The targeted removal of efficient but toxic corrosion inhibitors based on hexavalent chromium has provided an impetus for discovery of new, more benign organic compounds to fill that role. Developments in high-throughput synthesis of organic compounds, the establishment of large libraries of available chemicals, accelerated corrosion inhibition testing technologies, the increased capabilities of machine learning (ML) methods, and a better understanding of mechanisms of inhibition provide the potential to make discovery of new corrosion inhibitors faster and cheaper than ever before. These technical developments in the corrosion inhibition field are summarized herein. We describe how data-driven machine learning methods can generate models linking molecular properties to corrosion inhibition that can be used to predict the performance of materials not yet synthesized or tested. The literature on inhibition mechanisms is briefly summarized along with quantitative structure–property relationships models of small organic molecule corrosion inhibitors. The success of these methods provides a paradigm for the rapid discovery of novel, effective corrosion inhibitors for a range of metals and alloys, in diverse environments. A comprehensive list of corrosion inhibitors tested for various substrates that was curated as part of this review is accessible online https://excorr.web.app/database and available in a machine-readable format.

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Hydrogen gained momentum as a viable alternative to crude-derived fuels. Scalable production of green hydrogen harnessing solar energy emerged as one of the promising sustainable options that can be facilitated by photocatalyst-assisted water splitting. One-step and two-step photoexcitation systems for overall water splitting (OWS) processes gained much importance because of the ease with which they can be scaled up. This chapter gives a profound insight into the fundamental aspects of these systems, along with a broader picture regarding their possible pathway for commercial implementation. Thermodynamic and kinetic requisites of these novel systems have been described in detail and a critical appraisal of the selectivity of co-catalysts in the photocatalytic OWS process is presented. Subsequently, this chapter provides a comprehensive focus on various novel scalability studies like thin film systems, baggie reactors and the solar hydrogen farm project. The ultimate motive of this chapter is to summarize the current state-of-the-art strategies for producing green hydrogen through heterogeneous photocatalysis and the various limitations it possesses that preclude the system from reaching the market so far. By this it will motivate people to develop innovative pathways that would rectify the problems associated with it.@en

Creating durable, eco-friendly coatings for long-term corrosion protection requires innovative strategies to streamline design and development processes, conserve resources, and decrease maintenance costs. In this pursuit, machine learning emerges as a promising catalyst, despite the challenges presented by the scarcity of high-quality datasets in the field of corrosion inhibition research. To address this obstacle, we have created an extensive electrochemical library of around 80 inhibitor candidates. The electrochemical behaviour of inhibitor-exposed AA2024-T3 substrates was captured using linear polarisation resistance, electrochemical impedance spectroscopy, and potentiodynamic polarisation techniques at different exposure times to obtain the most comprehensive electrochemical picture of the corrosion inhibition over a 24-h period. The experimental results yield target parameters and additional input features that can be combined with computational descriptors to develop quantitative structure–property relationship (QSPR) models augmented by mechanistic input features.

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Despite extensive research, eliminating hexavalent chromium-based inhibitors from aerospace coatings remains challenging due to a lack of understanding of coating degradation during aircraft service. This study addresses the issue by investigating the protective mechanisms and aging processes of chromate-containing coatings on aircraft components after service for over 35 years. Four aircraft parts underwent visual inspection, disassembly, and analysis using scanning electron microscopy (SEM) and X-ray Photoelectron Spectroscopy (XPS). While most coating areas remained intact after extended use, three distinct degradation modes were identified: tip erosion, corrosion around rivets, and corrosion around fasteners at the leading edge. These findings reveal the complexity of corrosion protection, emphasizing that hexavalent chromium-containing coatings may not offer comprehensive protection at local design heterogeneities. The study also highlights the need to revisit traditional laboratory analysis protocols based on accelerated corrosion testing of oversimplified sample configurations, given the revealed end-of-service failure mechanisms.@en

Utilizing a dedicated micro-sized three-electrode cell, this study systematically investigates early-stage electrochemical properties and corrosion behavior of pure iron under single droplets. Various volumes and NaCl concentrations were considered during the evaporation-driven shape and concentration evolution of single droplets. The measurements disclosed that reducing the droplet size from 5 µL to 1.5 µL at 0.01 M NaCl concentration, increased noise resistance (R_n) and polarization resistance (R_p) values. However, at 0.1 M and 0.2 M NaCl concentrations, reducing droplet size led to the domination of relatively high chloride ion concentration over oxygen diffusion, resulting in a very low R_n and R_p and hence enhanced localized corrosion.

