CAREER: A Probabilistic Framework for the Nucleation of Recrystallization

当金属被加热并通过锻造等过程变形成工程部件时，它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节。这些外部参数可以用来控制材料的微观结构（“微结构”）；然而，这种关系是复杂的，因为有许多机制同时活跃。在这个研究项目中，PI Miller使用统计方法和机器学习来识别材料中最可能引发微观结构变化的部位。预测微观结构变化起始位置的能力可以帮助防止材料在极端环境（如飞机发动机或动力装置）中失效。它还可以用于优化制造过程中的材料加工，潜在地降低金属加工的成本。本研究的核心概念——材料微观结构的测量和量化——已被整合到中学到大学的教育和推广模块中。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。这些项目专门针对那些历史上代表性不足的群体或社会经济地位较低的地区，旨在提高在学术生涯早期接触材料科学的学生的多样性。此外，针对不同年龄组的模块的数字版本将通过有关的专业组织国际金相学会广泛传播。本研究计划通过引入一个概率框架来预测可能的再结晶位置，从而实现了在热处理过程中对固态显微组织演变的前所未有的控制。这是PI Miller职业生涯长期目标的关键组成部分，该目标是对位错的统计积累进行定量的、基于机制的理解，并利用这些知识来定义加工路径，从而产生具有独特性质的微观结构。对可能成核位置的先验预测可以更准确地模拟与再结晶相关的失效机制或再结晶后的微观结构。PI假设可以通过“再结晶指示参数（RXIP）”来捕获给定微结构部位再结晶的可能性，类似于疲劳和断裂中的疲劳指示参数的概念。这个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观结构部位成核的概率，例如曲率、滑移系统对准、施密德因子、失配等。这项研究的核心概念——材料微观结构的测量和量化——已经被整合到中学到大学的教育和推广模块中。PI将与佛罗里达大学现有的项目合作，通过教育部和康奈尔实验借阅图书馆资助的教师培训项目，对物理工具包进行试点和迭代改进。为了更广泛地传播，将通过国际金相学会作为一种教育工具分发这些模块的数字演示和数据处理版本。该奖项反映了美国国家科学基金会的法定使命，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.