Soft edge of hadron scattering and minijet models for the total and inelastic pp cross sections at LHC and beyond

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Flow Visualization with Quantified Spatial and Temporal Errors Using Edge Maps

Robust analysis of vector fields has been established as an important tool for deriving insights from the complex systems these fields model. Traditional analysis and visualization techniques rely primarily on computing streamlines through numerical integration. The inherent numerical errors of such approaches are usually ignored, leading to inconsistencies that cause unreliable visualizations and can ultimately prevent in-depth analysis. We propose a new representation for vector fields on surfaces that replaces numerical integration through triangles with maps from the triangle boundaries to themselves. This representation, called edge maps, permits a concise description of flow behaviors and is equivalent to computing all possible streamlines at a user defined error threshold. Independent of this error streamlines computed using edge maps are guaranteed to be consistent up to floating point precision, enabling the stable extraction of features such as the topological skeleton. Furthermore, our representation explicitly stores spatial and temporal errors which we use to produce more informative visualizations. This work describes the construction of edge maps, the error quantification, and a refinement procedure to adhere to a user defined error bound. Finally, we introduce new visualizations using the additional information provided by edge maps to indicate the uncertainty involved in computing streamlines and topological structures.

Scaled down physical properties of semiconductor nanowires for nanoelectronics scaling up

Semiconductor nanowires (NWs) are one- or quasi one-dimensional systems whose physical properties are unique as compared to bulk materials because of their nanoscaled sizes. They bring together quantum world and semiconductor devices. NWs-based technologies may achieve an impact comparable to that of current microelectronic devices if new challenges will be faced. This thesis primarily focuses on two different, cutting-edge aspects of research over semiconductor NW arrays as pivotal components of NW-based devices. The first part deals with the characterization of electrically active defects in NWs. It has been elaborated the set-up of a general procedure which enables to employ Deep Level Transient Spectroscopy (DLTS) to probe NW arrays’ defects. This procedure has been applied to perform the characterization of a specific system, i.e. Reactive Ion Etched (RIE) silicon NW arrays-based Schottky barrier diodes. This study has allowed to shed light over how and if growth conditions introduce defects in RIE processed silicon NWs. The second part of this thesis concerns the bowing induced by electron beam and the subsequent clustering of gallium arsenide NWs. After a justified rejection of the mechanisms previously reported in literature, an original interpretation of the electron beam induced bending has been illustrated. Moreover, this thesis has successfully interpreted the formation of NW clusters in the framework of the lateral collapse of fibrillar structures. These latter are both idealized models and actual artificial structures used to study and to mimic the adhesion properties of natural surfaces in lizards and insects (Gecko effect). Our conclusion are that mechanical and surface properties of the NWs, together with the geometry of the NW arrays, play a key role in their post-growth alignment. The same parameters open, then, to the benign possibility of locally engineering NW arrays in micro- and macro-templates.

Bottom-up solution synthesis of structurally defined graphene nanoribbons

Graphene nanoribbons (GNRs), which are defined as nanometer-wide strips of graphene, are attracting an increasing attention as one on the most promising materials for future nanoelectronics. Unlike zero-bandgap graphene that cannot be switched off in transistors, GNRs possess open bandgaps that critically depend on their width and edge structures. GNRs were predominantly prepared through “top-down” methods such as “cutting” of graphene and “unzipping” of carbon nanotubes, but these methods cannot precisely control the structure of the resulting GNRs. In contrast, “bottom-up” chemical synthetic approach enables fabrication of structurally defined and uniform GNRs from tailor-made polyphenylene precursors. Nevertheless, width and length of the GNRs obtainable by this method were considerably limited. In this study, lateral as well as longitudinal extensions of the GNRs were achieved while preserving the high structural definition, based on the bottom-up solution synthesis. Initially, wider (~2 nm) GNRs were synthesized by using laterally expanded monomers through AA-type Yamamoto polymerization, which proved more efficient than the conventional A2B2-type Suzuki polymerization. The wider GNRs showed broad absorption profile extending to the near-infrared region with a low optical bandgap of 1.12 eV, which indicated a potential of such GNRs for the application in photovoltaic cells. Next, high longitudinal extension of narrow (~1 nm) GNRs over 600 nm was accomplished based on AB-type Diels–Alder polymerization, which provided corresponding polyphenylene precursors with the weight-average molecular weight of larger than 600,000 g/mol. Bulky alkyl chains densely installed on the peripheral positions of these GNRs enhanced their liquid-phase processability, which allowed their formation of highly ordered self-assembled monolayers. Furthermore, non-contact time-resolved terahertz spectroscopy measurements demonstrated high charge-carrier mobility within individual GNRs. Remarkably, lateral extension of the AB-type monomer enabled the fabrication of wider (~2 nm) and long (>100 nm) GNRs through the Diels–Alder polymerization. Such longitudinally extended and structurally well-defined GNRs are expected to allow the fabrication of single-ribbon transistors for the fundamental studies on the electronic properties of the GNRs as well as contribute to the development of future electronic devices.

Analysis of spring break-up and its effects on a biomass feedstock supply chain in northern Michigan

Demand for bio-fuels is expected to increase, due to rising prices of fossil fuels and concerns over greenhouse gas emissions and energy security. The overall cost of biomass energy generation is primarily related to biomass harvesting activity, transportation, and storage. With a commercial-scale cellulosic ethanol processing facility in Kinross Township of Chippewa County, Michigan about to be built, models including a simulation model and an optimization model have been developed to provide decision support for the facility. Both models track cost, emissions and energy consumption. While the optimization model provides guidance for a long-term strategic plan, the simulation model aims to present detailed output for specified operational scenarios over an annual period. Most importantly, the simulation model considers the uncertainty of spring break-up timing, i.e., seasonal road restrictions. Spring break-up timing is important because it will impact the feasibility of harvesting activity and the time duration of transportation restrictions, which significantly changes the availability of feedstock for the processing facility. This thesis focuses on the statistical model of spring break-up used in the simulation model. Spring break-up timing depends on various factors, including temperature, road conditions and soil type, as well as individual decision making processes at the county level. The spring break-up model, based on the historical spring break-up data from 27 counties over the period of 2002-2010, starts by specifying the probability distribution of a particular county’s spring break-up start day and end day, and then relates the spring break-up timing of the other counties in the harvesting zone to the first county. In order to estimate the dependence relationship between counties, regression analyses, including standard linear regression and reduced major axis regression, are conducted. Using realizations (scenarios) of spring break-up generated by the statistical spring breakup model, the simulation model is able to probabilistically evaluate different harvesting and transportation plans to help the bio-fuel facility select the most effective strategy. For early spring break-up, which usually indicates a longer than average break-up period, more log storage is required, total cost increases, and the probability of plant closure increases. The risk of plant closure may be partially offset through increased use of rail transportation, which is not subject to spring break-up restrictions. However, rail availability and rail yard storage may then become limiting factors in the supply chain. Rail use will impact total cost, energy consumption, system-wide CO2 emissions, and the reliability of providing feedstock to the bio-fuel processing facility.