Journal of Thermal Spray Technology最新文献

Wire-Arc Spraying (WAS) is an economical and widely used thermal spray process. Applications include corrosion protection coatings on offshore wind power plants. While WAS is cost-efficient and technologically well-developed, the high process complexity results in a lack of physics-based models. The process is characterized by fluctuations of an electric arc which moves along the wire tips. Regular, periodic process fluctuations, caused by droplet detachment and the corresponding arc movement, are intrinsic to WAS. However, irregular, aperiodic fluctuations, such as arc interruptions, indicate an unstable process and must be avoided. These irregular fluctuations can lead to plant downtime, coating defects and therefore an increase in maintenance and quality control costs. This study employs time-series anomaly detection algorithms on WAS sensor data and introduces a novel optimization criterion, σ_L, which is specifically derived for thermal spraying processes for the purpose of process stability assessment. To collect the necessary time-series data, a sensor unit was set up on a WAS system. ZnAl15 wire and Fe₆₂Si₁₂B₈C₄Nb₂Mo₂Cr₁₀ cored wire were used as feedstock materials. ZnAl15 spraying included multiple experimental runs according to the design of experiment methodology. The ZnAl15 coatings were applied onto C45 steel substrate. Each sample was weighed before and after spraying to determine the deposition efficiency. Voltage and electric current in every experiment were measured at a sampling rate of 500 kHz. Fast Fourier Transformations (FFT) were calculated on the electrical resistance, which was derived by Ohm’s law. The signal analysis revealed WAS process-related fundamental frequencies in the range of 0.5-1.0 kHz, alongside frequencies at 20 kHz, which stem from the power control unit. The novel criterion σ_L is calculated on the first range of frequencies. The fact that σ_L shows low sensitivity to regular process fluctuations makes it superior to conventional metrics. By generalized linear modeling, σ_L as well as the deposition efficiency were fitted to the investigated parameters. Combining σ_L and known anomaly detection algorithms such as thresholding and k-means allows for the detection of detrimental fluctuations and process interruptions.

Cold spray is a coating process as well as rapidly emerging and scalable solid-state robotic additive manufacturing technology. Its high deposition rates (+10 kg/hr) allow for manufacturing of near net shape large metal and composite structures. For example, it is possible to additive manufacture near net shape IN718 parts directly from powder in addition to coating and repair of critical components for high-temperature applications and aviation industries. The challenge is that successful cold spray deposition of IN718 depends on careful optimization of multiple processing parameters. This study examines a developed digital twin for cold spraying to overcome the time-consuming optimization process for IN718 deposition with consideration of independently published data. This approach was taken to achieve realistic validation for Cold Spray Digital Twin (CSDT) that could eventually lead to an autonomous cold spray deposition capability. The CSDT was constructed according to a calibrated and validated three-dimensional (3D) multicomponent CFD model for visualization of cold spray supersonic flow combined with all input parameters of the industry-scale cold spray systems. The predicted in-flight particle temperature and velocity that are difficult to measure experimentally are reported. The results from CSDT simulations were in agreement with the three experimental studies with consideration of 10-15% error achieved through the 3D model calibration process. The CSDT capabilities were successfully applied to visualize and discuss the IN718 deposition in relation to cold spray nozzle, shockwave formation, nozzle, and substrate heat transfer including the effect of powder feed rate. Overall, CSDT outcomes proved to be a cost-effective tool providing detailed information that otherwise would only be possible through performing challenging experimentations. Analysis of the CSDT outputs presented the opportunity for advancing our understanding of cold spray bonding and improving process efficiency using industry-scale cold spray equipment with potential improvements in designing future cold spray systems.

