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Improvement of Microhardness and Corrosion Resistance of Stainless Steel by Nanocomposite Coating
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Abstract

 

Stainless steel (AISI 304) has good electrical and thermal conductivities, good corrosion resistance at ambient temperature, apart from these it is cheap and abundantly available; but has good mechanical properties such as hardness. To improve the  hardness and corrosion resistance of stainless steel its surface can be modified by developing nanocomposite coatings applied on its surface. The main objective of this paper is to study effect of electroco-deposition method on microhardness and corrosion resistance of stainless steel, and to analyze effect of nanoparticles (Al2O3, ZrO2 , and SiC)  on properties of composite coatings. In this paper employed Electroco-deposition process to develop a composite coating with (Ni) matrix and Ceramic oxide particles: Al2O3 (135nm), ZrO2 (40nm), and SiC (80nm) as reinforcements. The coatings were developed with 10 g/L, and 20 g/L concentrations in bath, at four different current densities (0.5, 1, 2, 3 A/dm2) using Watts bath to study the effect of current density and particle concentration in bath, on structure and properties of the coatings developed. The surface morphology of nanocomposite coating was characterized by Scanning Electron Microscopy (SEM). The hardness of the nanocoating was carried out using Digital Vickers  microhardness tester. The corrosion resistance property of nanocomposite coating was carried out in 3.5% NaCl solution used Open circuit potential (OCP) and potentialastic polarization. The results showed the nanocomposites coating have a smooth and compact surface and have higher hardness than the uncoated stainless steel (2.3 times), and also found that the nanocomposite coating improves the corrosion resistance significantly (89.25%).

 

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Publication Date
Wed Jun 01 2022
Journal Name
Results In Engineering
Behavioral nonlinear modeling of prestressed concrete flexural members with internally unbonded steel strands
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Clinical And Experimental Dentistry
Preventive effect of combined Er, Cr: YSGG and fluoride gel on acid resistance of the permanent tooth enamel: An in vitro study
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Publication Date
Fri Sep 26 2025
Journal Name
Applied Data Science And Analysis
Deep Learning in Genomic Sequencing: Advanced Algorithms for HIV/AIDS Strain Prediction and Drug Resistance Analysis
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Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

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Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Biological Sciences
Investigation of Plasmid-Associated Fluoroquinolone Resistance in Nosocomial Pseudomonas aeruginosa Isolated from Infected Burn Wounds
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Publication Date
Mon May 09 2022
Journal Name
مجلة علوم ديالى
The expression of PmrA gene in Acinetobacter baumannii bacteria that is responsible for Colistin resistance
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Publication Date
Tue Jan 18 2022
Journal Name
مجلة ديالى للعلوم الصرفة
Study the gene expression of aacC1 gene in Acinetobacter baumannii that responsible for Aminoglycoside resistance
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Publication Date
Mon Oct 13 2025
Journal Name
Mesopotamian Journal Of Cybersecurity
Improvement of the Face Recognition Systems Security Against Morph Attacks using the Developed Siamese Neural Network
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Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d

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Publication Date
Tue Apr 01 2003
Journal Name
Abhath Al- Yarmouk [basic Sciences And Engineering]
Methodology for selecting Nonprestressed Steel in Post- Tensioning Beams
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Publication Date
Sun Apr 01 2007
Journal Name
Journal Of Engineering
CURVATURE DUCTILITYOF REINFORCED CONCRETE BEAMSECTIONS STIFFENED WITH STEEL PLATES
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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Role of Participatory Budgeting in Improving Performance in light of Covid 19
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The current research aims to analyze the role of participatory budgeting in improving performance, especially during crises such as the Covid-19 crisis. The research used the descriptive analytical method to reach the results by distributing 100 questionnaires to a number of employees in Iraqi joint stock companies and at multiple administrative levels. The research came to several important conclusions, the most important of which is that the bottom-up approach to budgeting produces more achievable budgets than the top-down approach, which is imposed on the company by senior management with much less employee participation. Additionally, there is a better information flow from the lower levels of the organization to the upper management

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