Three-dimensional nonlinear thermal numerical simulations are conducted for the friction stir welding (FSW) of AA 7020-T53. Three welding cases with tool (rotational and travel) speeds of 900rpm-40mm/min, 1400rpm-16mm/min and 1400rpm-40mm/in are analyzed. The objective is to study the variation of transient temperature in a friction stir welded plate of 5mm workpiece thickness. Based on the experimental records of transient temperature at several specific locations during the friction stir welding process for the AA 7020-T53, thermal numerical simulation is developed. The numerical results show that the temperature field in the FSW process is symmetrically distributed with respect to the welding line, increasing travel speed decreasing tran

The paper discusses the structural and optical properties of In2O3 and In2O3-SnO2 gas sensor thin films were deposited on glass and silicon substrates and grown by irradiation of assistant microwave on seeded layer nucleated using spin coating technique. The X-ray diffraction revealed a polycrystalline nature of the cubic structure. Atomic Force Microscopy (AFM) used for morphology analysis that shown the grain size of the prepared thin film is less than 100 nm, surface roughness and root mean square for In2O3 where increased after loading SnO2, this addition is a challenge in gas sensing application. Sensitivity of In2O3 thin film against NO2 toxic gas is 35% at 300oC. Sensing properties were improved after adding Tin Oxide (SnO2) to be mo

The gas chromatography (GC) method in analytical chemistry is a quick and accurate method to detect volatile components like ethanol. A method for determining volatile components known as Headspace chromatography (HS-GC) was developed along with an internal standard method (ISM) to identify ethanol in fermented broth in the laboratory. The aim of this research is determining the concentration of ethanol in fermented broth using capillary column (ZB-1). This method can analyze ethanol concentrations in the fermented medium broth ranging from 10 to 200 g/L. The validation of this method was done in order to obtain the results to be of high precision and the significant, precision was represented as the relative standard deviation (RSD) which

The pure ZnS and ZnS-Gr nanocomposite have been prepared
successfully by a novel method using chemical co-precipitation. Also
conductive polymer PPy nanotubes and ZnS-PPy nanocomposite
have been synthesized successfully by chemical route. The effect of
graphene on the characterization of ZnS has been investigated. X-ray
diffraction (XRD) study confirmed the formation of cubic and
hexagonal structure of ZnS-Gr. Dc-conductivity proves that ZnS and
ZnS-Gr have semiconductor behavior. The SEM proved that
formation of PPy nanotubes and the Gr nanosheet. The sensing
properties of ZnS-PPy/ZnS-Gr for NO2 gas was investigated as a
function of operating temperature and time under optimal condition.
The sensitivity,

Computer modeling has been used to investing the Coulomb coupling parameter ?. The effects of the structure parameter K, grain charge Z, plasma density N, temperature dust grain Td, on the Coulomb coupling parameter had been studied. It was seen that the ? was increasing with increasing Z and N, and decrease with increasing K and T. Also the critical value of ? that the phase transfer of the plasma state from liquid to solid was studied.

Nano-crystalline iron oxide nanoparticles (magnetite) was synthesized by open vessel ageing process. The iron chloride solution was prepared by mixing deionized water and iron chloride tetrahydrate. The product was characterized by X-Ray, Surface area and pore volume by Brunauer-Emmet-Teller, Atomic Force Microscope (AFM) and Fourier Transform Infrared Spectroscopy(FTIR)  .  The results showed that the XRD in compatibility of the prepared iron oxide (magnetite) with the general  structure of standard iron oxide, and in Fourier Transform Infrared Spectroscopy, it is strong crests in 586 bands, because of  the expansion vibration manner related to the metal oxygen absorption band (Fe–O bonds in the crystals of iron ox

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp