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The degradation of dye in effluent from textile industries is a vital area of research for mitigating the effects of the dyestuff on the ecosystem. In this study, silver nanoparticles were synthesized using a green approach using Pongamia pinnata leaf extract as a natural reducing and capping agent. The leaf extract and synthesized silver nanoparticles (AgNPs) were characterized for identifying the active functional groups and UV absorbance. Further, the surface morphology, particle-size distribution, and elemental analysis of the silver nanoparticle were characterized. The photocatalytic studies of the synthesized AgNPs were done for acid dye – acid Brilliant Red 3BN under solar irradiation. The process variables like the dye concentration, contact time, catalyst concentration, and pH were analyzed by one factor at a time approach. The formation of silver nanoparticles from silver nitrate by P. pinnata leaf extract was evident at 432 nm. The average particle size was found to be 50 nm and the shape of the silver nanoparticle was spherical. The elemental analysis confirms the presence of silver nanoparticles. The optimum factors are 5 ppm of dye concentration, and 10 mg/L catalyst concentration with a reaction time of 2 h at pH 4 for achieving photocatalytic degradation of 74% of acid Brilliant Red 3BN dye. The kinetic studies reveal that the reaction showed a good fit for the first-order kinetics with a rate constant of 0.00577 min–1 with R2 value of 0.97629. This study confirms the green synthesis of silver nanoparticles and its effective degradation of acid Brilliant Red 3BN dye. [ABSTRACT FROM AUTHOR]

Scattering is one of the main challenges in scaling up photocatalytic water splitting using the most prevalent powder catalysts. This can be overcome by decoupling the reaction medium from light transmission, as in the case of optical fibers. Here we explore utilizing optical fibers coated with 5 wt% CuO supported on TiO 2 for photocatlytic H 2 production from water-methanol mixtures. CuO/TiO 2 is a well studied photo catalyst in which photoreduced Cu species are known to act as sensitizers for inducing visible light activity. Lower activity of sequentially coated systems indicates that appropriate interfaces of active Cu and TiO 2 with water are desirable. The scalability of such optical fiber-based systems along with potential in non-potable turbid water media are demonstrated. Maximum activity of 22 μmoles of H 2 in 8 h was obtained with 50 mg of catalyst coated on optical fibers, which increases linearly with increase in fiber numbers, whereas, drastic reduction in activity is observed in powder catalyst upon increasing the catalyst quantity. A one-to-one comparison of 700 mg of catalyst in powder form and coated on optical fibers indicates more than one order enhancement in activity in the optical fiber based system. In addition, ∼70% retention in activity in highly turbid non-potable water was observed as compared to powdered system which shows complete reduction in the activity by 99.99%. • 5 wt%CuO/TiO 2 coated optical fiber bundles are studied for photocatalytic hydrogen evolution via water splitting. • Change in directionality of light reduces scattering issues observed in powder catalysts on scale up. • H 2 production can be increased by merely increasing number of optical fibers. • More than one order enhancement in activity in the optical fiber when compared to powder on scale up. • Retention of ∼70% activity in turbid non-potable water. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jss.2010.07.036 Byline: S.R. Kannan (a)(b), A. Sathya (b), S. Ramathilagam (c)(d), R. Devi (b) Keywords: Fuzzy c-means; Clustering; Kernel function; Gaussian function; Image segmentation Abstract: The aim of this paper is to develop an effective fuzzy c-means (FCM) technique for segmentation of Magnetic Resonance Images (MRI) which is seriously affected by intensity inhomogeneities that are created by radio-frequency coils. The weighted bias field information is employed in this work to deal the intensity inhomogeneities during the segmentation of MRI. In order to segment the general shaped MRI dataset which is corrupted by intensity inhomogeneities and other artifacts, the effective objective function of fuzzy c-means is constructed by replacing the Euclidean distance with kernel-induced distance. In this paper, the initial cluster centers are assigned using the proposed center initialization algorithm for executing the effective FCM iteratively. To assess the performance of proposed method in comparison with other existed methods, experiments are performed on synthetic image, real breast and brain MRIs. The clustering results are validated using Silhouette accuracy index. The experimental results demonstrate that our proposed method is a promising technique for effective segmentation of medical images. Author Affiliation: (a) Department of Electrical Engineering, National Cheng Kung University, Tainan 70701, Taiwan (b) Department of Mathematics, Gandhigram Rural University, Gandhigram 624 302, India (c) Department of Engineering Science, National Cheng Kung University, Tainan 70701, Taiwan (d) Department of Mathematics, MVM Govt. College, Dindigul, India Article History: Received 22 September 2009; Revised 29 June 2010; Accepted 15 July 2010

[Display omitted] • Production of Hydrogen using Catalytic Dehydrogenation of Methane (CDM). • Fe doped with Al, C and Si as catalysts for CDM. • Fe (110) is the most active plane compared to Fe (100) and Fe (111). • The active plane 100 with 5.5 % C impurities has reduction barrier of 0.51 eV. • CI-NEB and AIMD simulations are also performed. Enhancing the efficiency of methane dehydrogenation through chemical modification of electrocatalytic iron surfaces with impurities that resemble cast iron properties is demonstrated computationally using Density Functional Theory methodologies. Investigating methane dehydrogenation on thermally stable Fe surfaces with discrete planes and anchoring impurities such as Al, C, and Si minimized reduction barriers. Electrochemical treatment of methane on these robust surfaces yields clean hydrogen and carbon-based compounds, such as carbon nanomaterials and carbon black. As for the most efficient active sites for enhanced methane dehydrogenation, the active plane 100 with 5.5 % C impurities and 0.51 eV reduction barrier is determined to be the most dependable, followed by the active plane 110 with 5.5 % Si impurities and the lower 0.98 eV reduction barrier. Utilizing CI-NEB (Nudged Elastic Band), the dissociation barrier investigation established the electrolytic catalysts' performance. This work paves the way for experimentalists and demonstrates the economic viability of Fe-based catalysts for the Catalytic Dehydrogenation of Methane. [ABSTRACT FROM AUTHOR]