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Understanding how late an inhibitor can be released once corrosion initiated without compromising corrosion protection may help in developing more efficient anticorrosion coatings. We explored this idea through time-controlled Ce(NO₃)₃ availability to AA2024-T3 immersed in 0.05 M NaCl. Ce(NO₃)₃ was supplied at 0, 30, 60, and 180 s from the start of immersion to get a concentration of 0.001 M. Detailed visualization of surface changes at the intermetallic particle level was obtained using in-situ reflected microscopy. SEM-EDX and confocal laser microscopy confirmed the extent of intermetallic degradation and local inhibitor deposition corresponding to operando changes. When the inhibitor is supplied within 60 s of immersion, the surface changes slowdown earlier and are visually less extensive than in uninhibited systems. Furthermore, our results highlight the potential of reflected microscopy for local corrosion inhibition studies and underscore the importance of understanding the interaction between inhibitor release timing and corrosion protection.

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The substitution of chromate-containing structural coating systems in aviation with alternatives complying with nowadays strict environmental, health and safety regulations remains a formidable challenge. This complexity is partly due to the absence of a standardized from-test-to-market methodology, including a performance comparison between chromate-containing and alternative coating systems. To address this gap, the present study delves into the identification of crucial degradation factors that merit inclusion in such a methodology. Concurrently, it investigates the protective mechanisms inherent in chromate-containing coating systems and proposes improvements that can be applied to alternative coating systems. This study entails a comprehensive post-service examination of the degradation of paint applied to an aircraft component with over 35 years of service, employing electrochemical, microscopic and spectroscopic techniques. The findings underscore the role of thermo-oxidation as a significant degradation factor in the aging process of such coatings. Furthermore, the investigation elucidates a notable phenomenon in which aluminium ions within the coating pores form an aluminium hydroxide gel onto which chromate adsorbs. This process contributes to an increase in pore resistance upon exposure to electrolyte, leading to a self-healing barrier effect within the coating. Remarkably, this self-healing mechanism continues to offer long-term protection even when the coating matrix is sub-optimally cured due to application errors. Furthermore, this study reveals that the significant changes in capacitance during immersion testing result primarily from inhibitor leaching, emphasizing the effectiveness of combining Electrochemical Impedance Spectroscopy (EIS) with Scanning Electron Microscopy (SEM) analysis for studying coating degradation.

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The authors regret that an error occurred in the description of equation 3 in the published version of the above-mentioned article, which should be as follows: [Formula presented] The correct equation was implemented for calculating all the results presented in the article, so all results, discussions and conclusions presented in the manuscript remain fully valid > The authors would like to apologise for any inconvenience caused.

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Corrosion-fatigue is considered to be one of the main degradation mechanisms affecting the structural integrity of offshore support structures. This paper presents a feasibility assessment for the detection and monitoring of corrosion-fatigue damage using non-contact acoustic emission (AE). An accelerated corrosion-fatigue experiment was conducted on a S420NL dog-bone specimen. A corrosion-fatigue cell was designed and fabricated to simultaneously apply accelerated corrosion and cyclic loads on the specimen submerged in artificial seawater. A three-electrode electrochemical configuration under potentiostatic control was used to accelerate corrosion. The ultrasound signals were continuously measured using underwater AE transducers (in the frequency range of 50–450 kHz) placed at a fixed distance from the tested coupon. The results of the accelerated corrosion-fatigue experiment suggest that corrosion-fatigue-induced ultrasound signals can be detected with a satisfactory signal-to-noise ratio using non-contact AE sensors. The mean energy of the corrosion-fatigue-induced ultrasound signals was one order of magnitude higher than that of the corrosion-induced signals. The trends of the AE parameters extracted from the AE signals were analysed as functions of the load cycles. The results revealed high potential for the identification and monitoring of corrosion-fatigue damage using the non-contact AE technique.

