Structure and Evolution of Embryos to Crystals in Supercooled Metallic Liquids

【非技术摘要】生产金属和其他材料最常见的方法之一是首先将所需元素制成液体混合物，然后将液体冷却，直到其冻结成固体。从液体开始是有帮助的，因为它使元素易于混合，并且只需将液体倒入合适形状的容器中，就可以制成合适形状的固体。了解原子如何在液体中运动，它们如何结合在一起形成固体，以及为什么它们形成一种固体而不是另一种固体，是材料科学和工程中的一个重要问题。在这个过程的最初阶段，当固体只有几十个原子时，特别难以研究。最近对非金属材料的研究表明，教科书中关于冻结早期阶段的模型是可以改进的。这个项目测试是否需要对金属的冷冻进行类似的更新。它使用一束纳米直径的电子束来探测原子团的排列，并使用世界上最快的电子相机之一来跟踪原子冻结时的运动。该项目的参与者正在开发跟踪原子的新方法，并使用人工智能来分析项目产生的tb大小的数据集。该项目旨在推进将金属液体转化为固体的基础科学，这可能有利于美国的金属制造业。它还训练学生掌握最先进的材料科学方法，并通过使用强大的电子显微镜对原子进行实时成像，向公众介绍科学的兴奋之处。【技术摘要】非经典成核已被广泛应用于多种体系，包括矿物在水溶液中的生长、蛋白质晶体的生长以及由蒸汽前体形成的金属晶体的生长。本项目研究类似成分的金属液体在金属晶体成核过程中可能的非经典行为。该方法使用世界上最快的电子相机之一的时间分辨相干电子纳米衍射。实验描述了晶体胚胎在成核和生长过程中的结构演变，以及其他不成核的竞争性液体结构，以及液体状态下空间非均质动力学对成核动力学的影响。机器学习和计算机视觉的方法被用于在大型纳米衍射数据集中发现结构相关的模式。该项目旨在加强对金属熔体非经典成核的理解，对包括铸造在内的金属制造有潜在的影响。参与该项目的学生将接受电子显微镜结构表征的先进方法和应用于材料表征的数据科学的培训。该项目还通过在威斯康星大学麦迪逊工程博览会等公共推广活动中进行原子分辨率电子显微镜的现场演示，为公众带来了看到原子的兴奋，原子是物质的基本组成部分。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。

NON-TECHNICAL ABSTRACTOne of the most common ways metals and other materials are produced is to first create a liquid mixture of the desired elements, then cool the liquid until it freezes into a solid. Starting with a liquid is helpful because it makes elements easy to mix, and the solid can be made the right shape just by pouring the liquid into the right shape container. Understanding how atoms move around in liquids, how they snap together to form a solid, and why they form one kind of solid and not another is a significant problem in materials science and engineering. The very earliest stages of the process, when the solid involves only a few tens of atoms, is particularly hard to study.Recent research on non-metallic materials has shown that textbook models of the earliest stages of freezing can be improved. This project tests whether a similar update is needed for freezing of metals. It uses a nanometer-diameter beam of electrons to probe the arrangements of small groups of atoms and one of the world’s fastest electron cameras to track the atom’s motions as they freeze. Participants in this project are developing new ways to track atoms and are using artificial intelligence to analyze the terabyte-sized data sets produced by the project.This project seeks to advance the fundamental science of transforming metallic liquids into solids, which could benefit metals manufacturing in the US. It also trains students in state-of-the-art methods in materials science and introduces the general public to the excitement of science through live imaging of atoms using powerful electron microscopes.TECHNICAL ABSTRACTNon-classical nucleation is well-established for a variety of systems, including growth of minerals in aqueous solution, growth of protein crystals, and the growth of metal crystals from vapor precursors. This project studies possible non-classical behavior in the nucleation of metal crystals from metallic liquids of similar composition. The approach uses time-resolved coherent electron nanodiffraction with one of the world’s fastest electron cameras. The experiments characterize the structural evolution of crystal embryos through nucleation and growth, other competing liquid structures which do not nucleate crystals, and the influence of spatially heterogeneous dynamics in the liquid state on nucleation kinetics. Approaches from machine learning and computer vision are used to find structurally-relevant patterns in the large nanodiffraction data sets.This project seeks to enhance the understanding of non-classical nucleation from metallic melts, with potential impact on metals manufacturing including casting. Students involved in the project are trained in advanced methods in structural characterization by electron microscopy and in data science applied to materials characterization. The project also brings the excitement of seeing atoms, the basic building blocks of matter, to the general public via live demonstrations of atomic-resolution electron microscopy during public outreach events like the University of Wisconsin-Madison Engineering Expo.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.