Coupled simulations of low temperature microstructural evolution in nanocrystalline metals
纳米晶金属低温微观结构演化的耦合模拟
基本信息
- 批准号:1307138
- 负责人:
- 金额:$ 30万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2013
- 资助国家:美国
- 起止时间:2013-09-15 至 2017-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Technical Abstract: From the earliest days of metalworking, it has been understood that quenching freezes in the desirable attributes of the finished object. However, the advent of nanocrystalline metals has offered significant counterexamples to this generalization, with substantial grain growth occurring in days, hours, even minutes at temperatures as low as 77K. The common denominator in these instances of low temperature evolution is abnormal grain growth (AGG), where a few grains grow very large at the expense of the more slowly evolving matrix grains.As yet, low temperature microstructural evolution has not been satisfactorily explained. Grain boundary motion is widely accepted to occur by thermally activated atomic processes, so that the rate of boundary motion should decrease exponentially as temperature decreases. However, a recent computational survey of grain boundary mobilities identified three new mobility categories that permit fast motion at low temperatures. In this project, a synthetic driving force molecular dynamics method will be applied to explore and characterize these fast, cold grain boundaries to confirm whether high mobility persists to low temperature; to discover the atomic mechanisms of low temperature boundary motion; and to determine the occurrence of these boundaries in real microstructures. This atomistic study will provide the first fundamental understanding of this newly revealed grain boundary motion regime. High mobility boundaries alone are not sufficient to cause the abnormal grain growth observed in nanocrystalline metals. AGG requires the concerted motion of most or all of the boundaries surrounding the abnormal grain, and as such is fundamentally a collective process within the grain boundary network. In this project, a mesoscale model of microstructural evolution, incorporating full grain and grain boundary structure and crystallography, will be coupled with the results of atomistic simulations of grain boundary motion to explore and characterize AGG in systems containing fast, cold boundaries. Initial simulations will address which microstructural features are required for AGG. Subsequent simulations will incorporate additional factors that enhance the frequency and rate of AGG. Finally the results will be used to develop analytical models for low temperature AGG.Low temperature grain growth in nanocrystalline metals is not just an academic problem. Implementation of nanocrystalline materials requires that the microstructure remains stable during service; microstructural evolution changes, and usually degrades, the desirable properties of these materials. Understanding low temperature evolution is the key to controlling it. Non-technical Abstract: We have all seen an image of a sword maker plunging a red-hot blade into cold water to freeze in its final structure. The same principle applies to many materials that we use in our everyday lives. Metal objects from a soup spoon to a car axle are manufactured using a series of heating and cooling operations, with the final structure frozen in by cooling to room temperature. Once the material has been quenched, we expect it not to change anymore, so it is an important scientific and technological issue when it does.Nanocrystalline metals are made from familiar ingredients - such as copper, nickel, or iron - processed into tiny crystallites one-millionth the size of a grain of sand that are packed closely together to form a solid substance. Because these new materials are harder and stronger than conventional metals, they may enable lighter airplanes and more reliable cars. But there is one major problem: scientists have observed that the structure of nanocrystalline metals changes over hours, days, or years at room temperature. In this project, we investigate how the structure of nanocrystalline metals evolves at low temperatures. We first use computer simulations of atomic motion to understand how individual interfaces between certain crystallites can move even at low temperatures. We then simulate the motion of large groups of interconnected interfaces to reveal how fast-moving interfaces can change the overall structure of the material.Understanding low temperature structural evolution is the key to controlling it. The goal of this project is to use computer simulations to develop that understanding.
