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A MATLAB Toolbox for Findable, Accessible, Interoperable, and Reusable Atom Probe Data Science.

Martina Heller1,2, Benedict Ott1, Valentin Dalbauer1

  • 1Institute for General Materials Properties, Department of Materials Science, Friedrich-Alexander Universität Erlangen-Nürnberg (FAU), Erlangen 91058, Germany.

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Summary
This summary is machine-generated.

This study introduces a MATLAB toolbox for atom probe tomography (APT) data analysis. It enables reproducible, FAIR data management and automated processing for complex materials science datasets.

Keywords:
FAIR atom probe data scienceHDF5atom probe data basestorage of APT data

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Area of Science:

  • Materials Science
  • Data Analytics
  • Scientific Instrumentation

Background:

  • Atom probe tomography (APT) data analysis traditionally relies on manual interpretation.
  • Increasingly complex datasets from advanced APT necessitate systematic and reproducible analysis methods.
  • The principles of findable, accessible, interoperable, and reusable (FAIR) data are crucial for scientific advancement.

Purpose of the Study:

  • To present a MATLAB-based toolbox for standardized APT data management and analysis.
  • To facilitate reproducible and automated processing of APT data.
  • To promote the adoption of FAIR data principles within the materials science community.

Main Methods:

  • Development of a MATLAB toolbox for APT data analytics.
  • Implementation of Hierarchical Data Format 5 (HDF5) for standardized data storage.
  • Creation of a scriptable environment to minimize manual data processing.
  • Design of an extensible metadata scheme for materials science applications.

Main Results:

  • The toolbox enables storage of raw and processed APT data in a FAIR-compliant format.
  • Data processing is largely scriptable, reducing manual input and enhancing reproducibility.
  • The system allows for seamless data interchange and analysis reproduction.
  • A standardized metadata scheme is provided, adaptable to various materials science experiments.

Conclusions:

  • The developed toolbox enhances the reproducibility and accessibility of APT data analysis.
  • It supports the automated processing of large and complex materials science datasets.
  • The approach facilitates the building of collective knowledge and promotes FAIR data practices in APT research.