Parametric optimization of electroless Ni-P-CNT coating using genetic algorithm to maximize the rate of deposition. (2022)

• Record Type: Journal Article
• Authors: Kumar Srivastwa, Ambikesh; Sarkar, Subhasish; De, Jhumpa; Majumdar, Gautam
• Is Part Of: Materials today. Volume 66:Part 9(2022)
• Page Start: 3769
• Page End: 3774
• Publication Date: 2022
• Subjects: Electroless Ni-P-CNT coating -- Composite coating -- Response surface method -- Genetic algorithm -- Rate of mass deposition; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2022.06.106
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: To improve the surface property of 99% pure copper substrate Electroless Ni-P-CNT coating was deposited. The effect of the elements of the coating bath on the rate of mass deposition has been examined and discussed in this study. The first order regression equation has been developed to predict the rate of deposited mass per unit area. The Student's t test have exhibited that the concentrations of Nickel Sulphate, Sodium hypophosphite and the carbon nanotubes (CNT) significantly affect the rate of deposition of the electroless Ni-P-CNT coating. A response order response surface model has been developed to consider the effect of curvature in predicting the response. The response surface and counter plots reveal that the variations in concentration of the individual process parameters influence the deposition rate dramatically. The F -test has confirmed that the predicted response surface equation shows an excellent fitting with the observed data. The optimum concentrations of Nickel Sulphate, Sodium hypophosphite and carbon nanotubes in the coating bath have been evaluated using genetic algorithm to maximise the rate of deposition of electroless Ni-P-CNT composite coating. The results of the genetic algorithm are consistent with the results of the confirmation run.