CAREER: A Probabilistic Framework for the Nucleation of Recrystallization

当金属被加热并通过锻造等工艺变形为工程部件时，这不仅仅是宏观形状的变化-金属本身的特性可以通过控制局部温度和变形速率来调整。这些外部参数可用于控制材料的微观结构（“微观结构”）;然而，由于同时存在许多机制，因此关系很复杂。在这项研究计划中，PI米勒使用统计方法和机器学习来识别材料中最有可能引发微观结构变化的部位。 预测微观结构变化的起始位置的能力可以帮助防止在极端环境中使用期间的材料失效，例如在飞机发动机或动力装置中。它还可用于优化制造过程中的材料加工，从而降低金属加工成本。这项研究的核心概念-材料微观结构的测量和量化-已被纳入从中学到大学的教育和推广模块。通过与佛罗里达大学现有项目的合作，PI将向中学教师分发工具包。这些计划专门针对历史上代表性不足的群体比例较高或社会经济地位较低的地区，旨在提高学生在学术生涯早期接触材料科学的多样性。此外，针对不同年龄组的数字版模块将通过相关专业组织国际金相学会广泛传播。该研究计划通过引入概率框架来预测可能的再结晶位点，从而实现了对热机械处理过程中固态微观结构演变的前所未有的控制。这是PI米勒职业生涯长期目标的关键组成部分，即对位错的统计累积进行定量的、基于机制的理解，并将这些知识用于定义产生具有独特特性的微结构的加工路径。可能的成核位置的先验预测允许在再结晶相关的故障机制或再结晶微观结构的建模中具有更大的保真度。PI假设，在给定的微观结构部位的再结晶的可能性可以通过“再结晶指示参数（RXIP）”来捕获，类似于疲劳和断裂中的疲劳指示参数的概念。该无量纲参数通过量化和加权促进或抑制成核的局部特征的贡献来描述给定微结构位点处的成核概率，例如，曲率，滑移系对齐，施密德因子，失配等这项研究的核心概念，测量和量化的材料的微观结构，已被集成到教育和推广模块，从中学到大学使用。PI将与佛罗里达大学的现有项目合作，通过由教育部和康奈尔实验借阅图书馆资助的教师培训项目，对物理套件进行试点和迭代改进。 为了更广泛的传播，数字演示和数据处理版本的模块将通过国际金相学会作为教育工具分发。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Non-Technical SummaryWhen metals are heated and deformed into engineering components by processes such as forging, it is not just a macroscopic shape change—the properties of the metal itself can be tuned by controlling the local temperatures and deformation rates. These external parameters can be used to control the material’s microscale structure ("microstructure"); however, the relationships are complicated as there are numerous mechanisms simultaneously active. In this research program, PI Miller uses statistical methods and machine learning to identify the most likely sites in the material for the microstructure changes to initiate. The ability to predict the initiation sites for microstructure changes can help to prevent material failure during service in extreme environments, such as in aircraft engines or powerplants. It can also be used to optimize materials processing during manufacturing, potentially reducing the cost of metals processing. The core concept of this research—measurement and quantification of the micro-scale structure of materials—has been integrated into education and outreach modules for use from middle school to university. Through partnerships with existing programs at the University of Florida, the PI will distribute kits to middle school teachers. These programs specifically target districts with a high fraction of historically under-represented groups or a low socioeconomic status, seeking to improve the diversity of students exposed to materials science early in their academic careers. Additionally, digital versions of the modules targeted to different age groups will be broadly disseminated through a relevant professional organization, the International Metallographic Society. Technical Summary This research program enables unprecedented control of solid-state microstructural evolution during thermomechanical treatment by introducing a probabilistic framework for the prediction of likely recrystallization sites. This is a key component of PI Miller’s career-long goal of developing a quantitative, mechanism-based understanding of the statistical accumulation of dislocations and deploy this knowledge to define processing paths that result in microstructures with unique properties. A priori prediction of likely nucleation sites allows for greater fidelity in modeling of recrystallization-related failure mechanisms or the as-recrystallized microstructure. The PI hypothesizes that the likelihood of recrystallization at a given microstructural site can be captured by a "recrystallization indicator parameter (RXIP)", similar to the concept of a fatigue indicator parameter in fatigue and fracture. This dimensionless parameter describes the probability of nucleation at a given microstructural site by quantifying and weighting the contributions of local features that promote or inhibit nucleation, e.g., curvature, slip system alignment, Schmid factor, misfit, etc. The core concept of this research—measurement and quantification of the microstructure of materials—has been integrated into education and outreach modules for use from middle school to university. The PI will partner with existing programs at the University of Florida to pilot and iteratively refine physical kits through teacher training programs funded by the Department of Education and the Cornell Lending Library of Experiments. For broader dissemination, digital demonstrations and data-processing only versions of the modules will be distributed as an educational tool through the International Metallographic Society.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.