Artificial intelligence techniques for modeling and optimization of the HDS process over a new graphene based catalyst

<p>A Co-Mo/graphene oxide (GO) catalyst has been synthesized for the first time for application in a defined hydrodesulfurization (HDS) process to produce sulfur free naphtha. An intelligent model based upon the neural network technique has then been developed to estimate the total sulfur output of this process. Process operating variables include temperature, pressure, LHSV and H₂/feed volume ratio. The three-layer, feed-forward neural network developed consists of five neurons in a hidden layer, trained with Levenberg–Marquardt, back-propagation gradient algorithm. The predicted amount of residual total sulfur is in very good agreement with the corresponding experimental values revealing a correlation coefficient of greater than 0.99. In addition, a genetic algorithm (GA) has been employed to optimize values of total sulfur as well as reaction conditions.</p

Silica/polyacrylamide nanocomposite for inhibition of asphaltene precipitation from unstable crude oils

Among various flow assurance problems, asphaltene precipitation is a major issue. This study aims to evaluate the potential application of silica-polyacrylamide nanocomposite to inhibit asphaltene precipitation for the first time. The nanocomposites were synthesized and characterized by Fourier transform infrared and field emission scanning electron microscopy techniques. The inhibitory effect of nanocomposites in water-based nanofluid on two unstable crude oils was evaluated using viscometry, asphaltene dispersion test, dynamic light scattering, and polarized microscopy techniques. The viscosity measurements indicate that nanocomposites postpone asphaltene onset of precipitation from 34 to 44 and 23 to 36 vol% nC7 for crude oil A and B, respectively. The maximum dispersion efficiency of nanocomposite was 69% and 79% at the 1% and 2.5% nanofluid volume dosages for crude oil A and B, respectively. Dynamic Light Scattering and microscopy results indicated the asphaltene size change to lower values in the presence of nanocomposites. Polyacrylamide attached to the silica surface promotes a surface with efficient functional groups that increase the asphaltene adsorption. Asphaltene adsorption leads to decreased aggregate size and controlling the asphaltene precipitation. The prepared nanocomposite was evaluated as an efficient dispersant and inhibitor that reveals the potential application of Silica-polyacrylamide for handling the asphaltene precipitation in reservoirs.</p

Graphene oxide-packed micro-column solid-phase extraction combined with flame atomic absorption spectrometry for determination of lead (II) and nickel (II) in water samples

<div><p>A sensitive and simple method has been established for simultaneous preconcentration of trace amounts of Pb (II) and Ni (II) ions in water samples prior to their determination by flame atomic absorption spectrometry. This method was based on the using of a micro-column filled with graphene oxide as an adsorbent. The influences of various analytical parameters such as solution pH, adsorbent amount, eluent type and volume, flow rates of sample and eluent, and matrix ions on the recoveries of the metal ions were investigated. Using the optimum conditions, the calibration graphs were linear in the range of 7–260 and 5–85 μg L⁻¹ with detection limits (3<i>S</i>_b) of 2.1 and 1.4 μg L⁻¹ for lead and nickel ions, respectively. The relative standard deviation for 10 replicate determinations of 50 μg L⁻¹ of lead and nickel ions were 4.1% and 3.8%, respectively. The preconcentration factors were 102.5 and 95 for lead and nickel ions, respectively. The adsorption capacity of the adsorbent was also determined. The method was successfully applied to determine the trace amounts of Pb (II) and Ni (II) ions in real water samples. The validation of the method was also performed by the standard reference material.</p></div

Newly Prepared Nano Gamma Alumina and Its Application in Enhanced Oil Recovery: An Approach to Low-Salinity Waterflooding

Nano gamma alumina (NGA) was prepared via a simple synthetic route and used for the preparation of a nanofluid in various salinities on the water-wet sandstone core samples. A new waterflooding experiment on sandstone rock for enhanced oil recovery (EOR) has been used by taking into account different water salinities. In this paper, the impressiveness of a new EOR process in the presence of alumina-based nanofluids to alter the dynamic adsorption of the sandstone core sample in low- and high-salinity brine injection has been experimentally studied. The nanofluids with a suitable concentration of NGA particles and salinities ranging from 2000 to 200 000 ppm and 25–80 °C were prepared. The results showed a reduced adsorption by the use of nanoparticles at low-salinity conditions. The ultimately optimum recoveries for 2000, 20 000, and 200 000 ppm of nanofluid injection were obtained as 56.95, 64.78, and 71.48%, respectively. It was found that these oil recoveries strongly depend upon the concentration of salinities and were increased with a decreasing salinity loading. Therefore, the dynamic adsorption behavior of nanofluid results shows a key role in clay migration in oil displacement