【摘要】 用电位阶跃方法研究了氯化钾镀锌溶液中不同添加剂（OP-10,苄基苯基酮,NNO和CH-1光亮剂）存在时锌在玻碳电极上的电结晶行为;同时针对传统求解电结晶动力学参数方法的不足,设计出一种基于实数编码的遗传算法通过拟合恒电位暂态曲线,演化优化求得动力学参数（晶核密度数N₀和位置转换为晶核的速率常数A）和金属离子扩散系数D,并在此基础上对演化求得的参数进行了分析和讨论.结果表明,使用此遗传算法对整条曲线拟合优化出的参数更为合理,可用来解释添加剂对锌在玻碳电极上电结晶的影响机理.更多还原

【Abstract】 The electrochemical behaviors of zinc deposition onto glassy carbon electrode (GCE) from potassium chloride solution with some conventional additives (NNO, OP- 10, phenylbenzyl ketone and CH - 1 brightener) have been examined by chronoamperometry. To overcome the drawbacks in estimating kinetic parameters of electrocrystallization by traditional methods, we proposed a floating - encoding genetic algorithm (FEGA) to estimate the parameters A (the nucleation rate constant per site), N0(the number density of active sites over the substrate surface) and D (the diffusion coefficient of zinc ions) simultaneously by fitting the entire current transients. Based on those evolved kinetic parameters, some discussion and analysis were made. The results indicated that the kinetic parameters obtained by FEGA are more reasonable and can be employed to explain the effects of additives on the electrocrystallization of zinc.更多还原