DYNA JOURNAL ENGINEERING

Corrosion and structural degradation represent an annual global cost of more than 2.5 trillion dollars, particularly in bridges, pipelines, and marine structures exposed to extreme conditions. Until now, the standard approach has been to intervene when damage is already visible or critical, with high economic and safety costs. The emerging trend for 2026 is to integrate IoT sensors with self-healing coatings to detect and repair damage at an early stage.

Modern self-healing coatings are based on microcapsules embedded in the paint or protective material. These microcapsules contain healing agents that remain inactive until a crack or localized corrosion appears. When damage occurs, the microcapsules break and release the agent, which polymerizes and seals the affected area within hours, restoring the protective barrier without direct human intervention.

Recent advances in microcapsule engineering—improved shell stability, controlled release, and new healing chemistries—allow these coatings to withstand demanding industrial processes and operate in harsh environments such as marine or petrochemical settings. In parallel, IoT sensors integrated into the structure monitor variables such as humidity, electrochemical potential, vibrations, or micro-strains, detecting micro-damage before it becomes visible.

Combining both technologies paves the way for truly predictive maintenance: systems can flag vulnerable zones, record the timing and frequency of micro-repairs, and prioritize interventions only where they are genuinely needed. Early commercial deployments are already underway on bridges, offshore platforms, and pipeline networks, and researchers are exploring biomedical applications with self-healing materials for implantable devices.

If industrial adoption continues at the expected pace, these solutions could significantly extend the service life of critical infrastructure, improve safety, and reduce costs, becoming a cornerstone of materials engineering and asset management in this decade.