Hydrothermal synthesis of zirconium oxide nanoparticles and its characterization

The paper presents the preparation and investigations of zirconium oxide (ZrO₂) nanoparticles that were synthesized by hydrothermal method. The products were characterized by means of powder X-ray diffraction, scanning electron microscopy (SEM), transmission electron microscopy (TEM), UV-absorption spectroscopy and photoluminescence (PL) spectroscopy. The crystal structure was determined using X-ray diffraction. The morphology and the particle size were studied using (SEM) and (TEM). The spherical shaped particles were confirmed through the SEM analysis. The transmission electron microscopic analysis confirmed the formation of the nanoparticles with the particle size. The FT-IR and Raman spectrum ascertained the strong presence of ZrO₂ nanoparticles. The optical properties were obtained from UV–visible absorption spectrum and also PL emission spectrum. The dielectric constant and the dielectric loss were measured as a function of frequency and temperature.     

Purification,characterization, antibacterial activity and N-terminal sequencing of buffalo-milk lysozyme

Lysozyme from buffalo milk was purified to homogeneity and its N-terminal amino acid sequence, biochemical properties and antibacterial spectrum were determined. The purification procedure, comprising ion-exchange chromatography using CM-cellulose and size-exclusion chromatography using Sephadex G-50, conferred 8622-fold purification and 39.3% recovery of lysozyme. The purified enzyme migrated as a single band on sodium dodecyl sulphate-polyacrylamide gel electrophoresis (SDS-PAGE) and native PAGE. Immunological purity of lysozyme preparation was confirmed by immuno-electrophoresis. Molecular weight of buffalo-milk lysozyme as determined by SDS-PAGE was 16 kDa and its amino acid composition was determined by reverse phase high performance liquid chromatography (HPLC). The sequence of 23 amino acid residues at the N-terminal end showed 56.5% homology with bovine milk lysozyme and 30.4% with equine milk lysozyme. The specific activity of buffalo milk lysozyme was ten-times that of bovine milk lysozyme. Buffalo-milk lysozyme was active over a wide range of pH and its activity was strongly influenced by molarity of the medium. Antibacterial activity of buffalo-milk lysozyme was determined against 11 species of bacteria; out of seven Gram-positive bacteria tested, four were inhibited, while Gram-negative bacteria were resistant.     

Rare earth (RE) doped phosphors and their emerging applications: A review

The evolution of luminescent materials has witnessed rapid advancement in research and development. Solid inorganic light-emitting materials or phosphors are the optoelectronic material of the 21st century because of their power-efficient potential over various illumination sources, eco-friendliness and resourceful display perspectives. The inorganic phosphors have been extensively explored to meet the demand of low voltage stimulated lighting sources owing to increased global energy consumption. Due to environmental friendliness, advantages long lifetime, lower energy consumption, reliability and high luminous efficiency, modern white light-emitting diodes (WLEDs) have replaced less effective incandescent and mercury-enclosing conventional fluorescent lighting sources. This review highlights the developments in preparation, luminescence and potential perceptions of rare-earth activated phosphors for solid-state lighting technologies. The role of RE ions as an activator as well as a sensitizer in doped materials and possible transitions within their energy levels are reviewed in detail. The paper reviews the substantial influence of host lattices such as aluminate, oxide, phosphate, silicate, sulfide, etc on the optical transitions of doped RE ions. Studies on the advancement into the design of novel phosphors are very crucial as they will provide an opportunity to boom prospects in the course of promising applications. The sustainable energy facilities include clean technologies providing a cheaper lighting source which can produce significant indirect economic benefits via limiting the deforestation and use of scrubbing technology to mitigate air pollution.     

Tailoring of optical and electrical properties of PMMA by incorporation of Ag nanoparticles

Silver–poly(methyl methacrylate) (Ag–PMMA) nanocomposite films were prepared via ex situ chemical route by employing sodium borohydride (\(\hbox {NaBH}_{4}\)) as a reducing agent. In this study, PVP-stabilized Ag nanoparticles were prepared and mixed with PMMA solution. Optical and structural characterizations of resulting nanocomposite films were performed using UV–visible spectroscopy, transmission electron microscopy (TEM) and scanning electron microscopy (SEM). Characteristic surface plasmon resonance (SPR) peak of Ag nanoparticles was observed at about 3.04 eV (408 nm) in absorption spectra of Ag–PMMA nanocomposite films. TEM micrograph revealed that the spherical Ag nanoparticles with an average diameter of 5.4\(\,\pm \,\)2.5 nm are embedded in PMMA. In Raman spectra, besides shifting of vibrational bands, enhancement in intensity of Raman signal with incorporation of Ag nanoparticles was observed. Current (I)–voltage (V) measurements revealed that conductivity of PMMA increased with increasing concentration of Ag nanoparticles. Analysis of I–V data further disclosed that at voltage <2 V, ohmic conduction mechanism is the dominant mechanism, while at voltage >2 V Poole–Frenkel is the dominant conduction mechanism. Urbach’s energy, the measure of disorder, increased from 0.40 eV for PMMA to 1.11 eV for Ag–PMMA nanocomposite films containing 0.039 wt% of Ag nanoparticles.     

