Advanced Materials Research Vols. 152-153

Abstract: A family of poly(ethylene glycol)-b-poly(ε-caprolactone) (PEG-PCL) were synthesized in high yields by the ring-opening polymerization of monomethoxy-terminated poly(ethylene glycol) (mPEG) with ε-caprolactone in the presence of stannous octoate (Sn(Oct)2). Their crystallization behaviors were studied by DSC, XRD. The results illustrated that crystallization behaviors of the copolymers depended on the copolymer composition and the relative length of each block in copolymers. The melting peak of PCL block appeared gradually in the XRD patterns and DSC curves in copolymers, with increasing of the length of PCL blocks.

Abstract: Sugar is one of the key nutrients required to microorganism growth. In this paper , the effects of various sugars on the mineralization of calcium carbonate induced by Bacillus pasteurii . The precipitation amount, forms and structures of calcium carbonate were characterized. The results indicated that the induced calcium carbonate precipitation are mainly calcite as irregular aggregated bodies and rhombus blocks and aragonite appeared when the culture medium was added with dextran. The calcium carbonate precipitation reached a maximum of 2.32 g when glucose was added into the culture.

Abstract: Biomorphic silicon carbide (bioSiC) was prepared at 1800 oC by reactive infiltration of gaseous silicon into a carbon template derived from millet. The pyrolysis process of millet was measured by thermogravimetric analysis. The morphology and microstructures of carbon template and purified bioSiC samples were characterized by scanning electron microscopy. The phase composition of bioSiC was analyzed by X-ray diffraction. The results suggest that the bioSiC consists of major cubic ß-SiC and a few α-SiC, and principally replicates the shape and microstructure of the carbon template.

Abstract: Biodegradable composites of polylactic acid reinforced with wood fiber are fabricated by using twin screw extruder followed by the injection molding machine. The effects of fiber mass fraction and alkali concentration on mechanical properties of biodegradable composites are investigated. The results show that the mechanical properties of biodegradable composites presented tendency which reduced first, elevated, and again reduced along with fiber mass fraction increased, after the alkali treatment, the mechanical properties of biodegradable composites have the tendency which increased first and then reduced, when the concentration of alkali solution is 8%, both the tensile strength and impact strength are best. The scanning electron microscope and Infrared Spectrum Analysis are also used for examination of biodegradable composites.

Abstract: Biomorphic silicon carbide (bioSiC) was prepared by high temperature pyrolysis and sol-gel and carbothermal reduction processing at 1600 oC. The morphology and microstructure of carbon-silica composites and purified bioSiC samples were characterized by scanning electron microscopy. The phase composition of the resulting sample was analyzed by X-ray diffraction. The results suggest that the bioSiC mainly consists of cubic ß-SiC, and principally replicates the shape and microstructure of the carbon template.

Abstract: Intraoral adjustment of ceramic prostheses involving cutting process is a central procedure in restorative dentistry because the quality of ceramic prostheses depends on the cutting process. In this paper, an artificial neural network (ANN) model was developed for the first time to forecast the dynamic forces in dental cutting process as functions of clinical operational parameters. The predicted force values were compared with the measured values in in vitro dental cutting of porcelain prostheses obtained using a novel two-degrees-of-freedom computer-assisted testing apparatus with a high-speed dental handpiece and diamond burs. The results indicate that there existed nonlinear relationships between the cutting forces and clinical operational parameters. It is found that the ANN-forecasted forces were in good agreement with the experiment-measured values. This indicates that the established ANN model can provide insights into the force-related process assessment and forecast for clinical dental cutting of ceramic prostheses.

Abstract: The number of corrosion pits with different corrosion times were got through extracting the corrosion character of LY12CZ aluminum alloy based on binary image disposal technique, through statistical fractal theory we can see that the distribution of corrosion pits have fractal character; the fractal dimension and weight loss rate increased with the corrosion time and the change rule of fractal dimension with different corrosion time consistent with weight loss rate, both are accordant with power function, so the fractal dimension can be regarded as an important parameter to evaluate the corrosion degree.

Abstract: The vibration noise control is critical in engineering fields and the phononic crystal provides a new mean to control the vibration noise. The band gap structure of one dimensional phononic crystal is studied in this paper. By using the equivalent masses method we obtain the band gap structure which depends on M, m and β, the influences of initial frequency of vibration band gap via the material density, the diameter of rod and the lattice constant are analyzed. The results show that the low-frequency broadband gap characteristic is obtained by increasing M and reducing m, β. The initial frequency of vibration band gap decreases as the metal material density, the diameter of metal rod or the lattice constant increase. Some conclusions from numerical calculation are examined by the vibration experiment.

Abstract: The objective of this study was to model the drug release property in terms of process variables of microwave-assisted modification of arrowroot starch using artificial neural network (ANN). The water content, microwave power and heating time were used as process variables for modification of arrowroot starch and the mean dissolution time was used as dependent variable. The correlation between process variables and dependent variable was examined using feed-forward back-propagation neural networks. The ANN model was optimized by considering goodness-of-fit and crossvalidated predictability. A “leave-one-out” cross-validation revealed that the neural network model could predict MDT values from matrix tablets with a reasonable accuracy (predictive r2 of 0.824 and predictive root mean square error of 19.53). The predictive ability of these models was validated by a set of 4 formulations that were not included in the training set. The predicted and observed MDT were well correlated.

Abstract: Gas diffusion electrodes (GDEs) were selected for the reactive brilliant red X-3B simulated wastewater treatment, perovskite oxide LaNiO3 as the catalyst. And a satisfying degradation effect was achieved. The optimal conditions for the catalyst preparation with sol-gel method were 1.5 as the molar ratio of citric acid and metal ions, 10 as the pH, and 750 °C as the roasting temperature. The optimal conditions for the electrodes preparation were 1 g pore-forming agent, 0.6 g catalyst, 3 g PTFE and 300 °C as the roasting temperature. Scanning electron microscope, X-ray diffraction were applied to analyze the performance of catalyst and electrodes, and the results were satisfying.