Graphene growth on liquid metal catalysts
Since the first experimental synthesis and characterization of graphene in 2004, this two-dimensional material (2DM) has attracted much interest owing to its remarkable structural and electronic properties such as its strength and flexibility and the exceptionally high electrical conductivity. Since then, a number of other materials such as hexagonal boron nitride, silicene and transition metal dichalcogenides have also appeared in the family of 2DMs and are currently intensively studied for their future applications in many technological areas. However, a full exploitation of these properties requires the development of effective mass production techniques. Chemical vapour deposition on (solid) metal surfaces has been established as an important and efficient synthesis method, but often the samples produced suffer from defects and impurities. Recent experimental evidence suggests that using liquid metal catalysts (LMCats) instead of solid ones bears the prospect of a continuous production of 2DMs with unprecedented quality and production speed. However, the current knowledge about the catalytic properties of LMCats is extremely poor, as they had no technological significance in the past. We study the properties of the metal catalyst both in solid and liquid form (initially focusing on Cu) and the growth of 2DMs (initially focusing on graphene) using either density functional theory or its tight binding version (density functional tight binding (DFTB)). To describe the time evolution of the liquid catalyst we perform DFTB-based molecular dynamics simulations. The calculated vibrational frequencies of the formed graphene patches can be directly compared to Raman experiments, while the structural information for the liquid metal catalyst can be directly compared to surface X-ray diffraction measurements from experimental collaborators. The obtained insights aid our understanding of the differences between solid and liquid catalysts and the mechanistic aspects of the growth process, which can be used to guide experiments.
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