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

被引:0
作者
Zhang, Zengbo [1 ]
Zhang, Haiyun [1 ,2 ]
Zhang, Jinjian [1 ]
Miao, Xu [1 ]
Fu, Yandi [1 ]
Meng, Jianbing [1 ,2 ]
Zhao, Yugang [1 ,2 ]
Gao, Yuewu [1 ,2 ]
机构
[1] Shandong Univ Technol, Sch Mech Engn, Zibo, Peoples R China
[2] Shandong Prov Key Lab Precis Mfg & Nontradit Machi, Zibo, Peoples R China
基金
中国国家自然科学基金;
关键词
Laser-assisted electrochemical composite etching; 2024 aluminum alloy; response surface method; parameters optimization; hydrophobicity; SUPERHYDROPHOBIC SURFACES; CONTACT ANGLES; FABRICATION; WETTABILITY; TRANSITION; RESISTANCE; SUBSTRATE; SILICA; ZNO;
D O I
10.1080/01694243.2023.2256560
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
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 20 & mu;J, current density 18 mA, and scan times 15. Under these conditions, the experimental values of apparent contact angle is 157 & DEG;, which is close to the predicted value (158 & DEG;) 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.
引用
收藏
页码:1438 / 1455
页数:18
相关论文
共 50 条
  • [31] Optimization of the process for preparing sodium silicate from serpentine silicon-rich slag based on the Box-Behnken response surface method
    Gao L.
    Yang X.
    Wu Y.
    Chen Y.
    [J]. Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology), 2022, 53 (10): : 3802 - 3810
  • [32] Hot Deformation Behavior of Laves Phase NbCr2/Nb Two-Phase Alloy and Optimization of Deformation Process Parameters Based on Response Surface Method
    Wang, Shuangjian
    Lu, Shiqiang
    Wang, Kelu
    Deng, Liping
    Xiao, Xuan
    Zhang, Kaiming
    [J]. RARE METAL MATERIALS AND ENGINEERING, 2024, 53 (08) : 2301 - 2313
  • [33] Optimization of Deformation Process Parameters of Ti2AlNb-Based Alloys Based on Response Surface Methodology
    Liu J.
    Wang J.
    Lu S.
    Li X.
    Huang W.
    Zeng Q.
    Zhou T.
    Wang Z.
    [J]. Xiyou Jinshu Cailiao Yu Gongcheng/Rare Metal Materials and Engineering, 2023, 52 (10): : 3581 - 3589
  • [34] Optimization of rare earth carbonate reactive-crystallization process based on response surface method
    Zhu, Dongmei
    Chen, Qianwen
    Qiu, Tingsheng
    Zhao, Guanfei
    Fang, Xihui
    [J]. JOURNAL OF RARE EARTHS, 2021, 39 (01) : 98 - 104
  • [35] Process analysis of biconvex tube hydroforming based on loading path optimization by response surface method
    Zhang, Chi
    Liu, Wen
    Huang, Lirong
    Wang, Chunge
    Huang, Haoran
    Lin, Li
    Wang, Peichao
    [J]. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2021, 112 (9-10) : 2609 - 2622
  • [36] Process analysis of biconvex tube hydroforming based on loading path optimization by response surface method
    Chi Zhang
    Wen Liu
    Lirong Huang
    Chunge Wang
    Haoran Huang
    Li Lin
    Peichao Wang
    [J]. The International Journal of Advanced Manufacturing Technology, 2021, 112 : 2609 - 2622
  • [37] Investigating the Optimum Model Parameters for Casting Process of A356 Alloy: A Cross-validation Using Response Surface Method and Particle Swarm Optimization
    Sensoy, Abdullah Tahir
    Colak, Murat
    Kaymaz, Irfan
    Dispinar, Derya
    [J]. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2020, 45 (11) : 9759 - 9768
  • [38] OPTIMIZATION OF PROCESS PARAMETERS FOR MICROWAVE-VACUUM PUFFING OF BLACK RADISH SLICES USING THE RESPONSE SURFACE METHOD
    Pawlak, Tomasz
    Ryniecki, Antoni
    Siatkowski, Idzi
    [J]. ACTA SCIENTIARUM POLONORUM-TECHNOLOGIA ALIMENTARIA, 2013, 12 (03) : 253 - 262
  • [39] A Two-Stage Optimization Method for the Stencil Printing Process based on Neural Network and Response Surface Method
    Pan, Ershun
    Jin, Yao
    Zhao, Mei
    Wang, Ying
    [J]. ADVANCED MANUFACTURING TECHNOLOGY, PTS 1, 2, 2011, 156-157 : 10 - 17
  • [40] Hot Stamping Parameters Optimization of Boron Steel Using a Response Surface Methodology Based on Central Composite Design
    Ming-dong HUANG
    Bao-yu WANG
    Jing ZHOU
    [J]. JournalofIronandSteelResearch(International), 2015, 22 (06) : 519 - 526