GOALI: Understanding Nucleation and Growth of Solute Clusters and GP Zones to Facilitate Industrial Fabrication of High-Strength Al Alloys

目标：了解溶质团簇和 GP 区的成核和生长，以促进高强度铝合金的工业制造

• 批准号: 1905421
• 负责人: Liang Qi
• 金额: $ 50万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1905421&HistoricalAwards=false
• 关键词: GOALI; Understanding; Nucleation; Growth; Solute

Non-technical Summary:This project will study the nucleation of precipitates in high-strength aluminum (Al) alloys to facilitate their application in the automobile industry. Alloying elements called 'solutes' in metallic materials can exist in different forms, or phases. The solutes are in solid solution phases if they are randomly distributed in alloys as individual atoms; they can also be in certain small particles or 'precipitate' phases if some solutes agglomerate together to form specific structures through typical nucleation and growth progresses. Mechanical properties of alloys depend on the phases of solutes. Generally, alloys in solid solution phases are soft and ductile, convenient for low-cost mechanical forming and fabrication; but alloys with certain precipitate phases can be much harder and, therefore, difficult for mechanical forming compared with their counterparts in solid solution phases, so they are usually achieved in alloy components at final product stages. 7000 series aluminum alloys with zinc (Zn) and magnesium (Mg) as the major alloying elements have a high strength-to-weight ratio after proper precipitation hardening (similar strength but half of the weight compared with conventional steel). Their widespread implementation in the automotive industry as structural components can achieve vehicles with lightweight and high fuel efficiency. However, the solute solution phases in these alloys can quickly (~30 minutes) transform into precipitate phases to harden the alloys even at room temperature, making significant challenges of their low-cost forming and fabrication using current automobile manufacturing techniques. This University of Michigan-General Motors collaborative GOALI project aims to apply an integrated computational, experimental and statistical approach to understand and control the early stages of solid-solution-to-precipitate transformation kinetics of 7000 series aluminum alloys. The key objective is to design new alloy chemistries to retard the nucleation and growth of early-stage precipitate phases at room temperatures. These early-stage precipitates are mainly solute clusters and Guinier-Preston (GP) zones, both of which are made of a small number (less than 1000) of solute atoms agglomerated together. Then these alloys can stay in soft solid-solution phases for a longer time, convenient for conventional automobile manufacturing techniques. In addition, the new alloy chemistries should not impede the final precipitation hardening at a higher temperature. The proposed research will potentially enable implementation of 7000 series aluminum alloys in the automobile industry, contributing to vehicle light-weighting and favorably impacting energy savings, sustainability, and competitiveness. The generated computational-experimental-statistical framework and new knowledge will be applicable to alloy design in general and thus accelerate material development for meeting future needs. The proposed teaching and training elements will enable an integrated-computational-materials-engineering (ICME) approach to be widely imparted to senior undergraduate and graduate students in materials major and champion outreach/education activities of K-12 students as well as opportunities for students of underrepresented groups to be engaged in start-of-the-art materials research.Technical Summary: Nucleation and growth theories of precipitates in solids are key fundamental principles to guide the development and application of advanced age-hardenable structural alloys. However, the conventional theories fail to provide quantitative guidance for the development and processing of multicomponent commercial alloys, where nucleation and growth of precipitates can occur in multiple steps with substantial structural-composition transformations under the influence of defects. This gap between theory and practice limits the industrial applications of many commercial alloys that require special fabrication and manufacturing processes. For example, high-strength Al-Zn-Mg-based 7000 series alloys have severe formability limitations if stamped more than ~30 minutes after the solutionizing treatment. These limitations result from fast precipitate kinetics at room temperature ('natural aging'), mainly the nucleation and growth of solute clusters and Guinier-Preston (GP) zones that can act as nuclei for subsequent precipitates. Understanding and controlling these nucleation and growth processes can slow down natural aging, and thereby expand the room temperature forming window amenable to the sustainable manufacturing of 7000 series Al alloys and other lightweight high-strength materials in the automobile industry, which has a significant impact on vehicle mass reduction.In this industry-university collaborative GOALI project, the applicants plan to apply an integrated theoretical, computational, experimental and machine learning approach to understand and control the nucleation and growth kinetics of solute clusters and GP zones in Al-Zn-Mg-based alloys. A multi-scale simulation framework based on first-principles calculations, atomistic simulations, and phenomenological hardening model will be constructed to quantitatively describe the solute clusters and GP zone kinetics and their effects on hardness increments. Alloys with the proposed solutes will be synthesized and subjected to thermal processing and indentation hardness tests to verify their natural aging kinetics. A combination of high-resolution transmission electron microscopy, electron energy loss spectroscopy and computer image simulations will be used to characterize the solute clusters and fine precipitates to verify the nucleation and growth mechanisms. A statistical machine learning surrogate model will be constructed to speed up the search of alloy chemistries to retard natural aging with further experimental confirmations. In this project, the research team proposes a transformative alloy design concept to tune the early-stage precipitation kinetics of complex commercial alloys by searching the trace solute elements to control the structures and compositions of solid clusters and GP zones beyond the role of individual atoms of trace solute elements. The research team also proposes an efficient routine to design advanced alloys with a large parameter space by applying the integrated computational, experimental and statistical machine learning methods. Quantitative understanding of precipitate nucleation and growth kinetics in 7000 series Al alloys using the newly developing computational and experimental tools will facilitate the development of advanced nucleation and growth theories for generalized multicomponent alloy systems.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.

