On the local corrosion behavior of coupled welded zones of the 2098-T351 Al-Cu-Li alloy produced by Friction Stir Welding (FSW): An amperometric and potentiometric microelectrochemical investigation

Contributions to a More Realistic Characterization of Corrosion Processes on Cut Edges of Coated Metals Using Scanning Microelectrochemical Techniques, Illustrated by the Case of ZnAlMg-Galvanized Steel with Different Coating Densities

Corrosion processes at cut edges of galvanized steels proceed as highly localized electrochemical reactions between the exposed bulk steel matrix and the protective thin metallic coating of a more electrochemically active material. Scanning microelectrochemical techniques can thus provide the spatially resolved information needed to assess the corrosion initiation and propagation phenomena, yet most methods scan cut edge sections as embedded in insulating resin to achieve a flat surface for scanning purposes. In this work, the galvanized coatings on both sides of the material were concomitantly exposed to simulated acid rain while characterizing the cut edge response using SECM and SVET techniques, thereby maintaining the coupled effects through the exposure of the whole system as rather realistic operation conditions. The cut edges were shown to strongly promote oxygen consumption and subsequent alkalization to pH 10-11 over the iron, while diffusion phenomena eventually yielded the complete depletion of oxygen and pH neutralization of the nearby electrolyte. In addition, the cathodic activation of the exposed iron was intensified with a thinner coating despite the lower presence of sacrificial anode, and preferential sites of the attack in the corners revealed highly localized acidification below pH 4, which sustained hydrogen evolution at spots of the steel-coating interface.

Uses of Scanning Electrochemical Microscopy (SECM) for the Characterization with Spatial and Chemical Resolution of Thin Surface Layers and Coating Systems Applied on Metals: A Review

Scanning Electrochemical Microscopy (SECM) is increasingly used in the study and characterization of thin surface films as well as organic and inorganic coatings applied on metals for the collection of spatially- and chemically-resolved information on the localized reactions related to material degradation processes. The movement of a microelectrode (ME) in close proximity to the interface under study allows the application of various experimental procedures that can be classified into amperometric and potentiometric operations depending on either sensing faradaic currents or concentration distributions resulting from the corrosion process. Quantitative analysis can be performed using the ME signal, thus revealing different sample properties and/or the influence of the environment and experimental variables that can be observed on different length scales. In this way, identification of the earlier stages for localized corrosion initiation, the adsorption and formation of inhibitor layers, monitoring of water and specific ions uptake by intact polymeric coatings applied on metals for corrosion protection as well as lixiviation, and detection of coating swelling—which constitutes the earlier stages of blistering—have been successfully achieved. Unfortunately, despite these successful applications of SECM for the characterization of surface layers and coating systems applied on metallic materials, we often find in the scientific literature insufficient or even inadequate description of experimental conditions related to the reliability and reproducibility of SECM data for validation. This review focuses specifically on these features as a continuation of a previous review describing the applications of SECM in this field.

Prediction of mechanical properties and hardness of friction stir welding of Al 5083/pure Cu using ANN, ICA and PSO model

The effect of parameters involved in prediction of mechanical properties of Friction Stir Welding have been investigated in this study through modeling. For this purpose, the friction stir welding on both sheets of 5083 Aluminum (Al5083) and pure Copper (Cu) was experimentally conducted at first level. Three factors of Rotation Speed (RPM), Traverse Speed (mm/min) and the Tool’s pin angle was examined. During the tentative test, many experiments were not satisfactorily performed. Thanks to a more rigorous study hypothesis, proper samples were obtained by changing the geometry of different tools. In order to overcome the softness of aluminum sheets and the rise of shoulder diameter, and also to avoid the vertical instability of the sheet, shortening the pin’s length was suggested. In this paper, the Full Factorial method has been employed to evaluate the result of Artificial Neural Networks (ANN), Imperialist Competitive Algorithm, Particle Swarm Optimization, and also the effects of input parameters of the process on output parameters. Moreover, Al5083 and Cu joining sheets were analyzed. Micro-hardness and tensile tests have been based on the process’ input parameters to obtain mechanical properties. The function of ANN model demonstrates that it can estimate the number of mechanical properties with an adequate precision. Using the evaluation factors of mechanical properties and micro-hardness and also a R2 ~ 0.943 analysis, the optimum parameters of Al5083 and Cu joining sheets can be anticipated. The rotation speed of 1150 rpm, traverse speed of 40 mm/min, and pin angle of 2° are the optimum conditions based on the average review of analyses. These optimum conditions led to improve the maximum tensile force up to 15 ~ 21%.