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GaInAsP and GaInAs epitaxial layers grown on Fe-doped InP substrates of {100} orientation have been studied using cross-sectional and plan-view transmission electron microscopy. Studies of the epilayer surface regions of LPE Ga[0.03]In[0.97] As[0.07]P[0.93] heavily doped with Mn or Mn and Ge have revealed at least seven precipitate types when classification is made according to precipitate morphology, configurations and associated strain fields. The origin of some of these second phase particles is shown to be iron-phosphide precipitation resulting from iron diffusion from the substrate. Furthermore, in a LPE Ga[0.47]In[0.53]As layer co-doped with Mn and Ge four distinct precipitate types were observed. Speckle and long wavelength microstructures in GalnAs grown by LPE, MOCVD and MBE have been studied. A long wavelength microstructure lying along directions which is observed in some MBE GalnAs layers is associated with reduced electron mobilities. In MOCVD GalnAs a long wavelength microstructure lying along directions was seen to vary as a function of distance from the interface. The presence and wavelength of the speckle contrast is shown to be independent of the growth technique employed. Some MBE GalnAs layers also reveal an island contrast along orthogonal directions. Undoped MOCVD GalnAs epilayers with large compositional fluctuations approximately half way through the thickness of the epilayer or small compositional fluctuations near the epilayer surface have been studied. These perturbations in composition are associated with a dislocation cell structure and a cross-hatch of dislocations along directions respectively. A variety of defects have been identified and the microstructure correlated with Sputter Auger profiles and depth-resolved Hall profiles. Cliff-Lorimer k-factors have been determined experimentally and theoretically for Ga, As and P relative to In and extinction distances for GalnAs and InP calculated.

In this research work, we have investigated the band engineering of epitaxial graphene using first principles calculations. Epitaxial graphene on SiC (0001) surface is modified by using different methods such as intercalation, doping, passivation and oxidation. The calculations are done using Density functional theory which is implemented in quantum espresso package. In the presence of H intercalation, epitaxial graphene is shown to have p type behavior with monolayer graphene. However this behavior is different for multilayer epitaxial graphene systems, and it depended on the concentration of the H atoms. When epitaxial graphene is intercalated with Ge atoms, the Ge atoms make clusters and these clusters are responsible for the electronic properties of the epitaxial graphene systems. As a result of oxidation of epitaxial SiC surface, the graphene layer is mostly stable on the surface for both silicates and oxynitrides structures. For silicate/SiC configurations, the epitaxial graphene is shown to be less n type. For oxynitrides/ SiC configurations, epitaxial graphene is shown to be neutral. In the presence of oxygen intercalation with silicate/SiC, epitaxial graphene is shown to have p type behavior. These systematic studies of epitaxial graphene will opens up great potential for electronic applications. Additionally the resultant models can be used to guide further studies.

Graphene is a promising material for chemical sensing applications and many studies have focused on incorporating graphene into \sgfet s sensors. The purpose of this work is to get a deeper understanding of the physics governing the surface interaction of graphene in \sgfet s with ions and charged molecules. With a clearer understanding of how these interactions register in the conductivity of graphene, it then may be possible to design the ultrasensitive sensors that are often predicted to be possible when using graphene. Epitaxial graphene (EG) and graphene produced by chemical vapor deposition (CVD) were used to fabricate \sgfet s that were tested under different ionic strength conditions and concentrations of charged proteins. To get a clearer picture of the electrostatic gating effect in ionic solutions, we analyzed our data combining two models: the electrical double layer model, which accounts for the distribution of ions inside the solution, and a ionization model that accounts for ionizable groups on the graphene surface. This gave us an insight into the influence of charged groups fixed to the surface on the gating effect which is fundamental to the performance of \sgfet s as sensors. Using our experimental data we were also able to estimate the density of charged impurities in two carrier density regimes. For high densities, we found a correlation between our estimated impurities and the surface charge that suggests that the ionizable groups act as impurities. For small carrier densities, we modeled the carriers using a self-consistent approximation (SCA). The impurities estimated from the SCA model do not seem to be related to the ionizable groups and so the origin of the conductivity for small density seems to be originated by the permanently charged impurities only. Our estimation of the charged impurities for our charged-protein adsorption experiments showed a relation between their values and the protein concentration. This shows that the proteins interact with the graphene as charged impurities. Overall, our experiments allowed us to gain a deeper understanding of the interaction of charged particles with graphene. The analysis performed in this work gives a guide for the development of graphene \sgfet s sensors by engineering the impurities at the surface to optimize the sensitivity. The design of receptors for specific sensing that do not require charged targets is possible with engineering the charge that the receptor presents to graphene when the analyte concentration changes.

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