Surface stabilization treatment serves as a primary method to promote stable rust layer formation on weathering steel (WS). However, due to the complex and multicomponent chemical formulations of stabilization treatment agents (STA), the precise control over STA component ratios to achieve the best stabilization treatment effect remains highly challenging. This study combines high-throughput experiment and machine learning method to establish an optimization framework for designing rust layer STA formulation. By employing high-throughput droplet dispensing experiments and wire beam electrode electrochemical testing, a predictive model is constructed using the AdaBoost algorithm. Interpretability analysis is further integrated to guide Bayesian optimization for iterative formulation refinement. After two optimization cycles, the optimal STA formulation (0.70 g/L CuSO₄, 0.20 g/L MgSO₄, 0.60 g/L Na₂HPO₄, and 0.20 g/L tannic acid) is identified from over 2.8 million candidate formulations. The optimized STA promotes the generation of stable rust layer on Q420 WS, which effectively reduces rust layer defects, inhibits corrosive medium penetration, and significantly enhances the corrosion resistance of WS.

Developing accelerated exposure tests that accurately predict the in-service performance of structural aircraft coatings remains challenging, largely due to the complexity of simulating real-world environmental conditions without altering key degradation mechanisms. This study evaluated four different coating systems under various accelerated exposure tests and compared their degradation behavior to in-service performance. Coating degradation was characterized using electrochemical impedance spectroscopy, scanning electron microscopy, and attenuated total reflectance Fourier transform infrared spectroscopy. Under in-service conditions, failure was primarily driven by the leaching of corrosion inhibitors, while the polymer matrix degraded predominantly through hydrolysis and thermo-oxidation. In contrast, during outdoor- or cyclic salt spray exposure, inhibitor leaching remained a key contributor to coating degradation although polymer degradation was mainly caused by ultraviolet radiation or hydrolysis. These findings emphasize the challenge of replicating real-world degradation in laboratory settings. Additionally, anodized oxide layers containing polymers within their pores played a critical role in maintaining protection during early coating failure. Chromate-based systems restored barrier properties, likely through chromate adsorption on hydrolyzed products within the oxide pores. In comparison, praseodymium-based systems failed to restore protection, while lithium-based systems sustained protection through an intact polymer.

In recent years, spinel-structured transition-metal oxide ZnMn₂O₄ has attracted attention as a low-cost anode material with high lithium-ion storage capacity. However, its practical application is limited by poor intrinsic electrical conductivity, sluggish reaction kinetics, and large volume changes during repeated lithiation and delithiation, leading to unstable cycling behavior. Although several strategies have been explored to improve cyclic stability, many reported systems still suffer from limited rate performance, multistep synthesis routes, and an incomplete understanding of nitrogen-doped graphene oxide (N-rGO)-induced interfacial effects. In this work, hybrid ZnMn₂O₄/N-rGO nanocomposites with controlled graphene oxide additions of 20 and 30 wt% were synthesized via a simple one-pot hydrothermal route, enabling intimate oxide–N-rGO interfacial contact. Structural, microscopic, and X-ray photoelectron spectroscopy analyses confirmed the formation of phase-pure tetragonal ZnMn₂O₄ nanoparticles uniformly distributed on the N-rGO framework. XPS revealed a redistribution of nitrogen bonding configurations at higher GO loading, with increased graphitic nitrogen contribution that may enhance electronic conductivity, while pyridinic and pyrrolic nitrogen species provide interfacial active sites. Brunauer-Emmett-Teller analysis showed that increasing GO content enhanced the specific surface area and pore volume while preserving mesoporous architecture. The ZnMn₂O₄/N-rGO nanocomposite containing 30 wt% graphene oxide (ZMO-30) delivered a reversible discharge capacity of 859.02 mAh g^-1 after 100 cycles at 100 mA g^-1 with superior rate performance and reduced charge-transfer resistance, demonstrating the beneficial role of oxide–N-rGO interfacial engineering in improving the kinetics and durability of ZnMn₂O₄ anodes.

