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Achieving realistic interface kinetics in phase-field models with a diffusional contrast.

G Boussinot1, Efim A Brener2

  • 1Peter Grünberg Institut, Forschungszentrum Jülich, D-52425 Jülich, Germany and Computational Materials Design Department, Max-Planck Institut für Eisenforschung, D-40074 Düsseldorf, Germany.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
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PubMed
Summary
This summary is machine-generated.

Phase-field models now realistically describe interface kinetics in diffusion-driven phase transformations. This new kinetic cross-coupling method resolves issues with diffusional contrast and temperature jumps at interfaces.

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Area of Science:

  • Computational physics
  • Materials science
  • Chemical engineering

Background:

  • Phase-field models are essential for simulating free-boundary problems.
  • Coupling of nonconserved phase field and conserved diffusion fields is crucial for phase transformations.
  • Existing models face challenges in realistically describing interface kinetics with diffusional contrast.

Purpose of the Study:

  • To introduce a kinetic cross-coupling term for phase-field models.
  • To address the long-standing problem of realistic interface kinetics description.
  • To eliminate temperature jumps and recover equilibrium boundary conditions.

Main Methods:

  • Incorporation of a kinetic cross-coupling term between phase and diffusion fields.
  • Application to the solidification of a pure substance.
  • Validation through numerical simulations.

Main Results:

  • A realistic description of interface kinetics is achieved.
  • The diffusional contrast between phases is effectively handled.
  • Temperature jumps at the interface are eliminated, restoring equilibrium boundary conditions.

Conclusions:

  • The proposed kinetic cross-coupling significantly enhances phase-field model realism.
  • This approach provides a robust framework for simulating diffusion-driven phase transformations.
  • The method successfully recovers equilibrium boundary conditions, crucial for accurate material behavior prediction.