Simulation Study of Heterogeneous Nucleation at Grain Boundaries During the Austenite-Ferrite Phase Transformation: Comparing the Classical Model with the Multi-Phase Field Nudged Elastic Band Method
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Abstract
In this work, molecular dynamics (MD) simulations have been used to study the heterogeneous nucleation occurring at grain boundaries (GBs) during the austenite (FCC) phase to ferrite (BCC) phase transformation in a pure Fe polycrystalline system. The critical nucleus properties (including size, shape, and activation energy) determined by classical nucleation theory are compared with those obtained by using a combination of the multi-phase field method (MPFM) and the nudged elastic band (NEB) method. For nucleation events that exhibit low-energy facets completely embedded within the parent FCC phase, there is a good agreement between the MD and the MPFM result with respect to the critical nucleus size, shape, and nucleation energy barrier. For systems where the emerging nucleus contains facets that cross the GB plane, the MPFM-NEB, when compared to MD, yields a better prediction than the classical approach for the nucleus morphology. New observations from the MPFM-NEB method indicate that the critical nucleus shape may change with volume and therefore depends on the nucleation driving force (undercooling).
Keywords
Molecular Dynamic Simulation Interfacial Energy Critical Nucleus Classical Nucleation Theory Nucleus ShapeNotes
Acknowledgments
The authors acknowledge the support of a Natural Sciences and Engineering Research Council (Canada) Strategic Project grant entitled “Simulation of complex microstructure path way for alloy design” and the computing resources of the Shared Hierarchical Academic Research Computing Network (Sharcnet) of Ontario. We gratefully acknowledge numerous helpful discussions with Dr. Gary Purdy and Dr. Hatem S. Zurob. H. Song acknowledges financial support from a Natural Sciences and Engineering Research Council of Canada postgraduate doctoral Scholarship (NSERC PGS-D). R. Shi and Y. Wang also would like to acknowledge financial support from the National Science Foundation under the DMREF program with Grant No. DMR-1435483.
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