Experimental Investigation of Corrosion Behaviour of Intelligent and Commercial Coatings on Carbon Steel Under Accelerated Salt Spray Exposure

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Abstract

Corrosion of carbon steel in chloride-rich environments remains a critical challenge for marine and industrial applications, necessitating the development of durable protective coating systems. This study evaluates the corrosion resistance of an intelligent coating in comparison with the commercial coating Intertherm 228 HS under accelerated salt spray exposure following ASTM B117. Coated carbon steel specimens were subjected to 1 and 5 wt.% NaCl solutions at pH 4 and 7, temperatures of 35 and 50°C, and exposure durations of 24, 96, and 168 h. Corrosion behavior and coating degradation were characterized using scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS). The results demonstrate that corrosion severity increases with chloride concentration, acidic conditions, elevated temperature, and prolonged exposure. SEM analysis revealed the progressive formation of pits, perforations, and corrosion products, while EDS showed increasing oxygen and chlorine contents accompanied by a decline in iron content, indicating accelerated coating deterioration and substrate corrosion. Compared with the commercial coating, the intelligent coating exhibited superior resistance to chloride-induced degradation, maintaining greater surface integrity and delaying corrosion propagation under all exposure conditions. These findings highlight the strong influence of environmental parameters on coating performance and demonstrate the potential of intelligent coatings to provide enhanced long-term corrosion protection for carbon steel structures operating in aggressive chloride-containing environments.

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    Summary

    This paper compares an intelligent coating with Intertherm 228 HS coating on carbon steel under salt spray conditions. The authors study the effects of salt concentration, temperature, pH, and exposure time using visual inspection, SEM, and EDS. The topic is interesting, but some parts of the experimental method and the discussion need to be clearer and explained with more details.

    Major Comments

    1. Number of samples is not clear. In one section, the authors say that 12 samples were prepared, but later they mention 24 samples and 12 experimental runs. The total number of samples and how they were divided between the different conditions should be explained more clearly.

    2. The statistical analysis is not shown. The authors mention using a fractional factorial design and Minitab, but the paper does not show the main statistical results. It would be useful to include some results showing which factors had the strongest effect on corrosion.

    3. The most severe corrosion condition is not completely clear. Some parts of the paper indicate that higher NaCl concentration causes more corrosion, while the conclusion says that the worst condition was 1 wt.% NaCl, 50 °C, and pH 4. The authors should check this and explain clearly which condition caused the highest corrosion.

    4. Some conclusions are stronger than the presented results. The paper says that the intelligent coating performs better, but corrosion is still observed on the intelligent coating in some conditions. The comparison between the two coatings should therefore be explained more carefully and demonstrated

    Minor Comments

    1. The English should be revised because some sentences are difficult to understand or may be interpreted wrongly.

    2. The figures and captions should be checked because some labels are not completely clear.

    3. The authors should explain the EDS measurements more clearly (I could not find any explanations regarding these measurements) especially where the measurements were taken and whether more than one measurement was used for each condition. (No information found at all).

    Competing interests

    The author declares that they have no competing interests.

    Use of Artificial Intelligence (AI)

    The author declares that they did not use generative AI to come up with new ideas for their review.