Exploration activities of the oil and gas industry generate loads of formation water called produced water (PW) up to thousands of tons each day. Depending on the geographic area, formation depth, oil production techniques, and age of oil supply wells, PW from different oil fields contain different chemical compositions. Currently, PW is also known as industrial waste water containing heavy metals that are toxic to humans and the environment, requiring special processing so that they can be disposed of in the environment. To determine the heavy metals content in PW from the Al-Ahdab oil field (AOF), the Ministry of Science and Technology/Agricultural Research Department determined some parameters including the concentrations of Cd, Co, Cr, Pd, and Ni using instrument inductively couple plasma (ICP-OES). Results of this study showed high concentrations of Cd (0.51-2.05, Cr (0.06-1.81), Co (0.11-0.72), Ni (0.12-0.22) and Pb (5.52-20.6) in the AOF compared to concentrations in water bodies about 16 km outside the field; Cd (0.01-0.32), Cr (0.01-0.11), Co (0.03-0.18), Ni (0.02-0.11) and Pb (0.04-1.73). These findings indicate there are increased levels of pollutants in the PW within the AOF of the Main Outfall Drain (MOD). The PW could not be as a source of drinking water and other daily activities, including fisheries and crop planting, unless advanced treatment, to remove the heavy metal content.
This research is presenting a study of optical and structural properties of (Fe2O3)1-x(MgO)x composites synthesized as thin film that can be used as a gas sensor. Pulsed laser deposition technique was used to prepare thin films of (Fe2O3)1-x(MgO)x. The pattern of X-ray diffraction of the composites powder showed the consistency of iron oxide (α-Fe2O3) hematite phase along with the planes (104) and (110) as preferred planes for crystal growth where the intensities of which varied with MgO content. The crystal size of the thin film material was varied in between (26.8-35.1) nm. The diffraction pattern of the pulsed laser deposited thin films was absent from any diffraction peaks. The maximum transparency obtained of hematite
... Show MoreThe present research was conducted to reduce the sulfur content of Iraqi heavy naphtha by adsorption using different metals oxides over Y-Zeolite. The Y-Zeolite was synthesized by a sol-gel technique. The average size of zeolite was 92.39 nm, surface area 558 m2/g, and pore volume 0.231 cm3/g. The metals of nickel, zinc, and copper were dispersed by an impregnation method to prepare Ni/HY, Zn/HY, Cu/HY, and Ni + Zn /HY catalysts for desulfurization. The adsorptive desulfurization was carried out in a batch mode at different operating conditions such as mixing time (10,15,30,60, and 600 min) and catalyst dosage (0.2,0.4,0.6,0.8,1, and 1.2 g). The most of the sulfur compounds were removed at 10 min for all catalyst types. The maximum
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Background Green synthesis of silver nanoparticles (AgNPs) using plant extracts has gained increasing attention as an environmentally friendly alternative to conventional chemical methods.
A Schiff base ligand (L) was used as primary ligand and potassium anthranilate (Anth) was used as the secondary ligand in the molar ratio M: L:2Anth to synthesize a new platinum(IV) mixed-ligand complex [Pt(L)(Anth)₂]Cl₂. The Schiff base ligand was synthesized by the condensation of 4-Aminoantipyrine with 4-Hydroxybenzaldehyde and was verified as a bidentate ligand. The UV-visible, FT-IR, 1 H NMR, 13 C NMR, CHN elemental analysis, molar conductance, chloride ion determination and melting point measurements were used to characterize the ligand and the complex. The results of the molar conductance showed that the electrolytic behavior was 1:2, where the two chloride ions were present outside the coordination sphere, while the spectroscopi
... Show MoreAmong the many modern skill-enhancing work practices, machine learning is among the mostskill-enhancing practices in the workplace, as it helps students remember more of what they havelearned, hone the technical talents and skills of football players, and make better use of theirmotor skills. The use of machine learning and its practical applications in football could havesignificant benefits by improving talent development and making better use of scientifictechniques. The primary objective of this study was to determine the effectiveness of machinelearning in improving soccer dribbling and passing accuracy in children aged 10-12 years. Thestudy authors hypothesized that soccer players in the Al-Zohour Neighborhood Youth Forumwould greatly
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