Role of magnesium in cast aluminium alloy matrix composites

Wetting between the dispersoid and the matrix alloy is the foremost requirement during the preparation of metal matrix composites (MMC) especially with the casting/liquid metal processing technique. The basic principles involved in improving wetting fall under three categories: (i) increasing the surface energies of the solids, (ii) decreasing the surface tension of the liquid matrix alloy, and (iii) decreasing the solid/liquid interfacial energy at the dispersoid matrix interface. The presence of magnesium, a powerful surfactant as well as a reactive element, in the aluminium alloy matrix seems to fulfil all the above three requirements. The role played by magnesium during the synthesis of aluminium alloy matrix composites with dispersoids such as zircon (ZrSiO₄), zirconia (ZrO₂), titania (TiO₂), silica (SiO₂), graphite, aluminium oxide (Al₂O₃) and silicon carbide (SiC), has been analysed. The important role played by the magnesium during the composite synthesis is the scavenging of the oxygen from the dispersoid surface, thus thinning the gas layer and improving wetting and reaction-aided wetting with the surface of the dispersoid. The combinations of magnesium and aluminium seem to have some synergistic effect on wetting.     

Production and recovery of poly‐3‐hydroxybutyrate from Methylobacterium sp V49

Bacterial polyesters have shown potential as biodegradable plastics. Microorganisms capable of producing these polyesters from cheaper carbon sources and methods for their efficient recovery are widely studied worldwide. Methylobacterium sp V49, an environmental isolate, was cultivated on a mineral salts medium containing different carbon sources. Maximum accumulation of poly‐3‐hydroxybutyrate (PHB) within the bacterial cell was observed with glucose as the carbon source. Methanol and sugars such as sucrose and lactose also induced PHB accumulation. The effect of C:N ratio on polymer accumulation was studied. Different strategies for the extraction and recovery of the polymer from the cells were compared. A non‐solvent‐based method using a high‐pressure homogenizer in the presence of SDS was found to be the most satisfactory. Maximum recovery of 98% was achieved by homogenizing the cells at 400 kgcm^?2 in 5% SDS solution. © 2002 Society of Chemical Industry     

Interfacial reactions in aluminosilicate short fiber-reinforced aluminum matrix composites

Aluminosilicate short fibers are one of the less expensive reinforcements used for the fabrication of metal matrix composites (MMCs). The present investigation evaluates the interfacial characteristics of Al-7Si-0.4Mg (356) alloy reinforced with 10 wt pct aluminosilicate short fibers using optical microscopy, electron microscopy, and X-ray analysis. The fibers used are standard- and zirconiagrade aluminosilicate short fibers. The interfacial analysis has shown the formation of MgAl₂O₄ and Si in both grades of fibers. In addition, ZrAl₃ formation is observed in the zirconia-grade fiber because of the interaction between the matrix and the dispersoid. The zirconia-grade fiber is more susceptible to interfacial reaction than the standard-grade fiber because of the presence of the highly reactive ZrO₂ phase and a lower amount of the Al₂O₃ phase, which provides resistance to the reaction.     

Analytical formulation of small signal stability analysis of power systems with nonlinear loads

The online version of the original article can be found at     

Trajectory approximations for direct energy methods that usesustained faults with detailed power system models

The authors address the effects of fast dynamics on direct energy methods that use a sustained fault trajectory to approximate critically cleared trajectories and the corresponding critical energies. Integral manifold concepts are used to explain why fast dynamics can destroy such an approximation. Methods to remedy this problem are given and illustrated with a ten-machine example     

Use of 2'-fluoro-5-methyl-beta-L-arabinofuranosyluracil as a novel antiviral agent for hepatitis B virus and Epstein-Barr virus

A novel anti-hepatitis B virus (anti-HBV) agent, 2'-fluoro-5-methyl-beta-L-arabinofuranosyluracil (L-FMAU), was synthesized and found to be a potent anti-HBV and anti-Epstein-Barr virus agent. Its in vitro potency was evaluated in 2.2.15 and H1 cells for anti-HBV and anti-Epstein-Barr virus activities, respectively. In vitro cytotoxicity in MT2, CEM, 2.2.15, and H1 cells was also assessed, and the results indicated high antiviral selectivities of L-FMAU in these cells.     

Microwatt MOSLED Using ${hbox {SiO}}_{rm x}$ With Buried Si Nanocrystals on Si Nano-Pillar Array

Microwatt light emission from a metal-oxide-semiconductor light-emitting diode (MOSLED) made by using SiOx film with buried Si nanocrystals on Si nano-pillar array is demonstrated. The Si nano-pillar array obtained by drying the rapidly self-aggregated Ni nano-dot-masked Si substrate exhibit size, aspect ratio, and density of 30 nm, 10, and 2.8times10¹⁰ cm^-2, respectively. These high-aspect-ratio Si nano-pillar array helps to enhance the Fowler-Nordheim tunneling-based carrier injection and to facilitate the complete relaxation on total internal reflection, thus increasing the quantum efficiency by one order of magnitude and improving the light extraction from the nano-roughened device surface by three times at least. The light-emission intensity, turn-on current and power-current slope of the MOSLED are 0.2 mW/cm² , 20-30 muA, and 3plusmn0.5 mW/A, respectively. At a biased current of 400 muA, the highest external quantum efficiency is over 0.2% to obtain the maximum EL power of > 1 muW. Compared with the same device made on smooth Si substrate under a power conversion ratio of 1 times 10^-4 , such an output power performance is enhanced by at least one order of magnitude.     

Using support vector machines to forecast the production values of the machinery industry in Taiwan

The machinery industry is one of the most important exporting industries in Taiwan. The values of Taiwan’s machinery industry have been increasing continuously over the past years. Therefore, forecasting of production values is an essential issue for the machinery industry in Taiwan. Support vector machines (SVMs), a novel forecasting technique, have been successfully applied in solving non-linear regression and time series problems. In this paper, SVMs are employed to examine the feasibility in forecasting seasonal time series data of production values of Taiwan’s machinery industry. In addition, two other forecasting approaches, namely the seasonal time series autoregressive integrated moving average (SARIMA) model and general regression neural networks (GRNN), are used to compare the performance of forecasting. Experimental results show that support vector machines outperform SARIMA and the general regression neural networks in terms of forecasting accuracy.