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The biodegradation of therapeutic magnetic-oxide nanoparticles (MONPs) in the human body raises concerns about their lifespan, functionality, and health risks. Interactions between apoferritin proteins and MONPs in the spleen, liver, and inflammatory macrophages significantly accelerate nanoparticle degradation, releasing metal ions taken up by apoferritin. This can alter the protein’s biological structure and properties, potentially causing health hazards. This study examines changes in apoferritin’s shape, electrical surface potential (ESP), and protein-core composition after incubation with cobalt-ferrite (CoFe₂O₄) oxide nanoparticles. Using atomic force microscopy (AFM) and scanning Kelvin probe force microscopy (SKPFM), we observed changes in the topography and ESP distribution in apoferritin nanofilms over time. After 48 h, the characteristic apoferritin hole (∼1.35 nm) vanished, and the protein’s height increased from ∼3.5 to ∼7.5 nm due to hole filling. This resulted in a significant ESP increase on the filled-apoferritin surface, attributed to the formation of a heterogeneous chemical composition and crystal structure (γ-Fe₂O₃, Fe₃O₄, CoO, CoOOH, FeOOH, and Co₃O₄). These changes enhance electrostatic interactions and surface charge between the protein and the AFM tip. This approach aids in predicting and improving the MONP lifespan while reducing their toxicity and preventing apoferritin deformation and dysfunction.

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This paper for the first time treats the interpretation of electrochemical noise time-frequency spectra as an image classification problem. It investigates the application of a convolutional neural network (CNN) for deep learning image classification of electrochemical noise time-frequency transient information. Representative slices of these spectra were selected by our transient analysis technique and served as input images for the CNN. Corrosion data from two types of pitting corrosion processes serve as test cases: AISI304 and AA2024-T3 immersed in a 0.01M HCl and 0.1M NaCl solution between 0 and 1ks after immersion, respectively. Continuous wavelet transform (CWT) spectra and modulus maxima (MM) are used to train the CNN, either individually or in a combined form. The classification accuracy of the CNN trained with the combined dataset is 0.97 and with the two individual datasets 0.72 (only CWT spectrum) and 0.84 (only MM). The ability to additionally classify a more progressed form of pitting corrosion of AA2024-T3 between 9 and 10ks after immersion indicates that the proposed method is sufficiently robust using combined datasets with CWT spectra and MM. The pitting processes can effectively be detected and classified by the proposed method. The most important contribution of the present work is to introduce a novel procedure that decreases the classical need for large amounts of raw data for training and validation purposes, while still achieving a satisfactory classification robustness. A relatively small number of individual signals thereby generates a multitude of input images that still contain all relevant kinetic information about the underlying chemo-physical process.@en

A detailed microstructural and electrochemical analysis of electroless nickel phosphorous (NiP) coatings with P contents of 13.2 ± 1.2 wt%, 12.9 ± 0.7 wt%, and 8.3 ± 0.8 wt% on a copper substrate was performed to study the corrosion behaviour of electroless NiP/Cu systems. The P content of the electroless NiP coatings plays an essential role in the microstructure of the coatings in terms of crystallinity. The crystallinity variations, representing the extent of crystalline and amorphous phases within the material, with P content, affect the local electrochemical characteristics and, hence, the corrosion protection behaviour of electroless NiP coatings. The coatings with the highest P content showed the best corrosion performance in a 3.5 wt-% NaCl solution. In contrast, the surface of the electroless NiP coatings with low P content is more susceptible to corrosion due to the presence of locations with heterogeneous electronic properties that initiate localised corrosion. Microgalvanic interactions with a high cathode-to-anode surface ratio govern the localised corrosion kinetics of the low P-content samples. A high concentration of nodule boundaries and/or other existing structural defects on the surface serve as anodic sites, whereas the remainder of the surface serves as cathodic sites.

