Fan Zhao, Rawat Deepak, Zarzycki Piotr, Whittaker Michael L, Asta Mark
Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720.
Department of Materials Science and Engineering, University of California, Berkeley, CA 94720.
Proc Natl Acad Sci U S A. 2025 Jun 24;122(25):e2425702122. doi: 10.1073/pnas.2425702122. Epub 2025 Jun 20.
Despite over a century of studies, fundamental questions remain about the processes governing crystal nucleation from melts or solutions. Research over the past three decades has presented mounting evidence for kinetic pathways of crystal nucleation that are more complex than envisioned by the simplest forms of classical theory. Such observations have been presented for colloidal and elemental systems with covalent and metallic bonding. Despite the technological and geochemical importance of molten salts, similar studies for these ionically bonded systems are currently lacking. Here we develop a machine learning interatomic potential for a model ionic system: LiF. The potential features quantum-level accuracy for both liquid and multiple solid polymorphs over wide temperature and pressure ranges and accurately reproduces experimentally measured properties. Thanks to the efficiency of the potential, which enables microsecond-scale molecular dynamics simulations, induction times for nucleation of LiF solids from their melts are computed over a range of undercoolings. With the aid of a set of robust local order parameters established here, the simulations reveal that homogeneous crystal nucleation in undercooled melts preferentially initiates from liquid regions showing slow dynamics and high bond orientational order simultaneously, and the second-shell order of both precritical nuclei and the surface of postcritical nuclei is dominated by hexagonal close packing and body-centered cubic local structure, even though the nucleus core is dominated by face-centered cubic structure corresponding to the stable rocksalt crystal structure. Finally, we establish a connection between the crystallization pathway and the equilibrium crystal-melt interface structure.
尽管经过了一个多世纪的研究，但关于熔体或溶液中晶体成核过程的基本问题仍然存在。过去三十年的研究提供了越来越多的证据，表明晶体成核的动力学途径比最简单形式的经典理论所设想的更为复杂。这种观察结果已在具有共价键和金属键的胶体和元素体系中得到证实。尽管熔盐在技术和地球化学方面具有重要意义，但目前缺乏针对这些离子键体系的类似研究。在这里，我们为一个模型离子体系——LiF开发了一种机器学习原子间势。该势在很宽的温度和压力范围内对液体和多种固体多晶型都具有量子水平的精度，并能准确再现实验测量的性质。由于该势的高效性，能够进行微秒级的分子动力学模拟，我们计算了LiF熔体在一系列过冷度下形成固体的诱导时间。借助于此开发的一组稳健的局部有序参数，模拟结果表明，过冷熔体中的均匀晶体成核优先从同时表现出慢动力学和高键取向序的液体区域开始，并且临界前核以及临界后核表面的第二壳层序都由六方密堆积和体心立方局部结构主导，尽管核芯由对应于稳定岩盐晶体结构的面心立方结构主导。最后，我们建立了结晶途径与平衡晶体 - 熔体界面结构之间的联系。
