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Enhancing Electrochemical Cells Performance with Modified Ionic Liquids and Deep Eutectic Solvents using Titanium Dioxide Nanoelectrodes- Graphite
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Ionic liquids (ILs) and deep eutectic solvents (DESs) have been found to be highly effective as electrolytes in TiO2 NTAs-graphite cells when combined with additives that enhance conductivity by reducing the viscosity of these liquids. The presence of CaCl2.6H2O: Acetamide DES with DI water as an additive resulted in a cell voltage of 1.31V and an internal resistance of 19 ohm. This can be attributed to the concentration and quality of the ionic species. The cells exhibited an interesting response to the AlCl3-chloroacetamide IL with dichloromethane DCM as an additive, with a cell voltage of 1.81V and an internal resistance of 5.0 ohm. Once again, this is influenced by the quality and concentration of the ionic species. Furthermore, the cells demonstrated thermal stability during the charging and discharging processes. Additionally, the surfaces of the TiO2 NTAs electrodes were examined, along with the impact of the IL and DES on these electrodes, using SEM and EDXA equipment.

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Molecular detection of the ability of Biosynthesized Titanium dioxide nanoparticles to curing some genes of virulence factors of Entamoeba histolytica
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The present study included the microscopic and molecular identification of Entamoeba histolytica by using specific primers to detect four virulence factors possessed by Entamoeba histolytica. Virulence factors included Active Cysteine proteinase, Galactose/N-acetyl-D-galactose-lectin, Amoeba pore C and Phospholipase. Titanium dioxide nanoparticles (TiO2NPs) were synthesized from Pseudomonas aeruginosa which producing Pyocyanin pigment as a reducing agent to form it. After that we studied the ability ofTiO2NPs to inhibit virulence factors production and curing the genes responsible for encoding them by using four different dose 2 ,3, 4, 6 mg/Kg and administered by intraperitoneal injection

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Publication Date
Wed Sep 14 2016
Journal Name
Journal Of Baghdad College Of Dentistry
Mechanical Evaluation of Pure Titanium Dental Implants Coated with a Mixture of Nano Titanium Oxide and Nano Hydroxyapatite
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Background: The type of dental implant surface is one of many factors that determine the success of implant restoration. This study aimed to study the effect of mixture of nano titanium oxide with nanohydroxyapatite coating of screw shaped CPTi dental implant on bond strength at bone implant interface by torque removal test related to two healing periods (2 and 6 weeks). Materials and methods: Dip coating process was performed to get an even coating layer on CPTi screws. X-ray diffraction (XRD) analysis and microscopical examination were performed on the coating surfaces of the CPTi. The tibia of 10 white New Zealand rabbits was chosen as implantation sites. The tibia of each rabbit received two screws, one was coated with mixture of nanoT

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Publication Date
Sun Dec 06 2015
Journal Name
Baghdad Science Journal
The Effect of The Electrochemical Deposition Potential Variation on The Coating of Hydroxyatite on Commertialy pure Titanium (CpTi) and Ti-6Al-4V Alloy
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In this research we investigated the corrosion behavior of the commertialy pure titanium and Ti-6Al-4V alloy that coated with hydroxyapatite by electrochemical deposition with applied voltage (6,9,12) Volt from aqueous solution containing Ca(NO3)2.H2O =7.0 gm/l , (NH4)2HPO4 =3.5 gm/l , Na(NO3)2 = 8.5 gm/l in order to improve the bonding strength of hydroxyapetite and medical metals and alloys and increasing the biocompatibility. The coating layer morphology was investigated by XRD, Optical microscope , and SEM tests, the corrosio tests was made by use senthesys simulated body fluid (SBF) , and we found that the propreate voltage for coatint on Ti was 9 Volt and for Ti-6Al-4Vwas12Volt.

