A series of overbased magnesium fatty acids such as caprylate, caprate, laurate, myristate, palmitate, stearate and oleate) were synthesized by the reaction of the fatty acids with active – 60 magnesium oxide and carbon dioxide (CO2) gas at 60 oC in the presence of ammonia solution as catalyst, toluene / ethanol solvent mixture (9:1vol/vol) was added.
The prepared detergent additives were characterized by FTIR, 1HNMR and evaluated by blending each additive in various concentrations with medium lubricant oil fraction (60 stock) supplied by Iraqi Midland Refineries Company. The total base number (TBN, mg of KOH/g) was determined, and the results of TBN were treated by using two-way analysis of variance (ANOVA) test. It was found that

In this work, silver (Ag) self-metallization on a polyimide (PI) film was prepared through autocatalytic plating. PI films were prepared through the solution casting method, followed by etching with potassium hydroxide (KOH) solution, sensitization with tin chloride (SnCl₂), and the use of palladium chloride (PdCl₂) to activate the surface of PI. Energy-dispersive X-ray analysis (EDX) showed the highest peak in the (Ag) region and confirmed the presence of AgNPs. The diffraction peaks at 2θ = 38.2^°, 44.5^°, 64.6^°, and 78.2^° represented the 111, 200, 220, and 311 planes of Ag, respectively. The FT–IR an

In this study, polymeric ultrafiltration (UF) membranes were prepared by phase inversion method to obtain both antibacterial and organic antifouling properties. The membranes were cast from a solution of polyvinylidene fluoride (PVDF) and formative silver (Ag) nanoparticles were successfully immobilized on a polymer. This was done using a solvent N, N-dimethylformamide (DMF) which is a solvent for the PVDF polymer meanwhile it is a reducing agent for silver ion. The effect of silver nanoparticles additives on the performance of polymeric ultrafiltration membrane was verified. Chemical composition and morphology of the surfaces of the membranes were characterized by Fourier transform infrared spectroscopy

Four batches of sertraline HCl microspheres were prepared using a poly (D-L-lactide-co-glycolide) (PLGA) polymer ( Mw. 9, 27, 30 and 83 KDa) as  a delivery system. The microspheres were prepared by a dispersion/solvent extraction-evaporation method and characterized for drug loading by UV, particle size by laser diffractometry and surface morphology by scanning electron microscopy (SEM). The in vitro sertraline HCl release was studied. Spherical microspheres with a mean diameter of 21 to 26 µm loaded with 24.6 – 38.2% were produced. The in vitro drug release was shown to be depend on polymer molecular weight and also on the drug loading. Differential scanning calorimetry (DSC) was employed to investigate the physical state

In this research four steps of the new derivatives of Naproxen drug have been made which are known as a high medicinal effectiveness; the first step involved converting Naproxen into the corresponding ester (A) by reaction Naproxen with methanol absolute in presence H2SO4. While the second step involved treatment methyl Naproxen ester (A) with hydrazine hydrate 80% in presence of ethanol .The third reaction requires synthesis of Schiff bases (C1-C10) by condensation. of Naproxen hydrazide (B) with many substituted aromatic aldehydes . Finally, the fourth step synthesized new tetrazole derivatives ( D1- D10) by the reaction of the prepared Schiff bases (in the third step) with Sodium azide in THF as a solvent .The prepared compounds wer

The optimization of artificial gas lift techniques plays a crucial role in the advancement of oil field development. This study focuses on investigating the impact of gas lift design and optimization on production outcomes within the Mishrif formation of the Halfaya oil field. A comprehensive production network nodal analysis model was formulated using a PIPESIM Optimizer-based Genetic Algorithm and meticulously calibrated utilizing field-collected data from a network comprising seven wells. This well group encompasses three directional wells currently employing gas lift and four naturally producing vertical wells. To augment productivity and optimize network performance, a novel gas lift design strategy was proposed. The optimization of

Particulate matter (PM) emitted from diesel engine exhaust have been measured in terms of mass, using
99.98 % pure ethanol blended directly, without additives, with conventional diesel fuel (gas – oil),to
get 10 % , 15 %, 20 % ethanol emulsions . The resulting PM collected has been compared with those
from straight diesel. The engine used is a stationary single cylinder, variable compression ratio Ricardo
E6/US. This engine is fully instrumented and could run as a compression or spark ignition.
Observations showed that particulate matter (PM) emissions decrease with increasing oxygenate
content in the fuel, with some increase of fuel consumption, which is due to the lower heating value of
ethanol. The reduction in

Due to the dramatic environmental impact of sulfur emissions associated with the exhaust of diesel engines, last environmental regulations for ultra-low-sulfur diesel require a very deep desulfurization (up to 15 ppm), which cannot be met by the conventional hydrodesulfurization units alone. The proposed method involves a batch ultrasound-assisted oxidative desulfurization (UAODS) of a previously hydrotreated diesel (containing 480 ppm sulfur) so as to convert the residual sulfur-bearing compounds into their corresponding highly polar oxides, which can be eliminated easily by extraction with a certain highly polar solvent. The oxidizing system utilized was H₂O₂ as an oxidant, CH₃COOH as a

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

Biodiesel is an environmentally friendly fuel and a good substitution for the fossil fuel. However, the purity of this fuel is a major concern that challenges researchers. In this study, a calcium oxide based catalyst has been prepared from local waste eggshells by the calcination method and tested in production biodiesel. The eggshells were powdered and calcined at different temperatures (700, 750, 800, 850 and 900 °C) and periods of time (1, 2, 3, 4 and 5 hr.). The effect of calcination temperature and calcination time on the structure and activity of the solid catalyst were examined by X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and Brunaure-Emmett-Teller (BET). The optimum catalyst performance was obtained at 900 °C