Hydrophobic silica aerogels were successfully preparation by an ambient pressure drying method from sodium silicate (Na2SiO3) with different pH values (5, 6, 7, 8, 9 and 10). In this study, acidic HCl (1M), a basic NH4OH (1M) were selected as a catalyst to perform the surface modification in a TMCS (trimethylchlorosilane) solution. The surface chemical modification of the aerogels was assured by the Fourier transform infrared (FTIR) spectroscopic studies. Other physical properties, such as pore volume and pore size and specific surface area were determined by Brunauer-Emmett- Teller (BET) method. The effect of pH values on the bulk density of aerogel. The sol–gel parameter pH value in the sol, have marked effects on the physical proper

This work aim to prepare Ag/R6G/PMMA nanocomposite thin
films by In-situ plasma polymerization and study the changes in the
optical properties of fluorophore due to the presence of Ag
nanoparticles structures in the vicinity of the R6G laser dye. The
concentrations of R6G dye/MMA used are: 10-4M solutions were
prepared by dissolving the required quantity of the R6G dye in
MMAMonomer. Then Silver nanoparticles with 50 average particles
size were mixed with MMAmonomer with concentration of 0.3, 0.5,
0.7wt% to get R6G silver/MMA in liquid phase. The films were
deposited on glass substrates by dielectric barrier discharge plasma
jet. The Ag/R6G/PMMA nanocomposite thin films were
characterization by UV-Visible

An inert matrix  that is used to control the release of  (PTX) was prepared using Eudragit RL100 and RSPM types as matrix forming agent . The matrices were prepared by either dry granulation(slugging) , or wet granulation method using chloroform as a solvent evaporation vehichle. The cumulative release was adjusted by using polyvinylpyrollidone (PVP) or ethylcellulose (EC) polymers .The results indicated that   both methods of preparation were valid for incorporation PTX as a sustained release granules .Moreover ,the results revealed that best polymer used  was Eudragit RSPM in 3:20 polymer drug ratio .Besides to that ,   the results indicated that the release profiles were affected by  pH- medium&

Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partia

This study was undertaken to diagnose routine settling problems within a third-party oil and gas companies’ Mono-Ethylene Glycol (MEG) regeneration system. Two primary issues were identified including; a) low particle size (<40 μm) resulting in poor settlement within high viscosity MEG solution and b) exposure to hydrocarbon condensate causing modification of particle surface properties through oil-wetting of the particle surface. Analysis of oil-wetted quartz and iron carbonate (FeCO₃) settlement behavior found a greater tendency to remain suspended in the solution and be removed in the rich MEG effluent stream or to strongly float and accumulate at the liquid-vapor interface in comparison to naturally water-wetted particles. As su

The goal of this work is to check the presence of PNS (photon number splitting) attack in quantum cryptography system based on BB84 protocol, and to get a maximum secure key length as possible. This was achieved by randomly interleaving decoy states with mean photon numbers of 5.38, 1.588 and 0.48 between the signal states with mean photon numbers of 2.69, 0.794 and 0.24. The average length for a secure key obtained from our system discarding the cases with Eavesdropping was equal to 125 with 20 % decoy states and 82 with 50% decoy states for mean photon number of 0.794 for signal states and 1.588 for decoy states.

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve