Numerical optimization of the nano-scale oxidation process of WC-12Co particles and influence analysis on the coating performance of HVOF thermal spraying

In the spraying process, even if there is a protective gas, the WC powder will oxidize due to the presence of local oxygen. Therefore, based on finite element analysis software, the oxidation of WC-12Co particles during thermal spraying was revealed in this study, the particle oxidation degree was taken as the optimization objective, and the optimal process parameters were obtained based on GA-BP neural network optimization method. Two groups of process parameters were used to prepare the WC coating, respectively. The microstructure, mechanical properties and corrosion resistance of the coating were compared by using various characterization methods. The results showed that the coating after optimization, the distribution of WC particles and Co bonding phase was more uniform, the surface pores and defects were less. Among them, the oxide content of the optimized coating is relatively low, with a mass percentage of only 3.67%. After optimization, a better bonding force was shown between the coating and the substrate, with the value reaching 141.7 N. In the artificial seawater corrosion test, the corrosion rate of the substrate was 0.32 mg·cm^− 2·^h−1, while the corrosion rate of the coating before optimization was 0.11 mg·cm^− 2·h^− 1. After optimization, the coating could significantly improve the corrosion resistance of the stainless-steel substrate. Meanwhile, it indicates that the numerical calculation in the early stage can accurately calculate the oxidation of particles during the spraying process. This study provides a theoretical basis in the field of stainless-steel surface strengthening.