Correlation between structure and electrochemistry of LiMO2 cathode materials (M = Ni, Co)

Technical diversity and various knowledge is required for the understanding of undoubtedly complex system such as a Lithium-ion battery. The peculiarity is to combine different techniques that allow a complete investigation while the battery is working. Nowadays, research on Li-ion batteries (LIBs) is experiencing an exponential growth in the development of new cathode materials. Accordingly, Li-rich and Ni-rich NMCs, which have similar layered structure of LiMO2 oxides, have been recently proposed. Despite the promising performance on them, still a lot of issues have to be resolved and the materials need a more in depth characterisation for further commercial applications. In this study LiMO2 material, in particular M = Co and Ni, will be presented. We have focused on the synthesis of pure LiCoO2 and LiNiO2 at first, followed by the mixed LiNi0.5Co0.5O2. Different ways of synthesis were investigated for LCO but the sol-gel-water method showed the best performances. An accurate and systematic structural characterization followed by the appropriate electrochemical tests were done. Moreover, the in situ techniques (in-situ XRD and in situ OEMS) allowed a deep investigation in the structural change and gas evolution upon the electrochemically driven processes.

Framework for anomaly detection on photovoltaic plants

Technological advancement has undergone exponential growth in recent years, and this has brought significant improvements in the computational capabilities of computers, which can now perform an enormous amount of calculations per second. Taking advantage of these improvements has made it possible to devise algorithms that are very demanding in terms of the computational resources needed to develop architectures capable of solving the most complex problems: currently the most powerful of these are neural networks and in this thesis I will combine these tecniques with classical computer vision algorithms to improve the speed and accuracy of maintenance in photovoltaic facilities.