Cadmium sulfide photodetector was fabricated. The CdS nano
powder has been prepared by a chemical method and deposited as a
thin film on both silicon and porous p- type silicon substrates by spin
coating technique. Structural, morphological, optical and electrical
properties of the prepared CdS nano powder are studied. The X-ray
analysis shows that the obtained powder is CdS with predominantly
hexagonal phase. The Hall measurements show that the nano powder
is n-type with carrier concentration of about (-5.4×1010) cm-3. The
response time of fabricated detector was measured by illuminating
the sample with visible radiation and its value was 5.25 msec. The
specific detectivity of the fabricated det

Improvement of optoelectrical characteristics of phosphorus diffused silicon photodiodes by Q-switched Nd:YAG laser pulses was investigated. Laser pulses have dissolved the precipitation of phosphorus resulted during thermal diffusion process. The experimental data show that responsivity higher than (0.32 A/W) at 850 nm can be achieved after laser annealing with (1.5 MW/cm2) for 6 shots.

In this work, yttrium oxide particles (powder) reinforced AL-Si matrix composites (Y2O3/Al-Si) and Chromium oxide particles reinforced AL-Si matrix composites (Cr2O3/AL-Si) were prepared by direct squeeze casting. The volume percentages of yttrium oxide used are (4, 8.1, 12.1, 16.1 vol %) and the volume percentages of the chromium oxide particles used are (3.1, 6.3, 9.4, 12.5 vol. %). The parameters affecting the preparation of Y2O3/Al-Si and Cr2O3/AL-Si composites by direct squeeze casting process were studied. The molten Al-Si alloy with yttrium oxide particles or with chromium oxide particles was stirred again using an electrical stirrer at speed 500 rpm  and the molten alloy was  poured  into the squeeze die cavity. Th

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation

The experimental and numerical analysis was performed on pipes suffering large plastic deformation through expanding them using rigid conical shaped mandrels, with three different cone angles (15◦, 25◦, 35◦) and diameters (15, 17, 20) mm. The experimental test for the strain results investigated the expanded areas. A numerical solution of the pipes expansion process was also investigated using the commercial finite element software ANSYS. The strains were measured for each case experimentally by stamping the mesh on the pipe after expanding, then compared with Ansys results. No cracks were generated during the process with the selected angles. It can be concluded that the strain decreased with greater angles of con