Bimetallic Au –Pt catalysts supporting TiO2 were synthesised using two methods; sol immobilization and impregnation methods. The prepared catalyst underwent a thermal treatment process at 400◦ C, while the reduction reaction under the same condition was done and the obtained catalysts were identified with transmission electron microscopy (TEM) and energy-dispersive spectroscopy (EDS). It has been found that the prepared catalysts have a dimension around 2.5 nm and the particles have uniform orders leading to high dispersion of platinum molecules .The prepared catalysts have been examined as efficient photocatalysts to degrade the Crystal violet dye under UV-light. The optimum values of Bimetallic Au –Pt catalysts supporting TiO2 have been found (0.05g of the catalyst prepared in sol immobilization method, 0.07 g of the synthesised in impregnation procedure. The impact of pH on the degradation reaction was tested; it has been found that pH 10 is the best media for the reaction. The effect of temperature has been discussed when various temperatures were used, and the heat of photoreaction Ea was estimated from the Arrhenius relationship, it has been concluded that the reaction is independent of temperature as the activation energy was very small (Ea= 22 kJ/ mole). The thermodynamic functions; entropy, enthalpy and the free energy have been figured out. It has been found that the positive values of enthalpy ∆H# refer to endothermic reaction, moreover, it has been demonstrated that the photoreaction is an endergonic one according to the calculated values of the free energy of activation. It has been noticed that when temperature increases, it promotes the production of free radicals, but it has been noticed that exceeding the temperature more than the used range causes reducing the percentage of degradation of crystal violet, the reason is due to the limitation conditions of adsorption process at higher temperature on the surface of the catalyst.
Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob
... Show MoreOur work included a synthesis of three new imine derivatives—1,3-thiazinan-4-one, 1,3-oxazinan-6-one and 1,3-oxazepin-4,7-dione—which contained an adamantyl fragment. These were produced via the condensation of the Schiff`s base (E)-N-(adamantan-1-yl)-1-(3-aryl)methanimine with 3-mercaptopropanoic acid; 3-chloropropanoic acid; and maleic, citraconic anhydride, respectively. These new imines were prepared via the condensation of adamantan-1-ylamine and 3-nitro-, 3-bromobenzaldehyde in n-BuOH. We obtained a good yield of products. FTIR, 1H NMR spectroscopy and C.H.N.S analysis were used to diagnostic the products. The molecular structure of (E)-N-(adamantan-1-yl
... Show MoreIn this research the a-As flims have been prepared by thermal evaporation with thickness 250 nm and rata of deposition r_d(1.04nm/sec) as function to annealing temperature (373 and 473K), from XRD analysis we can see that the degree of crystalline increase with T_a, and I-V characteristic for dark and illumination shows that forward bias current varieties approximately exponentially with voltage bias. Also we found that the quality factor and saturation current dependence on annealing temperatures.
In this research the a-As flims have been prepared by thermal evaporation with thickness 250 nm and rata of deposition (1.04nm/sec) as function to annealing temperature (373 and 373K), from XRD analysis we can see that the degree of crystalline increase with , and I-V characteristic for dark and illumination shows that forward bias current varieties approximately exponentially with voltage bias. Also we found that the quality factor and saturation current dependence on annealing temperatures.
Fullerene nanotube was synthesized in this research by pyrolysis of plastic waste Polypropylene (PP) at 1000 ° C for two hours in a closed reactor made from stainless steel using molybdenum oxide (MoO3) as a catalyst and nitrogen gas. The resultant carbon was purified and characterized by energy dispersive X-ray spectroscopy (EDX), X-ray powder diffraction (XRD). The surface characteristics of C60 nanotubes were observed with the Field emission scanning electron microscopy (FESEM). The carbon is evenly spread and has the highest concentration from SEM-EDX characterization. The result of XRD and FESEM shows that C60 nanotubes are present in Nano figures, synthesized at 1000 ° C and with pyrolysis tempera
... Show MoreThe effect of the magnetic abrasive finishing (MAF) method on the temperature rise (TR), and material removal rate (MRR) has been investigated in this paper. Sixteen runs were to determine the optimum temperature in the contact area (between the abrasive powder and surface of workpiece) and the MRR according to Taguchi orthogonal array (OA). Four variable technological parameters (cutting speed, finishing time, working gap, and the current in the inductor) with four levels for each parameter were used, the matrix is known as a L16 (44) OA. The signal to noise ratio (S/N) ratio and analysis of the variance (ANOVA) were utilized to analyze the results using (MINITAB17) to find the optimum condition and identify the significant p
... Show MoreFeed Forward Back Propagation artificial neural network (ANN) model utilizing the MATLAB Neural Network Toolbox is designed for the prediction of surface roughness of Duplex Stainless Steel during orthogonal turning with uncoated carbide insert tool. Turning experiments were performed at various process conditions (feed rate, cutting speed, and cutting depth). Utilizing the Taguchi experimental design method, an optimum ANN architecture with the Levenberg-Marquardt training algorithm was obtained. Parametric research was performed with the optimized ANN architecture to report the impact of every turning parameter on the roughness of the surface. The results suggested that machining at a cutting speed of 355 rpm with a feed rate of 0.07 m
... Show MoreAn investigation was conducted to suggest relations for estimating yield and properties of the improved light lubricating oil fraction produced from furfural extraction process by using specified regression.
Mass transfer in mixer-settler has been studied. Mass transfer coefficient of continuous phase, mass transfer coefficient of dispersed phase and the overall mass transfer coefficient extraction of light lubes oil distillate fraction by furfural are calculated in addition to all physical properties of individual components and the extraction mixtures.
The effect of extraction variables were studied such as extraction temperature which ranges from 70 to 110°C and solvent to oil ratio which ranges from 1:1 to 4:1 (wt/wt
... Show MoreThe objective of this work is to study the influence of end milling cutting process parameters, tool material and geometry on multi-response outputs for 4032 Al-alloy. This can be done by proposing an approach that combines Taguchi method with grey relational analysis. Three cutting parameters have been selected (spindle speed, feed rate and cut depth) with three levels for each parameter. Three tools with different materials and geometry have been also used to design the experimental tests and runs based on matrix L9. The end milling process with several output characteristics is solved using a grey relational analysis. The results of analysis of variance (ANOVA) showed that the major influencing parameters on multi-objective response w
... Show MoreIn this work, results of a mathematical analysis of the role of workpiece preheating in laser keyhole welding were presented. This analysis considered the steady-state welding as well as certain range of boundary conditions over which preheating effect would be indicated. This work is an attempt to interpret the role of preheating to increase welding depth and perform keyhole welding with high quality using physical and thermal properties of steel alloys.