Critical micelle concentration (CMC) is an important factor to avoid the formation of micelles from monomeric surfactant molecules. Trisodium citrate stabilized electroless NiB (ENi-B) coating on aluminium alloy (Al7075-T6) is attempted with the addition of amphoteric surfactant, 3-(N, N-Dimethylmyristylammonio) propanesulfonate (3-DMAPS), to enhance the surface finish (R_a) of the coatings. The main aim of the study is to investigate the influence of surfactant concentration on average surface roughness in ENi-B bath and determine the CMC of 3-DMAPS at minimum R_a. Mathematical models relating the concentration of amphoteric surfactant (0–0.162 g/L) as an independent variable and R_a as a dependent variable are developed using univariate regression analysis (Linear, quadratic, power, and exponential models) and back propagation neural network (BPNN) algorithm. The coefficient of determination (R²) is used to evaluate the goodness of fit between the models, and the BPNN model is found to be the best fit (R² > 0.98). The minimum R_a of 0.171 ± 0.001 μm was achieved at the CMC of 0.049 g/L (0.135 mM) from the genetic algorithm (GA) using the validated models developed by quadratic regression analysis and BPNN as fitness functions. SEM, XRD and AFM techniques were carried out for the characterization of ENi-B coatings with and without surfactant at CMC.

临界胶束浓度（CMC）是避免单体表面活性剂分子形成胶束的重要因素。尝试在铝合金（Al7075-T6）上添加柠檬酸三钠稳定的化学镀Ni B（ENi-B）涂层，并加入两性表面活性剂3-（N，N - N-二甲基肉豆蔻酰铵）丙烷磺酸盐（3-DMAPS），以提高表面光洁度（R_一）的涂层。该研究的主要目的是研究表面活性剂浓度对ENi-B镀液中平均表面粗糙度的影响，并确定在最低R _a下3-DMAPS的CMC _。关于两性表面活性剂（0–0.162 g / L）作为自变量的浓度和R _a的数学模型使用单变量回归分析（线性模型，二次模型，幂模型和指数模型）和反向传播神经网络（BPNN）算法开发作为因变量的变量。确定系数（R ²）用于评估模型之间的拟合优度，并且发现BPNN模型是最佳拟合（R ²  > 0.98）。遗传算法（GA）使用二次回归分析和BPNN作为适应度函数开发的经过验证的模型，在遗传算法（GA）中，CMC为0.049 g / L（0.135 mM）时，最小R _a为0.171±0.001μm。进行了SEM，XRD和AFM技术对CMC上有或没有表面活性剂的ENi-B涂层进行表征。