Cellular automata modeling of nitriding in nanocrystalline metals

Severe plastic deformation has made it possible to alter the grain size of metal surface to nanoscale. With refined nanograins, the grain boundary effect on diffusion and phase transformation cannot be neglected. Consequently, the widely used conventional 1D nitriding model is not applicable. In this study, a 2D model considering grain boundary diffusion has been developed to investigate nanocrystalline nitriding. As a multi-physical process, both phase transition and diffusion are modeled. Cellular automata method was used to integrate the two models, and more importantly to deal with the moving 2D interface induced by grain boundaries. The phase transition model and diffusion model were validated with experimental data and the Maxwell-Garnett effective diffusion model, respectively. After validation, nitriding of nanocrystalline iron at low temperature (300 °C) was simulated and compared with nitriding of coarse-grained (μm level) iron. In addition, the growth kinetic, composition and spatial distribution of the nitride layer in nanocrystalline nitriding, with different temperatures, surface nitrogen concentrations and different grain sizes, were studied. It has been found that these parameters could significantly affect the growth rate as well as the composition of the nitrided layers. The results also demonstrated that the presence of nanoscale grain can not only decrease nitriding temperature and nitriding duration making low temperature nitriding possible, but also increase the volume fraction of ∈ and γ′ phases in the nitride layer and therefore a better nitriding quality.