In this work, MWCNT in the epoxy can be prepared at room temperature and thickness (1mm) at different concentration of CNTs powder. Optical properties of multi-walled carbon nanotubes (CNTs) reinforced epoxy have been measured in the range of (300-800)nm. The electronic transition in pure epoxy and CNT/epoxy indicated direct allowed transition. Also, it is found that the energy gap of epoxy is 4.1eV and this value decreased within range of (4.1-3.5)eV when the concentration of CNT powder increased from (0.001-0.1)% respectively.
The optical constants which include (the refractive index (n), the extinction coefficient (k), real (ε1) and imaginarily (ε2) part of dielectric constant calculated in the of (300-800)nm at different concent

NiO0.99Cu0.01 films have been deposited using thermal evaporation
technique on glass substrates under vacuum 10-5mbar. The thickness
of the films was 220nm. The as -deposited films were annealed to
different annealing temperatures (373, 423, and 473) K under
vacuum 10-3mbar for 1 h. The structural properties of the films were
examined using X-ray diffraction (XRD). The results show that no
clear diffraction peaks in the range 2θ= (20-50)o for the as deposited
films. On the other hand, by annealing the films to 423K in vacuum
for 1 h, a weak reflection peak attributable to cubic NiO was
detected. On heating the films at 473K for 1 h, this peak was
observed to be stronger. The most intense peak is at 2θ = 37

In this research, a sensor for chemical solutions was designed and formed using optical fiber-based on a surface Plasmon resonance technology. A single-mode optical fiber with three different diameters (25, 45 and 65) µm was used, respectively.  The second layer of the low refractive fiber was replaced by gold, which was electrically deposited at 40 µm thickness. For each of the three types of optical fiber, different saline concentrations (different index of refraction) were used to evaluate the performance of the refractive index sensor (chemical sensor) by measuring its sensitivity and resolutions. The highest values we could get for these two parameters were 240mm/RIU, and 6*10^-5 RIU respectively, when the diameter of a

Chlorine doped SnS have been prepared utilizing chemical spray pyrolysis. The effects of chlorine concentration on the optical constants were studied. It was seen that the transmittance decreased with doping, while reflectance, refractive index, extinction coefficient, real and imaginary parts of dielectric constant were increased as the doping percentage increased. The results show also that the skin depth decrease as the chlorine percentage increased which could be assure that it is transmittance related.

It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).