Functional photoactive and electroactive nanodevices

Most of current ultra-miniaturized devices are obtained by the top-down approach, in which nanoscale components are fabricated by cutting down larger precursors. Since this physical-engineering method is reaching its limits, especially for components below 30 nm in size, alternative strategies are necessary. Of particular appeal to chemists is the supramolecular bottom-up approach to nanotechnology, a methodology that utilizes the principles of molecular recognition to build materials and devices from molecular components. The subject of this thesis is the photophysical and electrochemical investigation of nanodevices obtained harnessing the principles of supramolecular chemistry. These systems operate in solution-based environments and are investigated at the ensemble level. The majority of the chemical systems discussed here are based on pseudorotaxanes and catenanes. Such supramolecular systems represent prototypes of molecular machines since they are capable of performing simple controlled mechanical movements. Their properties and operation are strictly related to the supramolecular interactions between molecular components (generally photoactive or electroactive molecules) and to the possibility of modulating such interactions by means of external stimuli. The main issues addressed throughout the thesis are: (i) the analysis of the factors that can affect the architecture and perturb the stability of supramolecular systems; (ii) the possibility of controlling the direction of supramolecular motions exploiting the molecular information content; (iii) the development of switchable supramolecular polymers starting from simple host-guest complexes; (iv) the capability of some molecular machines to process information at molecular level, thus behaving as logic devices; (v) the behaviour of molecular machine components in a biological-type environment; (vi) the study of chemically functionalized metal nanoparticles by second harmonic generation spectroscopy.

Assimilation of Meteosat Second Generation (MSG) satellite data in a regional numerical weather prediction model using a one-dimensional variational approach

The quality of temperature and humidity retrievals from the infrared SEVIRI sensors on the geostationary Meteosat Second Generation (MSG) satellites is assessed by means of a one dimensional variational algorithm. The study is performed with the aim of improving the spatial and temporal resolution of available observations to feed analysis systems designed for high resolution regional scale numerical weather prediction (NWP) models. The non-hydrostatic forecast model COSMO (COnsortium for Small scale MOdelling) in the ARPA-SIM operational configuration is used to provide background fields. Only clear sky observations over sea are processed. An optimised 1D–VAR set-up comprising of the two water vapour and the three window channels is selected. It maximises the reduction of errors in the model backgrounds while ensuring ease of operational implementation through accurate bias correction procedures and correct radiative transfer simulations. The 1D–VAR retrieval quality is firstly quantified in relative terms employing statistics to estimate the reduction in the background model errors. Additionally the absolute retrieval accuracy is assessed comparing the analysis with independent radiosonde and satellite observations. The inclusion of satellite data brings a substantial reduction in the warm and dry biases present in the forecast model. Moreover it is shown that the retrieval profiles generated by the 1D–VAR are well correlated with the radiosonde measurements. Subsequently the 1D–VAR technique is applied to two three–dimensional case–studies: a false alarm case–study occurred in Friuli–Venezia–Giulia on the 8th of July 2004 and a heavy precipitation case occurred in Emilia–Romagna region between 9th and 12th of April 2005. The impact of satellite data for these two events is evaluated in terms of increments in the integrated water vapour and saturation water vapour over the column, in the 2 meters temperature and specific humidity and in the surface temperature. To improve the 1D–VAR technique a method to calculate flow–dependent model error covariance matrices is also assessed. The approach employs members from an ensemble forecast system generated by perturbing physical parameterisation schemes inside the model. The improved set–up applied to the case of 8th of July 2004 shows a substantial neutral impact.

Automatic code generation: from process algebraic architectural descriptions to multithreaded java programs

Process algebraic architectural description languages provide a formal means for modeling software systems and assessing their properties. In order to bridge the gap between system modeling and system im- plementation, in this thesis an approach is proposed for automatically generating multithreaded object-oriented code from process algebraic architectural descriptions, in a way that preserves – under certain assumptions – the properties proved at the architectural level. The approach is divided into three phases, which are illustrated by means of a running example based on an audio processing system. First, we develop an architecture-driven technique for thread coordination management, which is completely automated through a suitable package. Second, we address the translation of the algebraically-specified behavior of the individual software units into thread templates, which will have to be filled in by the software developer according to certain guidelines. Third, we discuss performance issues related to the suitability of synthesizing monitors rather than threads from software unit descriptions that satisfy specific constraints. In addition to the running example, we present two case studies about a video animation repainting system and the implementation of a leader election algorithm, in order to summarize the whole approach. The outcome of this thesis is the implementation of the proposed approach in a translator called PADL2Java and its integration in the architecture-centric verification tool TwoTowers.

