In the present work polymer electrolytes were formulated using the solvent casting technique. Under special conditions, the electrolyte content was of fixed ratio of polyvinylpyrolidone (PVP): polyacrylonitrile (PAN) (25:75), ethylene carbonate (EC) and propylene carbonate (PC) (1:1) with 10% of potassium iodide (KI) and iodine I₂ = 10% by weight of KI. The conductivity was increased with the addition of ZnO nanoparticles. It is also increased with the temperature increase within the range (293 to 343 K). The conductivity reaches maximum value of about (0.0296 S.cm^-1) with (0.25 g) ZnO. The results of FTIR for blend electrolytes indicated a significant degree of interaction between the polymer blend (PVP and PAN)

Electrospun nanofiber membranes are employed in a variety of applications due to its unique features. the nanofibers' characterizations are effected by the polymer solution. The used solvent for dissolving the polymer powder is critical in preparing the precursor solution. In this paper, the Polyacrylonitrile (PAN)-based nanofibers were prepared in a concentration of 10 wt.% using various solvents (NMP, DMF, and DMSO). The surface morphology, porosity, and the mechanical strength of the three prepared 10 wt.% PAN-based nanofibers membranes (PAN/NMP, PAN/DMF, and PAN/DMSO) were characterized using the Scanning Electron Microscopy (SEM), Dry-wet Weights method, and Dynamic Mechanical Analyzer (DMA). Using DMF as a solvent resulted in a lon

           Titanium dioxide nanoparticles (TiO₂ NPs) are generally used in different types of applications such as the industry of plastics, paper industry, paints, toothpaste, cosmetics, sunscreens, and in various lifestyles, because of the vast range of applications and our daily exposure to these nanoparticles and a lack of information on animal and human health this study was designed to reveal dose and time-dependent effects of TiO₂-NPs on the thyroid gland and kidney functions in male rats.

For this study 54, Sprague-Dawley albino adult male rats were classified into three main groups each of 18 rats treated for a particular duration (1,2, and 4) weeks respectively. Each group was subdivided i

Zinc Oxide (ZnO) thin films of different thickness were prepared
on ultrasonically cleaned corning glass substrate, by pulsed laser
deposition technique (PLD) at room temperature. Since most
application of ZnO thin film are certainly related to its optical
properties, so the optical properties of ZnO thin film in the
wavelength range (300-1100) nm were studied, it was observed that
all ZnO films have high transmittance (˃ 80 %) in the wavelength
region (400-1100) nm and it increase as the film thickness increase,
using the optical transmittance to calculate optical energy gap (Eg
opt)
show that (Eg
opt) of a direct allowed transition and its value nearly
constant (~ 3.2 eV) for all film thickness (150

We prepared polythiophene (PTH) with single wall carbon nanotube (SWCNT) nanocomposite thin films for Nitrogen dioxide (NO2) gas sensing applications. Thin films were synthesized via electrochemical polymerization method onto (Indium tin oxide) ITO coated glass substrate of thiophene monomer with magnesium perchlorate and different concentration from SWCNT (0.012 and 0.016) % in the presence130mL of Acetonitrile used. X-ray diffraction (XRD), Field Emission Scanning Electron microscopy (FE-SEM), Atomic Force Microscope (AFM) and Fourier Transform Infrared Spectroscopy (FT-IR) were used to characterized these nanocomposite thin films. The response of these nanocomposite for NO₂ gas was evaluated via monitoring the change

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s