Journal of Thermal Spray Technology最新文献

AlCoCrFeNi_2.1 eutectic high-entropy alloys (HEAs) are a new kind of alloy with high entropy and eutectic properties. Their advantages in terms of strength and shape matching can be fully exploited using extreme high-speed laser cladding (EHLA). In this paper, AlCoCrFeNi_2.1 eutectic HEA coatings were prepared by conventional laser cladding (CLA) and EHLA. The microstructures and phase compositions of the two coatings were analyzed by scanning electron microscopy, x-ray diffraction, and electron backscatter diffraction. The microhardness and wear resistance values of the coatings were tested using a microhardness tester and a friction and wear tester, respectively. The results showed that the surface qualities of both the CLA and EHLA coatings were good and had no cracks or defects. Compared with those of the CLA coating, the EHLA coating had finer grains and a more uniform distribution. Both coatings contained face-centered cubic (FCC) and body-centered cubic (BCC) phases, but the BCC phase of the EHLA coating was less precipitated than the CLA coating. The higher microhardness and better wear resistance of the EHLA coatings occurred in the presence of Hall–Petch strengthening.

Graphical Abstract

Lutetium monosilicate (Lu₂SiO₅) has been considered as environmental barrier coatings (EBCs) materials for SiC_f/SiC. Microstructural evolution and thermal properties changes of the Lu₂SiO₅ coating would occur in high temperature environment. In this study, Lu₂SiO₅ coating was fabricated by vacuum plasma spray technique. The microstructure, thermal stability, thermal conductivity, as well as thermal expansion behavior of the coating before and after thermal aging at 1350 °C were investigated. The tri-layer EBCs of Lu₂SiO₅/Yb₂Si₂O₇/Si were designed and prepared onto SiC_f/SiC substrates, and its thermal shocking behaviors were also explored. Results showed that the as-sprayed coating was mainly composed of Lu₂SiO₅, Lu₂O₃ and amorphous phases, and significant microstructural evolution, such as grain growth and defects reduction, was observed after thermal aging. The coating exhibited linear expansion, and the CTE of the coating before and after heat treatment were similar, while the thermal conductivity increased after thermal aging. Thermal shock results showed that the coating remained intact after 100 cycles, and penetrating microcracks in the Lu₂SiO₅ top layer were mostly stopped at the Lu₂SiO₅-Yb₂Si₂O₇ interface, indicating that the tri-layer EBCs on the SiC_f/SiC substrate had good thermal shock resistance. The thermal shock behaviors were explained based on microstructure combined with thermal stresses analysis.

The use of process–microstructure–property relationships for cold spray can significantly reduce application development cost and time compared to legacy trial and error strategies. However, due to the heterogeneous microstructure of a cold spray deposit, with (prior) particle boundaries outlining consolidated splats (deformed particles) in the as-spray condition, the use of automated analysis methods is challenging. In this work, we demonstrate the utility of quantitative data developed from a convolutional neural network (CNN) for feature extraction of cold spray microstructures. Specifically, the power of CNN is harnessed to automatically segment the deformed particles, which is hardly accessible at scale with traditional image processing techniques. Deposits produced with various processing conditions are evaluated with metallography. Parameters related to particle morphology such as flattening ratio are also quantified and correlated to strength.

The development of one-step deposition technology for metal oxide-based coatings is significant for the rapid fabrication of gas sensors. Gas sensors based on LaFeO₃ were fabricated by solution precursor plasma spraying (SPPS) strategy. Through a comparative analysis of material composition and cross-sectional morphology, we have determined the optimal spray distance (8 cm), ensuring the highest level of thickness uniformity in the coating (17.13 ± 0.34 μm). Furthermore, the influence of the number of passes on coating morphology and gas sensing performance was investigated. The optimal gas sensor possessed a higher response to isoamyl alcohol (236 at 25 ppm) at 250 °C. Meanwhile, excellent selectivity, repeatability, long-term stability (431.6 ± 9.2 at 60 ppm for 20 days), and a low limit of detection (144 ppb) were obtained. The superior low-concentration (< 25 ppm) gas-sensing performance should be ascribed to the loose porous morphology with uniform thickness and the higher surface activity of the optimal coating. Moreover, the practical experiment demonstrated the application potential of the sensors for monitoring wheat mildew. This work may provide a direction for the characteristic gas detection of wheat mildew and a successful case for the deposition of LaFeO₃ coating by SPPS.

