电沉积的建模与仿真:电解液电流密度和电导率对电镀厚度的影响

A. Mahapatro, Santosh Kumar Suggu
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引用次数: 21

摘要

电镀或电沉积是在电化学电池中进行的过程,其中电流被用来在金属表面形成涂层。开发和优化电镀工艺条件耗时长,可采用建模和仿真技术对电沉积工艺进行优化。电解质电流密度和电导率是电沉积系统的重要参数,因为它们决定了电解质系统中离子流动的整体效率,因此对这些参数进行优化是必要的。在这篇手稿中,我们报告了一个数学模型的发展,以预测铜和钴铬合金为电极,硫酸铜为电解质的电化学电池中铜在钴铬合金上的电沉积。通过实验验证了所建立的模型。利用扫描电子显微镜(SEM)和测厚仪对样品的镀层厚度进行了表征。在30 min时,模型预测铜的厚度为11.7 μm,而通过SEM和测厚仪的实验发现涂层厚度分别为9.445+/-1.79(平均值+/SD)和12.375+/-1.36(平均值+/SD)。当预测电流密度的影响时,模型准确地预测了一般趋势,但在模型没有考虑到电化学双层的显著影响的区域,模型似乎与实验值有所不同。该模型准确地预测了电解质电导率对镀层形成的影响趋势。因此,该模型可以作为预测工艺参数对电沉积厚度影响的起点*通信:Anil Mahapatro,威奇托州立大学生物医学工程系,1845 Fairmount Street, Wichita, KS 67260, USA, Tel: 316-978-5912;电子邮件:anil.mahapatro@wichita.edu
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling and simulation of electrodeposition: effect of electrolyte current density and conductivity on electroplating thickness
Electroplating or electrodeposition is a process carried out in an electrochemical cell where a current is used to form a coating on a metal surface. Developing and optimizing conditions for electroplating is time consuming and modeling and simulation could be used to optimize the electrodeposition process. Electrolyte current density and conductivity are important parameters for an electrodeposition system as they dictate the overall efficiency of flow of ions in the electrolyte system and thus optimization of these parameters is necessary. In this manuscript we report the development of a mathematical model to predict the electrodeposition of copper on cobalt chrome alloy in an electrochemical cell with copper and cobalt chrome alloy as the electrodes and copper sulfate as the electrolyte. The developed model was validated using experiments. The coating thickness of the samples was characterized using scanning electron microscope (SEM) and a thickness gage. At 30 min the model predicted the copper thickness to be 11.7 μm while experimentally the coating thickness was found to be 9.445+/-1.79 (mean +/SD) using SEM and 12.375+/-1.36 (mean +/SD) using thickness gauge. When predicting effect of current density the model accurately predicts general trends however the model seems to vary from experimental values in regions where there is significant effect of the electrochemical double layer that the model does not account for. The model accurately predicts the trend of effect of electrolyte conductivity on coating formation. The model can thus be used as a starting point to predict effect of process parameters on electrodeposition thickness *Correspondence to: Anil Mahapatro, Department of Biomedical Engineering, Wichita State University, 1845 Fairmount Street, Wichita, KS 67260, USA, Tel: 316-978-5912; E-mail: anil.mahapatro@wichita.edu
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