Ultimate oil recovery and displacement efficiency at the pore-scale are controlled by the rock wettability thus there is a growing interest in the wetting behaviour of reservoir rocks as production from fractured oil-wet or mixed-wet limestone formations have remained a key challenge. Conventional waterflooding methods are inefficient in such formation due to poor spontaneous imbibition of water into the oil-wet rock capillaries. However, altering the wettability to water-wet could yield recovery of significant amounts of additional oil thus this study investigates the influence of nanoparticles on wettability alteration. The efficiency of various formulated zirconium-oxide (ZrO2) based nanofluids at different nanoparticle concentrations (0-0.05 wt. %) was assessed through contact angle measurements. Results from the experiments showed ZrO2 nanofluid have great potentials in changing oil-wet limestone towards strongly water-wet condition. The best performance was observed at 0.05wt% ZrO2 nanoparticle concentration which changed an originally strongly oil-wet (152°) calcite substrate towards a strongly water-wet (44°) state thus we conclude that ZrO2 is a good agent for enhanced oil recovery.
This study investigates the influence of silver oxide (Ag₂O) nanoparticles on the gas-sensing properties of carbon nanotube (CNT) and poly(3-hexylthiophene) (P3HT) composite films. The goal is to enhance the sensitivity and stability of CNT/P3HT-based gas sensors for nitrogen dioxide (NO₂) detection. CNTs and P3HT are composited at various mass ratios, followed by integrating Ag₂O nanoparticles to improve gas interaction and electronic properties. Structural and morphological analyses, including x-ray diffraction, Fourier transform infrared spectroscopy, field emission scanning electron microscopy, and energy dispersive x-ray spectroscopy, ascertain the successful incorporation of Ag₂O into the composites and reveal its role in impr
... Show MoreThe annealing temperature (200–500 °C) effects of optical frequency response on the dielectric functions of sol–gel derived CuCoO
Bacterial resistance caused by antibiotic misuse has garnered substantial attention, prompting numerous researchers to develop materials that can combat these resistant pathogens. The hydrothermal method is employed to produce γ-MnO2 nanostars and to coat them with Fe2O3 nanoparticles. The materials are characterized using XRD, FE-SEM, EDX, and UV-vis spectrophotometry, as well as antioxidant and antibacterial activities. The nano γ-MnO2 star shapes are coated with tiny spherical Fe2O3 nanoparticles with diameters of 35-47 nm. The peaks located at the crystal planes (120), (031), (131), (230), (300), (160), (421), and (003) are represented by the values of 2θ = 22.36º, 34.36º, 37.22º, 38.78º, 42.56º, 56.14º, 65.48º and 68.
... Show MoreIn this study, pure SnO2 Nanoparticles doped with Cu were synthesized by a chemical precipitation method. Using SnCl2.2H2O, CuCl2.2H2O as raw materials, the materials were annealed at 550°C for 3 hours in order to improve crystallization. The XRD results showed that the samples crystallized in the tetragonal rutile type SnO2 stage. As the average SnO2 crystal size is pure 9nm and varies with the change of Cu doping (0.5%, 1%, 1.5%, 2%, 2.5%, 3%),( 8.35, 8.36, 8.67, 9 ,7, 8.86)nm respectively an increase in crystal size to 2.5% decreases at this rate and that the crystal of SnO2 does not change with the introduction of Cu, and S
... Show MoreIn this study lattice parameters, band structure, and optical characteristics of pure and V-doped ZnO are examined by employing (USP) and (GGA) with the assistance of First-principles calculation (FPC) derived from (DFT). The measurements are performed in the supercell geometry that were optimized. GGA+U, the geometrical structures of all models, are utilized to compute the amount of energy after optimizing all parameters in the models. The volume of the doped system grows as the content of the dopant V is increased. Pure and V-doped ZnO are investigated for band structure and energy bandgaps using the Monkhorst–Pack scheme's k-point sampling techniques in the Brillouin zone (G-A-H-K-G-M-L-H). In the presence of high V content, the ban
... Show MoreSeveral correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability
... Show MoreIn this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used: local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the
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