Low-dimensional carbon allotropes: an electron microscopy investigation

The research reported in this manuscript concerns the structural characterization of graphene membranes and single-walled carbon nanotubes (SWCNTs). The experimental investigation was performed using a wide range of transmission electron microscopy (TEM) techniques, from conventional imaging and diffraction, to advanced interferometric methods, like electron holography and Geometric Phase Analysis (GPA), using a low-voltage optical set-up, to reduce radiation damage in the samples. Electron holography was used to successfully measure the mean electrostatic potential of an isolated SWCNT and that of a mono-atomically thin graphene crystal. The high accuracy achieved in the phase determination, made it possible to measure, for the first time, the valence-charge redistribution induced by the lattice curvature in an individual SWCNT. A novel methodology for the 3D reconstruction of the waviness of a 2D crystal membrane has been developed. Unlike other available TEM reconstruction techniques, like tomography, this new one requires processing of just a single HREM micrograph. The modulations of the inter-planar distances in the HREM image are measured using Geometric Phase Analysis, and used to recover the waviness of the crystal. The method was applied to the case of a folded FGC, and a height variation of 0.8 nm of the surface was successfully determined with nanometric lateral resolution. The adhesion of SWCNTs to the surface of graphene was studied, mixing shortened SWCNTs of different chiralities and FGC membranes. The spontaneous atomic match of the two lattices was directly imaged using HREM, and we found that graphene membranes act as tangential nano-sieves, preferentially grafting achiral tubes to their surface.

Analysis of charge-transport properties in GST materials for next generation phase-change memory devices

The quest for universal memory is driving the rapid development of memories with superior all-round capabilities in non-volatility, high speed, high endurance and low power. The memory subsystem accounts for a significant cost and power budget of a computer system. Current DRAM-based main memory systems are starting to hit the power and cost limit. To resolve this issue the industry is improving existing technologies such as Flash and exploring new ones. Among those new technologies is the Phase Change Memory (PCM), which overcomes some of the shortcomings of the Flash such as durability and scalability. This alternative non-volatile memory technology, which uses resistance contrast in phase-change materials, offers more density relative to DRAM, and can help to increase main memory capacity of future systems while remaining within the cost and power constraints. Chalcogenide materials can suitably be exploited for manufacturing phase-change memory devices. Charge transport in amorphous chalcogenide-GST used for memory devices is modeled using two contributions: hopping of trapped electrons and motion of band electrons in extended states. Crystalline GST exhibits an almost Ohmic I(V) curve. In contrast amorphous GST shows a high resistance at low biases while, above a threshold voltage, a transition takes place from a highly resistive to a conductive state, characterized by a negative differential-resistance behavior. A clear and complete understanding of the threshold behavior of the amorphous phase is fundamental for exploiting such materials in the fabrication of innovative nonvolatile memories. The type of feedback that produces the snapback phenomenon is described as a filamentation in energy that is controlled by electron–electron interactions between trapped electrons and band electrons. The model thus derived is implemented within a state-of-the-art simulator. An analytical version of the model is also derived and is useful for discussing the snapback behavior and the scaling properties of the device.

Earthquake forecasting and seismic hazard analysis: some insights on the testing phase and the modeling

This thesis is divided in three chapters. In the first chapter we analyse the results of the world forecasting experiment run by the Collaboratory for the Study of Earthquake Predictability (CSEP). We take the opportunity of this experiment to contribute to the definition of a more robust and reliable statistical procedure to evaluate earthquake forecasting models. We first present the models and the target earthquakes to be forecast. Then we explain the consistency and comparison tests that are used in CSEP experiments to evaluate the performance of the models. Introducing a methodology to create ensemble forecasting models, we show that models, when properly combined, are almost always better performing that any single model. In the second chapter we discuss in depth one of the basic features of PSHA: the declustering of the seismicity rates. We first introduce the Cornell-McGuire method for PSHA and we present the different motivations that stand behind the need of declustering seismic catalogs. Using a theorem of the modern probability (Le Cam's theorem) we show that the declustering is not necessary to obtain a Poissonian behaviour of the exceedances that is usually considered fundamental to transform exceedance rates in exceedance probabilities in the PSHA framework. We present a method to correct PSHA for declustering, building a more realistic PSHA. In the last chapter we explore the methods that are commonly used to take into account the epistemic uncertainty in PSHA. The most widely used method is the logic tree that stands at the basis of the most advanced seismic hazard maps. We illustrate the probabilistic structure of the logic tree, and then we show that this structure is not adequate to describe the epistemic uncertainty. We then propose a new probabilistic framework based on the ensemble modelling that properly accounts for epistemic uncertainties in PSHA.