Efficiently designing lightweight alloys with combined high corrosion resistance and mechanical properties remains an enduring topic in materials engineering. Due to the inadequate accuracy of conventional stress-strain machine learning (ML) models caused by corrosion factors, a novel reinforcement self-learning ML algorithm combined with calculated features (accuracy R² >0.92) is developed. Based on the ML models, calculated work functions and mechanical moduli, a Computation Designed Corrosion-Resistant Al alloy is fabricated and verified. The performance (elongation reaches ∼30 %) is attributed to the H trapping Al-Sc-Cu phases (-1.44 eV H⁻¹) and Cu-modified η/η' precipitates inside the grain boundaries (GBs).

Prone H reduction is considered an important factor in the poor corrosion resistance of Mg and its alloys, while the reduced H simultaneously impacts their mechanical properties whose mechanism is still unclear. It can be experimentally found that the elongation of Mg charged with atomic H is 2.76 % greater than that in air. To reveal the underlying physics, multi-scale modeling combining first-principle calculation, molecular dynamic/static (MD/MS) simulation, and crystal plasticity finite element method (CPFEM) is first employed to elaborate the influence of H on Mg at different length scales. The first-principle results show that the Prism-I {101¯0} exhibits the most corrosive nature with an effective H adsorption density that reaches 18 nm⁻² and its diffusion barrier is only 0.156 eV H⁻¹. Conversely, the Basal {0001} has the best surficial H resistance. After H infiltration into the Mg matrix, the generalized stacking fault energies of most twining planes decrease by 2.26 % ∼18.49 %. Especially for the Basal {0001}, the H not only lowers its stacking fault energy to -7.13 J m⁻², but also impedes its cleavage cracking along [101¯0] according to the MD/MS simulation. The presence of H within the grains induces early initiation of stacking fault and elevates the critical stress at the crack tips. The CPFEM modeling reveals that the difference in twining growth is concentrated within 4 % strain. The H addition promotes the twining of Mg, however, following 4 % strain, the relative activity of planes in the Mg/Mg-H models is consistent.

Organic coatings are one of the most used and versatile technologies to mitigate corrosion of metals. However, organic coatings are susceptible to defects and damages that may not be easily detected. If not repaired timely, these defects may develop into major coating failures due to corrosion occurring in the damaged region, thereby limiting the lifetime of the to be protected structure. Thus, the development of smart coatings that can accurately identify corrosion location and reliably recover the damage autonomously is of particular interest. Herein, we reported a robust, corrosion-sensing and self-healing coating which incorporated pH-sensitive ZIF-8-capped CaCO₃ microcontainers containing the healing agent tung oil (TO) and the corrosion indicator/inhibitor 1,10-phenanthrolin-5-amine (APhen). The spontaneous leakage of incorporated TO and APhen was restrained, and the release initiated when local pH variation occurred. The corrosion protection performance of the coatings implanted with different contents of smart microcontainers were evaluated. The intact epoxy coating containing 7.5 wt% of the microcontainers exhibited the best protection performance with low water absorption (0.65 wt%), low O₂ permeability (0.21 × 10^–15 cm³ cm cm⁻² s⁻¹ Pa⁻¹), and a high storage modulus (3.0 GPa). Electrochemical impedance spectroscopy (EIS) measurements in 3.5 wt% NaCl solution demonstrated superior durability of the composite coating after self-healing. The immersion test and neutral salt spray test confirmed the coating can accurately report corrosion sites via coloration.

The influence of outward extracellular electron transfer (EET) of Pseudomonas aeruginosa in accelerating corrosion of 304 stainless steel was investigated. With less NO₃⁻ available as electron acceptor, P. aeruginosa biofilm accelerated the pitting corrosion. The ICP-MS and XPS results indicated that P. aeruginosa promoted the bioreductive dissolution of iron oxides in the passive film of stainless steel. Using in situ scanning electrochemical microscopy, we established a relationship between this accelerated deterioration of the passive film and the EET process mediated by the conversion of the redox states of pyocyanin secreted by P. aeruginosa.

