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Development of natural deep eutectic solvent‐assisted liquid–liquid extraction method for soap removal from biodiesel: Optimization and kinetics
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Abstract<p>The soap content in biodiesel is an important challenge during the production and purification processing of biodiesel. Natural deep eutectic solvents (NADES) have recently attracted considerable interest as an environmentally suitable substitute for traditional solvents in the biodiesel industry. This work investigates the soap removal from the contaminated biodiesel using NADES. Eight choline chloride‐based deep eutectic solvents (DESs) were screened using the conductor‐like screening model for real solvents (COSMO‐RS) to identify the most suitable solvent for soap removal and were validated experimentally. The effect of NADES molar ratio, NADES:biodiesel ratio, mixing speed and extraction time on the extraction efficiency were investigated. COSMO‐RS screening revealed that the malonic acid‐based NADES possess higher soap elimination, and this is compatible with the experimental screening. The higher extraction efficiency of 99.18% was achieved under the optimum conditions of 1:3 of NADES molar ratio, 1:1 DES:biodiesel, 150 rpm and 15 min of extraction time. The soap removal followed the first‐order kinetic equation with a rate constant of 0.183 min<sup>−1</sup>. This technique offers innovative and environmentally friendly routes for downstream processing of contaminated biodiesel.</p>
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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conf. Proc.
Preparation of nanostructured MnO2/carbon fiber composite electrode for removal of Cu2+ ions from aqueous solution by electrosorption process
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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 de

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Publication Date
Mon Jun 29 2015
Journal Name
Separation Science And Technology
An acidic injection well technique for enhancement of the removal of copper from contaminated soil by electrokinetic remediation process
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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Hazardous Materials
Cement kiln dust (CKD)-filter sand permeable reactive barrier for the removal of Cu(II) and Zn(II) from simulated acidic groundwater
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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

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Publication Date
Thu Dec 01 2022
Journal Name
Inorganic Chemistry Communications
Entrapment of polyethylene terephthalate derived carbon in Ca-alginate beads for solid phase extraction of polycyclic aromatic hydrocarbons from environmental water samples
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Publication Date
Mon Oct 27 2014
Journal Name
Desalination And Water Treatment
Simultaneous adsorption–precipitation characterization as mechanisms for metals removal from aqueous solutions by cement kiln dust (CKD)
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Publication Date
Wed Jul 01 2026
Journal Name
Next Materials
Waste-derived chitosan-functionalized poultry litter biochar as a sustainable adsorbent for congo red removal from wastewater
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The increasing discharge of dye-containing wastewater has become a serious environmental problem, requiring efficient and sustainable treatment technologies. In this study, poultry litter–derived biochar (BC) was prepared via pyrolysis at 550 °C and subsequently modified with chitosan to produce a composite adsorbent (BC/CS) for the removal of Congo Red (CR) from aqueous solutions. The materials were characterized using SEM, BET, XRD, FTIR, and XPS analyses. BET results showed that chitosan modification slightly decreased the specific surface area from 8.28 to 8.18 m²/g and pore volume from 0.035 to 0.030 cm³ /g, while introducing abundant amine and hydroxyl functional groups on the surface. Maximum adsorption occurred at pH 3, w

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Removal of Cadmium Ions from Simulated Wastewater Using Rice Husk Biosorbent
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Biosorption of cadmium ions from simulated wastewater using rice husk was studied with initial concentration of 25 mg/l. Equilibrium isotherm was studied using Langmuir, Freundlich, BET and Timken models. The results show that the Freundlich isotherm is the best fit model to describe this process with high determination coefficient equals to 0.983. There was a good compliance between the experimental and theoretical results. Highest removal efficiency 97% was obtained at 2.5g of adsorbent, pH 6 and contact time 100 min.

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Publication Date
Tue Mar 30 2010
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of dyes from polluted water by adsorption on maize cob
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This research aimed to examine the effect of concentration of dyes stuff, contact time, temperature and ratio of adsorbent weight in (gm) to volume of solution in (ml) on the percentage removal. Two dyes were used; direct blue 6 and direct yellow and the adsorbent was the maize cob. Batch experiments were performed by contacting different weights of adsorbent with 50 ml of solution of desired concentration with continuous stirring at various temperatures. The percentage of removal was calculated and the maximum percentage of removal was 80%. And as the concentration of solution, contact time, temperature and the ratio of adsorbent to volume of solution increase the percentage of removal increase.

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