Computational Study of Gas Interactions with Doped Graphene nanosheets

This abstract describes a computational study on graphene-based gas sensors. Using Density Functional Theory (DFT) calculations at the ωB97X-D3/def2-SVP level, via ORCA 6.0, ChemBOS, and Multiwfn, the authors investigated the interactions of NH₃ and NO₂ molecules with pure and group 13 (B, Al, Ga) doped graphene nanosheets of varying sizes.

Results indicate that boron doping (B@Gn) promotes the strongest NH₃ adsorption, showing higher overlap density, superior binding energy (-149.65 kJ/mol), and greater bond critical point density compared to aluminum. While the adsorption of the electron donor (NH₃) strongly depends on the dopant identity, the electron withdrawer (NO₂) displays uniform behavior across the systems. Notably, the group's newly developed OP/TOP model proved more sensitive to structural variations in the doped graphene sheets than the QTAIM methodology.