The nanostructured Manganese dioxide/Carbon fiber (CF) composite electrode was prepared galvanostatically using a facile method of anodic electrodeposition by varying the reaction time and MnSO4 concentration of the electrochemical solution. The effects of these parameters on the structures and properties of the prepared electrode were evaluated. For determining the crystal characteristics, morphologies, and topographies of the deposited MnO2 films onto the surfaces of carbon fibers, the X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and atomic force microscopy (AFM) techniques were used, respectively. It found that the carbon fibers were coated with γ-MnO2 with a density that increased with increasing the deposition time and MnSO4 concentration, and vice versa for the roughness value (RMS). At conditions of 0.35 M of MnSO4 and 4h, the MnO2 nanoparticles tended to create a thin film with a uniform structure and high capacitance. The electrosorptive properties of the NMO/CF electrode were investigated by using it for removing Cu2+ ions from the aqueous solution and the influence of the applied voltage and ion strength on the Cu2+ removal efficiency was examined. The results indicate that at conditions of 2.3V applied voltage and 3 g/l of NaCl, the removal efficiency reached 98.46 % with an adsorption capacity of 218.8 mg/g.
Sustainability including renewable energy and green power, is one of the important feature in recent years due to environmental constraints and the emission of CO2 from fossil fuel. Pressure retarded osmosis (PRO) process is considered one of the effective technology for power generation. This study assessed the application of pressure retarded osmosis to produce power from Tigris River water in Baghdad City, Iraq. Spiral wound TFC membrane was tested in the PRO process with different variables. The effect of different types of draw solutions (MgCl2, NaCl, Sodium Formate, KCl, Sodium Acetate), applied pressure (0 – 7 bar), and draw solution concentration (0.08 and 0.4 M) were tested in this work. The flux, recovery, and power density for
... Show MoreThe production of power using the process of pressure–retarded osmosis (PRO) has been studied both experimentally and theoretically for simulated sea water vs. river water and deionized water under two cases: the first is for simulated real conditions of sea water and river water and second under low brine solution concentration to examine the full profile of the power- pressure. The influence of concentration polarization (CP) on water flux has been examined as well.
Desalination is a process where fresh water produces from high salinity solutions, many ways used for this purpose and one of the most important processes is membrane distillation (MD). Direct contact membrane distillation (DCMD) can be considered as the most prominent type from MD types according to ease of design and modus operandi. This work studies the efficiency of using DCMD operation for desalination brine with different concentration (1.75, 3.5, 5 wt. % NaCl). Frame and plate cell was used with flat sheet PTFE hydrophobic type membrane. The study proves that MD is an effective process for desalination brines with feed temperature less than 60˚C especially for feed with low TDS. 37˚C, 47˚C, and 57˚C was feed t
... Show MoreIn this study, synthesised new ligand: potassium 2,2'-(quinoxaline-2,3- diyl)bis(1-phenylhydrazinecarbodithioate) (L). The ligand synthesised by reacting N1,N2-dip-tolyloxalamide as the starting material with CS2 and KOH to add the CS2 group and then with phenylendiammine to achieve (L). The ligand used in the synthesis of complexes with (CoII, NiII and CdII). The new ligand and its complexes characterised by FT-IR, UV-Vis, 1H, 13C-NMR, Mass spectroscopy, and elemental analysis, in addition to the above techniques were using magnetic moment, atomic absorption, chloride content, and melting point to describe the metal complexes.
Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
... Show MoreIn this study, chemical oxidation was employed for the synthesis of polypyrrole (PPy) nanofiber. Furthermore, PPy has been subjected to treatment using nanoparticles of neodymium oxide (Nd2O3), which were produced and added in a certain ratio. The inquiry centered on the structural characteristics of the blend of polypyrrole and neodymium oxide after their combination. The investigation utilises X-ray diffraction (XRD), FTIR, and Field Emission Scanning Electron Microscopy (FE-SEM) for PPy, 10%, 30%, and 50% by volume of Nd2O3. According to the electrochemical tests, it has been noted that the nanocomposites exhibit a substantial amount of pseudocapacitive activity.
