Study of Microstructure and Corrosion Properties of Electro-Codeposited Ni-SiO<sub>2</sub> Nanocomposite Coatings from Deep Eutectic Solvent (DES) Electrolyte
Notice bibliographique
Résumé
Metal matrix composites containing metal and semiconductor or insulator nanoparticles have been fabricated through different methods and mechanical and electrochemical behavior studied [1-8]. Electro-codeposition is a metal matrix nanocomposite coating fabrication method that is used widely due to its superior advantages such as homogeneous coatings, low cost, easy set-up and fast deposition rate [9,10]. Several examples of metal matrix composites are reported in the literature. In the case of nickel-based composites, many of the pure, ceramics and oxides nano/micro-sized particles such as Ti [1], TiO2 [2,3], SiC [4,5], SiO2 [6,7], and Al2O3 [8] are added as the second phase. In this paper, the fabrication of Ni-SiO2 nanocomposite coatings and the influence of the addition of SiO2 nanoparticles on composition, microstructure and corrosion properties of electrodeposited Ni-SiO2 nanocomposite coatings are discussed. A pulse electro-codeposition method was employed to prepare Ni-SiO2 nanocomposite coating on the surface of AISI 1045 medium carbon steel from a choline chloride (ChCl)/ethylene glycol (EG)-based deep eutectic solvent (DES) with a ChCl to EG molar ratio of 1/2. Nickel chloride [NiCl2.6H2O] and 15 g/L silicon dioxide (SiO2) nanopowder, 10-20 nm particle size and 99.5% purity, were then added to the electrolyte. The electro-codeposition process, for pure Ni and Ni-SiO2 nanocomposite coatings, was carried out at the same conditions of temperature, current density and frequency that were set to 70 °C, 8 mA/cm2 and 1000 Hz, respectively. Disc-shaped medium carbon steel substrates were mechanically polished and degreased followed by activation before electro-codeposition. Scanning electron microscopy (SEM), Energy-dispersive X-ray spectroscopy (EDS) and X-ray diffraction (XRD), were used to study microstructure, surface morphology, composition, and phase analysis of the Ni-SiO2 nanocomposite and pure Ni coatings. Corrosion properties of the coatings were evaluated by means of potentiodynamic polarization test in 3.5 wt.% NaCl solution at room temperature. SEM images revealed that the addition of silicon dioxide nanoparticles to the nickel film affects the grain size, microstructure and morphology of the coating surface. The microstructure of the nanocomposite coating is a combination of nano and micro-sized structures on the surface. A granular-like microstructure with a quasi-uniform dispersion of SiO2 nanoparticles in the coating was observed. Our characterization results confirm the incorporation of SiO2 nanoparticles into the Ni film. Potentiodynamic polarization results showed that the incorporation of SiO2 nanoparticles into the Ni film significantly improved the corrosion properties of the coatings compared to the pure nickel. Corrosion potential of Ni-SiO2 nanocomposite coating increased to a more positive value, and the corrosion current density decreased by a factor of 10 compared to that of pure Ni. Enhanced corrosion resistance in nanocomposite coating with respect to the pure Ni is explained by the effect of the addition of SiO2 nanoparticles on both microstructure and composition of the nanocomposite coating. Thus, the electrodeposition method using choline chloride/ethylene glycol-based DES solution can be used to produce Ni-SiO2 nanocomposite coating with uniformly dispersed SiO2 nanoparticles in the Ni film that exhibits clearly better corrosion resistance compared to pure Ni coating and suggesting its potential application in industry with the goal of surface corrosion protection. Keywords: corrosion, nanocomposite, coating, nickel, silicon dioxide, deep eutectic solvent References [1] Lekka, M.; Offoiach, R.; Revelant, F.; Fedrizzi, L. Trans. IMF 2019, 97, 73-81. [2] Mohajeri, S.; Dolati, A.; Ghorbani, M. J. Ultrafine Grained Nanostruct. Mater. 2016, 49, 51-63. [3] Danilov, F. I. et al. Surf. Eng. Appl. Electrochem. 2019, 55, 138–149. [4] Lanzutti, A. et al. Tribol. Int. 2019, 132, 50-61. [5] Zhou, Y.; Xie, F. Q.; Wu, X. Q.; Zhao, W. D.; Chen, X. J. Alloys Compd. 2017, 699, 366-377. [6] Li, R.; Hou, Y.; Liu, B.; Wang, D.; Liang, J. Electrochim. Acta 2016, 222, 1272–1280. [7] Ratajski, T. et al. Mater. Charact. 2018, 142, 478-491. [8] Jiang, S. W.et al. Surf. Coat. Technol. 2016, 286, 197-205. [9] Chen, W. W.; Gao, W.; He, Y. D. Surf. Coat. Technol. 2010, 204, 2493-2498. [10] Tu, W. Y. et al. J. Mater. Sci. 2008, 43, 1102-1108.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».