De-icing road salts are widely employed for snow and ice mitigation in cold climate regions, with sodium chloride (NaCl) being the most commonly used salt. The extensive application of NaCl has raised significant infrastructure, sustainability, and environmental concerns, and it has led to the emergence of various alternative de-icing salts, including other chloride-based and organic salts and compounds. In this study, the effect of zinc and acetate species on the corrosion behaviour of steels was systematically investigated using a combination of atmospheric corrosion testing, immersion testing, electrochemical measurements, cross-sectional microscopy, Zn K-edge X-ray absorption spectroscopy (XANES), and thermodynamic speciation modelling. The effect of eight chloride and non-chloride salts and their mixtures on the corrosion of structurally important galvanized steel, mild steel, and high-strength steel was studied. The chloride-based salts were found to be more detrimental than the organic salts to the corrosion of mild and high-strength steels, but all the salts were similarly corrosive to galvanized steel. It was found that the presence of both zinc and acetate species significantly enhanced corrosion and the Fe dissolution rate in steels. >40 wt.% of the 20 µm-thick galvanized zinc layer was dissolved after one week of immersion in 0.5 M sodium chloride or sodium acetate. After this one-week immersion, or the 10-week atmospheric field exposure, any remaining zinc was entirely in the form of zinc oxide. Our findings call for further investigation before using organic de-icing salts, alone or in mixtures with NaCl, on galvanized steel.

Passive metals protected by surface oxide films dominate modern structural materials. Thus, understanding the mechanisms governing passive film breakdown is essential. The electronically insulating TiO₂ passive film on titanium separates the underlying Ti⁰ from environmental oxidants, but microbial biofilms have been reported to catalyze titanium corrosion. Here we demonstrate that the common marine microbe Shewanella algae growing on titanium reduces TiO₂ to destabilize the passive film. The biofilm consumes oxygen, generating anaerobic conditions near the metal interface even when the bulk environment remains aerobic. High-resolution characterizations reveal thinning of the passive layer and accumulation of lower-valence titanium oxides. Electrochemical analyses show a 6-fold increase in corrosion current from Ti⁰ accompanied by enhanced pitting. Mutant studies and other approaches indicate that extracellular flavins function as an intermediary electron carrier for S. algae TiO₂ reduction. These results demonstrate how microbes create localized microenvironments that accelerate corrosion of otherwise highly corrosion-resistant metals.

Spinel ZnMn₂O₄ is a promising anode material for lithium-ion batteries owing to its high theoretical capacity, low cost, and environmental compatibility. However, its practical utilization is limited by poor electrical conductivity, sluggish reaction kinetics, and structural instability during repeated lithiation and delithiation. These limitations motivate the development of an interfacial strategy that can simultaneously improve charge transport and mitigate the structural degradation associated with conversion-type lithium storage. In this work, N-doped reduced graphene oxide (N-rGO) is intimately wrapped around porous ZnMn₂O₄ nanoparticles to construct an interconnected oxide–graphene interface. The N-rGO framework provides continuous electronic pathways and stable interfacial transport channels, while its flexible network helps accommodate volume variations and maintain electrical connectivity during cycling. The resulting ZMO-M/N-rGO nanocomposite exhibits improved electrochemical kinetics and high-rate capability compared with pristine ZMO-M, delivering a reversible discharge capacity of 541.09 mA h g⁻¹ at a current density of 2 A g⁻¹. Following an initial 10-cycle activation period, the nanocomposite maintains a stable electrochemical response for 300 cycles at 1 A g⁻¹, retaining a discharge capacity of 619.10 mA h g⁻¹, whereas pristine ZMO-M exhibits pronounced capacity fluctuations. Electrochemical impedance analysis further reveals lower interfacial resistance and a more gradual, controlled evolution of Li⁺ transport behavior in the nanocomposite. These results demonstrate that N-rGO interfacial wrapping is an effective approach for improving charge-transfer kinetics, maintaining stable transport pathways, and enhancing the long-term electrochemical stability of ZnMn₂O₄-based anodes.

