Inorganic Chemistry and Technology

The investigations will be directed in the field of the syntheses of new inorganic materials with specific properties and in the development of environmentally friendly technologies. The purpose of the research in the field of new materials is to find new synthetic routes for the preparation of new compounds with interesting electrical, optical and magnetic properties. The syntheses will be performed in superacids, at supercritical conditions of the solvent or one or more reactants, at high pressures (some kbar), in nonaqueous media, with the strongest known oxidants etc. Special emphasis will be given to the study of donor and acceptor properties of rare earth fluorides and the synthesis of new fluorolanthanoates which represent potential precursors for new coordination and organometalic chemistry of lanthanoids. The syntheses of new –onium ions will be also studied. Graphite fluorides will be synthesized. They are used as cathode in lithium batteries. New graphite fluorides will be prepared in simple protonic acid – anhydrous hydrogen fluoride with elemental fluorine in the presence of UV light. In the field of the synthesis and characterization of fluorinated aerogels their catalytical influence on the reactions in the gas phase will be studied. Here the goal is to exchange CFCs with HFCs which are environmentally friendly and decompose before reaching the stratosphere. In the field of applicative research the development of a dynamic non-stationary model of chemical processes will be continued. Such models are impossible to be described analytically due to their complexity. The results of the research will try to improve the calculation algorithms in order to gain in the speed of calculation. Quick dynamic models are useful not only for design, optimisation and scale up of processes and process equipment, but also for the process control. In the models development the emphasis will be given on the development of hybrid models by inclusion of certain chemometric techniques (e.g. artificial neural networks, particial least squares, genetic algorithms).