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Publication Date
Thu Apr 24 2025
Journal Name
Pertanika Journal Of Science And Technology
Enhancing Leachate Treatment with Electrocoagulation: A Computational Approach Using Response Surface Methodology
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Malaysia's growing population and industrialisation have increased solid waste accumulation in landfills, leading to a rise in leachate production. Leachate, a highly contaminated liquid from landfills, poses environmental risks and affects water quality. Conventional leachate treatments are costly and time-consuming due to the need for additional chemicals. Therefore, the Electrocoagulation process could be used as an alternative method. Electrocoagulation is an electrochemical method of treating water by eliminating impurities by applying an electric current. In the present study, the optimisation of contaminant removal was investigated using Response Surface Methodology. Three parameters were considered for optimisation: the curr

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Publication Date
Wed Apr 01 2026
Journal Name
Case Studies In Construction Materials
Performance Evaluation of Modified Hard-Grade Asphalt Binder Using Waste PVC Derived from Flex Banners
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Hard-grade asphalt binders, such as AC 20–30, offer excellent resistance to permanent deformation but are inherently brittle, making them highly susceptible to fatigue and low-temperature cracking. While polymer modification addresses these issues, virgin polymers remain expensive. Despite the growing interest in recycled plastics, the rheological impact of complex waste streams, specifically polyvinyl chloride (PVC) derived from flex banners containing plasticizers, on excessively stiff binders within the complete Superpave Performance Grading (PG) framework remains critically underexplored. This study introduces a novel valorization approach by utilizing solvent-extracted flex banner waste (WPVC) as a dual-action modifier. It leverages

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Publication Date
Thu Aug 29 2024
Journal Name
Materials
Experimental Study to Investigate the Performance-Related Properties of Modified Asphalt Concrete Using Nanomaterials Al2O3, SiO2, and TiO2
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The dual nature of asphalt binder necessitates improvements to mitigate rutting and fatigue since it performs as an elastic material under the regime of rapid loading or cold temperatures and as a viscous fluid at elevated temperatures. The present investigation assesses the effectiveness of Nano Alumina (NA), Nano Silica (NS), and Nano Titanium Dioxide (NT) at weight percentages of 0, 2, 4, 6, and 8% in asphalt cement to enhance both asphalt binder and mixture performance. Binder evaluations include tests for consistency, thermal susceptibility, aging, and workability, while mixture assessments focus on Marshall properties, moisture susceptibility, resilient modulus, permanent deformation, and fatigue characteristics. NS notably im

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Publication Date
Thu Aug 29 2024
Journal Name
Materials
Experimental Study to Investigate the Performance-Related Properties of Modified Asphalt Concrete Using Nanomaterials Al2O3, SiO2, and TiO2
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The dual nature of asphalt binder necessitates improvements to mitigate rutting and fatigue since it performs as an elastic material under the regime of rapid loading or cold temperatures and as a viscous fluid at elevated temperatures. The present investigation assesses the effectiveness of Nano Alumina (NA), Nano Silica (NS), and Nano Titanium Dioxide (NT) at weight percentages of 0, 2, 4, 6, and 8% in asphalt cement to enhance both asphalt binder and mixture performance. Binder evaluations include tests for consistency, thermal susceptibility, aging, and workability, while mixture assessments focus on Marshall properties, moisture susceptibility, resilient modulus, permanent deformation, and fatigue characteristics. NS notably im

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Cadmium Removal Using Bio-Electrochemical Reactor with Packed Bed Rotating Cylindrical Cathode: A Kinetics Study
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   The kinetics of removing cadmium from aqueous solutions was studied using a bio-electrochemical reactor with a packed bed rotating cylindrical cathode. The effect of applied voltage, initial concentration of cadmium, cathode rotation speed, and pH on the reaction rate constant (k) was studied. The results showed that the cathodic deposition occurred under the control of mass transfer for all applied voltage values ​​used in this research. Accordingly, the relationship between logarithmic concentration gradient with time can be represented by a first-order kinetic rate equation. It was found that the rate constant (k) depends on the applied voltage, the initial cadmium concentration, the pH and the rotational speed of cathode. It

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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
A modified Mobilenetv2 architecture for fire detection systems in open areas by deep learning
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

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