A liquid membrane process of Alkaloids extraction from Datura Innoxia solution was studied applying pertraction process in rotating discs contactor (RDC). Decane as a liquid membrane and dilute sulphuric acid as stripping solution were used. The effect of the fundamental parameters influencing the transport process, e.g. type of solvent used, effect of disks speed, amount of liquid membrane and effect of pH for feed and strip solution. The transport of alkaloids was analysed on the basis of kinetic laws of two consecutive irreversible first order reactions. Thus, the kinetic parameters (k1, k1, , tmax, and ) for the transport of alkaloids were determined. The effect of organic membrane type on percentage of Alkaloids transport was found

A liquid membrane process of Alkaloids extraction from Datura Innoxia solution was studied applying pertraction process in rotating discs contactor (RDC). Decane as a liquid membrane and dilute sulphuric acid as stripping solution were used. The effect of the fundamental parameters influencing the transport process, eg type of solvent used, effect of disks speed, amount of liquid membrane and effect of pH for feed and strip solution. The transport of alkaloids was analysed on the basis of kinetic laws of two consecutive irreversible first order reactions. Thus, the kinetic parameters (k1, k1,, tmax, and) for the transport of alkaloids were determined. The effect of organic membrane type on percentage of Alkaloids transport was found to be i

          In this paper, magnesium oxide nanoparticles (MgO NPS) have been prepared and characterized and its concentration effect has been studied on polymers surface (MgO NPS). The results showed that the degradation of poly methyl methacrylate increased when using such metal oxide. The results also showed that the metal oxide increased the degradation of poly methyl methacrylate. X-ray diffraction, scanning electron microscopy, atomic force microscopy were used to study the morphological characteristics and size of nano MgO particles analysis.  Films were prepared by mixing the different masses of MgO NPS (0.025, 0.05, 0.1, 0.2 and 0.4) % with a polymer solution ratio (W/V) 7 %. Photo-

PAN/PMMA) with different blend ratios (80/20, 75/25,70/30,65/35, and 60/40) wt% undoped and doped with various lithium (Li) salts (LiCO3, Li2SO4H2O, and LiCl) at 20 wt %. Different techniques were employed to investigate the composition and optical properties of the prepared blend samples undoped and doped with Lithium salts like FT-IR and UV-Visible spectroscopies. The optical properties analysis declared that the energy gap increased from (4.0 eV to 4.20 eV) by increasing of PMMA ratio from 20 to 40 wt %. In contrast, the energy gap reduced and shifted toward the low energy side by adding lithium salts; the minimum energy gap value was 2 eV obtained from 65 % PAN and 35 % PMMA doped with Li2CO3. The optical constants were determ

In this study, genetic algorithm was used to predict the reaction kinetics of Iraqi heavy naphtha catalytic reforming process located in Al-Doura refinery in Baghdad.  One-dimensional steady state model was derived to describe commercial catalytic reforming unit consisting of four catalytic reforming reactors in series process.

The experimental information (Reformate composition and output temperature) for each four reactors collected at different operating conditions was used to predict the parameters of the proposed kinetic model. The kinetic model involving 24 components, 1 to 11 carbon atoms for paraffins and 6 to 11 carbon atom for naphthenes and aromatics with 71 reactions. The pre-exponential Arrhenius constants and a

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