非技术摘要：该项目将研究高强度铝（AL）合金中沉淀物的成核，以促进其在汽车行业中的应用。金属材料中称为“溶质”的合金元素可以以不同的形式或相处存在。如果溶质作为单个原子在合金中随机分布在合金中，则溶质在固体溶液中；如果某些溶液聚集在一起以通过典型的成核和生长进展形成特定的结构，它们也可以在某些小颗粒中或“沉淀”相。合金的机械性能取决于溶质的相。通常，实心溶液阶段的合金柔软且延展性，方便低成本机械形成和制造；但是，具有一定沉淀相的合金可能要困难得多，因此，与实心溶液阶段相比，机械形成很难，因此通常在最终产品阶段的合金组件中实现它们。 具有锌（Zn）和镁（mg）的7000系列铝合金作为主要合金元素在适当的沉淀硬化后具有高强度重量比（相似的强度，但与常规钢相比，重量的一半）。由于结构性组件可以实现轻巧且燃油效率高的车辆，因此它们在汽车行业中的广泛实施。但是，这些合金中的溶液溶液阶段可以快速（〜30分钟）转变为降水阶段，即使在室温下也可以硬化合金，从而使用当前汽车制造技术对其低成本形成和制造面临重大挑战。密歇根大学的这项合作守门员项目旨在采用综合计算，实验和统计方法来理解和控制7000系列铝合金的固定溶液到过度转化动力学的早期阶段。关键目的是设计新的合金化学成分，以延迟室温下早期沉淀期的成核和生长。这些早期沉淀物主要是溶质簇和吉尼尔 - 普雷斯顿（GP）区域，这两种区域都是由少量（小于1000）的溶质原子组成的。然后，这些合金可以在柔软的固体阶段保持更长的时间，方便用于常规汽车制造技术。此外，新的合金化学物质不应阻止更高温度下的最终沉淀硬化。拟议的研究将有可能在汽车行业实施7000系列铝合金，从而有助于车辆的轻度加权，并有利地影响节能，可持续性和竞争力。生成的计算实验性统计框架和新知识通常适用于合金设计，因此可以加速材料开发以满足未来需求。拟议的教学和培训元素将使综合机构 - 材料工程（ICME）的方法能够广泛地授予材料专业的高级本科生和研究生K-12学生的活动，并为学生提供了机会代理材料研究的代表性不足的群体。技术摘要：固体中沉淀物的成核和生长理论是指导高级年龄可添加可添加的结构合金的开发和应用的关键基本原则。但是，常规理论未能为多组分商业合金的开发和处理提供定量指导，在这种情况下，沉淀物的成核和生长可以在多个步骤中发生，并在缺陷的影响下具有实质性的结构性组成转换。理论与实践之间的差距限制了许多需要特殊制造和制造工艺的商业合金的工业应用。例如，如果在解决方案处理后超过30分钟，则基于高强度的Al-Zn-mg 7000系列合金具有严重的可表明性限制。这些局限性是由室温下的快速沉淀动力学引起的，主要是溶质簇的成核和生长，以及吉尼利 - 普雷斯顿（GP）区域，可以充当后续沉淀物的核。理解和控制这些成核和增长过程可以减慢自然老化，从而扩大室温形成窗口，适合于汽车行业的7000系列Al Alloys和其他轻质高强度材料的可持续制造，这对这有重大影响，这对申请人计划采用综合的理论，计算，实验和机器学习方法，以了解和控制Al-Zn-MG中溶质群和GP区域的成核和生长动力学，以采用综合的理论，计算，实验性和机器学习方法，以减少车辆质量。基于合金。将构建基于第一原理计算，原子模拟和现象学硬化模型的多尺度模拟框架，以定量描述溶质簇和GP区动力学及其对硬度增量的影响。具有所提出溶质的合金将合成并进行热处理和压痕硬度测试，以验证其自然衰老动力学。高分辨率透射电子显微镜，电子能量损耗光谱和计算机图像模拟的组合将用于表征溶质簇和细沉淀物以验证成核和生长机制。将构建一个统计机器学习替代模型，以加快合金化学的搜索以通过进一步的实验确认来延迟自然衰老。在该项目中，研究团队提出了一个变革性的合金设计概念，通过搜索痕量溶质元素来控制固体簇和GP区域的结构和组成，超越各个原子的作用，以调整复杂商业合金的早期降水动力学。跟踪溶质元素。研究团队还提出了一个有效的例程，通过应用集成的计算，实验和统计机器学习方法来设计具有较大参数空间的高级合金。 使用新开发的计算和实验工具的7000系列合金中沉淀成核和生长动力学的定量理解将有助于开发高级成核和生长理论，用于广义多组分合金系统。这奖反映了NSF的法定任务，并被认为值得支持的支持值得支持。通过使用基金会的智力优点和更广泛影响的评论标准进行评估。

项目成果

Mechanism of local lattice distortion effects on vacancy migration barriers in fcc alloys

面心立方合金中局部晶格畸变对空位迁移势垒的影响机制

• DOI: 10.1103/physrevmaterials.6.073601
• 发表时间: 2022
• 期刊: Physical Review Materials
• 影响因子: 3.4
• 作者: Xi, Zhucong;Zhang, Mingfei;Hector, Louis G.;Misra, Amit;Qi, Liang
• 通讯作者: Qi, Liang

In situ transmission electron microscopy investigation of nucleation of GP zones under natural aging in Al-Zn-Mg alloy

• DOI: 10.1016/j.scriptamat.2021.114319
• 发表时间: 2021-10-07
• 期刊: SCRIPTA MATERIALIA
• 影响因子: 6
• 作者: Chatterjee, Arya;Qi, Liang;Misra, Amit
• 通讯作者: Misra, Amit