Herein, we report the development of a self-sensing and active corrosion protection coating which incorporates pH-sensitive multilayer chitosan/alginate-covered CaCO₃ microcontainers containing 1,10-phenanthrolin-5-amine (APhen). The microcontainers can respond to pH variation to release APhen which serves not only as a corrosion indicator but also as an inhibitor. An epoxy coating doped with 5 wt% microcontainers exhibited improved corrosion performance and was capable of inhibiting corrosion spreading from the damaged area in a 3.5 wt% NaCl solution. The salt spray test showed that corrosion damage can be quickly detected by the appearance of a red color within 2 min.

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.

Microbiologically influenced corrosion of metals is prevalent in both natural and industrial environments, causing enormous structural damage and economic loss. Exactly how microbes influence corrosion remains controversial. Here, we show that the pitting corrosion of stainless steel is accelerated in the presence of Shewanella oneidensis MR-1 biofilm by extracellular electron transfer between the bacterial cells and the steel electrode, mediated by a riboflavin electron shuttle. From pitting measurements, X-ray photoelectron spectroscopy and Mott-Schottky analyses, the addition of an increased amount of riboflavin is found to induce a more defective passive film on the stainless steel. Electrochemical impedance spectroscopy reveals that enhanced bioanodic and biocathodic process can both promote the corrosion of the stainless steel. Using in situ scanning electrochemical microscopy, we observe that extracellular electron transfer between the bacterium and the stainless steel is bidirectional in nature and switchable depending on the passive or active state of the steel surface.

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.

In this study, a new self-healing shape memory polymer (SMP) coating was prepared to protect the aluminum alloy 2024-T3 from corrosion by the incorporation of dual-function microspheres containing polycaprolactone and the corrosion inhibitor 8-hydroxyquinoline (8HQ). The self-healing properties of the coatings were investigated via scanning electron microscopy, electrochemical impedance spectroscopy, and scanning electrochemical microscopy following the application of different healing conditions. The results demonstrated that the coating possessed a triple-Action self-healing ability enabled by the cooperation of the 8HQ inhibitor, the SMP coating matrix, and the melted microspheres. The coating released 8HQ in a pH-dependent fashion and immediately suppressed corrosion within the coating scratch. After heat treatment, the scratched coating exhibited excellent recovery of its anticorrosion performance, which was attributed to the simultaneous initiation of scratch closure by the shape memory effect of the coating matrix, sealing of the scratch by the melted microspheres, and the synergistic effect of corrosion inhibition by 8HQ.

This work introduces a new self-healing superhydrophobic coating based on dual actions by the corrosion inhibitor benzotriazole (BTA) and an epoxy-based shape memory polymer (SMP). Damage to the surface morphology (e.g., crushed areas and scratches) and the corresponding superhydrophobicity are shown to be rapidly healed through a simple heat treatment at 60 °C for 20 min. Electrochemical impedance spectroscopy (EIS) and scanning electrochemical microscopy (SECM) were used to study the anti-corrosion performance of the scratched and the healed superhydrophobic coatings immersed in a 3.5 wt% NaCl solution. The results revealed that the anti-corrosion performance of the scratched coatings was improved upon the incorporation of BTA. After the heat treatment, the scratched superhydrophobic coatings exhibited excellent recovery of their anti-corrosion performance, which is attributed to the closure of the scratch by the shape memory effect and to the improved inhibition efficiency of BTA. Furthermore, we found that the pre-existing corrosion product inside the coating scratch could hinder the scratch closure by the shape memory effect and reduce the coating adhesion in the scratched region. However, the addition of BTA effectively suppressed the formation of corrosion products and enhanced the self-healing and adhesion performance under these conditions. Importantly, we also demonstrated that these coatings can be autonomously healed within 1 h in an outdoor environment using sunlight as the heat source.