In this work, metal oxide nanostructures, mainly copper oxide (CuO), nickel oxide (NiO), titanium dioxide (TiO2), and multilayer structure, were synthesized by the DC reactive magnetron sputtering technique. The effect of deposition time on the spectroscopic characteristics, as well as on the nanoparticle size, was determined. A long deposition time allows more metal atoms sputtered from the target to bond to oxygen atoms and form CuO, NiO, or TiO2 molecules deposited as thin films on glass substrates. The structural characteristics of the final samples showed high structural purity as no other compounds than CuO, NiO, and TiO2 were found in the final samples. Also, the prepared multilayer structures did not show new compounds other than th

In this work, the adsorption of reactive yellow dye (Remazol yellow FG dye) by granular activated carbon (GAC) was investigated using batch and continuous process. The batch process involved determination the equilibrium isotherm curve either favorable or unfavorable by estimation relation between adsorption capacity and concentration of dye at different dosage of activated carbon. The results were fitted with equilibrium isotherm models Langmuir and Freundlich models with R2value (>0.97). Batch Kinetic study showed good fitting with pseudo second order model with R2 (0.987) at contact time 5 h. which provesthat the adsorption is chemisorptions nature. Continuous study was done by fixed bed column where breakthrough time was increased

      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

The aim of this work is to enhance the mechanical properties of the glass ionomer cement GIC (dental materials) by adding Zirconium Oxide ZrO₂ in both micro and nano particles. GIC were mixed with (3, 5 and 7) wt% of both ZrO₂ micro and nanoparticles separately. Compressive strength (CS), biaxial flexural strength (BFS), Vickers Microhardness (VH) and wear rate losses (WR) were investigated. The maximum compression strength was 122.31 MPa with 5 wt. % ZrO₂ micro particle, while 3wt% nanoparticles give highest Microhardness and biaxial flexural strength of 88.8 VHN and 35.79 MPa respectively. The minimum wear rate losses were 3.776µg/m with 7 wt. % ZrO₂ nanoparticle. GIC-contai

Flat-plate collector considers most common types of collectors, for ease of manufacturing and low price compared with other collectors. The main aim of the present work is to increase the efficiency of the collector, which can be achieved by improving the heat transfer and minimize heat loss experimentally. Five types of solar air collectors have been tested, which conventional channel with a smooth absorber plate (model I), dual channel with a smooth absorber plate (model II), dual channel with perforating “V” corrugated absorber plate (model III), dual channel with internal attached wire mesh (model Ⅳ), and dual channel with absorber sheet of transparent honeycomb, (model Ⅴ). The dual channel collector used for

Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in