Titanium dioxide nanotube arrays (TiO2 NTAs) were successfully decorated with nanoclusters of cobalt by an electrochemical deposition method. This Co-TiO2 NTAs nanostructure exhibited high compatibility with aluminum chloride\ chloroacetamide (an ionic liquid) and calcium chloride dihydrate\ acetamide (a deep eutectic solvent), leading to significant improvements in the electrochemical properties of the system. Significantly, this led to a discernible augmentation in both potential and current values, concomitant with a decrease in internal resistance. The presence of cobalt facilitated a faster transfer of electric charge, enhancing the overall efficiency of the system. Moreover, the incorporation of cobalt exhibited a ben

The transfer of chemical pollutants from bottled water into water due to heat, sunlight and poor storage is one of the most serious threats to human health around the world, the objective of this study was to estimate the pH value and the transport of heavy metals from plastic bottles to water, for this purpose, 30 bottles of water for 10 local brands were collected and divided into three groups, the first was left at room temperature 25°C, The second was placed in a heat oven at 25°C and the third in another oven at 50°C for two weeks. The results showed significant differences at (P<0.05) between water samples, pH value and concentrations of heavy metals (Sb, Pb, Ni, Cu, Cr, Cd and Fe) we

   Gas lift is one of the most important artificial lift methods for increasing oil production, as wells often require this method after the reservoir's energy has decreased. In this research, an optimal gas lift system is designed for five horizontal wells in the Ahdab oil field, which suffers from low production. At the same time, water cut in some of these wells reaches 66%, while the productivity index is low in others, which makes the challenges clear, and a deep analysis is needed to find an optimal system. The Pipesim program is used to design the optimal gas lift system, which contains features that facilitate the implementation of the appropriate design and provide the ability to analyze and determine the optimal design v

     Hot-wire cutting is one of the important, non-traditional thermomechanical way to cut polymer, usually expanded foam and extruded foam, in low volume manufacturing. The study and analysis of Hot-Wire cutting parameters play an important role to enhance the quality and accuracy of the process and products. The effects on the surface have been investigated by using experimental tests designed according to the Taguchi orthogonal array (OA). In this study, four parameters with five levels for each parameter have been used: [temperature of wire (A) (100, 120, 130, 150, 160) °C], [diameter of wire (B) (0.3,0.4,0.5,0.7,0.8) mm], [velocity of cutting (C) (200, 300,400,500,600) mm/min], [and density of foam (D) (0.01,0.0

Oil recovery could be impacted by the relation between vertical permeability (K_v) and horizontal permeability (K_h) (K_v/K_h). 4816 plugs that have been getting hold of 18 wells of Mishrif formation in the West Qurna oilfield were used. K_v/K_h data provided some scatter, but the mean is ~1. K_v/K_h =1 was used for the Petrel model before upscaling according to the heterogeneity of each layer.

K_v/K_h values for Mishrif Formation in West Qurna Oilfield are 0.8 for relatively homogeneous, 0.4 for heterogeneous rock, and 0.1 for cap rocks (CRII).

   Eclipse ^TM was used for reservoir simulation. PVT and SCAL data e

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m