Collaborative Research: DMREF: Uncovering Mechanisms of Grain Boundary Migration in Polycrystals for Predictive Simulations of Grain Growth

University Of Florida, Gainesville FL

Investigators

Abstract

NON-TECHNICAL SUMMARY Most solid materials, including metals, ceramics, and even some polymers, have an internal network of grain boundaries that separate individual crystals. This grain boundary network strongly influences materials properties and, therefore, is important for the design of automobiles, aircraft, computers, and many other devices. The goal of this research is to develop accurate predictive simulations for the evolution of the grain boundary network in metals and ceramics. These simulations will accelerate the incorporation of polycrystalline components into devices and structures by defining processing conditions to achieve specific microstructures and properties. The project will rely on iterative feedback between experimental observations of grain growth, new theories for grain boundary migration, and computer simulations of the evolution of the grain boundary network. In this way, it is aligned with the Materials Genome Initiative. TECHNICAL SUMMARY The structure of the grain boundary network is determined by grain boundary migration when the material is processed at high temperature. Therefore, controlling materials properties is predicated on understanding and controlling grain boundary migration. The two prevailing models for grain boundary migration are diffusive migration and defect-controlled migration. To accurately simulate microstructure evolution, it is necessary to know if, and under what conditions, these two models provide an accurate description of grain boundary migration. X-ray microscopy will be used to measure the structure of the grain boundary networks in ferritic iron, nickel, and strontium titanate, and how they evolve with time. In situ heating experiments will be used to measure the migration rates of grain boundaries in polycrystals as a function of temperature. The results will be compared to atomistic simulations of grain boundary migration and to predictions from two theories for grain boundary migration to determine which one provides a superior description of the temperature dependence. The mechanistic information will then be used to parameterize three-dimensional mesoscale grain growth models. The outcome of this process can then guide the experiments to the most important temperature ranges or time scales for annealing. Understanding the mechanism of interface migration will make it possible to better predict microstructure evolution, a necessary step in accelerating the development of polycrystalline materials. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.