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Reduced graphene oxide-zinc oxide (rGO-ZnO) nanocomposites were successfully synthesized using a facile microwave-hydrothermal method under mild conditions, and their electrocatalytic properties towards O 2 evolution were investigated. The microwave radiation played an important role in obtainment of well dispersed ZnO nanoparticles directly on reduced graphene oxide sheets without any additional reducing reagents or passivation agent. X-ray diffraction (XRD), Raman and infrared spectroscopies indicated the reduction of GO as well as the successful synthesis of rGO-ZnO nanocomposites. The chemical states of the samples were shown by XPS analyses. Due to the synergic effect, the resulting nanocomposites exhibited high electronic interaction between ZnO and rGO sheets, which improved the electrocatalytic oxidation of water with low onset potential of 0.48 V (vs. Ag/AgCl) in neutral pH and long-term stability, with high current density during electrolysis. The overpotential for water oxidation decreased in alkaline pH, suggesting useful insight on the catalytic mechanism for O 2 evolution.

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SUMMARYThis work presents the implementation of optimized numerical tools for the coupled analysis of floating platforms for offshore oil exploitation. The focus is on time-domain, nonlinear dynamic analysis, considering the coupling between the hydrodynamic behaviour of the hull and the structural behaviour of the mooring lines and risers modelled by finite elements (FEs). Some aspects of the formulation and solution of the large-amplitude equations of motion of the hull of the platform are presented, including a brief description of the hydrodynamic models and calculation of the environmental forces. The main aspects of the formulation for the spatial and time discretization of the structural model for the lines are also discussed. Since coupled analyses may require excessive computational costs, the objective of this work is to present the implementation and application of domain decomposition methods, adapted and specialized for the problem at hand, in order to optimize the efficiency of the computational tool. Two groups of domain decomposition methods are considered: the first is a subcycling technique that takes into account the natural partition that exists between the hull and the lines; the second considers the internal decomposition of the mesh of FEs to represent the mooring lines and risers. The methods are devised having in mind their implementation in computers with parallel architecture. Results of a numerical application are presented in order to assess the performance of the methods.

The number of waveforms monitored in power systems is increasing rapidly. This creates a demand for computational tools that aid in the analysis of the phenomena and also that allow efficient transmission and storage of the information acquired. In this context, signal processing techniques play a fundamental role. This work is a tutorial reviewing the principles and applications of atomic signal modeling of electric disturbance signals. The disturbance signal is modeled using a linear combination of damped sinusoidal components which are closely related to the phenomena typically observed in power systems. The signal model obtained is then employed for disturbance signal denoising, filtering of "DC components," and compression.