Irregular dimples were prepared on the polished surface of an Al₂O₃ coating using laser texturing technology. Subsequently, the modified PTFE emulsion (M-PTFE) was infiltrated into the dimples via vacuum impregnation to obtain the Al₂O₃-PTFE composite coating. The microstructure and tribological behavior of the Al₂O₃-PTFE composite coating were systematically characterized and compared with those of the Al₂O₃ coating. The results demonstrated that M-PTFE successfully penetrated into the bottom of the textured dimples. Compared with the Al₂O₃ coating, the Al₂O₃-PTFE composite coating formed a continuous and stable PTFE lubricating film during the sliding process, which endowed it with outstanding friction-reducing and wear-resistant characteristics. The friction coefficient of the Al₂O₃-PTFE composite coating (0.08) was approximately 7 times lower than that of the Al₂O₃ coating (0.57). The wear rate of the Al₂O₃-PTFE composite coating after 2.5 × 10⁵ sliding cycles was 4.36 × 10⁻⁸ mm³(N⋅m)^− 1, representing a reduction of four orders of magnitude compared with that of the Al₂O₃ coating (2.53 × 10⁻⁴ mm³(N⋅m)^− 1) measured after 2 × 10⁴ cycles. Furthermore, the Al₂O₃ counterface ball sliding against the Al₂O₃-PTFE composite coating exhibited minimal surface degradation. This approach effectively bridges the gap between the hardness of ceramics and the lubrication requirements, offering a scalable and cost-effective solution for industrial applications where dry sliding performance is critical.

High-velocity oxygen–fuel (HVOF) is an effective method for preparing high-temperature wear-resistant coatings, which can significantly enhance the protective performance of the surface of parts. The spraying distance is a key controllable variable that directly affects the temperature, velocity, and deposition behavior of the flying particles, and thus determines the microstructure and comprehensive performance of the coating. A full-cycle model for the HVOF spraying process of nano-WC-10Co4Cr on AZ31B magnesium alloy is established in this study covers the combustion reaction, dynamic flame jetting, multiphase flow of nanoparticles, and particle deposition. The flight characteristics of nano-powders are simulated and analyzed. Based on these results, the spraying distance is optimized, and the deposition behavior is calculated, providing a theoretical foundation for actual process optimization. The study shows that the nano-powders are greatly affected by external conditions. The temperature and velocity of nanoparticles in the air domain rapidly decrease, which cannot meet the effective deposition conditions. By moving the substrate forward to be closer to the spray gun, the spraying distance is reduced from the original 545-450 mm. With the optimized spraying distance, the particle deposition rate increases by 29%. Moreover, the deposited particles exhibit better flattening and more uniform coverage of the substrate. On this basis, the deposition model is verified through SEM experiments. The microscopic morphology at the bonding surface under different spraying distances is analyzed. The results show that the bonding surface with the optimized spraying distance is smoother and flatter, the porosity of the coating decreases by 27.1%, and the coating quality is significantly improved. The validity of the model is verified, and the feasibility of adjusting the spraying distance to improve the coating quality is proved.

Engineering equipment operating in marine environments currently faces severe service conditions, including challenges such as seawater corrosion and mechanical impacts. Therefore, it is essential to apply protective coatings to marine engineering structures. The contact areas between dissimilar metals in these engineering components are particularly susceptible to both galvanic corrosion and impact damage, necessitating protective coatings that simultaneously exhibit high electrical resistivity and excellent fracture toughness. In this experiment, micro-sized and nano-sized Al₂O₃-3 wt.% TiO₂(AT3) were used as raw materials to prepare coatings via atmospheric plasma spraying. Both types of powders and coatings were analyzed using XRD for phase identification. The surface and cross section morphology of the powders and coatings were examined using SEM. The insulation resistance of the coatings before and after impact was measured using a high-resistance meter. The hardness and fracture toughness of the coatings were determined using a Vickers hardness tester. The surface of the deposited AT3-nm coating was relatively dense. The AT3-μm coating consisted mainly of γ-Al₂O₃, whereas the AT3-nm coating was primarily composed of α-Al₂O₃. The AT3-nm coating exhibited lower porosity, higher hardness, and better fracture toughness compared to the AT3-μm coating. In contrast, the AT3-μm coating demonstrated higher electrical resistivity, indicating better insulation performance. During the impact test, structural damage to the AT3-nm coating occurred more gradually, and the decrease in electrical resistivity was slower, demonstrating its superior impact resistance. In conclusion, the AT3-nm coating exhibits good insulation performance and provides excellent impact-resistant protection.

