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Preparation and Characterization of Nano-Iron Oxide by using Iraqi Orange Plant Extract and Testing for Adsorption Efficiency
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Nanomaterials, including nanoparticles such as iron oxide nanoparticles, have received great attention from researchers due to their unique properties and applications. There are several diverse methods, including chemical, physical, and green biological methods, to prepare iron oxide nanoparticles. The green method was chosen because it is safer, purer, and less toxic compared to other methods. Therefore, the green method is a promising and environmentally friendly method in the near future. The aqueous extract of Iraqi orange leaves was used to prepare nano iron oxide, it was examined structurally and spectrally by several techniques (X-ray diffraction- XRD, Fourier transform infrared - FT-IR, field emission scanning electron microscopy - FESEM, energy disperse X-ray spectroscopy - EDX, and UV-vis spectroscopy). Through the diagnosis, it was proven that the nano iron oxide was successfully prepared in a spherical form with an average size equal to 68.5 nm. The nano iron oxide particles were tested to remove the crystal dye from its aqueous solution, where the removal percentage reached 61% at 298K, dose adsorbent = 0.01 g, contact time = 90 min, and initial concentration = 11 mg/L. This indicates the possibility of using nano iron oxide which preparing by green method in the field of water treatment. Keywords: Fe3O4 NPs, green method, orange leaf aqueous extract, adsorption, crystal violet dye.  

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Publication Date
Wed Jan 01 2020
Journal Name
Plant Archives
The effect of adding some organic and mineral substances to calcareous soil on adsorption and desorption of copper and its removal efficiency from soil
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Publication Date
Sat Oct 19 2024
Journal Name
Baghdad Science Journal
Synthesis, Characterization and Biological Activity of New Ligand     Derived from 4-‎(Dimethylamino) Benzaldehyde and Nano Copper Complex
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الصيغة العامة للمعقدات الجديدة [M2(BDS)Cl4] الناتجة من تفاعل الليكاند الجديد] ن1,ن4-ثنائي(1أ –بنزو]د[ اميدازول-2-يل)-ن1,ن4-ثنائي(4-ثنائي مثيل امينو) بنزيل) سكسنمايد[ (BDS) مع الايونات الفلزية الكادميوم, الكوبلت, الزئبق, النحاس والنيكل. تم اشتقاق هذا الليكاند من تفاعل المواد الثلاث 4-(ثنائي ميثيل أمينو) بنزالدهيد، 2-أمينو بنزيميدازول، وكلوريد السكسينيل. تم تشخيص المركبات باستخدام مطيافية طيف الاشعة تحت الحمراء وطيف الرن

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
The Spatial Analysis for Bassia eriophora (Schrad.) Asch. Plant Distributed in all IRAQ by Using RS & GIS Techniques
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        Most vegetation’s are Land cover (LC) for the globe, and there is an increased attention to plants since they represent an element of balance to natural ecology and maintain the natural balance of rapid changes due to systematic and random human uses, including the subject of the current study (Bassia eriophora ) Which represent an essential part of the United Nations system for land cover classification (LCCS), developed by the World Food Organization (FAO) and the world Organization for environmental program (UNEP), to observe basic environmental elements with modern techniques. Although this plant is distributed all over Iraq, we found that this plant exists primarily in the middle

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Physics: Conference Series
Synthesis, Characterization, Antibacterial study and Efficiency of Inhibition of New di-β-enaminone Ligand and its Complexes
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Abstract<p>The new ligand [3,3’-(1,2-phenylenebis(azanediyl))bis(5,5-dimethylcyclohex-2-en-1-one)] (L) derived from 5,5-Dimethylcyclohexane-1,3-dione with 1,2-phenylenediamine was used to prepare a new chain of metal complexes of Mn(ii), Co(ii), Ni(ii), Cu(ii), Cd(ii) and Zn(ii) by inclusive formula [M(L)]Cl2. Characterized compounds on the basis of <sup>1</sup>H, <sup>13</sup>CNMR (for ligand (L)), FT-IR and U.V spectrum, melting point, molar conduct, %C, %H and %N, the percentage of the metal in complexes %M, Magnetic susceptibility, thermal studies (TGA), while its corrosion inhibition for (plain steel) in tap water is studied by weight loss. These measurements proved th</p> ... Show More
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Publication Date
Wed Jun 21 2023
Journal Name
Journal Of Electrochemical Science And Engineering
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

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Publication Date
Sun Jan 01 2017
Journal Name
Aip Conference Proceedings
Macro controlling of copper oxide deposition processes and spray mode by using home-made fully computerized spray pyrolysis system
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Publication Date
Tue Jun 22 2021
Journal Name
Expert Systems
Hybrid intelligent technology for plant health using the fusion of evolutionary optimization and deep neural networks
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Publication Date
Wed Aug 17 2022
Journal Name
Applied Sciences
Predicting Fruit’s Sweetness Using Artificial Intelligence—Case Study: Orange
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The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

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Publication Date
Tue Jun 11 2019
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Evaluating Health-Related Quality of Life (HRQoL) in Iraqi Adult and Pediatric Patients with Beta-Thalassemia Major Using Two Different Iron Chelation Therapies
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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

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