New frontiers in marine corrosion research

Introduction

Corrosion in marine environments is particularly aggressive due to the combined influence of chemical, mechanical and biological factors – which together accelerate material degradation. It is a crucial concern for industries reliant on durable marine infrastructure, including offshore wind farms, pipelines, and maritime vessels. The topics addressed in this issue highlight the importance of material selection, surface treatments, and alloying elements in enhancing the longevity and performance of structures exposed to such conditions. The application of advanced techniques, such as sol-gel treatments, plasma ion nitriding, and additive manufacturing (AM), allows for the development of future corrosion-resistant materials.

Surface treatments and coatings

Several papers within this issue focus on novel coatings and surface treatments that improve the corrosion resistance of materials in marine environments. For instance, Linder et al.1 investigate the corrosion resistance of additively manufactured (AM) aluminium alloys, which exhibit significant potential for marine applications. Another study by Li et al.2 evaluates Cr/GLC coatings sealed with Al2O3, demonstrating their capacity to withstand high hydrostatic pressures. In addition, a mini-review on metallic coatings for offshore wind structures by Syrek-Gerstenkorn and Paul3 highlights the growing demand for durable coatings as renewable energy infrastructure expands offshore to meet net-zero targets. The repair of carbon steel oxide scales using Ce3+ and Ni2+-doped sol-gel coatings, as discussed in the article by Zeng et al.4, further exemplifies how integrating chemical and physical processes can significantly enhance surface protection against marine corrosion.

New alloys and corrosion mechanisms

A key theme throughout this special issue is the role of alloying in enhancing corrosion resistance. Research examining the corrosion behaviour of high-strength, anti-seismic rebar, influenced by Nb and V additions, offers critical insights for the construction of durable structures in earthquake-prone coastal areas5. Similarly, the study on Mg–9Gd–3Y–2Zn–0.5Zr alloy by Chen et al.6 under simulated coastal storage conditions provides crucial findings for the development of lightweight materials, potentially reducing the maintenance costs associated with maritime structures. The influence of alloying elements such as Mo, Sn, Al, and Mn is also thoroughly examined. For instance, the paper by Sun et al.7 assesses the combined effects of Mo and Sn on the corrosion behaviour of low-alloy steel in tropical marine atmospheres, while Tang et al.8 demonstrate how the incorporation of Al and Mn optimizes rust layer formation on lightweight weathering steel, resulting in better understanding of corrosion resistance. The influence of Cr(III) on the formation and transformation of corrosion products of steel in marine environments is covered in detail in the paper by Serjaouan et al.9. Nitrogen is known to play a key role in the corrosion resistance of austenitic stainless steel and was envisioned in the paper by Gao et al.10 as an alternative element to develop new alloys with low Ni contents. Their work showed that high-nitrogen austenitic stainless steels (HNSS) have larger proportion of stable oxides in the passive films that facilitates the passivation/re-passivation process and contributes to the high corrosion resistance.

A fundamental aspect of corrosion research is understanding the underlying mechanisms that drive material degradation. Several studies in this issue focus on the electrochemical behaviour of materials in marine environments, including kinetic model development for steel corrosion11. The effects of plasma ion nitriding and electropolishing on the electrochemical resistance of UNS N08367 alloy (6% molybdenum super-austenitic stainless steel) is explored by Hwang and Kim12, while Laleh et al.13 introduces an innovative electrode array probe capable of simultaneously monitoring multiple localised corrosion processes in marine structures.

Biocorrosion and biofouling

Additionally, research on microbiologically influenced corrosion (MIC) enhances our understanding of how microorganisms, such as Bacillus cereus, contribute to stress corrosion of Cu-bearing steel14. The study of Cu-bearing steel presents promising strategies to improve resistance to MIC, a growing concern in long-term maritime operations. Another consequence of the interactions between materials surfaces and the biologically active natural seawater is biofouling. Like corrosion, it can threaten the functioning and integrity of marine structures. To hinder biofilm formation, Wu et al.15 tested successfully the effect of a natural antibacterial peptide and investigated the mechanisms of its action using a combination of complementary techniques.

Materials processing

Welding and additive manufacturing (AM) are critical to the construction and maintenance of structures, and several articles in this issue address the specific corrosion challenges associated with these processes. The corrosion performance of wire arc additively manufactured nickel–aluminium bronzes (NAB) is examined by Shahriari et al.16, providing valuable data for industries utilising AM for production of NAB. The corrosion behaviour of austenitic stainless steel and nickel-based welded joints is also explored by Vaccari et al.17, where key factors for maintaining joint integrity over time of underwater wet welding is presented. Rapid solidification in welding and additive manufacturing (AM) often leads to metastable microstructures which could have different corrosion behaviour to the wrought alloy. Such differences in the corrosion behaviour could also be a source of galvanic corrosion which is highlighted in the paper by Wang et al.18.

