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The European Physical Journal Special Topics

, Volume 223, Issue 3, pp 545–558 | Cite as

Phase field models for heterogeneous nucleation: Application to inoculation in alpha-solidifying Ti-Al-B alloys

  • M. Apel
  • J. Eiken
  • U. Hecht
Review
Part of the following topical collections:
  1. Heterogenous Nucleation and Microstructure Formation: Steps Towards a System and Scale Bridging Understanding

Abstract

This paper aims at briefly reviewing phase field models applied to the simulation of heterogeneous nucleation and subsequent growth, with special emphasis on grain refinement by inoculation. The spherical cap and free growth model (e.g. A.L. Greer, et al., Acta Mater. 48, 2823 (2000)) has proven its applicability for different metallic systems, e.g. Al or Mg based alloys, by computing the grain refinement effect achieved by inoculation of the melt with inert seeding particles. However, recent experiments with peritectic Ti-Al-B alloys revealed that the grain refinement by TiB2 is less effective than predicted by the model. Phase field simulations can be applied to validate the approximations of the spherical cap and free growth model, e.g. by computing explicitly the latent heat release associated with different nucleation and growth scenarios. Here, simulation results for point-shaped nucleation, as well as for partially and completely wetted plate-like seed particles will be discussed with respect to recalescence and impact on grain refinement. It will be shown that particularly for large seeding particles (up to 30 μm), the free growth morphology clearly deviates from the assumed spherical cap and the initial growth – until the free growth barrier is reached – significantly contributes to the latent heat release and determines the recalescence temperature.

Keywords

European Physical Journal Special Topic Heterogeneous Nucleation Seeding Particle Nucleation Event Heat Extraction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© EDP Sciences and Springer 2014

Authors and Affiliations

  • M. Apel
    • 1
  • J. Eiken
    • 1
  • U. Hecht
    • 1
  1. 1.ACCESS e. V., RWTH Aachen, Intzestr. 5AachenGermany

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