Optimization of process parameters for preparing the hydrophobic surface of aluminum alloy by laser-assisted electrochemical composite etching based on response surface method

Abstract

To explore the influence of electrolyte concentration, single pulse energy, current density and scan times on the hydrophobic properties of laser-assisted electrochemical composite etching 2024 aluminum alloy surface, the experimental platform of laser-assisted electrochemical composite etching is built. Based on the results of the single-factor experiments, the response surface method (RSM) is chosen to optimize the process parameters. The optimum combination of process parameters is obtained, and the accuracy of the regression equation is verified by experiments. Through residual analysis, the established regression model fits well. By analysis of variance (ANOVA), the sequence of influence of the factors on apparent contact angle (from large to small) is single pulse energy, scan times, electrolyte concentration, and current density. With the maximum apparent contact angle as the goal, the combination of process parameters adjusted after optimization is: electrolyte concentration 2.0 mol/L, single pulse energy 20µJ, current density 18 mA, and scan times 15. Under these conditions, the experimental values of apparent contact angle is 157°, which is close to the predicted value (158°) by the models. The relative errors is 0.6%. It indicates that the regression model is accurate and reliable. This study shows that RSM is an effective method to optimize the process parameters and obtain the ideal experimental results.

Keywords:

• Laser-assisted electrochemical composite etching
• 2024 aluminum alloy
• response surface method
• parameters optimization
• hydrophobicity

Disclosures

No potential conflict of interest was reported by the author(s).

Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

This work was supported by the [National Natural Science Foundation of China] under Grant [number 51875328]; [Natural Science Foundation of Shandong Province] under Grant [number ZR2019MEE013].