A numerical model coupling diffusion and grain growth in nanocrystalline materials

The optimization of material properties by tailoring nanoscale microstructure is garnering great attention from both material scientists and manufacturing engineers. One promising research direction is to apply conventional diffusion-based techniques such as nitriding, carburizing, coating and sintering to nanocrystalline materials to achieve unprecedented mechanical and chemical properties. Numerical methods to facilitate the experiment endeavor, however, are rare due to the extreme difficulty in dealing with the nanoscale structure evolution. In this work, a numerical scheme considering both grain growth and diffusion in the nanocrystalline structure is proposed. The diffusion along grain boundary and inner grain is modeled by a Cellular Automata (CA) method. The proposed CA method is stable, insensitive to mesh size, and most importantly numerically efficient, making it suitable for the simulation of long-time, large-scale manufacturing processes. This CA model is then integrated with a Monte Carlo (MC) algorithm to model grain growth, which typically accompanies the diffusion process. As a showcase, the integrated model is then applied to simulate the nitriding process in nanocrystalline iron. The results show that grain growth and impurities have an innegligible effect at the elevated temperature for nanocrystalline iron, consistent with experimental observations. The developed method has the potential to serve as a simulation engine for any diffusion-controlled manufacturing processing of nanostructured materials, enabling a numerical framework to establish the processing-microstructure relation.