CAREER: First-Principles Predictions of Solute Effects on Defect Stability and Mobility in Advanced Alloys

该职业奖支持开发和应用计算方法来理解金属合金中晶体缺陷行为的研究和教育活动，金属合金是由多种化学元素组成的金属材料。金属和合金中的原子以几乎完美的周期模式排列在晶体结构中，但这些结构仍然包含少量的不完美或“缺陷”，这是完美周期性的变化。在晶体结构中，许多机械和物理性能取决于在合金元素或溶质的影响下，缺陷是如何产生和移动的。例如，金属和合金的强度和延展性通常是由一种称为位错的缺陷控制的，一些溶质原子可以减缓或加速位错运动，使合金更强更脆，或更软更有延展性。该项目将重点研究基于某些过渡金属元素（如钨、钼、钛和锆）的高级合金中的缺陷。这些合金在高温下具有优异的机械性能，对许多能源、运输和航空航天应用至关重要，例如核反应堆、涡轮发动机和发电机的结构部件。为了开发这些具有增强性能的高级合金，需要了解溶质对缺陷行为的影响以及相应的力学性能变化。该项目的目标是开发和应用计算方法来预测溶质原子如何影响先进过渡金属合金中缺陷的稳定性和运动机制。传统上，精确的量子力学计算应用于研究完美晶体结构或包含简化缺陷结构的金属和合金，但实际合金中的缺陷行为取决于纳米尺度和中尺度上复杂结构的演变，长度相当于千分之一毫米。该项目旨在发现内在的、普遍的和定量的机制，这些机制基于量子力学计算的分析来确定缺陷-溶质相互作用。利用这些结果，PI将通过弥合电子、原子和中尺度水平之间的知识差距，开发模型来预测溶质对缺陷行为和机械性能的影响。该研究将为科学界和工业界提供通用模型、计算方法、软件工具和开放访问的数据存储库，以加速在大成分空间中开发新型先进合金。PI还建议通过综合研究和创新教学方法开展教育和推广活动。PI计划将虚拟现实技术应用于本科生复杂晶体和缺陷结构的教学，并利用计算材料科学的工具在研究生合金设计的教学中。建议的外展活动包括对具有不同背景的K-12学生进行晶体结构和热力学主题的教育，根据他们的兴趣和熟悉的主题，如食品加工，以提高公众对材料科学和工程的认识。PI还将参与密歇根大学工程多样性和推广中心的高中研究项目。所有基于虚拟现实和仿真工具的教育模块也将通过公共数据存储库共享。该职业奖支持一个综合研究和教育项目，开发新的计算方法来研究缺陷-溶质相互作用及其对先进过渡金属合金机械性能的影响，通过弥合跨越电子，原子和中尺度长度尺度的差距。溶质原子和晶体缺陷之间的相互作用，包括位错、孪晶界和晶界，在决定许多高级合金的机械和物理性能方面起着至关重要的作用。第一原理理论是研究这种相互作用的理想理论。然而，第一性原理计算受到随着系统尺寸增加计算强度的限制，使得很难预测溶质和杂质对涉及复杂原子结构的缺陷的稳定性和迁移性的影响，如位错扭结、孪核和晶界络合。最近，PI在几种先进过渡金属合金中发现了缺陷能量学和局部电子结构之间的一系列强相关性。这些新发现提出了一条通过理解电子水平上的化学键机制来准确预测复杂缺陷-溶质相互作用的途径。基于这种方法，PI的目标是：(i)基于化学键模型、第一性原理计算和机器学习方法，确定多种类型缺陷和溶质的局部电子/原子结构与缺陷-溶质相互作用之间的广义和定量相关性；（ii）应用上述相关性构建中尺度模拟方法和现象学模型，以预测溶质/杂质对缺陷稳定性和迁移率的影响；(3)采用上述方法和模型评价材料的固溶硬化/软化、双晶性和晶界脆化等力学行为。提出的研究旨在促进对缺陷-溶质相互作用的内在物理机制的基本理解，这对于先进过渡金属合金在不同环境条件下获得优异的机械性能至关重要。它将探索机器学习方法在基于电子和原子水平物理模型的合金设计中的应用。所研究的缺陷结构将被纳入虚拟现实工具，以增强大学生对晶格和化学缺陷及其对材料性能影响的理解；生成的数据和计算工具将应用于教育模块，以帮助研究生学习最先进的材料设计方法。这些数据和工具还将用于面向不同背景的K-12学生的外展教育和研究活动。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 CAREER award supports research and education activities in developing and applying computational methods for understanding the behavior of crystalline defects in metal alloys, which are metallic materials composed by more than one chemical element. Atoms in metals and alloys are arranged in crystal structures with almost perfect periodic patterns, but these structures still contain a small number of imperfections or "defects", variations from perfect periodicity. Many mechanical and physical properties depend on how defects are generated and move under the influences of alloying elements, or solutes, in crystal structures. For example, the strength and ductility of metals and alloys are usually controlled by a type of defect called dislocations, and some solute atoms can slow down or speed up dislocation motions to make alloys stronger and more brittle, or softer and more ductile. This project will focus on defects in advanced alloys based on certain transition-metal elements, such as tungsten, molybdenum, titanium, and zirconium. These alloys can have excellent mechanical properties at high temperatures and are critical for many energy, transport, and aerospace applications, such as structural components of nuclear reactors, turbine engines and electric generators. To develop these advanced alloys with enhanced performance would require the understanding of solute effects on defect behaviors and the corresponding variations of mechanical properties.The objective of this project is to develop and apply computational methods to predict how solute atoms affect the stability and motion mechanisms of defects in advanced transition-metal alloys. Conventionally, accurate quantum mechanical calculations are applied to study metals and alloys in perfect crystal structures or containing simplified defect structures, but defect behaviors in realistic alloys depend on the evolution of complex structures on the nanoscale and mesoscale, lengths comparable with one-thousandth of a millimeter. The PI aims to discover intrinsic, universal and quantitative mechanisms that determine defect-solute interactions based on analyses from quantum mechanical calculations. Using these results, the PI will develop the models to predict the solute effects on defect behavior and mechanical properties by bridging the knowledge gaps