In this work, the spectra of plasma glow produced by Nd:YAG laser operated at 1.064 μm on Al-Mg alloys with same molar ratio samples in air were analyzed by comparing the atomic lines of aluminum and magnesium with that of strong standard lines. The effect of laser energies on spectral lines, produced by laser ablation, were investigated using optical spectroscopy, the electron density was measured utilizing the Stark broadening of magnesium-aluminum lines and the electron temperature was calculated from the standard Boltzmann plot method. The results that show the electron temperature increases in magnesium and aluminum targets but decreases in magnesium: aluminum alloy target, also show the electron density increase all the aluminum,

Abstract

Paraffin wax is utilized for the heat storage applications taking advantage from the high stored latent heat during the phase change (from solid to fluid) period. What isn't right with this procedure is that the wax has a little heat transfer rate because of its low thermal conductivity. The thermal conductivity improvement of the paraffin wax has been examined utilizing nano-material with high thermal conductivity. In the recent study, (Al₂O₃) nanoparticles with weights of 1, 2, and 3% of the paraffin wax were added to the paraffin wax. The Iraqi paraffin wax accessible at the local markets was utilized as a phase change material (PCM).

Many properties of the

Solubility problem of many of effective pharmaceutical molecules are still one of the major obstacle in theformulation of such molecules. Candesartan cilexetil (CC) is angiotensin II receptor antagonist with very low water solubility and this result in low and variable bioavailability. Self- emulsifying drug delivery system (SEDDS) showed promising result in overcoming solubility problem of many drug molecules. CC was prepared as SEDDS by using novel combination of two surfactants (tween 80 and cremophore EL) and tetraglycol as cosurfactant, in addition to the use of triacetin as oil. Different tests were performed in order to confirm the stability of the final product which includes thermodynamic study, determination of self-emulsificat

The parameters of resistance spot welding (RSW) performed on low strength commercial aluminum sheets are investigated experimentally, the performance requirements and weldability issues were driven the choice of a specific aluminum alloy that was AA1050. RSW aluminum alloys has a major problem of inconsistent quality from weld to weld comparing with welding steel
alloys sheet, due to the higher thermal conductivity, higher thermal expansion, narrow plastic temperature range, and lower electrical resistivity. Much effort has been devoted to the study of describing the relation between the parameters of the process (welding current, welding time, and electrode force) and weld strength. Shear-tensile strength tests were performed to ind

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.