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We have studied theoretically, using density functional theory, several material properties when going from one C layer in graphene to two and three graphene layers and on to graphite. The properties we have focused on are the elastic constants, electronic structure (energy bands and density of states), and the dielectric properties. For any of the properties we have investigated the modification due to an increase in the number of graphene layers is within a few per cent. Our results are in agreement with the analysis presented recently by Kopelevich and Esquinazi (unpublished).

The formation of ultra-shallow junctions (USJs) for future integrated circuit technologies requires preamorphization and high dose boron doping to achieve high activation levels and abrupt profiles. To achieve the challenging targets set out in the semiconductor roadmap, it is crucial to reach a much better understanding of the basic physical processes taking place during USJ processing. In this paper we review current understanding of dopant-defect interactions during thermal processing of device structures – interactions which are at the heart of the dopant diffusion and activation anomalies seen in USJs. First, we recall the formation and thermal evolution of End of Range (EOR) defects upon annealing of preamorphized implants (PAI). It is shown that various types of extended defect can be formed: clusters, {113} defects and dislocation loops. During annealing, these defects exchange Si interstitial atoms and evolve following an Ostwald ripening mechanism. We review progress in developing models based on these concepts, which can accurately predict EOR defect evolution and interstitial transport between the defect layer and the surface. Based on this physically based defect modelling approach, combined with fully coupled multi-stream modelling of dopant diffusion, one can perform highly predictive simulations of boron diffusion and de/re-activation in Ge-PAI boron USJs. Agreement between simulations and experimental data is found over a wide range of experimental conditions, clearly indicating that the driving mechanism that degrades boron junction depth and activation is the dissolution of the interstitial defect band. Finally, we briefly outline some promising methods, such as co-implants and/or vacancy engineering, for further down-scaling of source-drain resistance and junction depth.

A physically motivated model that accounts for the spatial and temporal evolution of self-interstitial agglomerates in ion-implanted Si is presented. For the calibration of the model, a genetic algorithm is used to find the optimum set of physical parameters from experimental data. Mean-size evolution of {113} defects obtained by transmission electron microscopy and self-interstitial oversaturation results measured in the vicinity of extended defects are combined in the same fitting procedure. The calibration of parameters shows that binding energies of small self-interstitial clusters exhibit strong maxima, as reported in other investigations. Results of the calibrated model are compared to experimental data obtained in complementary investigations. It is demonstrated that the model is able to predict a wide variety of physical phenomena, from the oversaturation of self-interstitials via the mean-size evolution of {113} defects to the depth distribution of the density of the latter

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