Nano gamma alumina was prepared by double hydrolysis process using aluminum nitrate nano hydrate and sodium aluminate as an aluminum source, hydroxyle poly acid and CTAB (cetyltrimethylammonium bromide) as templates. Different crystallization temperatures (120, 140, 160, and 180) ⁰C and calcinations temperatures (500, 550, 600, and 650) ⁰C were applied. All the batches were prepared at PH equals to 9. XRD diffraction technique and infrared Fourier transform spectroscopy were used to investigate the phase formation and the optical properties of the nano gamma alumina. N₂ adsorption-desorption (BET) was used to measure the surface area and pore volume of the prepared nano alumina, the particle size and the

Tin Selenide (SnSe) Nano crystalline thin films of thickness 400±20 nm were deposited on glass substrate by thermal evaporation technique at R.T under a vacuum of ∼ 2 × 10− 5 mbar to study the effect of annealing temperatures (as-deposited, 100, 150 and 200) °C on its structural, surface morphology and optical properties. The films structure was characterized using X-ray diffraction (XRD) which showed that all the films have polycrystalline in nature and orthorhombic structure, with the preferred orientation along the (111) plane. These films was synthesized of very fine crystallites size of (14.8-24.5) nm, the effect of annealing temperatures on the cell parameters, crystallite size and dislocation density were observed.

This research delves into the realm of asphalt technology, exploring the potential of nano-additives to enhance traditional asphalt binder properties. Focusing on Nano-Titanium Dioxide (NT), Nano-Aluminum Oxide (NA), and Nano-Silica Oxide (NS), this study investigates the effects of incorporating these nanomaterials at varying dosages, ranging from 0% to 8%, on the asphalt binder’s performance. This study employs a series of experimental tests, including consistency, storage stability, rotational viscosity, mass loss due to aging, and rheological properties, to assess the impact of nano-additives on asphalt binder characteristics. The findings indicate a substantial improvement in the consistency of the asphalt binder with the add

Addition of bioactive materials such as Titanium oxide (TiO₂), and incorporation of bio inert ceramic such as alumina (Al₂O₃), into polyetheretherketone (PEEK) has been adopted as an effective approach to improve bone-implant interfaces. In this paper, hot pressing technique has been adopted as a production method. This technique gave a homogenous distribution of the additive materials in the proposed composite biomaterial. Different compositions and compounding temperatures have been applied to all samples. Mechanical properties and animal model have been studied in all different production conditions. The results of these new TiO₂/Al₂O₃/PEEK biocomposites with different

This study was undertaken to prepare Nano zinc oxide (ZnO) by precipitation and microemulsion methods. Scanning electron microscopy (SEM), X-ray diffraction (XRD), FTIR spectrometry, atomic force microscopy (AFM), and Brunauer Emmett Teller (BET) surface area were the techniques employed for the preparation. The particle size of prepared nano ZnO was 69.15nm and 88.49nm for precipitation and microemulsion methods, respectively, which corresponded to the BET surface area 20.028 and 16.369m²/g respectively. The activity of prepared nano ZnO as a photocatalyst was estimated by the removal of ampicillin (Amp) under visible light. This study, therefore, examined the effect of pH in the range of 5-11, initial concen

This work presents the study of the dark current density and the capacitance for porous silicon prepared by photo-electrochemical etching for n-type silicon with laser power density of 10mw/cm2 and wavelength (650nm) under different anodization time (30,40,50,60) minute. The results obtained from this study shows different chara that different characteristic of porous diffecteristics for the different porous Silicon layers.

This research delves into the realm of asphalt technology, exploring the potential of nano-additives to enhance traditional asphalt binder properties. Focusing on Nano-Titanium Dioxide (NT), Nano-Aluminum Oxide (NA), and Nano-Silica Oxide (NS), this study investigates the effects of incorporating these nanomaterials at varying dosages, ranging from 0% to 8%, on the asphalt binder’s performance. This study employs a series of experimental tests, including consistency, storage stability, rotational viscosity, mass loss due to aging, and rheological properties, to assess the impact of nano-additives on asphalt binder characteristics. The findings indicate a substantial improvement in the consistency of the asphalt binder with the add

A simple low-cost approach at various exposure times was utilized to generate cold plasma in the aim to fabricate AuNPs. UV-Visible spectra and X-ray diffraction were used to characterize the nanoparticles (XRD). Surface Plasmon resonance was observed in the synthesized AuNPs at 530, 540, and 533 nm. For all samples, the patterns of XRD show very intensive peaks implying the fcc crystalline structure of AuNPs. The average crystallite size of AuNPs is ranging between 20-30 nm. The observation of morphology by FESEM revealed the spherical formation of AuNPs. Doses of 100 and 200 ppm of AuNPs were adapted to investigate their effect on the blood-mixture with and without a 20-second of cold plasma exposure. The WBC components in the blood

The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be