In this work, silicon nitride (Si3N4) thin films were deposited on metallic substrates (aluminium and titanium sheets) by the DC reactive sputtering technique using two different silicon targets (n-type and p-type Si wafers) as well as two Ar:N2 gas mixing ratios (50:50 and 70:30). The electrical conductivity of the metallic (aluminium and titanium) substrates was measured before and after the deposition of silicon nitride thin films on both surfaces of the substrates. The results obtained from this work showed that the deposited films, in general, reduced the electrical conductivity of the substrates, and the thin films prepared from n-type silicon targets using a 50:50 mixing ratio and deposited on both surfaces of a titanium substrate reduced the electrical conductivity of this substrate by 30%. This reduction in the release of ions from the coated metal substrate is attributed to the dielectric properties of the deposited silicon nitride thin films. This result is very important and applicable. This work represents the first attempt in Iraq to study such effects and may represent a good starting point for advanced studies in biomedical engineering.
The problem of generated waste as a result of the implementation of construction projects, has been aggravated recently because of construction activity experienced by the world, especially Iraq, which is going through a period of reconstruction, where construction waste represents (20-40%) of the total generated waste and has a negative effect on the environment and economic side of the project. In addition, the rate of consumpted amounts of natural resources are estimated to be about 40% in the construction industry, so it became necessary to reduce waste and to be manage well. This study aims to identify the key factors affecting waste management through the various phases of the project, and this is accom
... Show MoreIn this paper, we investigate the basic characteristics of "magnetron sputtering plasma" using the target V2O5. The "magnetron sputtering plasma" is produced using "radio frequency (RF)" power supply and Argon gas. The intensity of the light emission from atoms and radicals in the plasma measured by using "optical emission spectrophotometer", and the appeared peaks in all patterns match the standard lines from NIST database and employed are to estimate the plasma parameters, of computes electron temperature and the electrons density. The characteristics of V2O5 sputtering plasma at multiple discharge provisos are studied at the "radio frequency" (RF) power ranging from 75 - 150 Wat
... Show MoreDestiny functional theory (DFT) calculations are undertaken in order to scrutinize the electrochemical and calcium (Ca) storage characteristics of a graphyne-like aluminum nitride monolayer (G-AlNyen) as an electrode material for Ca-ion batteries (CIBs). The results show that the change in internal energy as well as the cell voltage values for the CIB with the G-AlNyen anode are comparable to others with two-dimensional 2D nano-materials. It is shown that Ca is adsorbed primarily onto the center of a hexagonal and triangular ring of G-AlNyen with absorption energies of −2.06 and −0.42 eV. After increasing the concentration of Ca atoms on G-AlNyen, the adsorption energy as well as the cell voltage decreases. Lower values of 0.15–0.32 e
... Show MorePorous silicon (PS) layers were formed on n-type silicon (Si) wafers using Photo- electrochemical Etching technique (PEC) was used to produce porous silicon for n-type with orientation of (111). The effects of current density were investigated at: (10, 20, 30, 40, and50) mA/cm2 with etching time: 10min. X-ray diffraction studies showed distinct variations between the fresh silicon surface and the synthesized porous silicon. The maximum crystal size of Porous Silicon is (33.9nm) and minimum is (2.6nm) The Atomic force microscopy (AFM) analysis and Field Emission Scanning Electron Microscope (FESEM) were used to study the morphology of porous silicon layer. AFM results showed that root mean square (RMS) of roughness and the grain size of p
... Show MoreA simple physical technique was used in this study to create stable and cost-effective copper oxide (CuO) nanoparticles from pure copper metal using the pulsed laser ablation technique. The synthesis of crystalline CuO nanoparticles was confirmed by various analytical techniques such as particle concentration measurement using atomic absorption spectrometry (AAS), field emission scanning electron microscopy (FE-SEM), the energy dispersive X-ray (EDX), and X-ray diffraction (XRD) to determine the crystal size and identify of the crystal structure of the prepared particles. The main characteristic diffraction peaks of the three samples were consistent. The corresponding 2θ is also consistent, and the cytotoxicity of the nanoparticles was
... Show MoreIn this paper, a design of the broadband thin metamaterial absorber (MMA) is presented. Compared with the previously reported metamaterial absorbers, the proposed structure provides a wide bandwidth with a compatible overall size. The designed absorber consists of a combination of octagon disk and split octagon resonator to provide a wide bandwidth over the Ku and K bands' frequency range. Cheap FR-4 material is chosen to be a substate of the proposed absorber with 1.6 thicknesses and 6.5×6.5 overall unit cell size. CST Studio Suite was used for the simulation of the proposed absorber. The proposed absorber provides a wide absorption bandwidth of 14.4 GHz over a frequency range of 12.8-27.5 GHz with more than %90 absorp
... Show MoreIn this work, a deep computational study has been conducted to assign several qualities for the graph . Furthermore, determine the amount of the dihedral subgroups in the Held simple group He through utilizing the attributes of gamma.
Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
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