The electronic properties and Hall effect of thin amorphous Si1-xGex:H films of thickness (350 nm) have been studied such as dc conductivity, activation energy, Hall coefficient under magnetic field (0.257 Tesla) for measuring carrier density of electrons and holes and Hall mobility as a function of germanium content (x = 0–1), deposition temperature (303-503) K and dopant concentration for Al and As in the range (0-3.5)%. The composition of the alloys and films were determined by using energy dispersive spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS).
This study showed that dc conductivity of a-Si1-xGex:H thin films is found to increase with increasing Ge content and dopant concentration, whereas conductivity activati

Ferrite with general formula Ni1-x Cox Fe2O4(where x=0.0.1,0.3,0.5,0.7, and 0.9), were prepared by standard ceramic technique. The main cubic spinel structure phase for all samples was confirmed by x-ray diffraction patterns. The lattice parameter results were (8.256-8.299 ^°A). Generally, x -ray density increased with the addition of Cobalt and showed value between (5.452-5.538gm/cm³). Atomic Force Microscopy (AFM) showed that the average grain size and surface roughness was decreasing with the increasing cobalt concentration. Scanning Electron Microscopy images show that grains had an irregular distribution and irregular shape. The A.C conductivity was found to increase with the frequency and the addition of Cobal

The spectroscopic properties, potential energy curve, dipole moments, total charge density, Electrostatic potential as well as the thermodynamic properties of selenium diatomic halides have been studied using code Mopac.7.21 and hyperchem, semi-empirical molecular orbital of MNDO-method (modified neglected of differential overlap) of parameterization PM3 involving quantum mechanical semi-empirical Hamiltonian. The relevant molecular parameters like interatomic distance, bond angle, dihedral angle and net charge were also calculated.

Some of the characters of the Staphylolysin A and D enzymes purified from Pseudomonas aeruginosa P16 and P5 respectively were studied, the molecular weights of Staphylolysin A and D were 20.417 kilo dalton and 23.988 kilo Dalton respectively by SDS- polyacryl amide gel electrophoresis. The optimum pH for staphylolysin A activity was found to be 8 which gives higher activity reaches 150 unit/ml, and for enzyme stability was 7.5-8.5 in which the enzyme nearly retained its full activity, while it was 9.5 for staphylolysin D that gives higher activity of 16 unit/ml,and 8.5-9.5 for enzyme stability in which the enzyme nearly retained its full activity, Maximum activity of two enzymes was obtained at 40C in which the specific activity for st

The effect of doping by methyl red and methyl blue on the absorption spectra and the optical energy gap of poly (methyl methacrylat) PMMA film have been studied. The optical transmission (T%) in the wavelength range 190-900 nm for films deposited by using solvent casting method were measured. The Absorptance data reveals that the doping affected the absorption edge as a red and blue shift in its values. The films show indirect allowed interband transitions that influenced by the doping. Optical constants; refractive index, extinction coefficient and real and imaginary part of dielectric constant were calculated and correlated with doping.

In the present study a new synthesis method has been introduced for the decoration of platinum(Pt) on the functionalized graphene nanoplatelet (GNP) and also highlighted the preparation method of nanofluids. GNP–Pt uniform nanocomposite was produced from a simple chemical reaction procedure, which included acid treatment for functionalization of GNP. The surface characterization was performed by various techniques such as XRD, FESEMand TEM. The effective thermal conductivity, density, viscosity, specific heat capacity and stability of functionalized GNP–Pt water based nanofluids were investigated in different instruments. The GNP–Pt hybrid nanofluids were prepared by dispersing the nanocomposite in base fluid without adding any surfac

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

in this paper copper oxide (cuO thin films were prepared by the method of vacum thermal evaporation a pressure.