Structural characteriztion of Nd-doped in silica host matrix prepared by net chemical process

Silica host matrix containing neodymium which is potentially important for the formation of nanocrystalline metal oxides was prepared by solgel method, using tetra-ethoxysilane and Nd(NO3)3 as precursor materials. The prepared samples were changed from amorphous to nanocrystallites phase at sintered temperature 550℃ (4 h), 750℃ (8 h) and 950 ℃ (12 h). The thermally treated sample microstructures were investigated using X-ray diffraction (XRD), Fourier transformation infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). While a further increase of the temperature at 750 ℃ and annealing time (8 h) resulted in the formation of cubic and hexagonal Nd2O3 nanocrystallites. At constant sintering temperature 950℃ for 12 h, the samples showed sharper and intense peaks. The sizes of Nd2O3 nanocrystallites were characterized by XRD with average size～46 nm.     

Solution properties of methyl methacrylate–acrylonitrile copolymers

Characterization of methyl methacrylate-acrylonitrile copolymers is done through viscosity, swelling, and differential refractometric studies. Viscosities of the copolymers and homopolymers were determined at 30, 40, and 50°C. The activation parameters of viscous flow, voluminosity, and shape factor were also calculated. The average shape factor was observed to be 2.5 ± 0.005 for all copolymer systems. Viscosity molecular weights were calculated, and from intramolecular expansion factor (α), it was observed that copolymers are less flexible than are homopolymers. dn/dc values obtained from differential refractometry are in good agreement with those calculated theoretically. © 1993 John Wiley & Sons, Inc.     

An ensemble-based incremental learning approach to data fusion.

This paper introduces Learn++, an ensemble of classifiers based algorithm originally developed for incremental learning, and now adapted for information/data fusion applications. Recognizing the conceptual similarity between incremental learning and data fusion, Learn++ follows an alternative approach to data fusion, i.e., sequentially generating an ensemble of classifiers that specifically seek the most discriminating information from each data set. It was observed that Learn++ based data fusion consistently outperforms a similarly configured ensemble classifier trained on any of the individual data sources across several applications. Furthermore, even if the classifiers trained on individual data sources are fine tuned for the given problem, Learn++ can still achieve a statistically significant improvement by combining them, if the additional data sets carry complementary information. The algorithm can also identify-albeit indirectly-those data sets that do not carry such additional information. Finally, it was shown that the algorithm can consecutively learn both the supplementary novel information coming from additional data of the same source, and the complementary information coming from new data sources without requiring access to any of the previously seen data.     

Effect of low-density filler on mechanical properties of syntactic foams of cyanate ester

Syntactic foam composites of cyanate ester with varying volume fractions of resin and glass microballoon were processed and evaluated for tensile, flexural and compressive properties. The effect of nature and volume fraction of microballoon on the mechanical properties was studied. The mechanical properties showed a gradual decrease in strength with increase in volume fraction of microballoon. The specific strength values also manifested a similar order. A similar behaviour was observed for syntactic foams with microballoons of varying true density. The properties increased proportional to the strength of the microballoon in resin-rich systems implying a strong microballoon-resin interface, corroborated by Scanning Electron Microscopy studies. The compressive modulus showed a decreasing trend with enhanced microballoon loading.     

An improved algorithm for connectivity analysis of distribution networks

In the present paper, an efficient algorithm for connectivity analysis of moderately sized distribution networks has been suggested. Algorithm is based on generation of all possible minimal system cutsets. The algorithm is efficient as it identifies only the necessary and sufficient conditions of system failure conditions in n-out-of-n type of distribution networks. The proposed algorithm is demonstrated with the help of saturated and unsaturated distribution networks. The computational efficiency of the algorithm is justified by comparing the computational efforts with the previously suggested appended spanning tree (AST) algorithm. The proposed technique has the added advantage as it can be utilized for generation of system inequalities which is useful in reliability estimation of capacitated networks.     

