Synergistic Corrosion and Wear Protection of Aerospace Aluminum and Titanium Alloys Through Coatings and Engineered Surface Textures: A Critical Review

Aluminum and titanium alloys remain the structural backbone of modern airframes, engines, and landing systems because of their favorable strength-to-weight ratios. However, their service life is frequently limited, not by corrosion or wear acting independently, but by the synergistic interaction between the two under tribocorrosion conditions. This critical review evaluates the post-2021 literature on single-function coatings such as conversion coatings, plasma electrolytic oxidation, thermal spray deposits, diamond-like carbon, and PVD hard coatings; engineered surface textures produced via laser, chemical, electrochemical, and mechanical routes; and texture-coating hybrid architectures developed for aerospace-grade aluminum alloys and Ti-6Al-4V. Particular attention is given to the influence of additive-manufacturing defects and the post-processing history on coating continuity and surface functionality, together with recent developments in multiphysics modeling and machine-learning-assisted process design. The critical assessment shows that hybrid architectures provide the complimentary benefits when the texture geometry, coating continuity, interfacial adhesion, load-bearing capacity, and fatigue integrity are designed concurrently. Nevertheless, their apparent advantages have not yet been demonstrated consistently under simultaneous corrosion-wear loading and service-representative thermal, vibrational, and environmental conditions. Inconsistent test protocols, short-duration coupon studies, limited fatigue assessments, and insufficient validation based on complex geometries remain the principal barriers to aerospace qualification. Future progress therefore requires standardized tribocorrosion testing, damage-tolerant chromium-free systems, the co-qualification of additively manufactured substrates and surface treatments, and experimentally validated, uncertainty-aware modeling frameworks.