Thermal spray coatings are widely employed to enhance the wear resistance and frictional performance of engineering components operating under severe tribological conditions. In this study, WC-12Co and Al₂O₃-13TiO₂ coatings were deposited on AISI 6151 steel using the detonation gun (D-gun) spraying technique, and their wear and friction behavior were systematically investigated. A Taguchi L27 orthogonal array, combined with response surface methodology (RSM), was used to evaluate the effects of coating type, load, sliding speed, and test duration on the wear rate and coefficient of friction (CoF) under dry-sliding conditions. Microstructural and phase analyses were performed using SEM, EDS, and XRD to elucidate dominant wear mechanisms. In addition, machine learning (ML) models, including random forest (RF), decision tree (DT), K-nearest neighbors (KNN), and extreme gradient boosting (XGBoost), were developed to predict the wear rate and CoF from experimental data. Model performance was assessed using multiple error metrics and statistically validated through variance analysis and confidence intervals. The results indicate that WC-12Co exhibits superior wear resistance due to high hardness and low porosity, while Al₂O₃-13TiO₂ provides a balanced combination of moderate wear resistance and stable friction behavior. The ML models demonstrated high predictive accuracy within the investigated parameter space; however, given the structured and limited dataset, the models are primarily intended for interpolation rather than extrapolation beyond the experimental domain. This integrated experimental-statistical-ML framework provides a reliable decision-support tool for optimizing thermal spray coatings in practical engineering applications.

This study relied on laser cladding to prepare a number of Fe-based composite coatings with different WC contents (10-40 wt.%) on the surface of 27SiMn steel. Through an array of research involving the macroscopic/microscopic structure of the WC-Fe interfacial reactive layer, investigation was made into the mechanical properties, the wear behavior of the coatings, as well as the microstructural evolution laws of the WC-Fe reactive layer, and the wear mechanism. Results of microstructural analysis indicate that increasing WC content promotes the formation of a WC-Fe reaction layer by reducing the γ-Fe/WC interfacial energy. In case of a 40% WC content, the maximum thickness reaches 1.3 μm for the WC-Fe interface reaction layer. However, it is prone to incur microcracks at the grain boundaries by the high content and segregation of W element. The findings of the microhardness and fracture toughness imply the best strength–toughness match when the coating WC content is 20% (hardness of 884.7 HV_0.2 and fracture toughness of 4.43 MPa m^1/2). Naturally, it reveals the best surface flatness in the wear test owing to the solid solution of the W element and the diffuse distribution of carbide particles. On the contrary, the coating with 40% WC content underscores the worst hardness and toughness (hardness of 554.6 HV_0.2, fracture toughness of 2.98 MPa m^1/2). It also accidentally demonstrates commendable wear resistance. This may pertain to a unique self-lubricating layer and the microcracked stress buffering network structure on the coating surface, which further ascertains a new wear resistance mechanism of the microcracked network.

This study investigates the influence of ceramic reinforcement on the microstructure, hardness, and intrinsic flexural behavior of cold-sprayed Ti-6Al-4V Grade 23 (Ti-G23) multilayer deposits. Multilayer specimens comprising an E295 steel substrate with a nickel interlayer were prepared for microstructural and hardness evaluation, while freestanding Ti-G23 and Ti-G23/SiC deposits were fabricated for intrinsic flexural testing independent of substrate constraint. The Ni interlayer exhibited a compact fine-grained structure with porosity below 0.53%, ensuring stable interfacial integrity. The monolithic Ti-G23 coating showed up to 12% lower porosity than the composite counterpart. Incorporation of SiC increased the average hardness of the composite deposit to 419 HV1, while localized microhardness values measured near regions containing higher SiC content reached up to 549 HV0.1. Flexural testing of freestanding deposits demonstrated slightly higher strength and stiffness for Ti-G23 (559 ± 20 MPa; 68 ± 5 GPa) compared with Ti-G23/SiC (523 ± 14 MPa; 63 ± 3 GPa). Fractographic analysis of the composite deposit revealed localized particle decohesion and microcrack initiation in regions containing increased reinforcement concentration. The results demonstrate that although ceramic reinforcement contributes to localized hardness enhancement, it simultaneously increases structural heterogeneity and restricts deformation within the composite deposit, limiting improvements in intrinsic flexural performance.