Conclusions

The research presented in the collection not only advances the understanding of marine corrosion but also emphasises the importance of interdisciplinary approaches to addressing the complex challenges posed by marine environments. The integration of material science, electrochemistry, and marine engineering highlights the multifaceted nature of corrosion prevention and emphasises pathways for translating research into industrial applications. The application of mathematical tools such as statistical analysis could also provide powerful tools for data analysis and better understanding of corrosion processes19. As offshore energy production, global shipping, and coastal infrastructure continue to expand, the insights provided by these studies are invaluable for ensuring the sustainability and durability of marine structures. It is hoped that this collection of research will inspire further innovation and collaboration in the field, pushing the boundaries of corrosion science and technology.

Related Articles

Effects of electropolishing and plasma ion nitriding on UNS S31603 corrosion in ship scrubber water

Marine scrubbers use seawater as washing water and are damaged by sulfur oxides and chlorides during desulfurization. Therefore, surface treatments to enhance corrosion and pitting resistance of scrubber materials must be investigated. This investigation conducts cyclic potentiodynamic polarization experiments to analyze the effects of electropolishing and plasma ion nitiriding of UNS S31603 in washing water. The corrosion current density (0.186 μA cm2) of electropolishing is significantly lower than mechanical polishing (1.125 μA cm-2), but plasma ion nitriding is higher (18.995 μA cm2). Electropolishing forms a uniform and dense passivation film, increasing corrosion resistance, whereas plasma ion nitriding reduces corrosion resistance due to CrN formation. All specimens present local corrosion. Electropolishing reduces the maximum damage depth by 110.13 μm and increases pitting potential by 0.32 V compared to mechanical polishing. Plasma ion nitriding reduces maximum damage depth by 46.59 μm due to suppression of local acidification during hydrolysis.

Numerical simulation of spatial wind fields in Xumishan Grottoes over complex terrain

Windy weather frequently occurs in Northwest China, and wind erosion is a typical issue for stone carvings in the caves. In the present study, computational fluid dynamics (CFD) simulations relying on steady 3D Reynolds-averaged Navier-Stokes (RANS) equations were used to simulate the spatial wind field over complex terrain with field measurement validation. This study has the following two aims: (1) to evaluate the accuracy of wind fields simulations with the Interpolated Multiscale Profile (IMP) method over complex terrain; and (2) to provide spatial wind field data of Xumishan Grotto Zone under neutrally stratified atmospheric boundary layer (ABL) over complex terrain. Unmanned aerial vehicle (UAV) oblique photogrammetry and multirotor UAV technology provide application scenarios for the establishment of a high-precision digital model and the determination of accurate inlet boundary conditions. By compiling user-defined functions (UDF) and using the block interpolation method, this method addresses the overestimation of the inlet wind velocity caused by the large elevation difference of the inlet over complex terrain. The results show that the 3D steady RANS simulation based on the IMP method can reasonably and accurately simulate spatial wind fields over complex terrain. This study also provides spatial wind fields data for addressing stone carving erosion caused by strong winds in semi-open Grottoes.

Corrosion processes affecting copper-coated used fuel containers for the disposal of spent nuclear fuel: critical review of the state-of-knowledge

The uniqueness of the Canadian spent nuclear fuel disposal container design requires a detailed understanding of the copper corrosion processes that could occur in deep geological repositories. This review aimed to identify knowledge gaps surrounding impacts of changing conditions and the evolution of corrosion processes as conditions change from moist/cool, through warm/dry, to cool/fully saturated. This review indicates that early, unsaturated corrosion, and compounding influences of previous corrosion are understudied.

Probabilistic machine learning for battery health diagnostics and prognostics—review and perspectives

Diagnosing lithium-ion battery health and predicting future degradation is essential for driving design improvements in the laboratory and ensuring safe and reliable operation over a product’s expected lifetime. However, accurate battery health diagnostics and prognostics is challenging due to the unavoidable influence of cell-to-cell manufacturing variability and time-varying operating circumstances experienced in the field. Machine learning approaches informed by simulation, experiment, and field data show enormous promise to predict the evolution of battery health with use; however, until recently, the research community has focused on deterministic modeling methods, largely ignoring the cell-to-cell performance and aging variability inherent to all batteries. To truly make informed decisions regarding battery design in the lab or control strategies for the field, it is critical to characterize the uncertainty in a model’s predictions. After providing an overview of lithium-ion battery degradation, this paper reviews the current state-of-the-art probabilistic machine learning models for health diagnostics and prognostics. Details of the various methods, their advantages, and limitations are discussed in detail with a primary focus on probabilistic machine learning and uncertainty quantification. Last, future trends and opportunities for research and development are discussed.

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