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Band Gap Engineering in Two-Dimensional Materials by Functionalization: Methylation of Graphene and Graphene Bilayers.

Elham MazareiChristopher PenschkePeter Saalfrank
Published in: ACS omega (2023)
Graphene is well-known for its unique combination of electrical and mechanical properties. However, its vanishing band gap limits the use of graphene in microelectronics. Covalent functionalization of graphene has been a common approach to address this critical issue and introduce a band gap. In this Article, we systematically analyze the functionalization of single-layer graphene (SLG) and bilayer graphene (BLG) with methyl (CH 3 ) using periodic density functional theory (DFT) at the PBE+D3 level of theory. We also include a comparison of methylated single-layer and bilayer graphene, as well as a discussion of different methylation options (radicalic, cationic, and anionic). For SLG, methyl coverages ranging from 1/8 to 1/1, (i.e., the fully methylated analogue of graphane) are considered. We find that up to a coverage θ of 1/2, graphene readily accepts CH 3 , with neighbor CH 3 groups preferring trans positions. Above θ = 1/2, the tendency to accept further CH 3 weakens and the lattice constant increases. The band gap behaves less regularly, but overall it increases with increasing methyl coverage. Thus, methylated graphene shows potential for developing band gap-tuned microelectronics devices and may offer further functionalization options. To guide in the interpretation of methylation experiments, vibrational signatures of various species are characterized by normal-mode analysis (NMA), their vibrational density of states (VDOS), and infrared (IR) spectra, the latter two are obtained from ab initio molecular dynamics (AIMD) in combination with a velocity-velocity autocorrelation function (VVAF) approach.
Keyphrases
  • density functional theory
  • room temperature
  • molecular dynamics
  • carbon nanotubes
  • walled carbon nanotubes
  • dna methylation
  • genome wide
  • gene expression
  • molecular dynamics simulations
  • ionic liquid
  • data analysis