This contribution investigates the impact of adding transition metal of Ti to CeOy samples at various concentrations referring to 0, 15.84, 24.46, 34.46, 36.23, 38.46, 45.38% and pure TiOy, correspondingly. The samples were fabricated by the magnetron sputtering technique. X-ray diffraction (XRD) configurations demonstrate the presence of α-Ce2O3 and Ce2O3 phases with increased Ti contents in the systems. X-ray photoelectron spectroscopy (XPS) experimentation confirms the purity of the S1-sample (CeO2) and the purity of the S8-sample (TiO2). Further XPS analysis reveals that Ti incorporation in the doped systems functions as a reducing agent because of the existence of α-Ce2O3 and Ce2O3 phases. Moreover, based on UV–vis spectroscopy res

This contribution investigates the impact of adding transition metal of Ti to CeOy samples at various concentrations referring to 0, 15.84, 24.46, 34.46, 36.23, 38.46, 45.38% and pure TiOy, correspondingly. The samples were fabricated by the magnetron sputtering technique. X-ray diffraction (XRD) configurations demonstrate the presence of α-Ce2O3 and Ce2O3 phases with increased Ti contents in the systems. X-ray photoelectron spectroscopy (XPS) experimentation confirms the purity of the S1-sample (CeO2) and the purity of the S8-sample (TiO2). Further XPS analysis reveals that Ti incorporation in the doped systems functions as a reducing agent because of the existence of α-Ce2O3 and Ce2O3 phases. Moreover, based on UV–vis spectroscopy res

In 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.

This work includes synthesis of new six membered heterocyclic rings with effective amino group using the reaction of benzylideneacetophenone (chalcone) (1) with thiourea or urea in alcoholic basic medium to form: 1,3-thiazen-2-amine (2), and 1,3-oxazin-2-amine (8) respectively. The diazotization reaction was carried out with sodium nitrite in presence of hydrochloric acid to form diazonium salts which suffered coupling reaction with naphthols and phenols in the presence of sodium hydroxide to form colored azo dyes (4-7, and 10-13). o-methylation reaction of compounds (7) and (10) yielded : 1,3-thiazin -2-yl-diazenyl (14), and 1,3-oxazin-2-yl-diazenyl (15) respectively.The new compounds were characterized using vario

Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use

The estimation of the initial oil in place is a crucial topic in the period of exploration, appraisal, and development of the reservoir. In the current work, two conventional methods were used to determine the Initial Oil in Place. These two methods are a volumetric method and a reservoir simulation method. Moreover, each method requires a type of data whereet al the volumetric method depends on geological, core, well log and petrophysical properties data while the reservoir simulation method also needs capillary pressure versus water saturation, fluid production and static pressure data for all active wells at the Mishrif reservoir. The petrophysical properties for the studied reservoir is calculated using neural network technique