This paper provides a review of models commonly used over the years in the study of microscopic models of material corrosion mechanisms, data mining methods and the corrosion-resistant performance control of structural steels. The virtual process of material corrosion is combined with experimental data to reflect the microscopic mechanism of material corrosion from a nano-scale to macro-scale, respectively. Data mining methods focus on predicting and modeling the corrosion rate and corrosion life of materials. Data-driven control of the corrosion resistance of structural steels is achieved through micro-alloying and organization structure control technology. Corrosion modeling has been used to assess the effects of alloying elements, grain size and organization purity on corrosion resistance, and to determine the contents of alloying elements.

In this study, a superhydrophobic coating with excellent mechanical durability, chemical stability, anti-icing property and self-cleaning property was developed based on epoxy resin integrated with modified SiO₂ nanoparticles (m-SiO₂ NPs). The surface morphology and roughness of the coating were finely controlled by changing the content of m-SiO₂ NPs, with optimal hydrophobicity and self-cleaning efficiency observed at the m-SiO₂ NPs incorporation of 30 wt%. Benefitting from the three-dimensional stable micro-nano structure on the coating surface, the coating exhibited durable hydrophobicity upon multiple tape-peeling damages and good resistance to both acidic and alkaline corrosive environments. Furthermore, the SiO₂-EP coating showed a prominent anti-icing property which could delay the water freezing time from 96 s to 650 s. This coating underscored its potential for applications in environments prone to ice formation.

This study systematically compared the corrosion resistance and mechanisms of U71Mn and U75V rail steels in simulated solutions (3.5 wt.% NaCl, 0.01 M NaHSO3). The influence of vanadium (V) addition was investigated using microstructural characterization, electrochemical techniques (OCP, PDP, EIS), dry/wet cyclic corrosion tests, and rust layer analysis (SEM/EDS/XRD/CLSM). Results show: 1) U75V exhibits superior corrosion resistance in NaCl solution, evidenced by a significantly higher charge transfer resistance (2819 Ω·cm2) and lower corrosion current density (4.769 μA/cm2) versus U71Mn (1140 Ω·cm2, 5.357 μA/cm2). 2) U75V demonstrated lower weight loss and corrosion rate after NaHSO3 dry/wet cycling. 3) V in U75V refines grains and increases grain boundary density, hindering corrosive media diffusion. V also promotes a denser rust layer enriched with stable α-FeOOH (higher α/γ* ratio, γ* = Fe2O3 + Fe3O4 + γ-FeOOH), significantly reducing rust layer S content (4.54 wt.% vs. 7.80 wt.% in U71Mn) and impeding corrosive ion (e.g., SO42⁻) penetration. 4) U71Mn suffered severe localized corrosion with deep pits, linked to its coarse pearlite and porous rust layer. Conversely, U75V exhibited uniform corrosion with shallower pits, attributed to its refined microstructure and dense rust layer. The addition of V significantly enhances U75V corrosion resistance by synergistically optimizing the matrix microstructure and rust layer protectiveness.

In this paper, the corrosion failure mechanism of bearing outer rings for railway freight car wheelset and the wear performance of coatings were systematically analyzed and tested. The results show that the microcells formed by martensite and Fe 3 C in the matrix structure accelerate electrochemical corrosion, which is mainly dominated by Cl -induced localized corrosion. The main components in the rust layer, γ-FeOOH/γ-Fe 2 O 3 , have a loose and porous structure, making it difficult to effectively block the penetration of corrosive media and forming a cycle of "corrosion-infiltrationrecorrosion". In the wear performance tests of different coatings, the weight loss rate of the epoxy coating after friction reaches 0.0616%, that of the phosphating film is less than 0.0019%, and although the thermal spray coating has a higher friction coefficient, its weight loss rate is close to zero, making it suitable for high-load and severe-wear scenarios.

This study proposes a large language model, Corr-Lora-RAG, designed to address the complexity and uncertainty inherent in corrosion data. A dedicated corrosion knowledge database (CKD) was constructed, and dataset generation code was provided to enhance the model’s reproducibility and adaptability. Based on the Qwen2.5-7B model, the Corr-Lora model was developed by integrating prompt engineering and low-rank adaptation (LoRA) supervised fine-tuning (SFT) techniques, thereby improving the understanding and expression of domain-specific knowledge in the field of corrosion. Furthermore, the Corr-Lora-RAG model was built using retrieval-augmented generation (RAG) technology, enabling dynamic access to external knowledge. Experimental results demonstrate that the proposed model outperforms baseline models in terms of accuracy, completeness, and domain relevance, and exhibits knowledge generation capabilities comparable to those of large-scale language models under limited computational resources. This approach provides an intelligent solution for corrosion risk assessment, standards compliance analysis, and protective strategy formulation, and offers a valuable reference for the development of specialized language models in other engineering fields.

The corrosion failure of U75V heavy-haul railway rail steel in coal corrosive environments is fundamentally associated with the dynamic evolution of surface/interfacial topography of the steel substrate and protective coatings. This study systematically investigates the surface and interfacial topography evolution of bare U75V steel, waterborne epoxy zinc-rich primer (WEZRP)-coated steel, and waterborne epoxy zinc–aluminum primer (WEZAP)-coated steel as the central theme. Simulated coal corrosive solution was prepared, and immersion tests, electrochemical impedance spectroscopy, SEM-EDS and XRD were used to systematically characterize the dynamic evolution of surface/interface topography, phase composition and electrochemical corrosion behavior of the three systems during immersion. The results show that the corrosion behavior of U75V steel is closely related to surface topography evolution: pitting initiates in the early immersion stage, and transforms into uniform corrosion in the later stage, with internal cracks and delamination in the rust layer acting as rapid transport channels for corrosive media. WEZAP exhibits significantly superior corrosion resistance to WEZRP, with no red rust after 21 d of immersion, and its low-frequency impedance modulus (| Z | _0.01 Hz), coating pore resistance ( R _f ) and charge transfer resistance ( R _ct ) remain at significantly higher levels. Aluminum introduction regulates coating topography evolution, forming a dense zinc–aluminum composite corrosion product layer, reducing coating porosity, maintaining coating-substrate interface integrity, and improving chloride erosion resistance. Unlike existing Zn-Al coating studies focusing on conventional environments and separate morphology–electrochemistry analysis, this work first targets the heavy-haul railway coal corrosive environment of heavy-haul railways. It establishes an strong correlation between surface and interfacial topography evolution and corrosion electrochemical behavior, and verifies the feasibility of achieving high-performance corrosion protection with low pigment content, thereby providing a scientific basis for optimizing anti-corrosion coatings for heavy-haul rails.