Understanding Steel Corrosion: Surface Chemistry and Defects Explored Through DFT Modelling—A Review

Corrosion poses a critical challenge to the durability and performance of metals and alloys, particularly steel, with significant economic, environmental, and safety implications. The corrosion susceptibility of steel is influenced by aggressive chemical species, intrinsic material defects, and environmental factors. Understanding the atomic-scale mechanisms governing corrosion is essential for developing advanced corrosion-resistant materials. Density functional theory (DFT) has become a powerful computational tool for investigating these mechanisms, providing insight into the adsorption, diffusion, and reaction of corrosive species on iron surfaces, the formation and stability of metal oxides, and the influence of defects such as vacancies and grain boundaries in localised corrosion. This review presents a comprehensive analysis of recent DFT-based studies on iron and steel surfaces, emphasising the role of solvation effects and van der Waals corrections in improving model accuracy. It also explores defect-driven corrosion mechanisms and the formation of protective and reactive oxide layers under varying oxygen coverages. By establishing accurate DFT modelling approaches, this review provides up-to-date literature insights that support future integration with machine learning and multiscale modelling techniques, enabling reliable atomic-scale predictions.