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The influence of dissolved oxygen (DO) and Shewanella algae on the corrosion behavior of pure titanium were systematically studied in this work. The formation of S. algae biofilms on titanium surface was facilitated by the anaerobic environment, which accelerated titanium corrosion. Upon the breakdown of passive film, S. algae acquired electrons from the titanium base substrate through extracellular electron transfer (EET) processes. Various EET-related genes were overexpressed by the low DO condition, leading to enhanced EET kinetics. High concentration DO increased TiO2 content and the thickness of passive film, which enhanced the protective effect and mitigated microbiologically influenced corrosion.@en

Three imidazole-based compounds (imidazole, 2-mercaptobenzimidazole, and 2-mercapto-1-methylbenzimidazole) were studied as corrosion inhibitors of Cu, Zn, and a family of Cu-xZn brass alloys (x = 10−40 wt%) in 3 wt% NaCl solution. The composition of inhibitor layers on the surface was studied using X-ray photoelectron and infrared spectroscopies. The molecular adsorption modes on Cu and Zn were modelled using density-functional theory (DFT) calculations. Mercapto-based inhibitors act as efficient inhibitors on all materials studied due to the formation of inhibitor layer through bonding with nitrogen and sulphur atoms. In contrast, imidazole is a moderate inhibitor for Zn, while it is much less efficient for Cu.

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Microbially influenced corrosion (MIC) of metals exerts a negative effect on the marine environment and causes a great loss of marine facilities. Corrosion prevention in an eco-friendly and sustainable way is a difficult problem to address, especially in the marine environment. In this work, Nocardiopsis dassonville, a corrosive bacteria isolated from the South China Sea was studied by using carbon steel. The results indicate that N. dassonville caused a corrosion loss of 7.68 mg cm⁻² and a corrosion pit of 13.0 μm on the carbon steel surface, but the corrosion is inhibited in the presence of Vibrio sp. EF187016 in the medium. Vibrio sp. EF187016 preferentially occupied the carbon steel surface, forming a protective biofilm that hindered the attachment of N. dassonville. In addition, extracellular polymeric substances extracted from Vibrio sp. EF187016 was added to N. dassonvillei inoculated medium and showed a significant inhibition of MIC on carbon steel.

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The sol–gel process is a chemical surface preparation method based on hydrolysis and polycondensation reactions for enhanced adhesion for metallic substrates in adhesive bonding and coating applications. This paper describes an investigation into the effect of the microstructural complexity of two commonly used aerospace aluminium alloys (AAs) 2024-T3 and 7075-T6, on the response to different surface pre-treatments before deposition of the sol-gel coating and subsequent adhesive bonding. Different surface pre-treatments, including two abrasive treatments and three chemical surface pre-treatments were used, and their effect on surface chemistry, wettability and roughness was assessed. Surfaces were characterized by scanning electron microscopy, X-ray photoelectron spectroscopy, profilometry and static contact angles. A hybrid silane sol-gel film was deposited on the differently pre-treated aluminium alloys, an epoxy adhesive was applied and the adhesion properties were evaluated using pull-off testing. The role of the altered physicochemical properties of the pre-treated surfaces was related to the adhesion strength of the sol–gel reinforced epoxy/aluminium interfaces. The microstructural complexity of the aerospace alloys caused non-uniform responses to the pre-treatments, proving the importance of compatibility between material and treatment conditions. Statistical analysis revealed that, despite that overall higher adhesion values were obtained on rougher surfaces, only a strong correlation exists between the surface hydroxyl fraction and adhesion strength. The relation of roughness and water contact angle to interfacial adhesion was found to be non-significant. The findings of this study underscore the critical role of surface pre-treatments and their impact on adhesion strength in aerospace aluminium alloys, providing valuable insights for the effective utilization of sol-gel coatings in adhesive bonding and coating processes.

