Multimodal and Multiscale-driven Quantification of Micromechanical Metrics for Location-specific Fatigue Microcracking

该奖项支持旨在识别和量化金属材料疲劳损伤的机械驱动因素的研究和教育活动。疲劳是一种物理过程，与晶体材料在连续和重复的载荷作用下的失效有关。疲劳知识在防止机械、设备和结构中的金属结构部件失效方面具有巨大的价值。要准确地预测疲劳寿命，就需要知道微尺度（裂纹起始的尺度）裂纹萌生的控制机制驱动因素。然而，由于金属材料中裂纹起裂点附近的微观结构随着载荷的变化而不断变化，因此识别这些机械驱动因素是一项具有挑战性的任务。在该项目中，PI将通过综合计算和实验方法解决这一挑战，从而更深入地了解影响疲劳裂纹起裂的因素。该项目的主要重点将放在颗粒非常大的纯金属上，如镍。从研究中获得的见解和工具将提高各种大晶粒金属结构部件和经受循环应力的薄膜器件的疲劳寿命预测的准确性。此外，该项目还将支持数据密集型材料研究领域多样化的未来劳动力的教育和培训。为了激励初高中学生攻读材料科学和工程学位，PI将开发简短的，适合年龄的讲座，解释学生的基本课堂学习如何与专业工程师使用的实际工具和模型相关联，并让学生有机会使用这些工具进行非常基本的模拟。该奖项支持研究和教育活动，以确定和量化具有高层错能的粗晶面心立方材料疲劳裂纹成核的微机械驱动力指标。理解晶体材料的疲劳损伤是具有挑战性的，因为裂纹起始点附近的微观结构特征，如持久的滑移带及其相互作用，随着循环加载不断演变。微观结构的不断演变产生了复杂的微力学场和相互作用，这使得很难确定裂纹起裂的控制机制驱动因素。本工作的具体目标包括：(1)确定应变局部化如何影响循环加载过程中的表面变形；(2)建立对地下变形机制驱动因素的统一认识；(3)研究应变局部化作为裂纹萌生前兆的微观结构和微观力学原理；(4)确定高应变梯度对持久滑移带-基体界面微裂纹的影响。这将通过综合计算和实验方法来实现。从研究中获得的见解和工具将提高各种大晶粒金属结构部件和经受循环应力的薄膜器件的疲劳寿命预测的准确性。此外，该项目还将支持数据密集型材料研究领域多样化的未来劳动力的教育和培训。为了激励初高中学生攻读材料科学和工程学位，PI将开发简短的，适合年龄的讲座，解释学生的基本课堂学习如何与专业工程师使用的实际工具和模型相关联，并让学生有机会使用这些工具进行非常基本的模拟。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。

NONTECHNICAL SUMMARYThis award supports research and education activities aimed at identifying and quantifying the mechanistic drivers for fatigue damage in metallic materials. Fatigue is a physical process that is associated with the failure of crystalline materials under continuous and repeated application of loads. The knowledge of fatigue is of immense value in preventing the failure of metallic structural components in machinery, equipment and structures. The accurate prediction of fatigue life requires the need to know the governing mechanistic drivers for crack initiation at the microscale (the scale at which cracks initiate). However, since the microstructure in the vicinity of the crack initiation sites in metallic materials evolves continuously with loading, the identification of these mechanistic drivers is a challenging task. In this project, the PI will address this challenge with an integrated computational and experimental approach that will provide a deeper understanding of the factors influencing fatigue crack initiation. The primary focus of the project will be on pure metals with very large grains such as nickel. Insights and tools obtained from the research will improve the accuracy of fatigue life predictions for a variety of large-grained metallic structural components and thin film devices that undergo cyclic stresses. Additionally, the project will support the education and training of a diverse future workforce in data-intensive materials research. To inspire middle and high school students to pursue materials science and engineering degrees, the PI will develop brief, age-appropriate lectures that explain how students’ basic classroom learning relates to the actual tools and models that professional engineers use and give the students the chance to perform very basic simulations using the tools.TECHNICAL SUMMARYThis award supports research and education activities to identify and quantify the micromechanical driving force metrics for fatigue crack nucleation in coarse-grained face centered cubic materials with a high stacking fault energy. Understanding fatigue damage in crystalline materials is challenging because the microstructural features such as persistent slip bands and their interactions, in the vicinity of the crack initiation sites evolve continuously with cyclic loading. The continuous evolution of the microstructure generates complex micromechanical fields and interactions which makes it difficult to pinpoint the governing mechanistic drivers for crack initiation. Specific goals of this work include: (1) identify how strain localization affects the surface deformation during cyclic loading; (2) establish a unifying understanding of mechanistic drivers for subsurface deformation; (3) investigate the microstructural and micromechanical rationale for strain localization as a precursor to crack initiation and, (4) identify the influence of high strain gradients on microcracking at persistent slip band-matrix interfaces. This will be achieved through an integrated computational and experimental approach.Insights and tools obtained from the research will improve the accuracy of fatigue life predictions for a variety of large-grained metallic structural components and thin film devices that undergo cyclic stresses. Additionally, the project will support the education and training of a diverse future workforce in data-intensive materials research. To inspire middle and high school students to pursue materials science and engineering degrees, the PI will develop brief, age-appropriate lectures that explain how students’ basic classroom learning relates to the actual tools and models that professional engineers use and give the students the chance to perform very basic simulations using the tools.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.