Journal of Thermal Spray Technology最新文献

Based on machine learning algorithms, a method is proposed for quality diagnosis of atmospheric plasma spraying (APS) processes used in thermal barrier coatings with determined coating materials and processes, aiming to swiftly evaluate the quality of APS coatings. First, the three-dimensional morphology of the coating is reconstructed through surface interpolation fitting, employing one-dimensional morphology standards and abnormal training set samples of the plasma-sprayed thermal barrier coating. This algorithm enables the extraction of cross section data of the coating at any angle. The mapping relationship between the characteristic parameters of the Gaussian peak and the process and coating characteristics is thoroughly analyzed, and the 12-dimensional characteristic parameters are utilized to effectively represent the one-dimensional morphology samples. Subsequently, principal component analysis (PCA) and K-nearest neighbor (KNN) algorithms are employed for accurate prediction and classification of the process quality of coating samples. Additionally, an exploratory factor analysis (EFA) model is established to comprehensively depict the relationship between plasma spraying process parameters, the process, and the three-dimensional morphology of the coating. The experimental results show that the machine learning algorithm has high accuracy in quality diagnosis, and its robustness is further verified by K-fold cross-validation. When combined with the EFA model, the proposed method facilitates rapid feedback on process quality, enabling real-time evaluation. Overall, this innovative approach presents a novel solution for the quality diagnosis of atmospheric plasma spraying processes. The incorporation of machine learning techniques and the establishment of the EFA model contribute to enhanced efficiency and accuracy in the evaluation process, paving the way for advancements in thermal barrier coating applications.

This study establishes a machine learning (ML) model utilizing the expectation-maximization approach to predict maximum residual stresses, encompassing both tensile and compressive states, in the cold spraying process across various substrates. The main feature of the ML algorithm lies in its two-step iterative process, where the Expectation (E step) refines latent variable estimates, and the Maximization (M step) optimizes the model’s parameters, aligning them with the data. Based on the results, regression analysis highlighted the predictive capabilities of the proposed model for tensile and compressive residual stresses, exhibiting root mean square error values of 8.8 and 3.5%, along with determination coefficient values of 0.915 and 0.968, respectively, indicating higher prediction performance in the compression mode. This suggests higher predictability for residual stress within the depth of material’s body. Moreover, analyzing low residual stress levels underscored the significant impact of substrate and particle mechanical strength on prediction performance, whereas higher residual stress levels highlighted the strong influence of thermal conductivity. This correlation suggests that high stresses during the cold spray process generate more heat, thereby emphasizing the crucial role of thermal conductivity in predicting resultant residual stresses. Furthermore, a notable trend emerges as tensile stress increases, spotlighting the augmented influence of processing parameters in the prediction process. Conversely, at elevated compressive stresses, material properties’ weight factors assume a vital role in predictions. These findings offer insights into the intricate interplay between processing parameters and materials properties in determining resultant residual stresses during cold spraying.

Normally, aluminum-based (Al-based) anti-corrosion coatings are prepared by flame spraying and other coating technologies to improve the corrosion resistance of metal materials in the marine environment. However, the prepared coatings are usually found to be poor in quality owing to the shortcomings of traditional thermal spraying technologies, such as flame spraying, including the low jet temperature and low particle in-flight velocity. In this paper, pure Al coatings and Al/SiC composite coatings were prepared on the surface of low-carbon steel by innovatively adopting plasma transferred wire spraying technology and making full use of the technological advantages of plasma spraying. In addition, the experiments have shown that larger SiC particles play a role in shot peening during the spraying process, allowing Al droplets to spread and overlap more fully, effectively improving the density of the coating and reducing defects such as pores and cracks in the coating. However, there is no significant effect on improving the bonding strength of the coating. Therefore, the porosity of pure Al coating and Al/SiC composite coating is 3.9% and 2.5%, respectively; the microhardness is 36 HV_0.1 and 102 HV_0.1, respectively, increasing by about three times; the bonding strength with the matrix is 39.0 and 36.5 MPa, respectively; the corrosion resistance of Al/SiC composite coating is significantly better than that of pure Al coating, and the wear rate is reduced by 7 times compared to pure Al coating.

