Surface effects in graphite intercalation compounds

Abstract

The theoretical description of the band structure of these compounds has drastically changed during the last ten years [1–5]. The so called ONK description [1] first proposed the picture of a nearly rigid band structure, with the s band of the alkali atom partially filled. One of the main points was to calculate the charge transfer of the alkali atom (≈0.6 according to ONK calculations). Subsequently, Posternak et al. published a calculation exhibiting a completely new graphite band, the interlayer band [2]. They suggested that this level, located at 4 eV above the Fermi level in graphite, could play an important role in the intercalation mechanism and should be taken into account in the GIC band structure calculations. Later, this was clearly established for example by the calculations of Holzwarth et al. for LiC6 [3]. At the same time, a new calculation for the band structure of KC8 and CsC8 was presented by R.C. Tatar and S. Rabii (TR) [4], showing complete charge transfer from the alkali atoms, the corresponding s level lying respectively 1.5 and 3.4 eV above the Fermi level. Moreover, according to TR the Fermi surface presents a pocket in the center of the Brillouin Zone (BZ) which relates only to the π bands and not to the alkali metal. Recently, H. Kamimura has given a new interpretation of ONK calculations [5], according to which the alkali atom also yields a unit charge transfer. Following this interpretation, the Fermi pocket at the BZ center should be related mainly to the interlayer band. Now, both the revised ONK (rONK) and the TR descriptions agree on the full ionization of the alkali atoms, and on the graphitic origin of the central Fermi pocket. The main difference between these descriptions relies on the location of the corresponding states in real space: they are located on the graphite layers for TR and between them for rONK.KeywordsFermi SurfaceAuger Electron SpectroscopyAuger SpectrumSharp FeatureAlkali AtomThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.