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Bridging microscopy and atomistic simulations, this study introduces a hybrid data format. This method integrates atom probe data with Monte Carlo simulations for accurate material property prediction.

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Area of Science:

  • Materials Science
  • Computational Materials Science
  • Nanotechnology

Background:

  • Microscopy and atomistic simulations are crucial for understanding material microstructures.
  • A significant gap exists in seamlessly integrating microscopy data with atomistic simulation workflows.
  • Atom probe tomography provides 3D atomic-scale imaging but generates imperfect data.

Purpose of the Study:

  • To establish a direct link between experimental microscopy and atomistic simulations.
  • To develop a methodology for processing imperfect atom probe data.
  • To enable accurate prediction of material properties using integrated simulation techniques.

Main Methods:

  • Developed a hybrid data format combining atom probe and Monte Carlo simulation outputs.
  • Created atomically complete and lattice-bound models of material specimens.
  • Utilized density functional theory (DFT) for calculating local energetics and elastic properties.

Main Results:

  • Successfully created a hybrid data format that overcomes limitations of raw atom probe data.
  • Demonstrated the ability to use this hybrid data as direct input for DFT simulations.
  • Enabled accurate calculation of local energetics and elastic properties.

Conclusions:

  • The hybrid data format effectively bridges the gap between atom probe microscopy and atomistic simulations.
  • This integrated approach facilitates advanced materials engineering and property prediction.
  • Atom probe combined with theoretical methods is a powerful tool for modern materials science.