On-the-Fly Machine Learning Force Field Study of Liquid-Al/Solid-TiB₂ Interfaces

Using the on-the-fly machine learning force field, simulations were performed to study the atomic structure evolution of the liquid-Al/solid-TiB₂ interface with two different terminations, aiming to deepen the understanding of the mechanism of TiB₂ as nucleating particles in an aluminum alloy. We conducted simulations using MLFF for up to 100 ps, enabling us to observe the interfacial properties from a deeper and more comprehensive perspective. The nucleation potential of TiB₂ particles is determined by the formation of various ordered structures at the interface, which is significantly influenced by the termination of the TiB₂ (0001) surface. The evolution of the interface during heterogeneous nucleation processes with different terminations is described using structural information and dynamic characteristics. The Ti-terminated surface is more prone to forming quasi-solid regions compared to the B-termination. Analysis of mean square displacement and vibrational density of states indicates that the liquid layer at the Ti-terminated interface is closer in characteristics to a solid compared to the B-terminated interface. We also found that on the TiB₂ (0001) surface different terminations give rise to distinct ordered structures at the interfaces, which is ascribed to their different diffusion abilities.