Microstructural descriptors and cellular automata simulation of the effects of non-random nuclei location on recrystallization in two dimensions

Abstract

The effect of non-random nuclei location and the efficiency of microstructural descriptors in assessing such a situation are studied. Cellular automata simulation of recrystallization in two dimensions is carried out to simulate microstrutural evolution for nuclei distribution ranging from a periodic arrangement to clusters of nuclei. The simulation results are compared in detail with microstrutural descriptors normally used to follow transformation evolution. It is shown that the contiguity is particularly relevant to detect microstructural deviations from randomness. This work focuses on recrystallization but its results are applicable to any nucleation and growth transformation

Simulation of recrystallization in iron single crystals

“…Such an analysis may yield good curve fitting, but will obtain fitting parameters that are inaccurate. For example, in previous works, Rios et al 15,29,31 showed that CA simulations with non-randomly located nuclei yield a fitted value of the number of nuclei per unit of volume, N V , and a time exponent for the velocity from Equation 6 that were different from the number of nuclei per unit of volume and time exponent used in the simulation. Consequently, in the present work, the fact that we reproduced experimental results using quantities extracted from analytical models validates the CA simulation and the analytical treatment by V&R. However, in studies in which one has less experimental data this could become an issue.…”

“…Therefore, it is not surprising that CA is the choice of many researchers simulating recrystallization, including Gottstein 17,18 and Raabe 19,20 and many others [21][22][23][24][25][26] . We too have published a series of papers using CA simulations 15,[27][28][29][30][31] . In those papers CA simulation was shown to be geometrically sound in 2-d 28 and 3-d 30 by comparing the results with exact analytical theory available for recrystallization of randomly located nuclei.…”

“…In those papers CA simulation was shown to be geometrically sound in 2-d 28 and 3-d 30 by comparing the results with exact analytical theory available for recrystallization of randomly located nuclei. Moreover, we also used CA simulations to study the influence of non-randomness of nuclei distribution 15,27,29,31 . Nevertheless, our studies lacked direct comparison of CA simulation to experimental data, as is provided here.…”

Kinetics of dissolution-precipitation reaction at the surface of small particles: modelling and application

“…Several studies have been done dealing with phase transitions in one-component systems, which can be schematized as the occurrence of a single reaction. Significant advancements on the modelling of the process have been achieved, which include, among others, the study of the effect on the kinetics of the nucleation rate, of the anisotropic grain growth where the shielding effect comes into play and of the non-random distribution of nuclei as well [2][3][4][5][6][7][8][9]. Numerical and analytical methods have also been developed aimed at describing the particle size distribution function in nucleation and crystallization processes [10][11][12].…”

Inhomogeneous Poisson point process nucleation: comparison of analytical solution with cellular automata simulation

“…In previous papers [18][19][20][21][22][23][24] , cellular automata (CA) simulation of phase transformation/recrystallization in 2-d and 3-d were carried out and compared with KJMA analytical solutions. The purpose of the present paper is to simulate phase transformations/recrystallization in by cellular automata (CA) in order to compare the simulation with the analytical solution by Rios and Villa.…”