Scale up criteria for dual stirred gas-liquid unbaffled tank with concave blade impeller

Experimental investigation has been done in unbaffled gas-liquid stirred tanks using dual concave blade impeller to analyze the mass transfer, power consumption and gas holdup. Optimal impeller clearance has been suggested for lower and upper impeller based on maximum mass transfer rate. Numerical modeling has been done to analyze the flow pattern for different combinations of impeller clearance. The lower impeller positioned at 0.3 of tank diameter and clearance between lower and upper impeller at 0.4 of tank diameter gave the maximum mass transfer coefficient. Scale-up criteria for mass transfer rate, power and gas holdup have been developed for optimal geometrical similar systems of unbaffled stirred tanks with dual concave impeller.     

Electrical Conduction in Nano-Structured La0.9Sr0.1Al0.85Co0.05Mg0.1O3 Perovskite Oxide

Nanocrystalline La_0.9Sr_0.1Al_0.85Co_0.05Mg_0.1O₃ oxide powder was synthesized by a citrate–nitrate auto-ignition process and characterized by thermal analysis, X-ray diffraction, and impedance spectroscopy measurements. Nanocrystalline (50–100 nm) powder with perovskite structure could be produced at 900°C by this process. The powder could be sintered to a density more than 96% of the theoretical density at 1550°C. Impedance measurements on the sintered samples unequivocally established the potential of this process in developing nanostructured lanthanum aluminate-based oxides. The sintered La_0.9Sr_0.1Al_0.85Co_0.05Mg_0.1O₃ sample exhibited a conductivity of 2.40 × 10⁻² S/cm in air at 1000°C compared with 4.9 × 10⁻³ S/cm exhibited by La_0.9Sr_0.1Al_0.85Mg_0.15O₃.     

Mechanical,thermal, and microwave properties of conducting composites of polypyrrole/polypyrrole‐coated short nylon fibers with acrylonitrile butadiene rubber

Pyrrole was polymerized in the presence of anhydrous ferric chloride as oxidant and p‐toluene sulfonic acid as dopant. Polypyrrole‐coated short nylon fibers were prepared by polymerizing pyrrole in the presence of short nylon fibers. The resultant polypyrrole (PPy) and PPy‐coated nylon fiber (F‐PPy) were then used to prepare rubber composites based on acrylonitrile butadiene rubber (NBR). The cure pattern, direct current (DC) conductivity, mechanical properties, morphology, thermal degradation parameters, and microwave characteristics of the resulting composites were studied. PPy retarded the cure reaction while F‐PPy accelerated the cure reaction. Compared to PPy, F‐PPy was found to be more effective in enhancing the DC conductivity of NBR. The tensile strength and modulus values increased on adding PPy and F‐PPy to NBR, suggesting a reinforcement effect. Incorporation of PPy and F‐PPy improved the thermal stability of NBR. The absolute value of the dielectric permittivity, alternating current (AC) conductivity, and absorption coefficient of the conducting composites prepared were found to be much greater than the gum vulcanizate. PPy and F‐PPy were found to decrease the dielectric heating coefficient and skin depth significantly. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Improved field emission from multiwall carbon nanotubes with nano-size defects produced by ultra-low energy ion bombardment

Multiwalled carbon nanotubes were irradiated with ultra-low energy (few eV) nitrogen and hydrogen ions using a microwave discharge. These ultra-low energy plasma-ions remain confined to the nanotube walls, transferring their maximum energy to the carbon atoms, and produce extraordinary structural changes to the carbon nanotube pillars as well as within the carbon nanotubes. Conical shaped emitters and nanotube structures with nano-defects are produced that exhibit remarkable field emission with ultra-low turn-on electric field (∼0.16 V/μm) and a >300-fold increase in the maximum emission current density compared to non-irradiated nanotubes. Doping of nitrogen is also identified due to such irradiation processes.