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A self-consistent mean field model for concentration dependent phenomenological coefficients : application to Fe-Ni-Cr solid solution

Vincent Barbe, Maylise Nastar

2023frmodelingsimulationalloysmaterialskinetics

Abstract

Language:

We present an improvement of the self-consistent mean field (SCMF) approximation of the Lij which extends its applications to alloys presenting high jump frequency ratios. The objective is to develop a reliable atomic diffusion model that accounts for temperature and local composition effects, utilizing thermodynamic and kinetic parameters. The methodology involves applying this model to build a diffusion framework specifically for the Fe-Ni-Cr solid solution based on high-temperature experimental data, and subsequently testing the model against low-temperature resistivity measurements. The results indicate that the SCMF approach provides accurate predictions of the diffusion coefficients and reveals critical correlations between atom-vacancy exchange frequencies and the Lij in concentrated alloys. The analysis underscores that taking into account the local environment of atoms is essential for improving the accuracy of these models, ultimately leading to a better understanding of kinetic and thermodynamic interactions in solid solutions.

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Cite This Work

@article{52e4e1e8-13e9-47ff-be30-b9e8342d3dd9,
  title={A self-consistent mean field model for concentration dependent phenomenological coefficients : application to Fe-Ni-Cr solid solution},
  author={Vincent Barbe and Maylise Nastar},
  year={2023},
  language={fr}
}
TY  - JOUR
TI  - A self-consistent mean field model for concentration dependent phenomenological coefficients : application to Fe-Ni-Cr solid solution
AU  - Vincent Barbe
AU  - Maylise Nastar
PY  - 2023
LA  - fr
ER  -

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