The electronic properties (such as energy gap HOMO levels. LUMO levels, density of state and density of bonds in addition to spectroscopic properties like IR spectra, Raman spectra, force constant and reduced masses as a function of frequency) of coronene C24 and reduced graphene oxide C24OX , where x=1-5, were studied.. The  methodology employed was  Density Functional Theory (DFT) with Hybrid function B3LYP and 6-311G** basis sets. The energy gap was calculated for C24 to be 3.5 eV and for C24Ox was from 0.89 to 1.6862 eV  for x=1-5 ,respectively.   These energy gaps values are comparable to the measured gap of Graphene (1-2.2 eV). The spectroscopic properties were  compared with experimental measurements, specificall

This work includes preparation of Az, Qz, and Tz derivatives from the reaction of Schiff base (Sb) derivative with anthranilic acid, chloroacetyl chloride, and sodium azide, as well as, the characterization via FT-IR, 1H-NMR, and 13CNMR. The anticorrosion inhibition of these compounds was studied and the measurements of carbon steel (CS) corrosion in sodium chloride solution 3.5% (blank) and inhibitor in solutions were calculated at a temperature range of 293-323 K by the technique of electrochemical polarization. In addition, some thermodynamic and kinetic activation parameters for inhibitor and blank solutions (Ea⋇, ΔH⋇, ΔS⋇, and ΔG⋇) were determined. The results showed high inhibition efficacy for all the prepared compounds,

Gas sensors are essential for detecting noxious gases that have a detrimental effect on people's health and welfare. Carbon quantum dots (CQDs) are the fundamental component of gas detectors. CQDs and graphene (Gr) were prepared using the electrochemical method. The gas sensitivity of these materials was evaluated at different temperatures (150, 200, 250 °C) to assess their effectiveness. Subsequently, experiments were conducted at different temperatures to ascertain that the combination of CQDs and Gr, with various percentages of Gr and CQDs, exhibited superior gas sensitization properties compared to CQDs alone. This was evaluated based on criteria such as sensitivity, recovery time, and reaction time. Interestingly, the combination was

The aim of the present work to study the effect of changing velocity (Reynold's number) on oxygen cathodic polarization using brass rotating cylinder electrode in 0.1, 0.3 and 0.5N NaCl solutions (PH = 7) at temperatures 40, 50 and 600 C. Cathodic polarization experiments were conducted as a function of electrode rotational speed and concentration.

This work is devoted to study the properties of the ground states such as the root-mean square ( ) proton, charge, neutron and matter radii, nuclear density distributions and elastic electron scattering charge form factors for Carbon Isotopes (9C, 12C, 13C, 15C, 16C, 17C, 19C and 22C). The calculations are based on two approaches; the first is by applying the transformed harmonic-oscillator (THO) wavefunctions in local scale transformation (LST) to all nuclear subshells for only 9C, 12C, 13C and 22C. In the second approach, the 9C, 15C, 16C, 17C and 19C isotopes are studied by dividing the whole nuclear system into two parts; the first is the compact core part and the second is the halo part. The core and halo parts are studied using the

The evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed

Aggregate production planning (APP) is one of the most significant and complicated problems in production planning and aim to set overall production levels for each product category to meet fluctuating or uncertain demand in future. and to set decision concerning hiring, firing, overtime, subcontract, carrying inventory level. In this paper, we present a simulated annealing (SA) for multi-objective linear programming to solve APP. SA is considered to be a good tool for imprecise optimization problems. The proposed model minimizes total production and workforce costs. In this study, the proposed SA is compared with particle swarm optimization (PSO). The results show that the proposed SA is effective in reducing total production costs and req

Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mo