Monte Carlo simulation of grain growth and recrystallization in polycrystalline materials

The prediction and control of metal grain structures during processing have been major objectives of materials science. However, methodologies that are accurate and can be easily generalized to a variety of processing conditions have been difficult to formulate due to the complexity of the grain interactions. A novel Monte Carlo-based approach that explicitly incorporates these interactions has been developed to simulate the microstructural evolution driven by the minimization of grain boundary energy and lattice defect density. The applicability of this procedure has been demonstrated by the good correspondence between simulation results and experimental observations. This article reviews recent advances in the application of this technique to the investigation of a variety of phenomena, including normal and abnormal grain growth as well as static and dynamic recrystallization.