Size-dependent melting of onion-like fullerenic carbons: a molecular dynamics and machine learning study

Abstract

The melting thermodynamic characteristics of 2- to 20-layered onion-like fullerenes (OLF n ) (C60@C240 to C60@···@C6000···@C24000) are comprehensively explored using first-principles-based ReaxFF atomistic simulations and random forest machine learning (RF ML). It is revealed that OLF n shows lower thermal stability than the counterparts of single-walled fullerenes (SWF n ). The melting point of SWF n increases monotonically with increasing size, whereas for OLF n , an unusual size-dependent melting point is observed; OLF n with intermediate size shows the highest melting point. For small OLF n , the melting occurs from the inner to the outer, whereas for large OLF n , it nucleates from the inner to the outer and to intermediate fullerenes. The melting and erosion behaviors of both SWF n and OLF n are mainly characterized by the nucleation of non-hexagons, nanovoids, carbon chains and emission of C2. RF ML model is developed to predict the melting points of both SWF n and OLF n . Moreover, the analysis of the feature importance reveals that the Stone-Wales transformation is a critical pathway in the melting of SWF n and OLF n . This study provides new insights and perspectives into the thermodynamics and pyrolysis chemistry of fullerenic carbons, and also may shed some lights onto the understanding of thermally-induced erosion of carbon-based resources and spacecraft materials.