Enhanced anti-biofilm activity of facile synthesized silver oxide nanoparticles against K. pneumoniae

Journal of Inorganic and Organometallic Polymers and Materials - The silver oxide nanoparticle was successfully synthesized using floral waste by simple one pot, cost effective method. The complete...     

Synthesis and characterization of liquid crystalline polymers containing aromatic ester mesogen and a nonmesogenic ferrocene unit in the spacer

A new series of liquid crystalline polymers containing aromatic triad ester mesogen and 1,1′‐disubstituted ferrocene as a nonmesogenic unit along with polymethylene spacer was synthesized. The polymer was synthesized by a room temperature polycondensation reaction between bis(4‐chloroformyl phenyloxy alkyl ferrocene dicarboxylate) and quinol. The alkyl groups have been varied by an even number of methylene groups with a range from two to ten groups. All the polymers were found to possess liquid crystalline properties. The identification of the mesophase is more transparent with an increase in the spacer. The thermal characteristics were studied using thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). The results reveal that the thermal stability of the polymers was decreased with increasing spacer length. The T_g, T_m, and T_i of the polymers decreased with increasing methylene groups. The incorporation of the ferrocene moiety also has a considerable effect on the glass transition temperature. The char yield of the polymer decreases with an increasing methylene chain length. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 3494–3501, 2002     

Green synthesis of copper oxide nanoparticles and mosquito larvicidal activity against dengue,zika and chikungunya causing vector Aedes aegypti

In the present study, high purity copper oxide nanoparticles (NPs) were synthesised using Tridax procumbens leaf extract. Green syntheses of nano‐mosquitocides rely on plant compounds as reducing and stabilising agents. Copper oxide NPs were characterised using X‐ray diffraction (XRD) analysis, Fourier transform infrared (FT‐IR), Field‐emission scanning electron microscopy with energy dispersive spectroscopy, Ultraviolet–visible spectrophotometry and fluorescence spectroscopy. XRD studies of the NPs indicate crystalline nature which was perfectly matching with a monoclinic structure of bulk CuO with an average crystallite size of 16 nm. Formation of copper oxide NPs was confirmed by FT‐IR studies and photoluminescence spectra with emission peaks at 331, 411 and 433 nm were assigned to a near‐band‐edge emission band of CuO in the UV, violet and blue region. Gas chromatography–mass spectrometry studies inferred the phytochemical constituents of the leaf extract. Larvicidal activity of synthesised NPs using T. procumbens leaf extract was tested against Aedes aegypti species (dengue, chikungunya, zika and yellow fever transmit vector).Inspec keywords: photoluminescence, spectrophotometry, thermal analysis, chromatography, nanoparticles, antibacterial activity, field emission electron microscopy, microorganisms, wide band gap semiconductors, scanning electron microscopy, X‐ray diffraction, copper compounds, ultraviolet spectra, nanofabrication, X‐ray chemical analysis, crystallites, visible spectra, field emission scanning electron microscopy, nanobiotechnology, semiconductor materials, semiconductor growth, fluorescence, mass spectraOther keywords: energy dispersive spectroscopy, ultraviolet–visual spectrophotometry, fluorescence spectroscopy, chikungunya, green synthesis, mosquito larvicidal activity, zika, X‐ray diffraction analysis, field‐emission scanning electron microscopy, XRD, gas chromatography–mass spectrometry, copper oxide nanoparticles, dengue, tridax procumben leaf extract, nanomosquitocides, FTIR, monoclinic structure, crystallite size, photoluminescence spectra, near‐band‐edge emission band, phytochemical constituents, Aedes aegypti species, yellow fever transmit vector, CuO     

Fuzzy logic based assignable cause diagnosis using control chart patterns

Control chart patterns, besides determining the presence of assignable causes, also provide hints on the nature of assignable cause(s) present. Relating the patterns exhibited on the control chart to assignable causes is an ambiguous and vague task especially when multiple patterns co-exist. In this work, a rule based fuzzy inference system is developed for control chart to prioritize the control chart causes based on the accumulated evidence. When a process goes out of control, search for assignable causes can be assisted by the priorities assigned to the causes. For an in-control process, developing patterns can be tracked and preventive action can be taken to prevent the process from going out of control.     

MADE3D: Enabling the next generation of high-torque density wind generators by additive design and 3D printing

Forschung im Ingenieurwesen - Direct-drive wind turbine generators are increasing in popularity, thanks to recent project developments—especially offshore, where reliability and efficiency...     

Reinforcements,Manufacturing Techniques,and Respective Property Changes of Al2O3/SiC Based Composites: A Review

Silicon - Recent innovations in materials technology upsurge the use of Al2O3 and SiC based composites in aerospace, automotive, defence, transportation, and sporting industries. The reinforcements...     

Prediction of relationships between hydrostatic coefficients and processing parameters of porous PZT ceramics by radial basis function

The high hydrostatic coefficients of porous piezoelectric materials provide the reduced acoustic impedance for the effective coupling with water medium as well as biological tissues. The hydrostatic strain coefficient (d_h), voltage coefficients (g_h) and longitudinal piezoelectric coefficient (d₃₃) of porous piezoelectric materials has a strong dependence on processing parameters such as porosity parameter, polymer percentage, density and poling voltage. In this work, a nonparametric regression has been carried out to figure out the nonlinear relationships between the hydrostatic coefficients and its processing parameters. The nonparametric regression has been carried out by artificial neural network. The Network architecture utilized is radial basis function (RBF) which is combined with Fuzzy Clustering Method (FCM) to identify the hidden node numbers and widths. The porosity parameter was calculated from scanning electron micrographs of the porous piezoelectric materials using conventional image processing techniques. The results of the artificial neural network were evaluated against experimental data.