304 stainless steel (304SS) powder and novel Mo-cladded 304SS (304SS-Mo) powder were used as feedstocks to prepare metallic coatings with different inter-splat bonding qualities. Wear test was conducted to examine the dependence of wear behavior on the inter-splat bonding quality. The results showed that poor inter-splat bonding leads to much lower wear resistance in conventional 304SS coating relative to that of 304SS bulk, especially at high loading conditions (>75 N), where the wear rate increased to 5.53 × 10⁻³ mm³/(m⋅N) by 3.5 times higher than that at low-load range. However, the novel 304SS-Mo coating with metallurgical inter-splat bonding and minimized oxide inclusions exhibited a low wear rate comparable to that of 304SS bulk. Failure analysis of worn samples suggests that splat delamination contributes to low wear resistance of the 304SS coating; conversely, the absence of splat delamination results in higher wear resistance of the 304SS-Mo coating. Using Mo-cladded powders, significantly enhanced inter-splat bonding enables the use of plasma-sprayed metallic coating under high-load wear conditions. The strong dependence of wear resistance on the load in conventional coating implies that evaluation of wear performance of thermally sprayed metallic coating should consider both the wear rate and critical load.

In order to enhance the hardness and wear resistance of Cr12MoV, Al₂CrFeNiMo was designed and successfully prepared by laser cladding. Phase, microstructure, hardness and wear characteristics of the coating were analyzed by x-ray diffractometer, scanning electron microscope, Vickers hardness tester and reciprocating wear tester. The results indicated that the coating was composed of BCC and FCC phases having high lattice distortion and dislocation density. Microstructure of the coating presented the equiaxed grain which was rich in Fe, Cr and existed the segregation of Mo, Al, Ni. The coating demonstrated high hardness, with the values of 600 HV_0.2, which was increased by 150% than that of the substrate. Compared with the substrate, the friction coefficient and wear volume of the coating were reduced by 48.9 and 91.32%, respectively. The wear mechanism of the coating was the abrasive wear. However, the substrate exhibited the serious adhesive wear besides the abrasive wear.

Thermal spraying has become an industrial standard in the production of wear-resistant WC-Co and Cr₃C₂-NiCr composite coatings. However, generating optimum wear-resistant nano-reinforced carbide microstructures within the coatings remains challenging. The alternative two-step approach in this work involves coating formation under high energy conditions to generate maximum carbide dissolution, followed by heat treatment to precipitate nanocarbides. Microwave heating of particulate materials has been reported to offer several benefits over conventional furnace heating, including faster heating rates, internal rather than external heating, and acceleration of reactions/phase transformations at lower temperatures. This novel work explored the use of microwaves for heat treatment (as distinct from melting) of WC-Co and Cr₃C₂-NiCr thermal spray coatings and contrasted the rate of phase development with that from conventional furnace treatment. Coatings were successfully microwave heat-treated to generate the same phase composition as furnace treatment. Both treatments generated comparable results in the Cr₃C₂-NiCr system. The WC-Co system achieved a much more crystalline structure in a dramatically shorter time relative to the conventional furnace-treated sample. The results are contrasted as a function of material and microstructure interaction with microwaves and the critical phase transition temperatures to account for the observed responses.

Temperature sensors are critical components in many industrial and research applications, particularly in harsh environments where high temperatures, corrosion and mechanical stress are prevalent. In this paper, we investigate the use of plasma spray technique as a versatile and simple method to print multipoint thermocouples and resistance temperature detectors (RTDs) based on NiCr-NiAl coatings on steel and ceramic substrates using stencil masking and laser scribing. The thickness of alumina the dielectric layer was optimized using metal-insulator-metal test. The thermoelectric properties of the printed thermocouples were investigated up to 1000 °C. The thermal independency of printed thermocouples and the capability of multilocation measurement at the surface on the same substrate was demonstrated. The thermoelectric properties of the printed RTD were investigated up to 850 °C. The electrical resistance of the RTD sensor is linear with the temperature variation from room temperature to 500 °C. The oxidation effect of the printed sensor metallic layers at high temperature was investigated and discussed.

