The process of crystallization is often understood in terms of the fundamental microstructural elements of the crystallite being formed, such as surface orientation or the presence of defects. Considerably less is known about the role of the liquid structure on the kinetics of crystal growth. Here atomistic simulations and machine learning methods are employed together to demonstrate that the liquid adjacent to solid-liquid interfaces presents significant structural ordering, which effectively reduces the mobility of atoms and slows down the crystallization kinetics. Through detailed studies of silicon and copper we discover that the extent to which liquid mobility is affected by interface-induced ordering (IIO) varies greatly with the degree of ordering and nature of the adjacent interface. Physical mechanisms behind the IIO anisotropy are explained and it is demonstrated that incorporation of this effect on a physically-motivated crystal growth model enables the quantitative prediction of the growth rate temperature dependence.

通常根据形成的微晶的基本微观结构元素（例如表面取向或缺陷的存在）来理解结晶过程。关于液体结构对晶体生长动力学的作用了解的很少。在这里，原子模拟和机器学习方法一起使用，以证明与固液界面相邻的液体呈现出显着的结构有序性，从而有效地降低了原子的迁移率并减慢了结晶动力学。通过对硅和铜的详细研究，我们发现界面诱导的有序化（IIO）对液体迁移率的影响程度随有序化程度和相邻界面的性质而有很大不同。