Ni coatings were electrodeposited from 1:2 choline chloride (ChCl)-urea (U) deep eutectic solvents (DESs) on low carbon steel. We report on the interrelated influence of water content in the electrolyte and applied potential on the formation of Ni films and their chemical composition and morphology. This was investigated by cyclic voltammetry (CV) and chronoamperometry (CA) in combination with ex-situ characterization techniques (FE-SEM, EDS, XPS and Raman spectroscopy). Ni electrodeposition from DES is shown to be highly complex: Ni þ2 reduction is followed by water reduction, which triggers electrolyte decomposition. A water content higher than 4.5%wt and/or performing electrodeposition at potentials more negative than E ¼ À0:90V vs Ag quasi-reference electrode enhances the decomposition of the solvent. This breakdown appears via either an electrochemical reaction or triggered by water splitting. In both cases, it leads to the incorporation of DESs decomposition products, such as trimethylamine and acetaldehyde within the Ni film. Under these conditions, the films are composed of metallic Ni and NiO x (OH) 2(1Àx) .
In this paper a mechanistic model is elaborated to simulate the corrosion behavior of aluminum–zinc–magnesium coatings on steel. The model is based on the mass transport and reactions of the ions in the electrolyte (MITReM). The finite element method has been used, which allows to perform time‐dependent simulations with micrometer scale to study local corrosion effects. The formation of corrosion products and the prediction of electrolyte concentration distributions are compared for different metallic coating compositions. The spatial and temporal simulation of complex precipitates provides an additional tool to validate the model through corrosion product characterization. The simulation results are compared to experimental observations, presented in part I of this paper. The MITReM simulations are limited to the micro‐scale and therefore to small geometries. A link is made with the potential model which can be applied on macro‐scale objects. A qualitative agreement is found between the simulations at both scales and the experiments. Further quantification of this model would optimize the simulations for material design and for predictive maintenance.
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