技术摘要:从金属加工的最早的日子起,人们就知道淬火冻结在成品所需的属性中。然而,纳米晶金属的出现为这种概括提供了重要的反例,在低至77K的温度下,大量的颗粒生长在几天、几个小时、甚至几分钟内发生。这些低温演化的共同点是异常晶粒长大(AGG),其中少数晶粒长大非常大,而牺牲了较慢演化的基质颗粒。迄今为止,低温组织演变还没有得到令人满意的解释。晶界运动被普遍认为是通过热激活的原子过程发生的,因此晶界运动的速度应该随着温度的降低而指数下降。然而,最近一项关于晶界迁移率的计算调查发现了三种新的迁移率类别,它们允许在低温下快速运动。在这个项目中,将应用合成驱动力分子动力学方法来探索和表征这些快速、寒冷的晶界,以确定高迁移率是否持续到低温,发现低温晶界运动的原子机制,并确定这些晶界在真实微观结构中的存在。这一原子论研究将提供对这一新揭示的晶界运动机制的第一个基本理解。单靠高迁移率边界不足以引起纳米金属中观察到的异常晶粒长大。AGG需要异常颗粒周围的大部分或所有边界的协同运动,因此从根本上说是晶界网络内的集体过程。在这个项目中,一个微观结构演化的中尺度模型,结合了完整的晶界和晶界结构和结晶学,将与晶界运动的原子模拟结果相结合,以探索和表征包含快速、冷边界的系统中的AgG。初始模拟将解决AGG需要哪些微结构特征。随后的模拟将纳入其他因素,以提高AGG的频率和速率。最后,这些结果将被用来开发低温AGG的分析模型。纳米晶金属中的低温晶粒生长不仅仅是一个学术问题。纳米晶材料的实现要求材料的微观结构在使用过程中保持稳定;微结构的演变会改变这些材料所需的性能,并且通常会降低这些性能。了解低温演化是控制低温的关键。非技术摘要:我们都见过这样一个画面,一个制剑人将一把烧红的刀刃放入冷水中冻结在它的最终结构中。同样的原理也适用于我们日常生活中使用的许多材料。从汤匙到车轴的金属物体是通过一系列加热和冷却操作制造出来的,最终结构通过冷却到室温来冻结。一旦材料淬火,我们预计它不会再变化,所以当它发生变化时,这是一个重要的科学和技术问题。纳米晶体金属是由熟悉的成分--如铜、镍或铁--加工成沙粒大小的微小微晶,这些微晶紧密地堆积在一起形成固体物质。由于这些新材料比传统金属更硬、更坚固,它们可能会使飞机更轻,汽车更可靠。但有一个主要问题:科学家们已经观察到,在室温下,纳米晶体金属的结构会在几小时、几天或几年内发生变化。在这个项目中,我们研究了纳米金属的结构在低温下是如何演变的。我们首先使用计算机模拟原子运动,以了解某些微晶之间的单个界面如何在低温下运动。然后,我们模拟了大量相互连接的界面的运动,以揭示快速运动的界面如何改变材料的整体结构。了解低温结构演化是控制这种变化的关键。这个项目的目标是使用计算机模拟来发展这种理解。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Contrasting thermal behaviors in Σ3 grain boundary motion in nickel
镍中 Σ3 晶界运动的热行为对比
- DOI:10.1016/j.actamat.2019.06.003
- 发表时间:2019
- 期刊:
- 影响因子:9.4
- 作者:Humberson, Jonathan;Chesser, Ian;Holm, Elizabeth A.
- 通讯作者:Holm, Elizabeth A.
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Elizabeth Holm其他文献
ANTICIPATING THE WAVE: TMS Study Examines Potential of Artificial Intelligence
- DOI:
10.1007/s11837-022-05640-2 - 发表时间:
2022-12-15 - 期刊:
- 影响因子:2.300
- 作者:
Elizabeth Holm - 通讯作者:
Elizabeth Holm
Recent advances and applications of deep learning methods in materials science
深度学习方法在材料科学中的最新进展和应用
- DOI:
10.1038/s41524-022-00734-6 - 发表时间:
2022-04-05 - 期刊:
- 影响因子:11.900
- 作者:
Kamal Choudhary;Brian DeCost;Chi Chen;Anubhav Jain;Francesca Tavazza;Ryan Cohn;Cheol Woo Park;Alok Choudhary;Ankit Agrawal;Simon J. L. Billinge;Elizabeth Holm;Shyue Ping Ong;Chris Wolverton - 通讯作者:
Chris Wolverton
Correction to: Instance Segmentation for Direct Measurements of Satellites in Metal Powders and Automated Microstructural Characterization from Image Data
- DOI:
10.1007/s11837-021-04899-1 - 发表时间:
2021-09-22 - 期刊:
- 影响因子:2.300
- 作者:
Ryan Cohn;Iver Anderson;Tim Prost;Jordan Tiarks;Emma White;Elizabeth Holm - 通讯作者:
Elizabeth Holm
Elizabeth Holm的其他文献
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{{ truncateString('Elizabeth Holm', 18)}}的其他基金
QRM: Using Visual Information to Quantify Microstructure-Processing-Property Relationships
QRM:使用视觉信息量化微观结构-加工-性能关系
- 批准号:
1826218 - 财政年份:2018
- 资助金额:
$ 30万 - 项目类别:
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CDS
- 批准号:
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Continuing Grant
Extracting Knowledge from 100 years of Microstructural Images: Using Machine Vision and Machine Learning to Address the Microstructural Big Data Challenge
从 100 年的微观结构图像中提取知识:利用机器视觉和机器学习应对微观结构大数据挑战
- 批准号:
1507830 - 财政年份:2015
- 资助金额:
$ 30万 - 项目类别:
Continuing Grant
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DMREF:具有可调谐连接的三维碳纳米管气凝胶的力学
- 批准号:
1335417 - 财政年份:2013
- 资助金额:
$ 30万 - 项目类别:
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