Numerical study of graphene as a channel material for field-effect transistors

Graphene excellent properties make it a promising candidate for building future nanoelectronic devices. Nevertheless, the absence of an energy gap is an open problem for the transistor application. In this thesis, graphene nanoribbons and pattern-hydrogenated graphene, two alternatives for inducing an energy gap in graphene, are investigated by means of numerical simulations. A tight-binding NEGF code is developed for the simulation of GNR-FETs. To speed up the simulations, the non-parabolic effective mass model and the mode-space tight-binding method are developed. The code is used for simulation studies of both conventional and tunneling FETs. The simulations show the great potential of conventional narrow GNR-FETs, but highlight at the same time the leakage problems in the off-state due to various tunneling mechanisms. The leakage problems become more severe as the width of the devices is made larger, and thus the band gap smaller, resulting in a poor on/off current ratio. The tunneling FET architecture can partially solve these problems thanks to the improved subthreshold slope; however, it is also shown that edge roughness, unless well controlled, can have a detrimental effect in the off-state performance. In the second part of this thesis, pattern-hydrogenated graphene is simulated by means of a tight-binding model. A realistic model for patterned hydrogenation, including disorder, is developed. The model is validated by direct comparison of the momentum-energy resolved density of states with the experimental angle-resolved photoemission spectroscopy. The scaling of the energy gap and the localization length on the parameters defining the pattern geometry is also presented. The results suggest that a substantial transport gap can be attainable with experimentally achievable hydrogen concentration.

The coupling between electron transfer and Protein/Solvent Dynamics in Photosynthetic Reaction Centers: Spectroscopic Studies in Amorphous Matrices

We investigated at the molecular level protein/solvent interactions and their relevance in protein function through the use of amorphous matrices at room temperature. As a model protein, we used the bacterial photosynthetic reaction center (RC) of Rhodobacter sphaeroides, a pigment protein complex which catalyzes the light-induced charge separation initiating the conversion of solar into chemical energy. The thermal fluctuations of the RC and its dielectric conformational relaxation following photoexcitation have been probed by analyzing the recombination kinetics of the primary charge-separated (P+QA-) state, using time resolved optical and EPR spectroscopies. We have shown that the RC dynamics coupled to this electron transfer process can be progressively inhibited at room temperature by decreasing the water content of RC films or of RC-trehalose glassy matrices. Extensive dehydration of the amorphous matrices inhibits RC relaxation and interconversion among conformational substates to an extent comparable to that attained at cryogenic temperatures in water-glycerol samples. An isopiestic method has been developed to finely tune the hydration level of the system. We have combined FTIR spectral analysis of the combination and association bands of residual water with differential light-minus-dark FTIR and high-field EPR spectroscopy to gain information on thermodynamics of water sorption, and on structure/dynamics of the residual water molecules, of protein residues and of RC cofactors. The following main conclusions were reached: (i) the RC dynamics is slaved to that of the hydration shell; (ii) in dehydrated trehalose glasses inhibition of protein dynamics is most likely mediated by residual water molecules simultaneously bound to protein residues and sugar molecules at the protein-matrix interface; (iii) the local environment of cofactors is not involved in the conformational dynamics which stabilizes the P+QA-; (iv) this conformational relaxation appears to be rather delocalized over several aminoacidic residues as well as water molecules weakly hydrogen-bonded to the RC.

Hydrodynamical simulations of galaxy clusters in dark energy cosmologies

In this work we investigate the influence of dark energy on structure formation, within five different cosmological models, namely a concordance $\Lambda$CDM model, two models with dynamical dark energy, viewed as a quintessence scalar field (using a RP and a SUGRA potential form) and two extended quintessence models (EQp and EQn) where the quintessence scalar field interacts non-minimally with gravity (scalar-tensor theories). We adopted for all models the normalization of the matter power spectrum $\sigma_{8}$ to match the CMB data. For each model, we perform hydrodynamical simulations in a cosmological box of $(300 \ {\rm{Mpc}} \ h^{-1})^{3}$ including baryons and allowing for cooling and star formation. We find that, in models with dynamical dark energy, the evolving cosmological background leads to different star formation rates and different formation histories of galaxy clusters, but the baryon physics is not affected in a relevant way. We investigate several proxies for the cluster mass function based on X-ray observables like temperature, luminosity, $M_{gas}$, and $Y_{X}$. We confirm that the overall baryon fraction is almost independent of the dark energy models within few percentage points. The same is true for the gas fraction. This evidence reinforces the use of galaxy clusters as cosmological probe of the matter and energy content of the Universe. We also study the $c-M$ relation in the different cosmological scenarios, using both dark matter only and hydrodynamical simulations. We find that the normalization of the $c-M$ relation is directly linked to $\sigma_{8}$ and the evolution of the density perturbations for $\Lambda$CDM, RP and SUGRA, while for EQp and EQn it depends also on the evolution of the linear density contrast. These differences in the $c-M$ relation provide another way to use galaxy clusters to constrain the underlying cosmology.

On the Luminous and Dark Matter Distribution in Early-Type Galaxies

The way mass is distributed in galaxies plays a major role in shaping their evolution across cosmic time. The galaxy's total mass is usually determined by tracing the motion of stars in its potential, which can be probed observationally by measuring stellar spectra at different distances from the galactic centre, whose kinematics is used to constrain dynamical models. A class of such models, commonly used to accurately determine the distribution of luminous and dark matter in galaxies, is that of equilibrium models. In this Thesis, a novel approach to the design of equilibrium dynamical models, in which the distribution function is an analytic function of the action integrals, is presented. Axisymmetric and rotating models are used to explain observations of a sample of nearby early-type galaxies in the Calar Alto Legacy Integral Field Area survey. Photometric and spectroscopic data for round and flattened galaxies are well fitted by the models, which are then used to get the galaxies' total mass distribution and orbital anisotropy. The time evolution of massive early-type galaxies is also investigated with numerical models. Their structural properties (mass, size, velocity dispersion) are observed to evolve, on average, with redshift. In particular, they appear to be significantly more compact at higher redshift, at fixed stellar mass, so it is interesting to investigate what drives such evolution. This Thesis focuses on the role played by dark-matter haloes: their mass-size and mass-velocity dispersion correlations evolve similarly to the analogous correlations of ellipticals; at fixed halo mass, the haloes are more compact at higher redshift, similarly to massive galaxies; a simple model, in which all the galaxy's size and velocity-dispersion evolution is due to the cosmological evolution of the underlying halo population, reproduces the observed size and velocity-dispersion of massive compact early-type galaxies up to redshift of about 2.