Present investigation attempted to explore the tribological properties of atmospheric plasma sprayed coatings. In order to assess the role of solid lubricants, different weight percentages (5, 10, and 15 wt.%) of silver (Ag) were taken, whilst MoS₂ concentration remained fixed. Dry sliding wear tests were conducted for different specimens namely, Ni-Al-MoS₂-5 wt.% Ag (NA5), Ni-Al-MoS₂-10 wt.% Ag (NA10) and Ni-Al-MoS₂-15 wt.% Ag (NA15) at different loads of 4, 9, 14 & 19 N, and slid speed of 0.3 m/s under room temperature (RT) conditions. It was observed that coefficient of friction (COF) and wear rate of specimens decreased as the load increased till 14 N, and beyond that increasing trend was noticed. However, the NA10 specimen has revealed the best tribological properties in terms of minimum COF (0.48) and wear rate (4.7 × 10⁻⁵ mm³/Nm) at 14 N and 0.3 m/s. The synergy of Ag and MoS₂ on the frictional properties of specimens have been well explained with the help of worn surface morphologies and some useful conclusions were made.

This current work evaluates the efficacy of a co-flow nozzle for cold spray applications with the aim of mitigating nozzle clogging issues, which can occur during long-duration operations, by replacing the solid wall of a divergent nozzle section with an annular co-flow fluid boundary. Simulations were conducted on high-pressure nitrogen flowing through convergent–divergent (C–D) axisymmetric nozzles, with a stagnation pressure of 6 MPa and a stagnation temperature of 1273 K. In these simulations, Inconel 718 particles of varying sizes (15 µm to 35 µm) were modeled using a 2-way Lagrangian technique, and the model’s accuracy was confirmed through validation against experimental results. An annular co-flow nozzle with a circular cross section and straight passage covering the primary C–D nozzle has been designed and modeled for cold spray application. Co-flow was introduced to the reduced nozzle length to compensate for particle velocity loss at higher operating conditions. It was found that co-flow facilitates momentum preservation for primary flow by providing an annular gas boundary, resulting in increased particle speed for a longer axial distance beyond the nozzle exit of the reduced divergent length nozzle. The particle acceleration performance of the reduced divergent section nozzle, when combined with co-flow, is comparable to the original length nozzle.

In this paper, as-received Zn powder and as-prepared Zn@(ZnWO₄/ZnO) core–shell powder were used as feedstocks for plasma spraying to prepare Zn-based composite coatings and nano-ZnO was co-deposited by chemical vapor deposition induced by plasma spraying. The composition and morphology were controllable within certain range by plasma spraying power. The photocatalytic activities of the coatings were analyzed by the degradation efficiency of methyl orange (MO) solution. It was found the photocatalytic activity can be improved with ZnWO₄ decoration. The Zn/ZnO/ZnWO₄ coating which presented tremella-like surface morphology was testified to have the best photocatalytic activity under UV light irradiation among all coatings. On the other hand, the chemical surface modification with 1H,1H,1H,2H-perfluorodecyltriethoxysilane (FAS-17) was implemented to produce superhydrophobic coatings. Among all modified coatings, the ZnWO₄-containing coating with tremella-like surface structure presented the best superhydrophobicity. By the cyclic wetting and tape adhesion experiments, the tremella-like structure was proved to make a great improvement on the robustness of the Zn-based superhydrophobic coatings. The superhydrophobic and photocatalytic properties provide the possibility for the application of the coating in the fields of antifouling, antibacterial, and photocatalytic degradation of organics.

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