Fundamentals, Sustainable Strategies, and Emerging Technologies of Metal Protection and Corrosion Prevention: A Comprehensive Review
DOI:
https://doi.org/10.33003/fjs-2026-1018-5507Keywords:
Artificial Intelligence, Corrosion Prevention, Corrosion Monitoring, Green Inhibitors, Metal ProtectionAbstract
Corrosion is an intricate physicochemical process that gradually degrades and reduces the practical and engineering integrity of metallic substances or materials through exchange with their immediate environment. Mechanisms such as aggressive chemical species, electrochemical reactions, moisture, and extreme dissolved salt concentrations accelerate material deterioration, which often leads to structural and material failures. Corrosion impacts are widespread across critical sectors including manufacturing, production, energy, transportation, and civil infrastructure. This study presents a comprehensive review of corrosion science, corrosion monitoring techniques, and emerging artificial intelligence (AI)-driven approaches for corrosion prevention and corrosion management. Information on trends and patterns of publications on corrosion was systematically collected, synthesized, and refined from journals, conference proceedings, theses, books, and other credible scientific sources published between 1800 and June 2026. Universal academic search aggregators, engines, discipline-specific and regional repositories were utilised to identify and produce relevant papers. The review identified major forms of corrosion as atmospheric, cavitation, erosion, fatigue, fretting, galvanic, intergranular, microbiological, pitting, stress or cracking, selective leaching, chemical, electrochemical, and waterline. It was established that there are four phases of publications on corrosion and corrosion-related topics. Corrosion prevention methods depend on several factors. It was revealed that heterocyclic corrosion inhibitors include C5H5N, C3H4N2, C7H6N2, C2H3N3, C4H4S, C3H3NS, C3H3NO and C6H5N3. The study concludes that early corrosion prediction, coupled with effective monitoring and control strategies, can substantially reduce economic losses, while AI-driven approaches offer practical advantages over traditional methods of corrosion prevention, particularly in inaccessible or hazardous environments.
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