We report on a numerical study of electronic transport in chemically doped 2D graphene materials. By using ab initio calculations, a self-consistent scattering potential is derived for boron and nitrogen substitutions, and a fully quantum-mechanical Kubo-Greenwood approach is used to evaluate the resulting charge mobilities and conductivities of systems with impurity concentration ranging within [0.5, 4.0]%. Even for a doping concentration as large as 4.0%, the conduction is marginally affected by quantum interference effects, preserving therefore remarkable transport properties, even down to the zero temperature limit. As a result of the chemical doping, electron-hole mobilities and conductivities are shown to become asymmetric with respect to the Dirac point.
The electronic structure of Ge nanocrystals is studied using a sp3 tight binding description. Analytical laws for the confinement energies, valid over the whole range of sizes, are derived. We validate our results with ab initio calculations in the local density approximation for smaller clusters. Comparing to experimental data, we conclude that, similar to the case of silicon: (a) the blue-green photoluminescence (PL) of Ge nanocrystals comes from defects in the oxide and (b) the size dependent PL in the near infrared probably involves a deep trap in the gap of the nanocrystals. We predict that the radiative lifetimes remain long in spite of the small difference (0.14 eV) between direct and indirect gaps of bulk Ge.
Calculations of the electronic states of donor and acceptor impurities in nanowires show that the ionization energy of the impurities is strongly enhanced with respect to the bulk, above all when the wires are embedded in a material with a low dielectric constant. In free-standing nanowires with diameter below 10 nm, the ionization of the impurities at 300 K is strongly reduced and heavy doping is necessary to obtain conductive systems. These results imply that the critical density for metal-nonmetal transitions is not the same as in the bulk. Experiments are proposed to test the predictions.
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