Molybdenum disulfide (MoS ₂) has emerged as a promising electrocatalyst for the electrochemical reduction of CO ₂, primarily yielding carbon monoxide. However, product selectivity is known to be highly sensitive to structural features such as edge termination and defect density. In this work, we report the formation of higher hydrocarbons (C ₂+ products) enabled by the presence of inherent sulfur vacancies in MoS ₂ when combined with various ionic liquids as co-catalysts. While MoS ₂ has traditionally shown limited hydrocarbon output, our findings demonstrate for the first time that native defect sites, interacting synergistically with the electrolyte environment, can facilitate the production of significant amounts of C ₂+ species. These results provide new insights into defect-mediated catalytic pathways and highlight the importance of electrolyte design in tuning product distribution during CO ₂ electroreduction.

Understanding localized corrosion under atmospheric droplets is critical, yet previous studies have mostly focused on single-droplet systems or general trends, leaving the role of individual droplets within multi-droplet environments yet to be explored. Here, we present a fully automated, image-based, data-driven framework for analyzing corrosion progression under thousands of droplets simultaneously. Using time-resolved optical imaging and pre-trained large vision models for droplet segmentation, we construct per-droplet color features and propose a probability-based representation of corrosion product formation in inner and outer regions of interest. This approach overcomes the limitations of binary classification by capturing the continuous and spatially heterogeneous nature of corrosion product formation. Applied to carbon steel exposed to over 1500 pre-sprayed 1 M NaCl droplets of various sizes, the method reveals that the probability of corrosion product presence strongly depends on droplet size, with larger droplets more likely to exhibit products both under and around the droplet footprint. Moreover, corrosion products in the outer region can appear independently of under-droplet corrosion, suggesting a role for inter-droplet interactions. By transforming raw imaging data into physically meaningful per-droplet metrics, this work offers a scalable platform for investigating localized corrosion kinetics and morphology in complex, real-world droplet populations, opening new opportunities for connecting droplet formation and population behavior to local and overall atmospheric corrosion rates.

Seagoing vessels operate in harsh environments which make them especially prone to progressive degradation mechanisms such as fatigue and corrosion. Acoustic emission (AE) monitoring is gaining interest from ship operators and inspectors for its potential as an early-warning structural health monitoring technique for these types of damage. A major challenge facing the implementation of AE is dealing with the background noise. This article presents an experimental study of ultrasonic noise levels in representative environments and conditions AE monitoring. The probability of detection (PoD) is proposed as a quantitative metric for the detection of damage in the presence of operational noise. Measurements were carried out in multiple locations on board of a vessel under different operational conditions. Measurements at cruising speed on hull plates inside the engine room suggest that the ultrasonic background noise level exceeded 90 dB under 100 kHz but rapidly reduced in the higher frequencies associated with the failure mode-related AE signals. The PoD was estimated to be 94% for damage signals above 100 kHz. These results suggest that acoustic emission monitoring has the potential to perform reliably under noisy conditions. This perspective is promising to the future of a structural health monitoring system based on AE measurement.

The surging demand for high-energy density lithium-ion batteries (LIBs) necessitates the exploration of anode materials with higher storage capacity. Nickel‑cobalt (Ni-Co) based transition metal oxides (TMOs) are strong contenders due to their high theoretical capacity based on conversion reactions. The copper (Cu) doping strategy is adopted to improve the electrochemical performance through addressing the drawbacks of NiCo₂O_4, such as lower conductivity and volume expansion. In this work, Cu-doped NiCo₂O₄ nanomaterials are synthesized via a rapid, efficient, and scalable microwave-assisted synthesis route. When evaluated as an anode material for LIBs, the Cu-doped NiCo₂O₄ electrode delivers a high reversible specific capacity of 662 mAh g⁻¹ at a current density of 100 mAg⁻¹. The enhanced performance is attributed to the unique porous nanorod-like structure with a high surface area of 59.4 m²/g, which provides short lithium-ion diffusion pathways. Significantly, the copper acts as an inactive material that accommodates volume changes effectively during cycling when compared to pure NiCo₂O₄. Furthermore, the electrode exhibits an excellent rate capability and remarkable cycling stability. These findings indicate that copper doping is found to be an efficient approach for enhancing the cyclic performance of TMO-based anodes for next-generation LIBs.

