Key Takeaways & Executive Findings
- •• A random forest model successfully identified critical environmental thresholds (RH >80%, temperature <22.5°C) that accelerate organic coating degradation in tropical marine atmospheres. • High relative humidity and temperature have a cumulative effect on coating degradation, with corrosion risk peaking at nighttime. • The data-driven approach enables accurate prediction of coating degradation using environmental data, improving when considering the duration of influential conditions. • The study provides a cost-effective alternative to traditional exposure tests, offering insights for coating selection and corrosion control in marine environments.
Abstract
The corrosion degradation of organic coatings in tropical marine atmospheric environments results in substantial economic losses across various industries. The complexity of a dynamic environment, combined with high costs, extended experimental periods, and limited data, places a limit on the comprehension of this process. This study addresses this challenge by investigating the corrosion degradation of damaged organic coatings in a tropical marine environment using an atmospheric corrosion monitoring sensor and a random forest (RF) model. For damage simulation, a polyurethane coating applied to a Fe/graphite corrosion sensor was intentionally scratched and exposed to the marine atmosphere for over one year. Pearson correlation analysis was performed for the collection and filtering of environmental and corrosion current data. According to the RF model, the following specific conditions contributed to accelerated degradation: relative humidity (RH) above 80% and temperatures below 22.5°C, with the risk increasing significantly when RH exceeded 90%. High RH and temperature exhibited a cumulative effect on coating degradation. A high risk of corrosion occurred in the nighttime. The RF model was also used to predict the coating degradation process using environmental data as input parameters, with the accuracy showing improvement when the duration of influential environmental ranges was considered.
1. Introduction
Atmospheric corrosion poses crucial threats to safety in transportation, energy, manufacturing, and other industries [1–2]. Organic coatings represent the most common method for the prevention of atmospheric corrosion through the formation of physical barriers between metal substrates and the corrosive environment. However, coatings inevitably degrade over time during service, which induces defects, such as blistering, cracking, and delamination, that impair their protection against corrosion. A large cathode area and subtle initial phenomena make the atmospheric corrosion of damaged coatings particularly dangerous. Under service conditions, complex coating degradation causes difficulty in the timely observation and accurate prediction, both of which are crucial for coating selection and corrosion control.
The corrosion degradation of organic coatings has been extensively studied under outdoor and laboratory conditions. Corrosion in outdoor air, soil, and seawater environments is often investigated through coupon exposure tests [3–6], which are costly and lengthy. However, the limited data obtained from coupon tests are often insufficient to capture the dynamic environmental effects on coating corrosion degradation processes. Laboratory-accelerated tests, such as salt spray, immersion, wet–dry cycling, and ultraviolet (UV) aging tests [7–11], are also frequently used in the evaluation of coating corrosion degradation. However, these tests only simulate the static effects of individual environmental parameters or their simple combinations, which differ considerably from real service environments. Under laboratory conditions, mechanistic insights into coating corrosion degradation can be derived through macroscale electrochemical measurements (e.g., electrochemical impedance spectroscopy, EIS), microscale electrochemical measurements (e.g., scanning electrochemical microscopy, scanning Kelvin probe, and local electrochemical impedance spectroscopy) [12–16], or surface analyses, such as scanning electron microscopy, confocal laser scanning microscopy, and Fourier transform infrared spectroscopy [17–21].
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Shaopeng Liu, Lingwei Ma, Jinke Wang, Yiran Li, Haiyan Gong, Haitao Ren, Xiaogang Li, Dawei Zhang (2025). Towards understanding and prediction of corrosion degradation of organic coatings under tropical marine atmospheric environment via a data-driven approach. Int. Journal of Minerals, Metallurgy and Materials (矿物冶金与材料学报). https://doi.org/10.1007/s12613-024-3045-y
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Frequently Asked Questions
What environmental conditions accelerate organic coating degradation in tropical marine atmospheres?
The study found that relative humidity above 80% and temperatures below 22.5°C significantly accelerate degradation, with risk increasing when RH exceeds 90%.
How does the random forest model predict coating degradation?
The random forest model uses environmental data (e.g., RH, temperature) as input parameters to predict the degradation process, with improved accuracy when considering the duration of influential environmental ranges.
What is the significance of nighttime in corrosion risk?
The model indicated a high risk of corrosion during nighttime, likely due to higher RH and lower temperatures that promote moisture retention on the coating surface.
What are the limitations of traditional coupon exposure tests?
Traditional coupon exposure tests are costly, lengthy, and provide limited data that often fails to capture dynamic environmental effects on coating degradation.
How can this research benefit coating selection and corrosion control?
By identifying critical environmental thresholds and enabling accurate predictions, this data-driven approach helps in selecting appropriate coatings and implementing timely corrosion control measures in tropical marine environments.
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