This work introduces a novel nanocomposite coating with dual-action self-healing corrosion protection activated by the photothermal response of plasmonic titanium nitride nanoparticles (TiN NPs). TiN@mesoporous SiO₂ core–shell nanocontainers were developed as reservoirs for benzotriazole (BTA) corrosion inhibitors and incorporated into the shape memory epoxy coating matrix. Under near-infrared (NIR) light irradiation, the thermogenesis effect of TiN could not only promote the release of corrosion inhibitors from nanocontainers into the crevice, but also trigger the shape memory effect of damaged epoxy to merge the coating scratch. As such, the dual-action self-healing mechanisms combining the formation of an inhibitor-based protective layer and the scratch closure efficiently suppressed the corrosion process at the exposed metal surface. Surface characterization and electrochemical measurement results proved that the nanocomposite coating incorporated with 2 wt% of TiN-BTA@SiO₂ exhibited the optimal corrosion protection as well as an excellent self-healing performance that can be initiated within 30 s of NIR illumination. This photo-controlled self-healing approach is potentially useful in designing next-generation self-healing coatings with ultrafast response time and high healing efficiency.

The atmospheric corrosion of carbon steel was monitored by a Fe/Cu type galvanic corrosion sensor for 34 days. Using a random forest (RF)-based machine learning approach, the impacts of relative humidity, temperature and rainfall were identified to be higher than those of airborne particles, sulfur dioxide, nitrogen dioxide, carbon monoxide and ozone on the initial atmospheric corrosion. The RF model demonstrated higher accuracy than artificial neural network (ANN) and support vector regression (SVR) models in predicting instantaneous atmospheric corrosion. The model accuracy can be further improved after taking into consideration of the significant effect of rust formation on the sensor.

Recently, lubricant-infused surfaces (LIS) have emerged as a prominent class of surface technology for antifouling, anti-icing and anticorrosion applications. However, long-term corrosion exposure and mechanical damages may deteriorate the practical performance of LIS during application. In this study, a robust LIS was fabricated by the vacuum impregnation of mineral oil into anodized aluminum oxide (AAO) nanochannels with a depth of 50 μm. The impregnation of the lubricant through the entire depth of the high-aspect-ratio nanochannels was visualized under cryo-scanning electron microscopy (cryo-SEM) and also confirmed by weight gain measurements. Electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization (PDP) tests showed that the lubricant stored in the deep nanochannels of LIS can provide excellent corrosion protection during long-term immersion. Furthermore, the as-prepared LIS demonstrated superior resistance to mechanical damage due to a self-healing effect by the lubricant. As shown by cryo-SEM observation and PDP tests, the micro-cracks formed on the LIS can be instantaneously repaired by the in-flow of the oil from the surrounding surface. In the tribological tests, the LIS also presented high wear resistance and superior mechanical durability.