The search for non-toxic alternatives to hexavalent chromium based corrosion inhibitors requires a comprehensive understanding of the factors critical to effective corrosion protection. Key considerations include the evolution of corrosion inhibition with inhibitor concentrations and exposure times, the inhibition efficacy in the presence and following absence of inhibitors, and the stability of inhibition upon polarisation. In our electrochemical comparison of promising organic molecules with sodium dichromate, we found that even top-performing candidates can lead to premature conclusions if such critical factors are overlooked. While organic molecules can match the inhibition performance of chromates under specific conditions, this can be misleading when considering concentration, time, and polarisation dependent behaviour. Initial high performance can also be deceptive in dynamic environments, as we observed that the inhibition provided by most organic molecules drastically decreases when the inhibitor is absent in the electrolyte. These observations call for broader comprehensive inhibitor robustness studies that take into account factors including time, concentration, stability, and polarisation effects in inhibitor efficacy analysis.

Eliminating hexavalent chromium-based corrosion inhibitors from structural aircraft coatings remains a significant challenge, primarily due to the lack of reliable accelerated test methods. This study evaluates the performance of various structural aircraft coatings under different exposure conditions, i.e. outdoor exposure, cyclic salt spray testing and in-service conditions, supplemented by environmental sensors. Quarterly inspections and scanning electron microscopy were used to evaluate corrosion damage. The findings highlight a lack of correlation between accelerated testing and outdoor exposure testing, likely driven by disparities in salt deposition, UV-radiation, time of wetness and temperature cycling. Additionally, galvanic couples between skin and fasteners remain difficult to protect, with chromate-based systems offering limited inhibition and alternative systems struggling to protect such complex assemblies. However, in lap-joints, alternative coatings outperformed chromate-based counterparts, likely due to their polymer matrices providing improved barrier properties, hence limiting access of electrolyte to the coating-aluminium alloy interface.

XPS analysis is routinely used in corrosion studies to analyse corrosion product and protective layers on a range of metals. In the case of transition metals and especially iron, the extraction of information about chemical species including identification and quantification requires complex fitting of the metal 2p spectrum. Unfortunately, there is extensive misunderstanding of what is required for fitting of these metal 2p photoelectron peaks. In the case of high spin Fe 2p compounds there is a complex structure based on multiplet and satellite peaks which is often ignored. In this review of the application of XPS in the study of corrosion and protection of ferrous metals; we quantify the extent of misinterpretation of XPS Fe 2p spectra within the literature. It is found that in over 70 % of papers there is an adamant misunderstanding of the requirements for fitting Fe 2p, which can be divided into three groups. First, in the most serious case, there seems to be a lack of understanding of spin orbit coupling which gives rise to the major Fe 2p_3/2 and Fe 2p_1/2 peaks with the latter being incorrectly assigned to a different chemical species. Second, satellite structures are often assigned to a different chemical species. Third, single peaks are used to fit chemical components whereas a complex multiplet structure should be employed. We establish the extent to which these errors are made by critical appraisal of over 220 papers published in selected years between 2015 and 2024.

2D materials, characterized by their extensive surface area and customizable chemical and electronic properties, offer compelling advantages as advanced materials. These unique attributes pave the way for the development of next-generation electronics and optoelectronics, photo- and electro-catalysis, energy storage and conversion devices, and sensors. The most prominent and commonly available 2D transition metal dichalcogenide, molybdenum disulfide (MoS₂), has already shown its potential for advanced applications. However, its relatively unfavorable electronic structure and limited intrinsic conductivity lower its suitability for applications that require high conductivity, such as electrocatalysts. One way to enhance its conductivity is by electrochemically intercalating alkali metal ions, e.g., Na⁺ and K⁺, into its layered structure, potentially adjusting its electronic structure. Here, we present a comprehensive investigation into the atomic-scale intercalation mechanism using molecular dynamics simulations, complemented by experimental analysis of structural and electronic properties at the macro scale through various characterization techniques. It is demonstrated that the hydration shell of ions serves as an energy barrier to intercalation as it undergoes a structural change during the intercalation. When alkali metal ions are intercalated into MoS₂, they introduce more defects and enhance conductivity. Notably, these effects are more pronounced for potassium than for sodium.