Based on nonlinear self- diffraction technique, the nonlinear optical properties of thin slice of matter can be obtained. Here, nonlinear characterization of nano-fluids consist of hybrid Single Wall Carbon Nanotubes and Silver Nanoparticles (SWCNTs/Ag-NPs) dispersed in acetone at volume fraction of 6x10-6, 9x10-6, 18x10-6 have been investigated experimentally. Therefore, CW DPSS laser at 473 nm focused into a quartz cuvette contains the previous nano-fluid was utilized. The number of diffraction ring patterns (N) has been counted using Charge - Coupled- Device (CCD) camera and Pc with a certain software, in order to find the maximum change of refractive index ( of fluids. Our result show that the fraction volume of 18x10-6 is more nonli

The Albian Carbonate-clastic succession in the present study is represented by the Mauddud and Nahr Umr formations were deposited during the Albian stage within the Wasia Group More than 200 thin sections of cores and cuttings in addition to well logs data for Nahr Umr and Mauddud formations from 4 boreholes within two oil fields (Ba-4, Ba-8, Ns-2 and Ns-4) were used to interpret the different associations facies as well as the facies architectures to describe the sedimentary framework of the basin and development the petrophysical properties. Seven major microfacies were diagnosed in the carbonate succession of the Mauddud Formation, while the Nar Umr Formation includes five lithofacies; their grain types characteristic and deposit

A metal-assisted chemical etching process employing p-type silicon wafers with varied etching durations is used to produce silicon nanowires. Silver nanoparticles prepared by chemical deposition are utilized as a catalyst in the formation of silicon nanowires. Images from field emission scanning electron microscopy confirmed that the diameter of SiNWs grows when the etching duration is increased. The photoelectrochemical cell's characteristics were investigated using p-type silicon nanowires as working electrodes. Linear sweep voltammetry (J-V) measurements on p-SiNWs confirmed that photocurrent density rose from 0.20 mA cm^-2 to 0.92 mA cm^-2 as the etching duration of prepared SiNWs increased from 15 to 30 min. The

The photo-electrochemical etching (PECE) method has been utilized to create pSi samples on n-type silicon wafers (Si). Using the etching time 12 and 22 min while maintaining the other parameters 10 mA/cm² current density and HF acid at 75% concentration.. The capacitance and resistance variation were studied as the temperature increased and decreased for prepared samples at frequencies 10 and 20 kHz. Using scanning electron microscopy (SEM), the bore width, depth, and porosity % were validated. The formation of porous silicon was confirmed by x-ray diffraction (XRD) patterns, the crystal size was decreased, and photoluminescence (PL) spectra revealed that the emission peaks were centered at 2q of 28.5619° and 28.7644° for et

Industrial characteristics calculations concentrated on the physical properties for break down voltage in sf6, cf4 gases and their mixture with different concentrations are presented in our work. Calculations are achieved by using an improved modern code simulated on windows technique. Our results give rise to a compatible agreement with the other experimental published data.

Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye