Microscopic origin of polytype-dependent melting in SiC revealed by machine-learning molecular dynamics

Predicting how crystal structure influences high-temperature stability remains a key challenge in materials modeling and design. Silicon carbide (SiC), one of the most thermally and chemically stable materials known, provides an ideal system for studying this problem because its many polytypes preserve similar local tetrahedral bonding while differing in long-range stacking geometry. To determine the impact of polytype structure on the high-temperature stability of SiC, we combine phase-coexistence machine-learning molecular dynamics with finite-temperature phonon analysis, enabled by a fine-tuned MACE interatomic potential that accurately describes crystalline, high-temperature, and disordered configurations across multiple SiC polytypes. We identify a clear stability ordering, 3C > 2H > 9R, reflected consistently in structural disordering, interlayer sliding, and finite-temperature phonon spectra. Across all polytypes, melting initiates through the formation of short C-C contacts and carbon-rich local regions, followed by a progressive loss of tetrahedral Si-C connectivity. The reduced stability of the long-period 9R polytype is associated with a denser manifold of low-frequency transverse-acoustic modes arising from its stacking periodicity and associated zone folding, which broaden and soften further at high temperature. These modes can provide additional low-energy channels for thermally activated lateral bilayer motion, consistent with the larger sliding amplitudes observed in 9R and their positive correlation with local structural disorder.