  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.
