Graphite nanoparticles were successfully synthesized using mixture of H2O2/NH4OH with three steps of oxidation. The process of oxidations were analysis by XRD and optics microscopic images which shows clear change in particle size of graphite after every steps of oxidation. The method depend on treatments the graphite with H2O2 in two steps than complete the last steps by reacting with H2O2/NH4OH with equal quantities. The process did not reduces the several sheets for graphite but dispersion the aggregates of multi-sheets carbon when removed the Van Der Waals forces through the oxidation process.

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

TiO2 thin films were deposited by reactive d.c magnetron sputtering method on a glass substrate with various ratio of gas flow (Oxygen /Argon) (50/50, 100/50 and 150/50) at substrate temperature 573K. It can be observe that the optical energy gap of TiO2 thin films dependent on the ratio of gas flow (oxygen/argon), it varies between (3.45eV-3.57eV) also it is seen that the optical constants (α, n, K, εr and εi ) has been varied with the change of the ratio of gas flow (Oxygen /Argon).

Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s

Abstract: Tin oxide thin films were deposited by direct current (DC) reactive sputtering at gas pressures of 0.015 mbar – 0.15 mbar. The crystalline structure and surface morphology of the prepared SnO2 films were introduced by X-ray diffraction (XRD) and atomic force microscopy (AFM). These films showed preferred orientation in the (110) plane. Due to AFM micrographs, the grain size increased non-uniformly as the working gas pressure increased.

The present work is devoted to investigate the performance of a homemade Y-shape catalytic microreactor for degradation of dibenzothiophene (DBT), as a model of sulphur compounds including in gas oil, utilizing solar incident energy. The microchannel was coated with TiO2 nanoparticles which were used as a photocatalyst. Performance of the microreactor was investigated using different conditions (e.g., DBT concentration, LHSV, operating temperature, and (H₂O₂/DBT) ratio). Our experiments show that, in the absence of UV light, no reaction takes place. The results revealed that outlet concentration of DBT decreases as the mean residence time in the microreactor increases. Also, it was noted that operating temperature s