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Machine learning is a powerful means for the rapid development of high-performance functional materials. In this study, we presented a machine learning workflow for predicting the corrosion resistance of a self-healing epoxy coating containing ZIF-8@Ca microfillers. The orthogonal Latin square method was used to investigate the effects of the molecular weight of the polyetheramine curing agent, molar ratio of polyetheramine to epoxy, molar content of the hydrogen bond unit (UPy-D400), and mass content of the solid microfillers (ZIF-8@Ca microfillers) on the low impedance modulus (lg|Z|_0.01Hz) values of the scratched coatings, generating 32 initial datasets. The machine learning workflow was divided into two stages: In stage I, five models were compared and the random forest (RF) model was selected for the active learning. After 5 cycles of active learning, the RF model achieved good prediction accuracy: coefficient of determination (R ²) = 0.709, mean absolute percentage error (MAPE) = 0.081, root mean square error (RMSE) = 0.685 (lg(Ω·cm²)). In stage II, the best coating formulation was identified by Bayesian optimization. Finally, the electrochemical impedance spectroscopy (EIS) results showed that compared with the intact coating ((4.63 ± 2.08) × 10¹¹ Ω·cm²), the |Z|_0.01Hz value of the repaired coating was as high as (4.40 ± 2.04) × 10¹¹ Ω·cm². Besides, the repaired coating showed minimal corrosion and 3.3% of adhesion loss after 60 days of neutral salt spray testing.

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Mg and its alloys are promising biodegradable materials for orthopedic implants and cardiovascular stents. The first interactions of protein molecules with Mg alloy surfaces have a substantial impact on their biocompatibility and biodegradation. We investigate the early-stage electrochemical, chemical, morphological, and electrical surface potential changes of alloy WE43 in either 154 mM NaCl or Hanks’ simulated physiological solutions in the absence or presence of bovine serum albumin (BSA) protein. WE43 had the lowest electrochemical current noise (ECN) fluctuations, the highest noise resistance (Zn = 1774 Ω·cm2), and the highest total impedance (|Z| = 332 Ω·cm2) when immersed for 30 min in Hanks’ solution. The highest ECN, lowest Zn (1430 Ω·cm2), and |Z| (49 Ω·cm2) were observed in the NaCl solution. In the solutions containing BSA, a unique dual-mode biodegradation was observed. Adding BSA to a NaCl solution increased |Z| from 49 to 97 Ω·cm2 and decreased the ECN signal of the alloy, i.e., the BSA inhibited corrosion. On the other hand, the presence of BSA in Hanks’ solution increased the rate of biodegradation by decreasing both Zn and |Z| while increasing ECN. Finally, using scanning Kelvin probe force microscopy (SKPFM), we observed an adsorbed nanolayer of BSA with aggregated and fibrillar morphology only in Hanks’ solution, where the electrical surface potential was 52 mV lower than that of the Mg oxide layer.@en

The quest for novel alternatives to hexavalent-chromium-based corrosion inhibitors is of utmost significance and urgency. Strict international health and safety regulations, due to growing concerns regarding the impact of hexavalent chromium on human health and the environment, have pushed the commercial introduction of many alternative inhibitor types, but the implementation of alternative active protective primers for structural parts in the aerospace industry is still pending. This endeavour has proven to be remarkably challenging, as the potential replacement coating types must meet numerous functional requirements encompassing cost-effectiveness and exceptional corrosion protection for intrinsically corrosion susceptible aerospace aluminium alloys. In recent years, considerable attention has been drawn to lithium salts as environmentally friendly corrosion inhibitors forming the basis for a novel active protective coating technology. The involvement of lithium ions has been shown to play a pivotal role in the conversion process of aluminium alloy surfaces by stabilizing the reaction products, thereby facilitating the gradual development of a protective layer with a multi-layered configuration, which exhibits considerable variability in morphology, depending on local chemical and electrochemical conditions. The versatility of the lithium-based corrosion protection extends to their application as corrosion inhibiting pigments in organic coatings or as a pre-treatment, directly forming conversion layers, thereby enhancing their practical implementation. However, previous chromate replacement reviews only introduced the promising outcomes provided by the lithium technology, omitting key details of its development and formation mechanism. This paper critically reviews and summarizes the studies conducted to date on lithium-based inhibitor technologies for the corrosion protection of aluminium alloys as well as topics to be investigated in the future.

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