CAREER: Connecting Grain Boundary's Metastability Evolution to Mechanical Behavior of Nanocrystalline Alloys During Non-Equilibrium Processing

非技术摘要：工程金属广泛用于先进能源、交通和国防应用。 有趣的是，纳米晶体金属由紧密堆积在一起的微小纳米级微晶组成，具有卓越的强度和更高的耐用性。 在每个微晶内，金属原子以高度有序的方式排列。然而，由于微晶相对于彼此可以具有不同的空间取向，因此相邻微晶之间的边界附近的原子不再良好地排列并且被视为缺陷。这些缺陷对机械强度的增强起着决定性的作用。 因此，为了了解这些缺陷如何提高机械强度，PI 和他的团队将使用阿贡国家实验室提供的同步加速器 X 射线源，并辅以 PI 开发的先进原子建模技术，以确定这些缺陷附近的原子在各种应力​​、温度和机械变形速率下变形过程中的运动。 这些见解将用于推进纳米微晶金属的时间依赖性和环境敏感性机械性能的预测理论。这项研究的成果还将通过虚拟现实（VR）辅助教学创新应用于课堂教学。此外，该项目旨在通过推广各种平台来指导下一代 STEM 劳动力，激励资源不足的 K-12 学生和具有不同背景的潜在未来工程师，并吸引公众并提高他们对材料科学的认识，从而产生更广泛的影响。技术摘要：了解复杂环境中亚稳态晶界的行为对于开发先进能源、交通和国防应用所需的经济高效且高性能的纳米晶合金至关重要。该项目的主要目标是建立描述极端条件下晶界的结构和亚稳态演化的基本基础，并利用该基础来解释和预测非平衡加工下纳米晶合金发生的晶界介导的变形和由此产生的机械性能。该项目将结合先进的原子采样技术、势能景观理论和机器学习工具：（i）通过诱导特定位置的扰动，获得无序原子堆积环境中基本结构重排和相关激活能谱的集合； (ii) 使用随机样本共识机器学习算法，通过非仿射位移场分析，自动检测容易发生塑性变形的核原子； （iii）建立自洽的动力学理论，以构建势能景观中晶界的各种亚稳态之间的连通性，并预测随时间变化的亚稳态的演化； (iv) 使用势能景观辅助的新型原子建模协议，发现跨多个时间尺度的亚稳态晶界和钉扎位错之间的相互作用机制。该项目还将进行设计的假设驱动实验，包括 X 射线衍射、亚烧蚀飞秒激光脉冲和纳米压痕，以验证建模和理论预测。拟议的研究将直接将晶界内的原子级过程（例如，短程原子重排和非仿射原子位移）与纳米晶合金的宏观行为联系起来，这可能有助于开发纳米晶合金的新设计/加工空间，确定在复杂环境下获得具有增强性能和耐用性的新状态的优化途径。该研究计划将与教育创新和外展活动相结合，包括：（i）在开发的关于晶界和晶界的新课程中利用虚拟现实和其他先进技术结构材料的其他缺陷； (ii) 通过参加密歇根大学和国家实验室的暑期学校，指导 STEM 领域的下一代劳动力； (iii) 通过各种平台向资源匮乏的 K-12 学生和具有不同背景的潜在未来工程师进行外展，并分享 PI 的研究和职业道路，为他们提供信息和启发，并促进高等教育； (iv) 探索博物馆等有吸引力的场所，以吸引公众并提高他们对材料科学的认识。该奖项由材料研究部的金属和金属纳米结构以及凝聚态物质和材料理论项目共同资助。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力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 Summary:Engineering metals are used broadly for advanced energy, transportation, and defense applications. Intriguingly, nano-crystalline metals, which are made of tiny nanometer-sized crystallites packed tightly together, exhibits superior strength and improved durability. Within each crystallite, the metal atoms are arranged in a highly orderly manner. However, as the crystallites can have various spatial orientations with respect to each other, the atoms near the boundaries between neighboring crystallites are no longer well aligned and are viewed as defects. These defects play a decisive role in the enhanced mechanical strength. Thus, to understand how these defects improve the mechanical strength, the PI and his team will use synchrotron X-ray sources available at the Argonne National Laboratory complemented with advanced atomistic modeling techniques developed by the PI in order to determine the motion of these atoms near these defects during deformation under various stresses, temperatures, and rates of mechanical deformation. Such insights will be used to advance predictive theory of the nano-crystallite metals’ time-dependent and environment-sensitive mechanical performances. The outcome of this research will also be leveraged into classroom instruction using a virtual reality (VR)-assisted teaching innovation. In addition, this project aims for broader impacts by outreaching to a variety of platforms to mentor the next generation workforce in STEM, inspire under-resourced K-12 students and potential future engineers with diverse backgrounds, and engage the public and increase their awareness of material science.Technical Summary:Understanding the behavior of metastable grain boundaries at complex environments is crucial to develop cost-effective and high-performance nanocrystalline alloys demanded in advanced energy, transportation, and defense applications. The primary objective of this project is to establish a fundamental basis to describe the structural and metastability evolution of grain boundaries at extreme conditions, and to use this basis to explain and predict the grain boundary-mediated deformation and the resultant mechanical properties of nanocrystalline alloys taking place under non-equilibrium processing. The project will combine advanced atomistic sampling techniques, potential energy landscape theory, and machine learning tool to: (i) obtain the ensemble of elementary structural rearrangements and associated activation energy spectra in disordered atomic packing environments by inducing location-specific perturbations; (ii) enable an automated detection of kernel atoms prone to plastic deformation through the non-affine displacement field analysis using a random sample consensus machine learning algorithm; (iii) establish a self-consistent kinetic theory to construct the connectivity between grain boundaries’ various metastable states in the potential energy landscape and to predict the evolution of time-dependent metastability; and, (iv) discover the interaction mechanisms between metastable grain boundaries and pinning dislocations across multiple timescales using potential energy landscape-assisted novel atomistic modeling protocol. This project will also carry out designed hypothesis-driven experiments, including X-ray diffraction, sub-ablation femtosecond laser pulses, and nano-indentation, to validate the modeling and theoretical predictions. The proposed research will directly link the atomic level processes (e.g., short-range atomic rearrangements and non-affine atomic displacement) inside the grain boundaries with the macroscopic behavior of nanocrystalline alloys, which may facilitate exploiting new design/processing space of nanocrystalline alloys, identifying optimized routes to access novel states with enhanced performance and durability under complex environments.The research program will be integrated with educational innovations and outreach activities, including: (i) utilizing virtual reality and other advanced techniques in the developed new course on the subject of grain boundaries and other defects in structural materials; (ii) mentoring the next generation workforce in STEM fields by participating in Summer Schools both at the University of Michigan and at National Laboratories; (iii) outreaching to under-resourced K-12 students and potential future engineers with diverse background through various platforms, and sharing the PI’s research and career path to inform and inspire them and to promote higher education; and, (iv) exploring the attractive venues such as museums to engage the public and increase their awareness of materials science.This award is cofunded through the Metals and Metallic Nanostructures and Condensed Matter and Materials Theory programs in the Division of Materials Research.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.