Abstract
In the electroless nickel-boron coating process, surfactant helps to minimize the surface tension between the substrate and the electrolyte in the bath. Despite, its high cost and the formation of micelles from monomeric surfactant molecules at its critical micelle concentration (CMC), it is essential to optimize the concentration while using in the bath. In this study, to solve this problem, mathematical models are developed using regression and artificial neural network (ANN) techniques to relate the concentration of amphoteric surfactant (0-0.162 g/L) as an independent variable and microhardness as a dependent variable. Then, the developed model was used to optimize microhardness at CMC using a genetic algorithm (GA). The goodness of fit of the models was evaluated using the coefficient of determination (R2). The ANN model was found to be the best fit with R2 = 0.99. The maximum microhardness of 852 HV was achieved at the CMC of 0.064 g/L, from the GA using the validated model as a fitness function.
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