Hybrid neuro-swarm optimization approach for design of distributed generation power systems

The global energy sector faces major challenges in providing sufficient energy to the worlds ever-increasing energy demand. Options to produce greener, cost effective, and reliable source of alternative energy need to be explored and exploited. One of the major advances in the development of this sort of power source was done by integrating (or hybridizing) multiple different alternative energy sources (e.g., wind turbine generators, photovoltaic cell panels, and fuel-fired generators, equipped with storage batteries) to form a distributed generation (DG) power system. However, even with DG power systems, cost effectiveness, reliability, and pollutant emissions are still major issues that need to be resolved. The model development and optimization of the DG power system were carried out successfully in the previous work using particle swarm optimization (PSO). The goal was to minimize cost, maximize reliability, and minimize emissions (multi-objective function) subject to the requirements of the power balance and design constraints. In this work, the optimization was performed further using Hopfield neural networks (HNN), PSO, and HNN-PSO techniques. Comparative studies and analysis were then carried out on the optimized results.     

Supported Nano-Gold Catalysts for Epoxidation of Styrene and Oxidation of Benzyl Alcohol to Benzaldehyde

Nano-gold particles supported on different alkaline earth oxides (viz. MgO, CaO, BaO and SrO), Gr. IIIa metal oxides (viz. Al₂O_3, Ga₂O_3, In₂O₃ and Tl₂O₃), transition metal oxides (viz. TiO_2, Cr₂O_3, MnO_2, Fe₂O_3, CoO_x, NiO, CuO, ZnO, Y₂O₃ and ZrO₂), rare earth metal oxides (viz. La₂O_3, Ce₂O_3, Nd₂O_3, Sm₂O_3, Eu₂O_3, Tb₂O_3, Er₂O₃ and Yb₂O₃) and U₃O₈ [all prepared by depositing gold on corresponding metal oxide support by deposition precipitation (DP) and/or homogeneous deposition precipitation (HDP) method] were evaluated for their catalytic performance in the liquid phase epoxidation of styrene by tert-butyl hydroperoxide (TBHP) to styrene oxide and also in the solvent-free benzyl alcohol-to-benzaldehyde oxidation (by molecular oxygen or TBHP) reactions. For the epoxidation, the catalytic performance (styrene oxide yield) of the most promising nano-gold catalysts prepared by the HDP method was in the following order: Au/MgO > Au/Tl₂O₃ > Au/Yb₂O₃ > Au/Tb₂O₃ > Au/CaO (or TiO₂). However, for the oxidation of benzyl alcohol to benzaldehyde by molecular oxygen, the order of choice for the most promising catalysts (based on benzaldehyde yield) was Au/U₃O₈ > Au/Al₂O₃ > Au/ZrO₂ > Au/MgO. Whereas, when TBHP was used as an oxidizing agent for the benzyl alcohol oxidation, the order of choice for the most promising catalysts was Au/U₃O₈ > Au/MgO > Au/TiO₂ > Au/ZrO₂ > Au/Al₂O₃. The catalytic performance of a particular supported nano-gold catalyst was thus found to depend on the reaction catalysed by them. Moreover, it is strongly influenced by a number of catalyst parameters, such as the metal oxide support, the method of gold depositon on the support, the gold loading and also on the catalyst calcination temperature. Nano-gold particles-support interactions seem to play an important role in controlling the deposition of gold (amount of gold deposited and size and morphology of gold particles), formation of different surface gold species (Au⁰, Au¹⁺ and Au³⁺) and electronic properties of gold particles and, consequently, control the catalytic performance (both the activity and selectivity) of the supported nano-gold catalysts in the reactions. The nano-gold catalysts prepared by the HDP method showed much better catalytic performance than those prepared by the DP, coprecipitation or impregnation method; in general, the HDP method provided supported gold catalysts with much higher gold loading and/or smaller size gold particles than that achieved by the DP and other methods.     

Si nanotubes and nanospheres with two-dimensional polycrystalline walls

We report on the characteristics of a new class of Si-based nanotubes and spherical nanoparticles synthesized by the dc-arc plasma method in a mixture of argon and hydrogen. These two nanostructures share common properties: they are hollow and possess very thin, highly polycrystalline and mainly oxidized walls. In particular, we get several hints indicating that their walls could constitute only one single Si oxidized layer. Moreover, we find that only the less oxidized nanotubes exhibit locally atomic ordered, snakeskin-like areas which possess a hexagonal arrangement which can be interpreted either as an sp(2) or sp(3) hybridized Si or Si-H layer. Their ability to not react with oxygen seems to suggest the presence of sp(2) configuration or the formation of silicon-hydrogen bonding.     

Carbon-free dry reforming of methane to syngas over NdCoO3 perovskite-type mixed metal oxide catalyst

CoNdO_x (Co/Nd = 1) is a highly promising catalyst for the carbon-free CO₂ reforming of methane. Influence of the Co/Nd ratio on the catalyst performance in the CO₂ reforming and also on the crystalline phases and reduction by temperature programmed reduction (TPR) of the CoNdO_x catalyst has also been investigated. The CoNdO_x (CoNd = 1.0) catalyst consisted of mainly NdCoO₃ perovskite-type mixed metal oxide and it showed not only a high resistance to carbon formation at different process conditions (viz. temperature = 750–900 °C and gas hourly space velocity (GHSV) = 10000–50000 cm³ g^–1 h^–1) but also high activity and selectivity in the CO₂ reforming process. The high resistance to carbon formation for this catalyst is attributed mostly to strong metal (Co°)–support (Nd₂O₃) interactions.