Statistical Model of Grain Growth in Polycrystalline Nanomaterials

Nanomaterials, due to their fine grain sizes, exhibit enhanced mechanical properties. However, their low stability at also relatively low temperatures might limit their future applications. In the present work, a statistical model has been proposed in order to study grain growth processes in nanomaterials. The Hillert’s approach has been extended by incorporating two mechanisms of growth for an individual grain: grain boundary migration – GBM - (diffusion based - continuous) and grain-rotation coalescence – GRC - (discontinuous). The influence of the grain size distribution on the grain growth process has been studied. The results show that the inclusion of GRC mechanisms results in a departure from the parabolic law of grain growth. Such a deviation has also been observed experimentally, especially in nanomaterials. The results reveal that grain growth rate increases with higher dispersion of the fine grains and the rotation mechanism can initiate growth even with low dispersion. This causes a steady increase in the coefficient of variation which, after some time interval, decays to homogeneity. This paper also demonstrates that the average rotation mobility which is a consequence of the varying misorientation angle contributes up to about 50% of the overall average boundary mobility.