Nanoscale-electrical and optical properties of iii-nitrides

III-nitrides are wide-band gap materials that have applications in both electronics and optoelectronic devices. Because to their inherent strong polarization properties, thermal stability and higher breakdown voltage in Al(Ga,In)N/GaN heterostructures, they have emerged as strong candidates for high power high frequency transistors. Nonetheless, the use of (Al,In)GaN/GaN in solid state lighting has already proved its success by the commercialization of light-emitting diodes and lasers in blue to UV-range. However, devices based on these heterostructures suffer problems associated to structural defects. This thesis primarily focuses on the nanoscale electrical characterization and the identification of these defects, their physical origin and their effect on the electrical and optical properties of the material. Since, these defects are nano-sized, the thesis deals with the understanding of the results obtained by nano and micro-characterization techniques such as atomic force microscopy(AFM), current-AFM, scanning kelvin probe microscopy (SKPM), electron beam induced current (EBIC) and scanning tunneling microscopy (STM). This allowed us to probe individual defects (dislocations and cracks) and unveil their electrical properties. Taking further advantage of these techniques,conduction mechanism in two-dimensional electron gas heterostructures was well understood and modeled. Secondarily, origin of photoluminescence was deeply investigated. Radiative transition related to confined electrons and photoexcited holes in 2DEG heterostructures was identified and many body effects in nitrides under strong optical excitations were comprehended.

Physical models for numerical simulation of Si-based nanoscale FETs and sensors

To continuously improve the performance of metal-oxide-semiconductor field-effect-transistors (MOSFETs), innovative device architectures, gate stack engineering and mobility enhancement techniques are under investigation. In this framework, new physics-based models for Technology Computer-Aided-Design (TCAD) simulation tools are needed to accurately predict the performance of upcoming nanoscale devices and to provide guidelines for their optimization. In this thesis, advanced physically-based mobility models for ultrathin body (UTB) devices with either planar or vertical architectures such as single-gate silicon-on-insulator (SOI) field-effect transistors (FETs), double-gate FETs, FinFETs and silicon nanowire FETs, integrating strain technology and high-κ gate stacks are presented. The effective mobility of the two-dimensional electron/hole gas in a UTB FETs channel is calculated taking into account its tensorial nature and the quantization effects. All the scattering events relevant for thin silicon films and for high-κ dielectrics and metal gates have been addressed and modeled for UTB FETs on differently oriented substrates. The effects of mechanical stress on (100) and (110) silicon band structures have been modeled for a generic stress configuration. Performance will also derive from heterogeneity, coming from the increasing diversity of functions integrated on complementary metal-oxide-semiconductor (CMOS) platforms. For example, new architectural concepts are of interest not only to extend the FET scaling process, but also to develop innovative sensor applications. Benefiting from properties like large surface-to-volume ratio and extreme sensitivity to surface modifications, silicon-nanowire-based sensors are gaining special attention in research. In this thesis, a comprehensive analysis of the physical effects playing a role in the detection of gas molecules is carried out by TCAD simulations combined with interface characterization techniques. The complex interaction of charge transport in silicon nanowires of different dimensions with interface trap states and remote charges is addressed to correctly reproduce experimental results of recently fabricated gas nanosensors.

The effect of two-dimensional squat elements on the seismic behavior of building structures

This thesis reports a study on the seismic response of two-dimensional squat elements and their effect on the behavior of building structures. Part A is devoted to the study of unreinforced masonry infills, while part B is focused on reinforced concrete sandwich walls. Part A begins with a comprehensive review of modelling techniques and code provisions for infilled frame structures. Then state-of-the practice techniques are applied for a real case to test the ability of actual modeling techniques to reproduce observed behaviors. The first developments towards a seismic-resistant masonry infill system are presented. Preliminary design recommendations for the seismic design of the seismic-resistant masonry infill are finally provided. Part B is focused on the seismic behavior of a specific reinforced concrete sandwich panel system. First, the results of in-plane psuudostatic cyclic tests are described. Refinements to the conventional modified compression field theory are introduced in order to better simulate the monotonic envelope of the cyclic response. The refinements deal with the constitutive model for the shotcrete in tension and the embedded bars. Then the hysteretic response of the panels is studied according to a continuum damage model. Damage state limits are identified. Design recommendations for the seismic design of the studied reinforced concrete sandwich walls are finally provided.

Two-Dimensional Bin Packing Problem with Guillotine Restrictions

This thesis, after presenting recent advances obtained for the two-dimensional bin packing problem, focuses on the case where guillotine restrictions are imposed. A mathematical characterization of non-guillotine patterns is provided and the relation between the solution value of the two-dimensional problem with guillotine restrictions and the two-dimensional problem unrestricted is being studied from a worst-case perspective. Finally it presents a new heuristic algorithm, for the two-dimensional problem with guillotine restrictions, based on partial enumeration, and computationally evaluates its performance on a large set of instances from the literature. Computational experiments show that the algorithm is able to produce proven optimal solutions for a large number of problems, and gives a tight approximation of the optimum in the remaining cases.