Probabilistic approaches in civil engineering: generation of random fields and structural identification with genetic algorithms

The inherent stochastic character of most of the physical quantities involved in engineering models has led to an always increasing interest for probabilistic analysis. Many approaches to stochastic analysis have been proposed. However, it is widely acknowledged that the only universal method available to solve accurately any kind of stochastic mechanics problem is Monte Carlo Simulation. One of the key parts in the implementation of this technique is the accurate and efficient generation of samples of the random processes and fields involved in the problem at hand. In the present thesis an original method for the simulation of homogeneous, multi-dimensional, multi-variate, non-Gaussian random fields is proposed. The algorithm has proved to be very accurate in matching both the target spectrum and the marginal probability. The computational efficiency and robustness are very good too, even when dealing with strongly non-Gaussian distributions. What is more, the resulting samples posses all the relevant, welldefined and desired properties of “translation fields”, including crossing rates and distributions of extremes. The topic of the second part of the thesis lies in the field of non-destructive parametric structural identification. Its objective is to evaluate the mechanical characteristics of constituent bars in existing truss structures, using static loads and strain measurements. In the cases of missing data and of damages that interest only a small portion of the bar, Genetic Algorithm have proved to be an effective tool to solve the problem.

A chemical-loop approach for the generation of hydrogen by means of ethanol reforming

The work investigates the feasibility of a new process aimed at the production of hydrogen with inherent separation of carbon oxides. The process consists in a cycle in which, in the first step, a mixed metal oxide is reduced by ethanol (obtained from biomasses). The reduced metal is then contacted with steam in order to split the water and sequestrating the oxygen into the looping material’s structure. The oxides used to run this thermochemical cycle, also called “steam-iron process” are mixed ferrites in the spinel structure MeFe2O4 (Me = Fe, Co, Ni or Cu). To understand the reactions involved in the anaerobic reforming of ethanol, diffuse reflectance spectroscopy (DRIFTS) was used, coupled with the mass analysis of the effluent, to study the surface composition of the ferrites during the adsorption of ethanol and its transformations during the temperature program. This study was paired with the tests on a laboratory scale plant and the characterization through various techniques such as XRD, Mössbauer spectroscopy, elemental analysis... on the materials as synthesized and at different reduction degrees In the first step it was found that besides the generation of the expected CO, CO2 and H2O, the products of ethanol anaerobic oxidation, also a large amount of H2 and coke were produced. The latter is highly undesired, since it affects the second step, during which water is fed over the pre-reduced spinel at high temperature. The behavior of the different spinels was affected by the nature of the divalent metal cation; magnetite was the oxide showing the slower rate of reduction by ethanol, but on the other hand it was that one which could perform the entire cycle of the process more efficiently. Still the problem of coke formation remains the greater challenge to solve.

Potential Analysis for Hypoelliptic Second Order PDEs with Nonnegative Characteristic Form

In this Thesis we consider a class of second order partial differential operators with non-negative characteristic form and with smooth coefficients. Main assumptions on the relevant operators are hypoellipticity and existence of a well-behaved global fundamental solution. We first make a deep analysis of the L-Green function for arbitrary open sets and of its applications to the Representation Theorems of Riesz-type for L-subharmonic and L-superharmonic functions. Then, we prove an Inverse Mean value Theorem characterizing the superlevel sets of the fundamental solution by means of L-harmonic functions. Furthermore, we establish a Lebesgue-type result showing the role of the mean-integal operator in solving the homogeneus Dirichlet problem related to L in the Perron-Wiener sense. Finally, we compare Perron-Wiener and weak variational solutions of the homogeneous Dirichlet problem, under specific hypothesis on the boundary datum.

1st and 2nd Generation Ethanol from Biomass Crops

In chapter 1 and 2 calcium hydroxide as impregnation agent before steam explosion of sugarcane bagasse and switchgrass, respectively, was compared with auto-hydrolysis, assessing the effects on enzymatic hydrolysis and simultaneous saccharification and fermentation (SSF) at high solid concentration of pretreated solid fraction. In addition, anaerobic digestion of pretreated liquid fraction was carried out, in order to appraise the effectiveness of calcium hydroxide before steam explosion in a more comprehensive way. In As water is an expensive input in both cultivation of biomass crops and subsequent pretreatment, Chapter 3 addressed the effects of variable soil moisture on biomass growth and composition of biomass sorghum. Moreover, the effect of water stress was related to the characteristics of stem juice for 1st generation ethanol and structural carbohydrates for 2nd generation ethanol. In the frame of chapter 1, calcium hydroxide was proven to be a suitable catalyst for sugarcane bagasse before steam explosion, in order to enhance fibre deconstruction. In chapter 2, effect of calcium hydroxide on switchgrass showed a great potential when ethanol was focused, whereas acid addition produced higher methane yield. Regarding chapter 3, during crop cycle the amount of cellulose, hemicellulose and AIL changed causing a decrease of 2G ethanol amount. Biomass physical and chemical properties involved a lower glucose yield and concentration at the end of enzymatic hydrolysis and, consequently, a lower 2G ethanol concentration at the end of simultaneous saccharification and fermentation, proving that there is strong relationship between structure, chemical composition, and fermentable sugar yield. The significantly higher concentration of ethanol at the early crop stage could be an important incentive to consider biomass sorghum as second crop in the season, to be introduced into some agricultural systems, potentially benefiting farmers and, above all, avoiding the exacerbation of the debate about fuel vs food crops.