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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Chandrashekarappa, Manjunath Patel Gowdru
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (10/10 displayed)
- 2022Effect of Pin Geometry and Orientation on Friction and Wear Behavior of Nickel-Coated EN8 Steel Pin and Al6061 Alloy Disc Paircitations
- 2021Corrosion behaviour of high-strength Al 7005 alloy and its composites reinforced with industrial waste-based fly ash and glass fibre: comparison of stir cast and extrusion conditionscitations
- 2021Experimental investigation of selective laser melting parameters for higher surface quality and microhardness propertiescitations
- 2021Image processing of Mg-Al-Sn alloy microstructures for determining phase ratios and grain size and correction with manual measurementcitations
- 2021The effect of Zn and Zn–WO3 composites nano-coatings deposition on hardness and corrosion resistance in steel substratecitations
- 2016Multi-Objective Optimization of Squeeze Casting Process using Evolutionary Algorithmscitations
- 2016Multi-Objective Optimization of Squeeze Casting Process using Genetic Algorithm and Particle Swarm Optimizationcitations
- 2015Prediction of Secondary Dendrite Arm Spacing in Squeeze Casting Using Fuzzy Logic Based Approachescitations
- 2014Forward and Reverse Process Models for the Squeeze Casting Process Using Neural Network Based Approaches
- 2014Forward and Reverse Process Models for the Squeeze Casting Process Using Neural Network Based Approachescitations
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article
The effect of Zn and Zn–WO3 composites nano-coatings deposition on hardness and corrosion resistance in steel substrate
Abstract
Pure Zn (Zinc) and its Zn–WO<sub>3</sub> (Zinc–Tungsten trioxide) composite coatings were deposited on mild steel specimens by applying the electrodeposition technique. Zn–WO<sub>3</sub> composites were prepared for the concentration of 0.5 and 1.0 g/L of particles. The influence of WO<sub>3</sub> particles on Zn deposition, the surface morphology of composite, and texture co-efficient were analyzed using a variety of techniques, such as X-ray diffraction (XRD) and scanning electron microscopy (SEM) with Energy Dispersive X-ray analysis (EDX). Higher corrosion resistance and microhardness were observed on the Zn–WO<sub>3</sub> composite (concentration of 1.0 g/L). The higher corrosion resistance and microhardness of 1.0 g/L Zn–WO<sub>3</sub> nanocomposite coatings effectively protect the steel used for the manufacture of products, parts, or systems from chemical or electrochemical deterioration in industrial and marine ambient environments.