NiCrBSi-based composites are immensely in demand to replace hard chrome coating for wear, corrosion-resistant applications and necessary to scale up the production. In the present work, we fabricated 1wt.% and 2wt.% nanodiamond (ND)-reinforced NiCrBSi composite coatings and evaluated the microstructural, mechanical, tribological and corrosion behavior comparing it with bare NiCrBSi coating. Our findings showed that the ND-reinforced plasma-sprayed NiCrBSi exhibited relative density up to 97.7% and offered strong mechanical properties, viz. hardness: ~ 1076.8 HV and elastic modulus: ~ 93.2 GPa. Also, the presence of outer graphitic shells in the detonated ND ignited tribological performance, restricting its wear rate at 0.21 ± 0.043 × 10⁻⁵ mm³/N.m. Further, the corrosion study proved that the incorporation of ND acted as a barrier to mitigate the corrosive electrolyte and enhanced the corrosion resistance rate by 93.70%. The involved synergetic mechanisms have been discussed in terms of lamellar structure and associated stacked splat, splat adhesion, etc. Hence, the ND-reinforced plasma-sprayed NiCrBSi coatings can be recommended as a protective coating in automotive and aerospace sectors.

Plasma spraying is characterized by high flexibility, but has challenges of high energy consumption and oxidation of the metallic spray particles. Modified plasma spraying processes using a gas or solid shroud have been developed to address these challenges, which aim to reduce the introduction of ambient air into the plasma jet and improve the process efficiency. Prior research mainly focused on single-cathode plasma generators, and the use of a shroud in multi-arc plasma spraying systems has not been thoroughly explored. The primary goal of this study is to analyze the effects of a solid shroud as a nozzle extension on the plasma jet of a three-cathode plasma generator numerically and experimentally. Computational fluid dynamics (CFD) is used to simulate a solid shroud, and the resulting design is constructed for experimental analysis. The experimental setup includes a nozzle extension with a transparent window for diagnostic measurements by a high-speed camera. To isolate the effects of the solid shroud from fluctuations in the power input, current, and voltage measurements are carried out synchronized with the high-speed recordings. Particle diagnostics are also conducted to analyze the properties of the in-flight particles without and with the solid shroud. The developed numerical model can be further used to optimize the shroud geometry for different process parameters.

Cold spray additive manufacturing is an emerging solid-state deposition process that enables large-scale components to be manufactured at high-production rates. Control over geometry is important for reducing the development and growth of defects during the 3D build process and improving the final dimensional accuracy and quality of components. To this end, a machine learning approach has recently gained interest in modeling additively manufactured geometry; however, such a data-driven modeling framework lacks the explicit consideration of a depositing surface and domain knowledge in cold spray additive manufacturing. Therefore, this study presents surface-aware data-driven modeling of an overlapping-track profile using a Gaussian Process Regression model. The proposed Gaussian Process modeling framework explicitly incorporated two relevant geometric features (i.e., surface type and polar length from the nozzle exit to the surface) and a widely adopted Gaussian superposing model as prior domain knowledge in the form of an explicit mean function. It was shown that the proposed model could provide better predictive performance than the Gaussian superposing model alone and the purely data-driven Gaussian Process model, providing consistent overlapping-track profile predictions at all overlapping ratios. By combining accurate prediction of track geometry with toolpath planning, it is anticipated that improved geometric control and product quality can be achieved in cold spray additive manufacturing.

A relatively small change in oxide content and microstructure in MCrAlY coatings (M = Co, Ni) can affect the functionality of the coating for oxidation protection or as a bond coat. The objective of this study is to fabricate a CoNiCrAlY coating with low porosity and low oxide content. The high velocity air-fuel (HVAF) process, with its relatively low process temperature, is particularly suitable for the deposition of spray materials that are susceptible to oxidation or degradation at high temperature. A CFD simulation model of HVAF process is developed to determine the process parameters for fabricating CoNiCrAlY coating. The simulation results are validated by particle diagnostics, thereby establishing a comprehensive understanding of the underlying process. To assess the coating microstructure, XRD and EDS analyses as well as observation of cross sections of the coatings are conducted. The results highlight the influence of various factors, such as the variation of carrier gas and particle size distribution, on the quality of the coatings. Consequently, the utilization of simulation-based process parameter development is well supported by the coating fabrications, offering valuable insights into the processes prior to implementation.

This study evaluated the biological response of cold-sprayed coatings composed of bioactive glass 45S5 and polyetheretherketone (PEEK). The functional coatings were produced by cold gas spray (CGS) technology, a technique that allows the deposition of powders at significantly low temperatures, avoiding heat damage to polymeric surfaces. By CGS, blends with different ratios of bioactive glass and PEEK powders have been deposited onto PEEK substrates to improve the response of the bio-inert polymer. The bioactivity of the coatings when immersed in a simulated body fluid solution was evaluated by observation with scanning electron microscopy (SEM) and x-ray diffraction (XRD). Results verify that bioactive glass particles in the composite coatings enhance their bioactivity. A degradation test was performed with Tris–HCl solution. From the results obtained by inductively coupled plasma optical emission spectroscopy (ICP-OES) and the weight loss of the samples, it was noticed that the degradation was directly related to the amount of glass in the coatings. Finally, the ability of bone-forming cells to adhere and proliferate on the coatings was evaluated. These experiments showed that the presence of glass particles does not cause a significant increase in cell proliferation. Combining a bioactive material with PEEK leads to forming a final component that provides suitable bioactivity to the final implant.