Use of phosphorylated chitosan/alumina nanoadditives for polymer performance improvement

Cellulose - In this research, a new generation of ternary nanocomposites based on poly(ethylene terephthalate) (PET), phosphorylated chitosan and surface modified alumina nanoparticles were...     

First Report of a Lipopeptide Biosurfactant from Thermophilic Bacterium Aneurinibacillus thermoaerophilus MK01 Newly Isolated from Municipal Landfill Site

A biosurfactant-producing thermophile was isolated from the Kahrizak landfill of Tehran and identified as a bacterium belonging to the genus Aneurinibacillus. A thermostable lipopeptide-type biosurfactant was purified from the culture medium of this bacterium and showed stability in the temperature range of 20–90 °C and pH range of 5–10. The produced biosurfactant could reduce the surface tension of water from 72 to 43 mN/m with a CMC of 1.21 mg/mL. The strain growing at a temperature of 45 °C produces a substantial amount of 5 g/L of biosurfactant in the medium supplemented with sunflower oil as the sole carbon source. Response surface methodology was employed to optimize the biosurfactant production using sunflower oil, sodium nitrate, and yeast extract as variables. The optimization resulted in 6.75 g/L biosurfactant production, i.e., 35 % improved as compared to the unoptimized condition. Thin-layer chromatography, FTIR spectroscopy, ¹H-NMR spectroscopy, and biochemical composition analysis confirmed the lipopeptide structure of the biosurfactant.     

Nanoparticulate Hollow TiO2 Fibers as Light Scatterers in Dye‐Sensitized Solar Cells: Layer‐by‐Layer Self‐Assembly Parameters and Mechanism

Hollow structures show both light scattering and light trapping, which makes them promising for dye‐sensitized solar cell (DSSC) applications. In this work, nanoparticulate hollow TiO₂ fibers are prepared by layer‐by‐layer (LbL) self‐assembly deposition of TiO₂ nanoparticles on natural cellulose fibers as template, followed by thermal removal of the template. The effect of LbL parameters such as the type and molecular weight of polyelectrolyte, number of dip cycles, and the TiO₂ dispersion (amorphous or crystalline sol) are investigated. LbL deposition with weak polyelectrolytes (polyethylenimine, PEI) gives greater nanoparticle deposition yield compared to strong polyelectrolytes (poly(diallyldimethylammonium chloride), PDDA). Decreasing the molecular weight of the polyelectrolyte results in more deposition of nanoparticles in each dip cycle with narrower pore size distribution. Fibers prepared by the deposition of crystalline TiO₂ nanoparticles show higher surface area and higher pore volume than amorphous nanoparticles. Scattering coefficients and backscattering properties of fibers are investigated and compared with those of commercial P25 nanoparticles. Composite P25–fiber films are electrophoretically deposited and employed as the photoanode in DSSC. Photoelectrochemical measurements showed an increase of around 50 % in conversion efficiency. By employing the intensity‐modulated photovoltage and photocurrent spectroscopy methods, it is shown that the performance improvement due to addition of fibers is mostly due to the increase in light‐harvesting efficiency. The high surface area due to the nanoparticulate structure and strong light harvesting due to the hollow structure make these fibers promising scatterers in DSSCs.     

A cosmological viewpoint on the correspondence between deformed phase-space and canonical quantization

We employ the familiar canonical quantization procedure in a given cosmological setting to argue that it is equivalent to and results in the same physical picture if one considers the deformation of the phase-space instead. To show this we use a probabilistic evolutionary process to make the solutions of these different approaches comparable. Specific model theories are used to show that the independent solutions of the resulting Wheeler–DeWitt equation are equivalent to solutions of the deformation method with different signs for the deformation parameter. We also argued that since the Wheeler–DeWitt equation is a direct consequence of diffeomorphism invariance, this equivalence is only true provided that the deformation of phase-space does not break such an invariance.     

Normal distribution profile for doping concentration in multilayer tunnel junction

In this paper, the effect of doping concentration and layer thickness on the performance of tunnel junctions (TJs) is studied. We investigate the behavior of single, double and triple layer structures of TJs. Triple layer structure shows better performance in comparison with the other structures and can reach the higher tunneling current besides lower voltage drop. Also, the behavior of the triple layer TJ with different doping concentration profiles is studied. We propose a new normal distribution profile for doping concentration in multilayer TJs which shows better performance in comparison with the linear and graded doping concentration profiles. The higher $\upalpha $ parameters in normal distribution enhance the device performance with increasing the smoothness of doping variations in the center and edge of the TJ. Finally, we examine different thicknesses of triple layer TJ in order to achieve the optimum structure.     

Net demand prediction for power systems by a new neural network‐based forecasting engine

Integration of renewable generations, such as wind and photovoltaic, into electrical power systems is rapidly growing throughout the world. Stochastic and variable nature of these resources makes some operational challenges to power systems. The most effective way to tackle these challenges is short‐term prediction of their available powers. Despite various developed methods to forecast generation of renewable resources, still they have large errors, which may lead to under/over‐commitment of conventional generators in power systems. Prediction of net demand (ND), defined as electrical load minus renewable generations, can provide useful information for accurate scheduling of conventional generators. In this article, characteristics of the time series of electric load, renewable generations and ND are analyzed, and a new hybrid prediction strategy is presented for direct prediction of ND. The training mechanism of the proposed forecasting engine is composed of a new stochastic search method and Levenberg–Marquardt learning algorithm based on an iterative procedure and greedy search. The suggested prediction strategy is tested on different real‐world power systems and its obtained results are compared with the results of several other forecast methods and published literature figures. These comparisons confirm the validity of the developed forecasting strategy. © 2016 Wiley Periodicals, Inc. Complexity 21: 296–308, 2016     

Particle creation from vacuum by Lorentz violation

It is shown that the vacuum state in the presence of Lorentz violation can be followed by a universe filled with particles at late times similar to the current status of the universe. In this model a modification in dispersion relation (Lorentz violation) appears representing the regime of quantum gravity which has been dominant in the early universe. The existence of the particles can be interpreted as an evidence for quantum effects of gravity at early times. It is concluded that the present observable particles have a geometrical origin due to the well-known correspondence between geometry and gravity.