between electronic, atomistic and mesoscale levels. The research will provide generalized models, computational methods, software tools, and an open access data repository for both the scientific and industrial communities to speed up the development of novel advanced alloys in large compositional space. The PI also proposes educational and outreach activities by integration of research and innovative teaching methods. The PI plans to apply virtual reality techniques in teaching complex crystal and defect structures to undergraduates, and to utilize the tools of computational materials science in teaching alloy designs to graduate students. Proposed outreach activities include the education of K-12 students with a diverse background on the topics of crystal structures and thermodynamics based on their interest and familiar subjects such as food processing to increase the public awareness of materials science and engineering. The PI will also participate in the high-school research projects by the Center for Engineering Diversity and Outreach at University of Michigan. All education modules based on virtual reality and simulation tools will also be shared through the public data repository.TECHNICAL SUMMARYThis CAREER award supports an integrated research and education project to develop new computational approaches to study defect-solute interactions and their effects on the mechanical properties of advanced transition metal alloys by bridging the gaps across electronic, atomistic and mesoscale length scales. Interactions between solute atoms and crystalline defects, including dislocations, and twin and grain boundaries, play essential roles in determining the mechanical and physical properties of many advanced alloys. First-principles theory is ideal for investigating such interactions. However, first-principles calculations are limited by increasing computational intensity with system size, making it difficult to predict the solute and impurity effects on the stability and mobility of defects involving complex atomistic structures, such as dislocation kinks, twin nuclei, and grain boundary complexions.Recently, the PI discovered a series of strong correlations between defect energetics and local electronic structures in several types of advanced transition metal alloys. These new findings suggest a path to predict accurately complex defect-solute interactions by understanding chemical bonding mechanisms at the electronic level. Based on this approach, the PI aims to: (i) identify generalized and quantitative correlations between local electronic/atomistic structures and defect-solute interactions for multiple types of defects and solutes based on chemical bonding models, first-principles calculations and machine learning methods, (ii) apply the above correlations to construct mesoscale simulation methods and phenomenological models to predict the solute/impurities effects on defect stability and mobility, and (iii) employ the above methods and models to evaluate the mechanical behavior, such as solid-solution hardening/softening, twinability, and grain boundary embrittlement. The proposed research aims to advance fundamental understanding of the intrinsic physical mechanisms of defect-solute interactions that are critical for advanced transition metal alloys to achieve excellent mechanical performance under varying environmental conditions. It will explore the application of machine learning methods for alloy design based on physical models at electronic and atomistic levels. The investigated defect structures will be incorporated into the virtual reality tools to enhance the undergraduates' understanding of lattice and chemical defects and their effects on materials properties; the generated data and computational tools will be applied in education modules to help graduate students to learn the state-of-the-art materials design approaches. These data and tools will also be utilized in outreach education and research activities for K-12 students with diverse backgrounds.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.