Structure and Evolution of Embryos to Crystals in Supercooled Metallic Liquids

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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.