Coatings

26 pages, 15251 KB

Open AccessArticle

Study on Wear Resistance and Multi-Factor Coupled Hot Corrosion Resistance of Ti-Al-Si Composite Coatings

by Xiaoyuan Hu, Xuejing Yao, Pingping Zhao, Yan Liu and Faguo Li

Coatings 2026, 16(6), 632; https://doi.org/10.3390/coatings16060632 (registering DOI) - 22 May 2026

A Ti-Al-Si composite coating was prepared on Ti65 titanium alloy using a two-step hot-dipping + pre-oxidation method to improve its tribological performance and high-temperature oxidation resistance. The second-step dipping time strongly affected the coating microstructure and wear behavior. The optimal coating, prepared with a dipping time of 5 min in each step, exhibited negligible wear after oxidation at 800 °C for 1000 h and 2500 h, with slight adhesive wear and oxidative wear as the dominant mechanisms. Longer dipping times led to mixed wear modes and reduced wear resistance. Under high-temperature corrosion conditions, the coating showed good long-term stability in water vapor, with its mass gain following a sub-parabolic law, Δm = 0.39·t^0.47, because the internal multilayered structure effectively blocked inward oxygen diffusion. However, in environments containing NaCl or 75 wt.% Na₂SO₄ + 25 wt.% NaCl, catastrophic hot corrosion occurred, regardless of the presence of water vapor, through a chlorine-driven oxidation–chlorination–reoxidation autocatalytic cycle. In the mixed salt environment, Na₂SO₄ decomposition supplied additional oxygen and alkaline species, accelerating the degradation and spallation of the Al₂O₃ and TiO₂ scales. Water vapor further intensified this cycle by generating HCl, which promoted rapid consumption of Al and Ti in the coating. This study reveals the wear behavior and hot corrosion failure mechanisms of Ti-Al-Si coatings under complex conditions, providing guidance for process optimization and applications in marine atmospheres. Full article

(This article belongs to the Section Corrosion, Wear and Erosion)

21 pages, 7101 KB

Open AccessArticle

Time-Dependent Corrosion Behaviors of Al-Si Coated Steel Sheet Under a Chlorine-Containing Wet–Dry Cycling Environment

by Chunlin Lu, Weiming Liu, Hailian Wei, Hairong Gu, Yun Zhang, Lei Cui, Hongbo Pan, Huiting Wang, Xiaohui Shen, Yonggang Liu and Yangyang Xiao

Coatings 2026, 16(6), 631; https://doi.org/10.3390/coatings16060631 - 22 May 2026

Abstract

The corrosion behavior and time-dependent mechanism of 22MnB5 steel featuring a thinned Al-Si coating (60 g/m²) were systematically investigated in a chloride ion wet–dry cyclic environment, motivated by the demand for thinning and toughening development of aluminum-silicon coatings. A periodic immersion accelerated corrosion test using 3.5% NaCl solution was conducted, together with macro/microscopic morphology observation (SEM/EDS), phase analysis (XRD, FTIR), and electrochemical measurements (polarization curves, EIS). The Al-Si coated steel was studied over corrosion periods of 1, 8, 10, and 20 days to elucidate its corrosion behavior, interfacial evolution, and failure mechanism. The results indicated that the corrosion process exhibited a three-stage evolution: stable protection, rapid failure, and dynamic equilibrium. At the initial stage (1 day), a dense Al₂O₃ passive film formed on the coating surface, providing excellent substrate protection, with a corrosion current density of only 1.77 µA/cm² and a maximum charge-transfer resistance (R₂) of 652 Ω·cm². In the middle stage (8 days), Cl⁻ permeated through the cracked film, triggering selective dissolution of Al, while Si was enriched in situ to form a porous residual layer; the corrosion current density (I_corr) sharply increased to 13.25 µA/cm², and R₂ dropped to its minimum of 156.6 Ω·cm². Corrosion products at this stage were mainly Al₂O₃ and SiO₂, accompanied by small amounts of iron oxyhydroxides and hydroxides, and local coating failure began to appear. During the later stage (10–20 days), the corrosion products evolved into γ-FeOOH, α-FeOOH, and Fe₂O₃, which, together with an amorphous SiO₂ gel network enriched at the interface, formed a dual-layer composite rust layer. R2 consequently recovered from 156.6 Ω·cm² at 8 days to 424 Ω·cm² at 20 days, indicating a reduced corrosion rate and entry into a stable inhibition stage. The critical failure mechanism is that Cl⁻ preferentially penetrates the surface of the Al₂O₃ passive film, disrupting the metastable state of the coating and thereby creating pathways for corrosive media intrusion. The findings of this study can provide technical support for the safe application of such as-received coatings in non-load-bearing components with heat and corrosion resistance requirements. Full article

