Mechanisms for Graphene Growth on SiO 2 Using Plasma-Enhanced Chemical Vapor Deposition: A Density Functional Theory Study.
Roberto C LongoHirokazu UedaKyeongjae ChoAlok RanjanPeter L G VentzekPublished in: ACS applied materials & interfaces (2022)
Plasma-enhanced chemical vapor deposition (PE-CVD) of graphene layers on dielectric substrates is one of the most important processes for the incorporation of graphene in semiconductor devices. Graphene is moving rapidly from the laboratory to practical implementation; therefore, devices may take advantage of the unique properties of such nanomaterial. Conventional approaches rely on pattern transfers after growing graphene on transition metals, which can cause nonuniformities, poor adherence, or other defects. Direct growth of graphene layers on the substrates of interest, mostly dielectrics, is the most logical approach, although it is not free from challenges and obstacles such as obtaining a specific yield of graphene layers with desired properties or accurate control of the growing number of layers. In this work, we use density-functional theory (DFT) coupled with ab initio molecular dynamics (AIMD) to investigate the initial stages of graphene growth on silicon oxide. We select C 2 H 2 as the PE-CVD precursor due to its large carbon contribution. On the basis of our simulation results for various surface models and precursor doses, we accurately describe the early stages of graphene growth, from the formation of carbon dimer rows to the critical length required to undergo dynamical folding that results in the formation of low-order polygonal shapes. The differences in bonding with the functionalization of the silicon oxide also mark the nature of the growing carbon layers as well as shed light of potential flaws in the adherence to the substrate. Finally, our dynamical matrix calculations and the obtained infrared (IR) spectra and vibrational characteristics provide accurate recipes to trace experimentally the growth mechanisms described and the corresponding identification of possible stacking faults or defects in the emerging graphene layers.