Hidden One-Electron Interactions in Carbon Nanotubes Revealed in Graphene Nanostrips

Abstract

Many single-wall carbon nanotube (SWNT) properties near the Fermi level were successfully predicted using a nearest-neighbor tight-binding model characterized by a single parameter, V1. We show however that this model fails for armchair-edge graphene nanostrips due to interactions directly across hexagons. These same interactions are found largely hidden in the description of SWNTs, where they renormalize V1 leaving previous nearest-neighbor model SWNT results largely intact while resolving a long-standing puzzle regarding the magnitude of V1.

Gate Electrostatics and Quantum Capacitance of Graphene Nanoribbons

“…Figure 1b neighbor tight-binding model. 15 The quantum capacitance curve of a metallic or a semiconducting A-GNR, as shown in Fig.1c, has the same qualitative shape as the DOS of the A-GNR, or its corresponding zigzag CNT, with the Van Hove singularities of the DOS broadened by the thermal energy. An important difference, however, exists between an A-GNR and its corresponding zigzag CNT.…”

Zigzag-Shaped Superlattices on the Basis of Graphene Nanoribbons: Structure and Electronic Properties

“…In the first case, one can observe the regular oscillations that slowly abate with the increase in 1 w . One should note that it is slower than the abating 1/w known for graphene nanoribbons, where w is ribbon width [24,27]. The maximal series is clearly distinguished and manifests the following dependence on index …”

“…The nearest neighbors were taken into account up to the third order. Hopping integrals were selected as in [24] 2 presents the typical band spectra obtained by calculations. As one can see from the figure, some of the structures are metallic or almost metallic.…”

Tight-binding description of the quasiparticle dispersion of graphite and few-layer graphene

“…It has already been shown in Ref. 26 that these very interactions have considerable magnitude in graphene and must also be considered to reproduce first-principles data in graphene nanoribbons.…”