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Phenol removal by electro-Fenton process using a 3D electrode with iron foam as particles and carbon fibre modified with graphene
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The 3D electro-Fenton technique is, due to its high efficiency, one of the technologies suggested to eliminate organic pollutants in wastewater. The type of particle electrode used in the 3D electro-Fenton process is one of the most crucial variables because of its effect on the formation of reactive species and the source of iron ions. The electrolytic cell in the current study consisted of graphite as an anode, carbon fiber (CF) modified with graphene as a cathode, and iron foam particles as a third electrode. A response surface methodology (RSM) approach was used to optimize the 3D electro-Fenton process. The RSM results revealed that the quadratic model has a high R2 of 99.05 %. At 4 g L-1 iron foam particles, time of 5 h, and 1 g of graphene, the maximum efficiency of phenol removal of 92.58 % and chemical oxygen demand (COD) of 89.33 % were achieved with 32.976 kWh kg-1 phenol of consumed power. Based on the analysis of variance (ANOVA) results, the time has the highest impact on phenol removal efficiency, followed by iron foam and graphene dosage. In the present study, the 3D electro-Fenton technique with iron foam partials and carbon fiber modified with graphene was detected as a great choice for removing phenol from aqueous solutions due to its high efficiency, formation of highly reactive species, with excellent iron ions source electrode.

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Publication Date
Mon Dec 31 2012
Journal Name
Journal Of Electrochemical Science And Technology
Mass Transfer to Amalgamated Copper Rotating Disk Electrode
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Publication Date
Sun Jan 01 2012
Journal Name
International Journal Of Chemical Engineering
Phosphorus Removal from Wastewater Using Oven-Dried Alum Sludge
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Publication Date
Wed Sep 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Tetracycline from Wastewater Using Circulating Fluidized Bed
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   In this study, the circulating fluidized bed was used to remove the Tetracycline from wastewater utilizing a pistachio shell coated with ZnO nanoparticles. Several parameters including, Tetracycline solution flowrate, initial static bed height, Tetracycline initial concentration and airflow rate were systematically examined to show their effect on the breakthrough curve and the required time to reach the adsorption capacity and thus draw the fully saturated curve of the adsorbent. Results showed that using ZnO nanoparticles will increase the adsorbent surface area and pores and as a result the adsorption increased, also the required time for adsorbent saturation increased and thus the removal efficiency may be achieved at mi

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Environmental Management
Treatment of vegetable oil refinery wastewater by sequential electrocoagulation-electrooxidation process
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Publication Date
Fri Dec 01 2017
Journal Name
International Journal Of Chemtech Research
The Effect of Ginger Plant (Zingiber officinale) Aqueous Extract on Function and Histological Structure of Kidney in Mice Treated with Carbon Tetrachloride
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The percent work was designed to determine the effect of ginger plant aqueous extract on function and histological structure of kidney in mice treated with carbon tetrachloride (CCl4). Ginger plant caused a protective effect against CCl4 induced kidney damage and improved the kidney weight and biochemical parameters including urea, uric acid and creatinine. The ginger plant has a protective effect against injury in the kidney of mice treated with CCL4, because the ginger plant protects the tissues of kidney from toxic effect of CCL4. The kidney of CCL4 treated mice showed many histological alterations in the kidney included: atrophy, vascular degeneration and hemorrhage, death cell, degeneration of epithelial cells, destruction of basement

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Publication Date
Sun Aug 08 2021
Journal Name
Proceedings Of International Conference On Emerging Technologies And Intelligent Systems
Drone Altitude Control Using Proportional Integral Derivative Technique and Recycled Carbon Fiber Structure
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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
A study the electrical properties of a Se:2.5%as thin films prepared by thermal cvaporation
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thin films of se:2.5% as were deposited on a glass substates by thermal coevaporation techniqi=ue under high vacuum at different thikness

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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
A Tile with Nested Chain Abacus
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This study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.

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Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

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