Re-use of the byproduct wastes resulting from different municipal and industrial activities in the reclamation of contaminated water is real application for green projects and sustainability concepts. In this direction, the synthesis of composite sorbent from the mixing of waterworks and sewage sludge coated with new nanoparticles named “siderite” (WSSS) is the novelty of this study. These particles can be precipitated from the iron(II) nitrate using waterworks sludge as alkaline agent and source of carbonate. Characterization tests using X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) mapping revealed that the coating process was correctly achieved and siderite nanoparticles were planted on the surface of the composite sorbent. Interaction between Congo Red dye and composite sorbent was evaluated through a set of batch tests under the variation of agitation time, pH of aqueous solution, and sorbent dosage. The results proved that the prepared sorbent had a high ability in the treatment of water contaminated with Congo Red dye in comparison with previous studies and the maximum adsorption capacity reached to maximum value i.e. 9416 mg/g. The sorption process was governed by electrostatic attractions; however, Sips and Pseudo-second-order models described this process with coefficient of determination greater than 0.99.
The synthesized ligand (3-(2-amino-5-(3,4,5-tri-methoxybenzyl)pyrimidin-4-ylamino)-5,5-dimethylcyclohex-2-enone] [H1L1] was characterized via fourier transform infrared spectroscopy (FTIR), 1H, 13C – NMR, Mass spectra, (CHN analysis), UV-vis spectroscopic approaches. Analytical and spectroscopic techniques like chloride content, micro-analysis, magnetic susceptibility UV-visible, conductance, and FTIR spectra were used to identify mixed ligand complexes. Its (ML13ph) mixed ligand complexes [M= Co (II), Ni (II), Cu (II), Zn (II), and Cd (II); (H1L1) = β-enaminone ligand=L1 and (3ph) =3-aminophenol= L2]. The results demonstrate that the complexes are produced with a molar ratio of M: L1:L2 (1:1:1). To generate the appropriate compl
... Show MoreA mathematical model constructed to study the combined effects of the concentration and the thermodiffusion on the nanoparticles of a Jeffrey fluid with a magnetic field effect the process of containing waves in a three-dimensional rectangular porous medium canal. Using the HPM to solve the nonlinear and coupled partial differential equations. Numerical results were obtained for temperature distribution, nanoparticles concentration, velocity, pressure rise, pressure gradient, friction force and stream function. Through the graphs, it was found that the velocity of fluid rises with the increase of a mean rate of volume flow and a magnetic parameter, while the velocity goes down with the increasing a Darcy number and lateral walls. Also, t
... Show More1-[4-(2-Hydroxy-4, 6-dimethyl-phenylazo)-phenol]-ethanone (HL1) and 2-(4-methoxy-phenylazo)-3, 5- dimethyl-phenol (HL2) were produced by combination the diazonium salts of amines with 3, 5- dimethylphenol. The geometry of azo compounds was resolved on the basis of (C.H.N) analyses, 1H and 13CNMR, FT-IR and UV-Vis spectroscopic mechanisms. Complexes of La (III) and Rh (III) have been performed and depicted. The formation of complexes has been identified by using elemental analysis, FTIR and UV-Vis spectroscopic process as well, conductivity molar quantifications. Nature of complexes produced have been studied obeyed mole ratio and continuous alteration ways, Beer's law followed through a concentration scope (1×10-4 - 3×10-4 M). High molar
... Show MoreThe corrosion behavior of mild sleet in saturated aerated and de-aerated Ca(OH)2 solution was investigated using electrochemical measurements. The work was carried out with small coupons immersed in solutions containing different quantities of NaCl in presence of various NaN02 concentrations as corrosion inhibitors. It has been found thal:(1 ) In presence of NaCl, the time required to reach O2 evolution potential in de-aerated Ca(OH)2 polarized at 10μA/cm 2 is function of inhibitor concentration and it becomes lass as NaN02 increases compared with zero presence indicating the effectiveness of N
... Show MoreThe Ant System Algorithm (ASA) is a member of the ant colony algorithms family in swarm intelligence methods (part of the Artificial Intelligence field), which is based on the behavior of ants seeking a path and a source of food in their colonies. The aim of This algorithm is to search for an optimal solution for Combinational Optimization Problems (COP) for which is extremely difficult to find solution using the classical methods like linear and non-linear programming methods.
The Ant System Algorithm was used in the management of water resources field in Iraq, specifically for Haditha dam which is one of the most important dams in Iraq. The target is to find out an efficient management system for
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Water pollution is one of the global challenges that the society must address in the 21st century aiming to improve the water quality, reduce human pollutants and ecosystem health impacts. In phytotoxicity test, the plant of Iresine herbstii was exposed to remove nickel from simulated wastewater using two different ratios (mass of plant to the mass of nickel) (,Rp/Ni) for 21 days with sub-surface batch system. During the exposure period, the removal of Ni concentrations (2, 5 and 10 mg/L) for two mass ratio (2,800 and 34,000) were (83.6%, 77.2%, 78.0%) and (86.8%, 97% and 95.6%), respectively. final result of the rate was found that the highest removal occurred, 97%, at a mass ratio of 34,000 and
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The great scientific progress has led to widespread Information as information accumulates in large databases is important in trying to revise and compile this vast amount of data and, where its purpose to extract hidden information or classified data under their relations with each other in order to take advantage of them for technical purposes.
And work with data mining (DM) is appropriate in this area because of the importance of research in the (K-Means) algorithm for clustering data in fact applied with effect can be observed in variables by changing the sample size (n) and the number of clusters (K)
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