Molecular dynamics simulations reveal enhanced interlayer bonding in graphene films through atomic vibrations during high-temperature annealing, suggesting new pathways for improving mechanical...
Due to its exceptional mechanical properties, graphene is widely used in nanotechnological applications. However, the overall mechanical performance of graphene films (GFs) is significantly limited by weak interlayer interactions, and enhancing interlayer bonding remains a key challenge. In this work, molecular dynamics simulations were employed to construct microscopic GF models and to systematically analyze the fusion behavior of graphene flakes with different contact modes as well as the corresponding mechanical enhancement mechanisms under high-temperature annealing. The results show that the fusion of flakes with different contact modes is mainly driven by pronounced out-of-plane atomic vibrations induced at high temperatures. This can be attributed to the strong in-plane covalent bonding constraints within graphene flakes and the relatively weak van der Waals forces in the out-of-plane direction. Moreover, a general melting behavior was identified in which the main body of the flakes undergoes dominant out-of-plane vibrations, while edge atoms undergo thermal diffusion. Around the critical temperature of 3150 K, a notable sp³-to-sp² hybridization transition was observed. Interestingly, this transition was found to be independent of the heating or annealing duration and was solely related to the average atomic potential energy. Further analysis indicates that this fusion mechanism enhances stress transfer efficiency, leading to an increase of over 200% in tensile strength, along with substantial improvements in penetration energy and maximum load capacity under impact loading. These findings provide valuable insights into the key factors governing interlayer strengthening during high-temperature annealing and offer a theoretical basis for the structural optimization and mechanical reinforcement of graphene-based films.
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Zheng et al. (2026) studied this question.
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