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bsj-2175
Asemi-Empirical Study of the Adsorption of Some Organic Pollutants on Modified Iraqi Clays
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In this work semi–empirical method (PM3) calculations are carried out by (MOPAC) computational packages have been employed to calculate the molecular orbital's energies for some organic pollutants. The long– chain quaternary ammonium cations called Iraqi Clays (Bentonite – modified) are used to remove these organic pollutants from water, by adding a small cationic surfactant so as to result in floes which are agglomerates of organobentonite to remove organic pollutants. This calculation which suggests the best surface active material, can be used to modify the adsorption efficiency of aniline , phenol, phenol deriviatives, Tri methyl glycine, ester and pecticides , on Iraqi Clay (bentonite) by comparing the theoretical results with experimental results achived in previous experimental studies between some organic pollutants and modified bentonite by (1- Hexadecyl pyridinium bromide) (HDPYBr). The theoretical calculation is made by using three surface active materials [1- (Hexadecyl pyridinium bromide) (HDPYBr), (1,12- Dipyridiniododecane dibromide) (DPYDDBr2) and Hexadecyl trimethyl ammonium bromide (HDTMA)]. Using (HDTMA) leads to the best adsorption efficiency for most pollutants involved in this study. The enthalpy of formations, dipole and energy of molecular orbitale HOMO and LUMO energies levels are calculated for all pollutants and the three surface active materials.

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Publication Date
Fri Mar 10 2017
Journal Name
Superconductor Science And Technology
Conceptual designs of conduction cooled MgB<sub>2</sub> magnets for 1.5 and 3.0 T full body MRI systems
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Publication Date
Sun Jan 01 2023
Journal Name
Materials Today: Proceedings
Preparation, characterization and preliminary cytotoxic evaluation of 6-mercaptopurine-coated biotinylated carbon dots nanoparticles as a drug delivery system
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Publication Date
Thu Nov 19 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
CFD Simulation of Velocity Distribution in a River with a Bend Cross Section and a Cubic Bed Roughness Shape
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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Preparation and characterization of biomass-alumina composite as adsorbent for safranine-o dye from aqueous solution at different temperatures
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Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Publication Date
Thu Feb 06 2020
Journal Name
Scientific Reports
Waste foundry sand/MgFe-layered double hydroxides composite material for efficient removal of Congo red dye from aqueous solution
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Abstract<p>We aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure</p> ... Show More
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Publication Date
Wed Jun 28 2023
Journal Name
Engineering Applications Of Computational Fluid Mechanics
Comprehensive analysis of melting enhancement by circular Y-shaped fins in a vertical shell-and-tube heat storage system
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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
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Publication Date
Sat Jun 01 2024
Journal Name
Case Studies In Chemical And Environmental Engineering
Optimization of photocatalytic process with SnO2 catalyst for COD reduction from petroleum refinery wastewater using a slurry bubble photoreactor
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