swiss Light Source, Paul Scherrer Institut, Forschungsstrasse 111, 5232, Villigen, Aargau, Switzerland.

Scientific Reports
|October 3, 2020
PubMed
Summary

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A new automated pipeline (rSIRT-PWC-DIFF) reconstructs and segments dynamic processes in X-ray tomographic microscopy data. This significantly reduces manual labor and post-processing time, enabling more extensive dynamic investigations.

Area of Science:

  • Materials Science
  • Physics
  • Engineering

Background:

  • X-ray dynamic tomographic microscopy enables volumetric investigation of dynamic processes.
  • Current methods require extensive manual interaction, limiting analysis scope and time.
  • This hinders the full exploitation of time-resolved X-ray tomographic stations.

Purpose of the Study:

  • To present a fully automated iterative tomographic reconstruction pipeline (rSIRT-PWC-DIFF).
  • To enable reconstruction and segmentation of dynamic processes within a static matrix.
  • To reduce post-processing time and manual labor in dynamic X-ray investigations.

Main Methods:

  • The rSIRT-PWC-DIFF pipeline utilizes automatic dynamic feature separation via difference sinograms.
  • Incorporates a virtual sinogram step for interior tomography datasets.

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A Guide to Concentration Alternating Frequency Response Analysis of Fuel Cells
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  • Features time-regularization for small sub-regions and an automatic stopping criterion.

    • Main Results:

    • Demonstrated advantages on dynamic fuel cell data, reducing post-processing time by at least a factor of 4.
    • Achieved full independence from manual interaction.
    • Enabled straightforward up-scaling for processing larger datasets.

    Conclusions:

    • The automated pipeline significantly boosts possibilities for future dynamic X-ray tomographic investigations.
    • Reduces computational time and manual effort, making advanced analysis more accessible.
    • Facilitates more comprehensive volumetric analysis of dynamic processes.