CAREER: Understanding Grain Boundary Strength via Adaptive Electron Backscatter Diffraction and Multiscale Analysis

非技术人员使用金属和合金已有数千年的历史，并通过开发制造它们的新方法不断提高它们的强度和性能。这一改进金属的过程在很大程度上依赖于猜测和检查。尽管人们已经变得更擅长猜测，也变得更快地进行检查，但智能设计更坚固、更安全、更有弹性的金属的基础知识仍然缺乏。改进金属和合金的部分挑战是，它们的性能取决于数万亿个缺陷的类型、密度和分布，这些缺陷比几个原子大不了多少。这些缺陷的两种重要类型是位错和晶界，位错允许金属变形，晶界在金属中移动时充当位错的障碍。晶界的性质影响位错在材料中移动的难易程度，进而影响金属的强度。然而，晶界的性质与位错运动的势垒有多强之间的直接联系尚未建立。通过在百万分之一米或更小的超小长度尺度上观察晶界，该项目将建立这种直接联系。为了做到这一点，电子显微镜将被用来观察材料在弯曲时如何在晶界附近积累位错。电子显微镜能够对材料进行低至单个原子级别的成像。人工智能(AI)将被内置到电子显微镜中，以便快速和自动地探测数万个晶界，以获得对晶界特征与其强度之间关系的统计理解。这一认识将有助于指导开发更坚固、更安全、使用寿命更长的新金属和合金。这项工作的范围更广，包括让来自代表性不足社区的高中生参加暑期实习研究项目。这些实习生将与该计划支持的研究生密切合作，研究金属的强度，并将制定包含虚拟现实元素的教案，以便在下一学年带回课堂。暑期实习还将参观Novelis研究中心，这是一家全球性的铝业公司，研究总部位于亚特兰大附近。技术总结长期以来，晶界在决定金属和合金的机械行为和失效敏感性方面的核心作用一直得到认可。然而，由于对决定单个晶界强度的因素的不完全理解，理解晶界特征的变化如何影响材料性能的努力一直受到阻碍。这个项目的目的是确定决定晶界强度的特征，这里定义为晶界对位错扩展造成的势垒强度。将开发一种基于自适应重新网格化电子背散射衍射(AR-EBSD)的新方法，将在线处理和自动自适应网格重新网格化相结合，以快速采样建立可应用机器学习方法的库所需的数万个晶界。该方法将与透射电子显微镜表征和原子模拟相结合，将晶界强度与位错转移机制相关联。这种耦合的方法将促进对晶界空间的前所未有的探索，就所调查的晶界数量而言，允许建立严格的晶界强度函数。此外，在拟议工作过程中开发的多尺度电子显微镜技术将成为材料表征工具箱中广泛适用的补充，用于研究环境和极端条件下的材料变形。此外，代表不足的少数族裔参与STEM研究的渠道将通过一个针对来自代表不足的社区的高中生的“可视化科学”暑期实习计划来创建。这些实习生将与该项目支持的研究生一起研究金属的延性断裂行为，学习机械测试和表征技术，并参观Novelis研究中心，这是一家总部位于亚特兰大附近的全球性铝业公司。为了扩大这项计划的影响力，实习生还将制定包含虚拟现实元素的课程计划，带回高中课堂。这一奖项反映了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。

NON-TECHNICAL SUMMARYPeople have been using metals and alloys for thousands of years and have constantly improved their strength and performance through developing new ways to make them. This process of improving the metals has relied largely on guess and check. Although people have become better at guessing and faster at checking, the foundational knowledge to intelligently design stronger, safer, more resilient metals is still missing. Part of the challenge in improving metals and alloys is that their performance is dependent on the type, density, and distribution of trillions of defects that are not much bigger than a few atoms. Two important types of these defects are dislocations, which allow metals to deform, and grain boundaries, which act as barriers to dislocations as they move through the metal. The character of a grain boundary influences how easily dislocations can move through the material, and in turn, affects the strength of the metal. However, a direct link between the character of a grain boundary and how strong of a barrier it is to dislocation motion has not been established. By looking at grain boundaries at ultra-small length scales of one millionth of a meter and smaller, this project will establish that direct link. To do so, electron microscopes, capable of imaging materials down to the level of individual atoms, will be used to see how dislocations accumulate in the material near grain boundaries while the material is being bent. Artificial intelligence (AI) will be built into the electron microscopes in order to rapidly and automatically explore tens of thousands of grain boundaries to obtain a statistical understanding of how grain boundary character is connected to its strength. This understanding will be instrumental in guiding the development of new metals and alloys that are stronger, safer, and longer lasting in application. The broader outreach of this work includes integrating high school students from underrepresented communities in a summer internship research program. These interns will work closely with graduate students supported by the program to investigate the strength of metals and will also develop lesson plans incorporating virtual reality elements to take back to their classes in the following school year. The summer internship will also include visits to the Novelis research center, a global Al company with research headquarters near Atlanta.TECHNICAL SUMMARYThe central role of grain boundaries has long been recognized in dictating the mechanical behavior and failure susceptibility of metals and alloys. However, efforts to understand how variations in grain boundary characteristics affect material properties have been hampered by an incomplete understanding of what determines the strength of individual grain boundaries. The purpose of this project is to determine the characteristics that dictate grain boundary strength, here defined as the barrier strength that grain boundaries pose to dislocation propagation. A new adaptive remeshing electron backscatter diffraction (AR-EBSD)-based approach will be developed, combining in-line processing and automated adaptive grid remeshing to rapidly sample the tens of thousands of grain boundaries needed to build a library to which machine learning approaches can be applied. This approach will be coupled with transmission electron microscopy (TEM) characterization and atomistic simulations to correlate grain boundary strength with dislocation transfer mechanisms. This coupled approach will facilitate an unprecedented exploration of grain boundary space in terms of the number of grain boundaries investigated, allowing rigorous grain boundary strength functions to be established. In addition, the multiscale electron microscopy techniques developed over the course of the proposed work will be a widely applicable addition to the materials characterization toolbox in investigating material deformation under ambient and extreme conditions. Furthermore, a pipeline for underrepresented minorities to engage in STEM research will be created by a “visualizing science” summer internship program for high school students from underrepresented communities. These interns will work with graduate students supported by this program to investigate the ductile fracture behavior of metals, learn mechanical testing and characterization techniques, and visit the Novelis research center, a global Al company with research headquarters near Atlanta. To enhance the broader impact of this program, the interns will also develop lesson plans incorporating virtual reality elements to take back to their high school classes.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.