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The work presented involves the multiphysical modelling, simulation and design optimization of a key component of a Solar Selective Coatings (SSC). The investigated SSC absorber consists of a near homogeneous distribution of nanoparticles of Titanium Nitride (TiN) in a matrix of Aluminium Nitride (AlN), to form a composite dielectric. With the aim of achieving high absorbance in the visible region of the spectrum and minimum reflectance in the infrared region of the spectrum, our work highlights the numerical design, the synthesis and optical characterization of a composite dielectric of approximately 500 nm thickness. A bottom-up approach for the preparation of a stack with alternate layers, consisting of a distribution of TiN nanoparticles with a layer of AlN on top, was adopted. The TiN nanoparticles, laid on a substrate (Silicon/Glass) by wet chemical method, are coated with conformal layer of AlN, via Plasma-enhanced Atomic Layer Deposition (PE-ALD). The control of the morphology at the nanoscale is fundamental in improving the optical performance of the material. For this reason, two composites were prepared. One starting with TiN dispersions made with dry TiN powder and deionized water, and the other with ready-made TiN dispersions. In both composites, the particles were 20–30 nm in diameter. In both the cases, fewer clusters of about 0.5–1 μmof TiN particles were present however, enough steps were taken to minimize these clusters into smaller particles. Parameters, such as the size of TiN nanoparticles, the thickness of AlN thin film, were revealed by the numerical simulations, performed using Wave-Optics module in COMSOL Multiphysics. The work showcased clearly compares the two kinds of composites, using scanning electron microscope, X-ray photoelectron spectroscopy and electrical conductivity measurement. In addition, the optical performance of the two prepared composites is used as a means of validating the computational model.

Reducing greenhouse gas emissions becomes a top priority in the world with the emergence of global warming and environmental problems. Various renewable energies appear during the last decades. Ocean captures and stores huge amounts of energy, which could satisfy five times of world energy demand. Due to technology limitations and economic considerations, marine current energy appears the most attractive choice compared with the other ocean energy form. Although the existing expertise and technology in offshore wind energy conversion system can be partially transferred to marine current energy conversion system due to the similar structure, there are still many technological challenges to overcome. Meanwhile, the system operates under the water will inevitably have some negative or positive impacts on the surrounding environment. In this paper, it shows the interest and the principle of the marine current energy, and also discusses the advantages and disadvantages. The environmental impacts around the devices, the technological challenges, and the essential support structures are presented as well. The state-of-the-art horizontal axis turbines and their relative technologies and the latest projects are described finally. This review paper gives the useful information about the attraction and challenge of the marine current energy, and the newest development of the technologies and projects.

This paper presents torque ripple reduction with speed control of 8/6 Switched Reluctance Motor (SRM) by the determination of the optimal parameters of the turn on, turn off angles Theta_(on), Theta_(off), and the supply voltage using Particle Swarm Optimization (PSO) algorithm and steady state Genetic Algorithm (ssGA). With SRM model, there is difficulty in the control relapsed into highly non-linear static characteristics. For this, the Finite Elements Method (FEM) has been used because it is a powerful tool to get a model closer to reality. The mechanism used in this kind of machine control consists of a speed controller in order to determine current reference which must be produced to get the desired speed, hence, hysteresis controller is used to compare current reference with current measured up to achieve switching signals needed in the inverter. Depending on this control, the intelligent routing algorithms get the fitness equation from torque ripple and speed response so as to give the optimal parameters for better results. Obtained results from the proposed strategy based on metaheuristic methods are compared with the basic case without considering the adjustment of specific parameters. Optimized results found clearly confirmed the ability and the efficiency of the proposed strategy based on metaheuristic methods in improving the performances of the SRM control considering different torque loads.