A modified chemical method was used to prepare titanium dioxide nanoparticles (TiO2 NPs), which were diagnosed by several techniques: X-ray diffraction, Fourier transform infrared, field emission scaning electron microscopy, energy disperse X-ray, and UV-visible spectroscopy, which proved the success of the preparation process at the nanoscale level. Where the titanium oxide particles have an average particle size equal to 6.8 nm, titanium dioxide particles were used in the process of adsorption of Congo red dye from its aqueous solutions using a batch system. The titanium oxide particles gave an adsorption efficiency of Congo red dye up to more than 79 %. The experimental data of the adsorption process were analyzed with kinetic models and

The present study explores the solar-induced photocatalytic degradation of reactive red (RR) and reactive turquoise (RT) dyes in a single system using TiO2 immobilized in xanthan gum (TiO2/XG), synthesized using the sol–gel dip-coating technique for direct precipitation. SEM-EDX, XRD, FTIR, and UV–Vis were used to assess the characteristics of the resulting catalyst. Moreover, the effects of different operating parameters, specifically pH, dye concentration, TiO2/XG concentration, H2O2 concentration, and contact time, were also investigated in a batch photocatalytic reactor. The immobilized TiO2/XG catalyst showed a slight adsorption degradation efficiency and then improved the RR and RT dye degradation activity (92.5 and 90.8%

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

The increase globally fossil fuel consumption as it represents the main source of energy around the world, and the sources of heavy oil more than light, different techniques were used to reduce the viscosity and increase mobility of heavy crude oil. this study focusing on the experimental tests  and modeling with Back Feed Forward Artificial Neural Network (BFF-ANN) of the dilution technique to reduce a  heavy oil viscosity that was collected from the south- Iraq oil fields using organic solvents, organic diluents with different weight percentage  (5, 10 and  20 wt.% )  of  (n-heptane, toluene, and a mixture of  different ratio

Modified bentonite has been used as effective sorbent material for the removal of acidic dye (methyl orange) from aqueous solution in batch system. The natural bentonite has been modified using cationic surfactant (cetyltrimethyl ammonium bromide) in order to obtain an efficient sorbent through converting the properties of bentonite from hydrophilic to organophilic. The characteristics of the natural and modified bentonite were examined through several analyses such as Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and Surface area. The batch study was provided the maximum dye removal efficiency of 88.75 % with a sorption capacity of 555.56 mg/g at specified conditions (150 min, pH= 2, 250 rpm, and 0.

The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t

In this paper waste natural material (date seed) and polymer particles(UF) were used for investigation of  removal dye of the potassium permanganate. Also study effect some variables such as pH, dye concentration and adsorbent concentration on dye removal. 15 experimental runs were done using  the itemized conditions designed established on the Box-Wilson design employed to optimize dye removal. The optimum conditions for the dye removal were found: (pH) 12, (dye con.) 2.38 ppm, (adsorbant con.) 0.0816 gm for date seed with 95.22% removal and for UF (pH) 12, (dye con.) 18 ppm, (adsorbant con.) 0.2235 gm with 91.43%. The value of R-square was 85.47%  for Date seed  and (88.77%) for UF.