Thermal stability of monolayer fullerene networks: A molecular dynamics study with machine-learning potential

Computational Materials Science. 2025. Vol. 248. Article 113572.

Alekseev D., Logunov M., Lazarev M., Zhukov S., Orekhov N.

Two-dimensional C60 carbon allotropes have gained much attention since their first synthesis in 2022, but many of their thermophysical and mechanical properties remain unreported in the literature. In this article, we performed a high-temperature molecular dynamics study of quasi-hexagonal (qHP) and quasi-tetragonal (qTP) C60 phases using the modern machine-learning interatomic potential GAP-20. We show that, contrary to previous calculations, at T
 K, both phases are unstable and decompose into individual C60 molecules. A low bending modulus indicates the possibility of nanoripple excitation at high temperatures, similar to those in graphene. We also demonstrate the crucial role of interatomic potential verification for MD analysis of previously unexplored carbon allotropes.

Keywords: thermal stability, carbon, machine-learning methods, Fullerene