Aleppo bentonite was investigated to remove ciprofloxacin hydrochloride from aqueous solution. Batch adsorption experiments were conducted to study the several factors affecting the removal process, including contact time, pH of solution, bentonite dosage, ion strength, and temperature. The optimum contact time, pH of solution and bentonite dosage were determined to be 60 minutes, 6 and 0.15 g/50 ml, respectively. The bentonite efficiency in removing CIP decreased from 89.9% to 53.21% with increasing Ionic strength from 0 to 500mM, and it increased from 89% to 96.9% when the temperature increased from 298 to 318 K. Kinetic studies showed that the pseudo second-order model was the best in describing  the adsorption sys

Nanotechnology is a continually expanding field for its uses and applications in multiple areas i.e. medicine, science, and engineering. Biosynthesis is straightforward, less-toxicity, and cost-effective technology. TiO2 NPs biosynthesis has attained consideration in recent decades. In this study, probiotic bacteria were isolated from cow’s raw milk samples, and then were identified by using the Vitek2 system; as Leuconostoc spp. included Leuconostoc mesenteroides subsp. mesenteroides (Leu.1), Leuconostoc mesenteroides subsp. cremoris (Leu.4), and Leuconostoc pseudomesenteroides (Leu.14). All Leuconostoc spp. isolates showed an ability for TiO2 NPs bio-production, after being incubated at anaerobic conditions (30 o C/ 24 h) in DeM

The adsorption of Cr (VI) from aqueous solution by spent tea leaves (STL) was studied at different initial Cr (VI) concentrations, adsorbent dose, pH and contact time under batch isotherm experiments The adsorption experiments were carried out at 30°C and the effects of the four parameters on chromium uptake to establish a mathematical model description percentage removal of Cr (VI). The
analysis results showed that the experimental data were adequately fitted to second order polynomial model with correlation coefficients for this model was (R2 = 0.9891). The optimum operating parameters of initial Cr (VI) concentrations, adsorbent dose, pH and contact time were 50 mg/l, 0.7625 g, 3 and 100 min, respectively. At these conditions, th

Iraqi crude Atmospheric residual fraction supplied from al-Dura refinery was treated to remove metals contaminants by solvent extraction method, with various hydrocarbon solvents and concentrations. The extraction method using three different type solvent (n-hexane, n-heptane, and light naphtha) were found to be effective for removal of oil-soluble metals from heavy atmospheric residual fraction. Different solvents with using three different hydrocarbon solvents (n-hexane, n-heptane, and light naphtha) .different variables were studied solvent/oil ratios (4/1, 8/1, 10/1, 12/1, and 15/1), different intervals of perceptual (15, 30-60, 90 and 120 min) and different temperature (30, 45, 60 and 90 °C) were used. The metals removal perce

This work dealt with separation of naphthenic hydrocarbons from non-naphthenic hydrocarbons and in particular concerns an improved process for increasing the naphthenes concentration in naphtha, The separation was examined using adsorption by Y and  B zeolite in a fixed bed process. The concentration of naphthenes in the influent and effluent streams was determined using PONA classification. The effect of different operating variables such as feed flow rate (2- 4 L/hr); bed length (50 - 80 cm) on the adsorption capacity of Y and  zeolite was studied. Increasing the bed length lead to increase the naphthenes concentration, and increasing the flow rate lead to decrease in the concentration of naphthenes, It was found that the decrease

Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in