Derivati polimerici organometallici ancorati su matrice inorganica per applicazioni in chimica fine

Organotin compounds have found in the last few decades a wide variety of applications. Indeed, they are used successfully as antifouling paints, PVC stabilizers and ion carriers, as well as homogeneous catalysts. In this context, it has been proved that the Lewis acidity of the metal centre allows these compounds to promote the reaction between alcohol and ester. However their use is now limited by their well-known toxicity, moreover they are hardly removable from the reaction mixture. This problem can be overcome by grafting the organotin derivative onto a polymeric cross-linked support. In this way the obtained heterogeneous catalyst can be easily filtered off from the reaction mixture, thus creating the so-called "clean organotin reagents", avoiding the presence of toxic organotin residues in solution and the tin release in the environment. In the last few years several insoluble polystyrene resins containing triorganotin carboxylate moieties have been synthesized with the aim of improving their catalytic activity: in particular we have investigated and opportunely modified their chemical structure in order to optimize the accessibility to the metal centre and its Lewis acidity. Recently, we replaced the polymeric matrix with an inorganic one, in order to dispose of a relatively cheaper and easily available support. For this purpose an ordered mesoporous silica, characterized by 2D-hexagonal pores, named MCM-41, and an amorphous silica have been selected. In the present work two kinds of MCM-41 silica containing the triorganotin carboxylate moiety have been synthesized starting from a commercial Cab-O-Sil M5 silica. These catalysts have two different spacers between the core and the tin-carboxylate moiety, namely a polyaliphatic chain (compound FT29) or a poliethereal one (compound FT6), with the aim to improve the interaction between catalyst and reacting ester. Three catalysts supported onto an amorphous silica have been also synthesized: the structure is the same as silica FT29, i.e. a compound having a polialiphatic chain, and they have different percentage of organotin derivative grafted on the silica surface (10, 30, 50% respectively for silica MB9, SU27 and SU28). The performances of the above silica as heterogeneous catalysts in transesterification reactions have been tested in a model reaction between ethyl acetate and 1-octanol, a primary alcohol sensitive to the reaction conditions. The alcohol conversion was assessed by gas-chromatography, determining the relative amount of transesterified product and starting alcohol after established time intervals.

Parallel modeling of the electric field distribution in the brain

The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.