Collaborative Research: DMREF: Microstructure by Design: Integrating Grain Growth Experiments, Data Analytics, Simulation, and Theory

大多数技术上有用的材料是由无数由晶界界定的小单晶颗粒组成的多晶微结构。了解晶界的演变和相关的晶粒长大(粗化)对于确定材料在多个尺度上的性质至关重要。然而，尽管在建立微观结构模型方面取得了巨大的进展，但目前的描述并不能完全解释各种晶粒生长机制、详细的晶粒拓扑结构以及不同时间尺度对微观结构演变的影响。因此，传统理论的预测能力有限。该项目的目标是通过构建新的、紧密集成的数据驱动的数值模拟和数学模型，结合数据分析、分析和一系列关键实验，开发多晶材料中的晶粒生长预测理论。这个跨学科的项目需要应用数学家和材料科学家的互补专业知识，与材料基因组倡议坚定地保持一致。该项目将产生的新知识和新工具将对用于许多技术有用的系统和结构的多晶材料的性能和可靠性产生深远影响，从而加快先进材料的开发和部署。预测计算算法和数据将向其他研究人员提供和访问。对于下一代材料劳动力的培训，除了指导研究生和本科生外，来自哥伦比亚大学、伊利诺伊理工学院、利哈伊大学和犹他大学的PI将参加外联活动，并将继续努力增加STEM内的多样性和扩大参与。颗粒生长是一个非常复杂的过程，可以被视为大型亚稳定网络的各向异性演变。该项目的主要目标之一将是发现可能的随机过程，这些过程定义了各种颗粒生长统计指标的演变，发现它们之间的关系，并建立与材料属性的联系。保留结构的数值模拟结果与关键的实验集和新的实验数据一起，将在建模和分析中发挥不可估量的作用。该项目还将创建和使用特定的数据分析技术，在实验和计算系统中研究颗粒的动态演变，目的是验证和进一步完善微观结构模型。该项目的这一组成部分将导致a)新材料信息学方法的发展，b)创新的随机微分方程式/微分方程式的颗粒生长模型，c)粗化系统的新的数学和数值分析技术，以及d)改进的计算工具。反过来，综合数据分析、建模和分析的结果将用于指导后续实验的设计。在实验上，将研究典型的金属薄膜(Pd、Ni、Cr、Fe)中的颗粒生长。由于大多数元素金属和许多金属合金具有立方结构，建议的研究将具有广泛的适用性。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Most technologically useful materials are polycrystalline microstructures composed of a myriad of small monocrystalline grains delimited by grain boundaries. An understanding of the evolution of grain boundaries and associated grain growth (coarsening) is essential in determining the properties of materials across multiple scales. Despite tremendous progress in formulating microstructural models, however, current descriptions do not fully account for various grain growth mechanisms, detailed grain topologies and the effects of different time scales on microstructural evolution. As a result, conventional theories have limited predictive capability. The goal of the project is to develop a predictive theory of grain growth in polycrystalline materials through the construction of novel, closely integrated data-driven numerical simulation and mathematical modeling combined with data analytics, analysis, and a set of critical experiments. This interdisciplinary project, requiring the complementary expertise of applied mathematicians and materials scientists, is firmly aligned with the Materials Genome Initiative. The new knowledge and tools that will emerge from the project will have a profound impact on the performance and reliability of polycrystalline materials used in many technologically useful systems and structures, thereby expediting advanced materials development and deployment. Predictive computational algorithms and data will be made available and accessible to other researchers. For the training of the next-generation materials workforce, in addition to mentoring of graduate and undergraduate students, the PIs (from Columbia University, Illinois Institute of Technology, Lehigh University and University of Utah) will participate in outreach activities and will continue to work towards increasing diversity and broadening participation within STEM.Grain growth is a very complex process and may be viewed as the anisotropic evolution of a large metastable network. One of the main thrusts of the project will be to uncover possible stochastic processes that define the evolution of various statistical measures of grain growth, discover relations among them, and establish links to materials properties. Results from structure-preserving numerical simulations alongside critical sets of experiments and new experimental data will be invaluable in navigating the modeling and analysis. The project will also create and employ specific data analysis techniques for the study of dynamic evolution of grains in experimental and computational systems with the goal of validating and further refining the microstructural models. This component of the project, will lead to a) the development of new materials informatics methods, b) innovative stochastic differential equations/differential equations models of grain growth, c) new mathematical and numerical analysis techniques for coarsening systems, as well as d) improved computational tools. In turn, the results of combined data analytics, modeling and analysis will be used to guide the design of subsequent experiments. Experimentally, grain growth will be examined in prototypical metallic thin films (Pd, Ni, Cr, Fe). As most elemental metals and many metallic alloys have cubic structures, the proposed studies will have broad applicability.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.