(This article belongs to the Special Issue Advances in Protective Coatings for Metallic Surfaces)

► Show Figures

Figure 1

14 pages, 6039 KB

Open AccessArticle

Tribological and Wear Properties of DLC Composite Coatings with Different Ratios of CrN/Cr₂N

by Shuling Zhang, Xiangdong Yang, Guangjun Liu, Lingxin Bu, Shuaichao Fan and Xinghua Ma

Coatings 2026, 16(6), 630; https://doi.org/10.3390/coatings16060630 - 22 May 2026

Abstract

CrN/DLC composited coatings were deposited on 431 stainless steel, and their structure was analyzed, with particular emphasis on the influence of CrN content on the coating properties. X-ray photoelectron spectroscopy (XPS), nanoindentation testing, scratch testing, and reciprocating tribometry were employed to characterize the chemical composition, mechanical properties, adhesion strength, and tribological performance of the coatings, respectively. Structural analysis indicates that when the ratio of CrN/Cr₂N is relatively low (<1), a high content of chromium dinitride (Cr₂N) is formed in the interlayers, resulting in a porous and loose coating structure. When the ratio achieves 1:1, an optimal balance, with the CrN content reaching a maximum of 21.04% and the Cr₂N content decreasing to a minimum of 20.68%, the densification degree of the coatings is increased, the coating adhesion strength is improved to 11.87 N. Meanwhile, the enhanced formation of the CrN phase improves the hardness to 12.27 GPa. Tribological test results demonstrate that when the ratio is approximately 1:1, the coating exhibits the lowest friction coefficients under dry sliding, deionized water, and artificial seawater conditions (0.0932, 0.1409, and 0.1021, respectively), as well as the minimum wear rates. With the decrease in CrN content of the coatings, the interfacial mismatch degree of the coatings is aggravated, which leads to not only more interfacial defects but also a relatively loose structure, as well as a decrease in the bonding strength (6.81 N), hardness (5.22 GPa), and deformation resistance. Therefore, an excessive Cr₂N phase may degrade the hardness-to-elastic modulus ratio (H/E) of the coatings by increasing interfacial mismatch and reducing structural compactness. Full article

(This article belongs to the Special Issue Advances in Alloy Coatings: Tailored Performance for Modern Applications)

► Show Figures

Figure 1

22 pages, 5019 KB

Open AccessArticle

Hyperspectral Detection and Classification of Stain-Contaminated Waste Textiles

by Jiacheng Zou, Haonan He, Wei Tian, Chengyan Zhu, Fei Ye and Xiaoke Jin

Coatings 2026, 16(6), 629; https://doi.org/10.3390/coatings16060629 - 22 May 2026

Abstract

Surface stain contamination poses a critical barrier to the automated, high-precision fiber identification required for industrial-scale waste textile recycling. In this study, a dataset comprising 120 physical specimens (yielding 1200 regions of interest, ROIs) across 12 contamination categories was constructed by contaminating cotton, polyester, and poly-cotton blend textiles with carbon black, protein, and oil stains. The spectral interference effects of stains—including baseline drift and spectral overlapping induced by physical shielding and chemical absorption—were systematically analyzed. To identify the optimal classification pipeline, three mathematical preprocessing methods (First Derivative, FD; Standard Normal Variate, SNV; and Multiplicative Scatter Correction, MSC) were evaluated alongside Support Vector Machine (SVM) and One-Dimensional Convolutional Neural Network (1D-CNN) models. Results show that among the SVM-based pipelines, the FD-SVM model effectively resolves overlapping absorption peaks, achieved an average accuracy of 98.17% ± 1.33%, but remains highly dependent on mathematical preprocessing. In contrast, the 1D-CNN model employing a progressive stacking architecture of multi-scale convolutional kernels attains a highly robust mean accuracy of 99.58% ± 0.56% under a strict specimen-level 10-fold cross-validation. It achieves this by directly utilizing radiometrically calibrated raw spectra, thereby effectively bypassing manual spectral feature engineering. These findings demonstrate that Hyperspectral Imaging coupled with end-to-end deep learning provides a feasible and industrially deployable solution for simultaneous stain detection and fiber identification in waste textile sorting. Full article

(This article belongs to the Special Issue Smart Materials and Textiles Coatings: Preparation, Properties and Applications)

► Show Figures

Graphical abstract

Journal Menu

Journal Browser

Coatings, Volume 16, Issue 6 (June 2026) – 4 articles

Further Information

Guidelines

MDPI Initiatives

Follow MDPI