A review on the modeling and simulations of solid-state diffusional phase transformations in metals and alloys

Abstract

Solid-state diffusional phase transformations are vital approaches for controlling of the material microstructure and thus tailoring the properties of metals and alloys. To exploit this mean to a full extent, much effort is paid on the reliable and efficient modeling and simulation of the phase transformations. This work gives an overview of the developments in theoretical research of solid-state diffusional phase transformations and the current status of various numerical simulation techniques such as empirical and analytical models, phase field, cellular automaton methods, Monte Carlo models and molecular dynamics methods. In terms of underlying assumptions, physical relevance, implementation and computational efficiency for the simulation of phase transformations, the advantages and disadvantages of each numerical technique are discussed. Finally, trends or future directions of the quantitative simulation of solid-state diffusional phase transformation are provided.Keywords: Solid-state diffusional phase transformation / numerical simulation / empirical and analytical models / phase-field models / cellular automata / Monte Carlo models / molecular dynamics methods *

In Situ Observation of γ′ Phase Transformation Dynamics During Selective Laser Melting of CMSX‐4

“…Phase transformations are induced by driving forces and controlled by the diffusivities of the relevant species. [ 37 ] In this study, the as‐solidified material consists solely of the γ phase. In thermodynamic equilibrium, CMSX‐4 consists of roughly 70 % γ′ phase embedded in the γ matrix.…”

Synthesis, microstructure and indentation Vickers hardness for (Y3Fe5O12)x/Cu0.5Tl0.5Ba2Ca2Cu3O10-δ composites

“…4a). Solid-state diffusional phase transformation, which includes nucleation, growth, and impingement, is directly responsible for the arrangements of constituent composites, which include a specific volume fraction of spatially distributed phases with various compositions, grain size and morphology with random orientation, and their spatial distribution [20]. Numerical simulation approaches may be employed, in future scope of the current work, to account for experimental condition limitations and dynamically recreate microstructure development.…”

“…Numerical simulation approaches may be employed, in future scope of the current work, to account for experimental condition limitations and dynamically recreate microstructure development. Empirical and analytical models [20], phase-field models [21,22], cellular automaton models, Monte Carlo models, and molecular dynamics approaches [20] are now the most sophisticated numerical simulation methods. In general, empirical and analytical models provide more average information, such as average grain size and phase volume fraction of microstructure development at the macroscale.…”

Mean field and full field modelling of microstructure evolution and phase transformations during hot forming and cooling of low carbon steels

“…Among many published PF papers those dedicated to phase transformations should be mentioned (Rudnizki et al, 2011;Steinbach & Apel, 2006). Recently published research focus on the 3D solution (Bollada et al, 2015) and multi PF approach (see Mecozzi et al, 2016;Liu et al, 2018). Good review of the FP models can be also found in the book by Choudhury (2013).…”

“…A review of the full field models of diffusional phase transformations including CA, MC and MD methods is presented by Liu et al (2018). A thorough comparative discussion of the mean field and full field approaches to modelling dynamic recrystallization is presented in the Maire's PhD thesis (2018).…”