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The use of Artificial Neural Network (ANN) for modeling of Cu (II) ion removal from aqueous solution by flotation and sorptive flotation process
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Publication Date
Fri Jun 30 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Comparative Study for Removal of Zn+2 Ions from Aqueous Solutions by Adsorption and Forward Osmosis
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The aim of this paper was to investigate the removal efficiencies of Zn+2 ions from wastewater by adsorption (using tobacco leaves) and forward osmosis (using cellulose triacetate (CTA) membrane). Various experimental parameters were investigated in adsorption experiment such as: effect of pH (3 - 7), contact time (0  - 220) min, solute concentration (10 - 100) mg/l, and adsorbent dose (0.2 - 5)g. Whereas for forward osmosis the operating parameters studied were: draw solution concentration (10 - 150) g/l, pH of feed solution (4 - 7), feed solution concentration (10 - 100) mg/l. The result showed that the removal efficiency by using adsorption was 70% and the removal efficiency by using forward osmosis was 96.2 %. 

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Publication Date
Thu Aug 24 2023
Journal Name
Environmental Monitoring And Assessment
Rice husk coated with copper oxide nanoparticles for 17α-ethinylestradiol removal from an aqueous solution: adsorption mechanisms and kinetics
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The 17 α-ethinylestradiol (EE2) adsorption from aqueous solution was examined using a novel adsorbent made from rice husk powder coated with CuO nanoparticles (CRH). Advanced analyses of FTIR, XRD, SEM, and EDSwere used to identify the classification parameters of a CRH-like surface morphology, configuration, and functional groups. The rice husk was coated with CuO nanoparticles, allowing it to create large surface area materials with significantly improved textural qualities with regard to functional use and adsorption performance, according to a detailed characterization of the synthesized materials. The adsorption process was applied successfully with elimination effectiveness of 100% which can be kept up to 61.3%. The parameters of ads

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Publication Date
Mon Oct 25 2021
Journal Name
Iraqi Journal Of Science
Synthesis, Characterization and Kinetic Studies of Chelate Polymer Derived from 3-Nonyl Benzene and its Use for the Removal of Some Heavy Metals from Aqueous Solutions
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    A new chelate polymer (2-5-hydroxy-3-methyl-2- (3-nonyl benzene) imino) methyl) benzyl) 4-6-dimethyphenol] (K4) was prepared by using the condensation reaction method and identified by several techniques, including FT-IR, NMR, and atomic absorption spectroscopy, as well as TG-DTA thermal analysis. The kinetic equilibrium for the sorption of lead and cadmium ions on the chelate polymer surface was also investigated. The results showed that the sorption of both ions followed the pseudo-first-order and pseudo-second-order kinetic equilibrium. The rate constant values of pseudo-first-order reaction  were equal to 0.062 and 0.057 min-1  , while the values of pseudo-second-order were 0.0103 and 0.053 L.m

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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Acetaminophen Residues from Wastewater by Bulk Liquid Membrane Process
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   The removal of Anit-Inflammatory drugs, namely; Acetaminophen (ACTP), from wastewater by bulk liquid membrane (BLM) process using Aliquat 336 (QCl) as a carrier was investigated. The effects of several parameters on the extraction efficiency were studied in this research, such as the initial feed phase concentration (10-50) ppm of ACTP, stripping phase (NaCl) concentration (0.3,0.5,0.7 M), temperature (30-50oC), the volume ratio of feed phase to membrane phase (200-400ml/80ml), agitation speed of the feed phase (75-125 rpm), membrane stirring speed (0, 100, 150 rpm), carrier concentration (1, 5, 9 wt%), the pH of feed (2, 4, 6, 8, 10), and solvent type (CCl4 and n-Heptane). The study shows that high ext

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Publication Date
Mon Sep 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Wool Dyes from Industrial Wastewater by Reverse Osmosis Process
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Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of bubble size in Bubble columns using Artificial Neural Network
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In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

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Publication Date
Mon Dec 02 2024
Journal Name
Engineering, Technology & Applied Science Research
An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

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Publication Date
Tue Sep 06 2022
Journal Name
Methods And Objects Of Chemical Analysis
Spectrophotometric Analysis of Quaternary Drug Mixtures using Artificial Neural network model
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A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

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Publication Date
Tue Sep 27 2016
Journal Name
Mine Water Environ.
Dominant Mechanisms for Metal Removal from Acidic Aqueous Solutions by Cement Kiln Dust
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Publication Date
Wed Jun 29 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Kinetics and Energetic Parameters Study of Phenol Removal from Aqueous Solution by Electro-Fenton Advanced Oxidation Using Modified Electrodes with PbO2 and Graphene
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The Electro-Fenton oxidation process is one of the essential advanced electrochemical oxidation processes used to treat Phenol and its derivatives in wastewater. The Electro-Fenton oxidation process was carried out at an ambient temperature at different current density (2, 4, 6, 8 mA/cm2) for up to 6 h. Sodium Sulfate at a concentration of 0.05M was used as a supporting electrolyte, and 0.4 mM of Ferrous ion concentration (Fe2+) was used as a catalyst. The electrolyte cell consists of graphite modified by an electrodepositing layer of PbO2 on its surface as anode and carbon fiber modified with Graphene as a cathode. The results indicated that Phenol concentration decreases with an increase in current dens

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