Computational Materials Science2022，Vol.2027.DOI:10.1016/j.commatsci.2021.110955

Towards predictive simulations of spinodal decomposition in Fe-Cr alloys

Mukherjee, Deepjyoti Forslund, Axel Hoglund, Lars Ruban, Andrei Larsson, Henrik Odqvist, Joakim
Computational Materials Science2022，Vol.2027.DOI:10.1016/j.commatsci.2021.110955
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  • NSTL
  • Elsevier

Towards predictive simulations of spinodal decomposition in Fe-Cr alloys

Mukherjee, Deepjyoti 1Forslund, Axel 1Hoglund, Lars 1Ruban, Andrei 1Larsson, Henrik 1Odqvist, Joakim1
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作者信息

  • 1. KTH Royal Inst Technol
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Abstract

Simulations of spinodal decomposition in an Fe-36 wt%Cr alloy at 773 K are performed by solving the non -linear Cahn-Hilliard equation, and the results are compared with atom probe tomography measurements. The influence of gradient energy coefficient, atomic mobilities and initial structure on the kinetics of spinodal decomposition is studied. It is shown that a proper initial structure, accounting for the thermal history above the miscibility gap, is crucial and enables predictive simulations of spinodal decomposition in Fe-Cr alloys.

Key words

Spinodal decomposition/Monte-Carlo/DFT/APT/Radial distribution function/Gradient energy coefficient/Mobilities/Initial structure/GRADIENT ENERGY COEFFICIENT/INITIO MOLECULAR-DYNAMICS/ATOM-PROBE TOMOGRAPHY/PHASE-SEPARATION/TRANSITION/MOBILITIES/NUCLEATION/GROWTH/NI

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出版年

2022
Computational Materials Science

Computational Materials Science

EISCI
ISSN：0927-0256
被引量2
参考文献量52
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