Management of Multipurpose Multireservoir Using Fuzzy Interactive Method

In this paper a fuzzy interactive method is proposed for efficient management of multipurpose multireservoir problems. The proposed method provides an option to decision maker (DM) to work in an interactive manner to achieve the conflicting objectives as close to their desired values as is practically feasible. In each iteration, fuzzy membership functions of various objectives are framed and combined into a single objective using the product operator. The single objective nonlinear optimization model thus framed in each iteration is numerically solved using genetic algorithm. The solution provides the values of the objectives which can be actually achieved keeping in view their aspired values as provided by DM. At the end of each iteration, DM has the option to modify the aspired values of one or more objectives keeping in view the results obtained by the algorithm thus far. The algorithm is stopped when DM feels satisfied with the results. The working of the proposed method has been demonstrated on the mathematical model of a realistic multipurpose multireservoir system taken from literature.     

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.     

Hybrid approach for congestion management using optimal placement of distributed generator

Congestion management (CM) in a large power system network is a difficult task which can be solved by placing one or more distributed generators (DGs) on congested lines. The first concern is to determine the exact location of congested line for the placement of optimal size of DG so that cost can be minimised. In this work, hybridisation of firefly technique and differential evolution optimisation search has been proposed, which manages congestion effectively by rescheduling of generators satisfying the system constraints both technically and economically in the deregulated market scenario. To validate the proposed hybrid approach, results have been compared with firefly optimisation technique results. It is observed that the hybrid approach is an efficient tool in handling CM resulting in a secure operation to reduce flows in the heavily loaded lines with low system loss and increasing power capability with improved stability of network by controlling power flows in the network.     

Structural and thermal characterization of CaO–MgO–SiO2–P2O5–CaF2 glasses

The influence of varying the CaO/MgO ratio on the structure and thermal properties of CaO–MgO–SiO₂–P₂O₅–CaF₂ glasses was studied in a series of eight glass compositions in the glass forming region of diopside (CaMgSi₂O₆)–fluorapatite [Ca₅(PO₄)₃F]–wollastonite (CaSiO₃) ternary system. The melt-quenched glasses were characterized for their structure by infrared spectroscopy (FTIR) and magic angle spinning (MAS)-nuclear magnetic resonance (NMR) spectroscopy. Silicon is predominantly present as Q² (Si) species, while phosphorus tends to coordinate in orthophosphate environment. The sintering and crystallization parameters of the glasses were obtained from differential thermal analysis (DTA) while crystalline phase fractions in the sintered glass–ceramics were analyzed by X-ray diffraction adjoined with Rietveld refinement. Diopside, fluorapatite, wollastonite and pseudowollastonite crystallized as the main crystalline phases in all the glass–ceramics with their content varying with respect to variation in CaO/MgO ratio in glasses. The implications of structure and sintering behaviour of glasses on their bioactivity were discussed.     

Artificial bee colony based energy‐aware resource utilization technique for cloud computing

Cloud computing is a form of distributed computing, which promises to deliver reliable services through next‐generation data centers that are built on virtualized compute and storage technologies. It is becoming truly ubiquitous and with cloud infrastructures becoming essential components for providing Internet services, there is an increase in energy‐hungry data centers deployed by cloud providers. As cloud providers often rely on large data centers to offer the resources required by the users, the energy consumed by cloud infrastructures has become a key environmental and economical concern. Much energy is wasted in these data centers because of under‐utilized resources hence contributing to global warming. To conserve energy, these under‐utilized resources need to be efficiently utilized and to achieve this, jobs need to be allocated to the cloud resources in such a way so that the resources are used efficiently and there is a gain in performance and energy efficiency. In this paper, a model for energy‐aware resource utilization technique has been proposed to efficiently manage cloud resources and enhance their utilization. It further helps in reducing the energy consumption of clouds by using server consolidation through virtualization without degrading the performance of users’ applications. An artificial bee colony based energy‐aware resource utilization technique corresponding to the model has been designed to allocate jobs to the resources in a cloud environment. The performance of the proposed algorithm has been evaluated with the existing algorithms through the CloudSim toolkit. The experimental results demonstrate that the proposed technique outperforms the existing techniques by minimizing energy consumption and execution time of applications submitted to the cloud. Copyright © 2014 John Wiley & Sons, Ltd.