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

合作研究：DMREF：揭示多晶晶界迁移机制，用于晶粒生长的预测模拟

• 批准号: 2246833
• 负责人: Amanda Krause
• 金额: $ 37.04万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-10-15 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2246833&HistoricalAwards=false
• 关键词: Collaborative; Research; DMREF; Uncovering; Mechanisms

NON-TECHNICAL SUMMARYMost 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 SUMMARYThe 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.

非技术摘要的最固体材料，包括金属，陶瓷，甚至某些聚合物，具有内部晶界的内部网络，可以将单个晶体分开。该晶界网络强烈影响材料特性，因此对于汽车，飞机，计算机和许多其他设备的设计非常重要。这项研究的目的是为金属和陶瓷中晶界网络的演变开发准确的预测模拟。这些模拟将通过定义处理条件以实现特定的微观结构和性能，将多晶组件掺入设备和结构中。该项目将依赖于晶粒生长的实验观察，新的晶界迁移理论与晶界面进化的计算机模拟之间的迭代反馈。通过这种方式，它与材料基因组倡议对齐。技术总结晶界网络的结构是在材料在高温下处理时晶界迁移确定的。因此，控制材料特性是基于理解和控制晶界迁移的。晶界迁移的两个流行模型是扩散迁移和缺陷控制的迁移。为了准确模拟微观结构的演变，有必要知道这两个模型是否提供了晶界迁移的准确描述。 X射线显微镜将用于测量铁素铁，镍和钛酸盐中晶界网络的结构，以及它们如何随时间发展。原位加热实验将用于测量多晶体中晶界的迁移速率，这是温度的函数。结果将与晶界迁移的原子模拟和晶界迁移的两个理论的预测进行比较，以确定哪个提供了对温度依赖性的较高描述。然后，机械信息将用于参数化三维中尺度晶粒生长模型。然后，此过程的结果可以指导实验到最重要的温度范围或时间尺度进行退火。了解界面迁移的机制将使更好地预测微观结构的演变是可能的，这是加速多晶材料发展的必要步骤。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的智力优点和更广泛影响的审查标准通过评估来获得支持的。