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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A 2D finite element model is developed to simulate the protection of active protective coatings in a defect. The leaching kinetics, inhibitor-electrolyte reactions and electrochemical surface reactions on homogenized AA2024-T3, are considered. Changes in local oxygen distribution, pH, and current density over time are validated using surface scanning micro-probe techniques. The limitations posed by the prediction of surface current density at the metal interface using a FEM model with a homogenized microstructure are identified and addressed. The validated FEM is then used to predict inhibitor concentration and pH dependent on the initial inhibitor pigment concentration in an organic coating.

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Chromium coatings, famed for their superior wear and corrosion resistance, are a critical component in countless industrial processes. However, the longevity of these coatings in aggressive corrosive environments continues to be a significant hurdle, even with recent advances in deposition technology and microstructural improvements. An advanced thin dense chromium (TDC) coating, with a near-nanocrystalline structure and unique morphology, naturally forms a non-conductive nano-bilayer oxide. This passive and protective layer effectively moderates electrical charge transfer, offering superior corrosion resistance. X-ray photoelectron spectroscopy (XPS) shows significant Cr³⁺ oxide layer formation, distinguished by multiplet splitting, after 7 days in a 0.6 M NaCl solution. The unique characteristics of this non-conductive bilayer oxide structure promote its growth and densification, leading to vertical differential charging in the O1s electron energy region. This effect arises from the enhanced resistivity of the oxide layer. Electrochemical impedance spectroscopy (EIS) confirmed these findings, showing a substantial increase in charge transfer resistance at the chromium metal/bilayer oxide interface, reaching 1.01 MΩ. Scanning Kelvin probe force microscopy (SKPFM) analysis shows that both TDC nodules and their boundaries exhibit high surface potential and work function. However, after exposure to NaCl media, these values are moderately reduced, likely due to diminished electrical surface charge distribution.

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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.

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The discovery of synergistic strategies effectively improves the corrosion inhibition capability of amino acids. However, the wide variety of amino acid formulations and the time-consuming nature of corrosion tests make combinatorial discovery challenging to achieve. Herein, a library of 70 amino acids was created and tested in a high-throughput manner. Benefiting from a vast amount of labeled data of amino acid formulations, an interpretable machine learning approach was used to reveal the contribution of molecular features to inhibition performance of amino acids and the synergisms in the optimal formulation. The synergism was verified by electrochemical tests and quantum chemical calculations.

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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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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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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

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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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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This paper presents a novel approach to investigate atmospheric corrosion kinetics of carbon steel under multi-droplet conditions. A homemade climate chamber has been developed to accurately control and monitor environmental conditions, including temperature (T) and relative humidity (RH), during exposure. Carbon steel corrosion kinetics are monitored with a custom-designed Electrical Resistance (ER) sensor pair. Savitzky-Golay (S-G) based filtering technique has been used for the corrosion signal processing. In parallel, top-view droplet temporal evolution has been recorded by microscopic imaging and analyzed for both droplet size distribution and the solid-liquid contact angle. The droplet size distribution can typically be described with a power-law form curve. The curve shows a decrease in height and a concurrent expansion in width with progressive drying. The introduction of NaCl into the electrolyte and surface roughness variations have also been identified to substantially influence the carbon steel corrosion rate. A strong correlation between the corrosion rate derived from the ER monitoring method and the RH can be observed. This correlation is further analyzed to incorporate the impact of droplet-based electrolyte conditions. This study offers valuable insights into the development of mechanistic and kinetic prediction models for atmospheric corrosion.

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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

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

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

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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Nowadays, Thin Dense Chromium (TDC) coatings are being industrially used in rolling bearings applications due to their claimed advantages such as high hardness, low wear, and good corrosion resistance. However, despite their broad commercial use, very little has been published in the open scientific literature regarding their microstructure, nanomechanical, and tribological properties. In this paper, TDC coatings with a thickness of about 5 µm were deposited by a customized electrochemical process on ASTM 52100 bearing steel substrates. Surface microstructure and chemical composition analysis of the TDC coatings was carried out by scanning electron microscopy and atomic force microscopy. The results revealed a coating with a dense, nodular, and polycrystalline microstructure. Unlike standard electrodeposited “Hard Chromium” coatings, TDC coatings show no presence of micro/nano-cracks, likely contributing to their superior corrosion resistance. The nanomechanical behavior, studied by nanoindentation as a function of penetration depths, exhibits a pronounced size effect near the coating surface that can be linked to the nodular microstructure. A hard surface with hardness HIT 14.9 ± 0.5 GPa and reduced elastic modulus Er = 216.8 ± 3.9 GPa was observed. Tribological characterization under the presence of lubricants was performed by two single-contact tribometers using coated and uncoated steel balls against flat steel substrates. An in-house fretting wear rig was used to measure the lubricated friction coefficient in pure sliding conditions, whilst the friction performance in rolling/sliding lubricated conditions was evaluated using a WAM test rig. In pure sliding, TDC/TDC contacts show ~13% lower friction than for steel. Under rolling/sliding conditions with 5% sliding, the traction coefficient of TDC/TDC coating contact was at least 20% lower than that for steel/steel contact. The tribological results obtained in various contact conditions demonstrate the benefits of applying TDC coatings to reduce bearing friction.@en

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

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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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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