Cold spray processing of AA2024/Al2O3 coating on magnesium AZ31B alloy: Process parameters optimization, microstructure and adhesive strength performance of coating

Abstract

The automotive and aerospace sectors are progressively employing the magnesium (Mg) alloy of the grade AZ31B because of its excellent castability, low density, and high ration of strength to weight. Nevertheless, the limited ability of AZ31B alloy to withstand corrosion limits their use in several fields of technology. In order to solve this problem, the AZ31B alloy is coated utilizing an AA2024/Al2O3 metal matrix composite (MMC) coating that is applied by the cold spray coating (CS) method. The primary goal of this work is the parametric optimization of CS process for maximizing adhesive strength of MMC-coated Mg-alloy substrate. Response surface methodology (RSM) is implemented to find the optimum CS parameters, including feed rate of powder – FRP (g/min), standoff distance of gun – SDG (mm) and processing temperature – TEMP (oC). The regression-based parametric adhesion strength prediction (ASP) model was formulated using the RSM and statistically validated using analysis of variance (ANOVA). Employing 3D surface of responses, the influence of CS parameters on the adhesion strength of an MMC-coating was assessed. The findings revealed that when the MMC-coating was cold sprayed on the Mg-alloy using FRP of 22 g/min, SDG of 12 mm, and TEMP of 520oC, the maximum adhesion strength of MMC-coating was 70 MPa (actual). Given less than 2% error at 95% confidence, the parametric ASP model correctly predicted the adhesion strength of the MMC-coating. The ANOVA findings showed that FRP (g/min) had significant effect on adhesive strength of MMC-coating followed by SDG (mm) and TEMP (oC). The MMC-coating applied using the RSM optimized CS parameters showed 70.73% superior adhesive strength owing to the lower porosity formation of 2 vol.% which offers greater interfacial area. The ASP equation was formulated using the “best fitting line” approach and validated using ANOVA for predicting the adhesive strength (MPa) from the porosity formation (vol.%) in the MMC-coating.