Method and model development for the simulation of layer thickness distributions on complexly shaped components in galvanic layer deposition processes

表面性质可以通过电镀在很大范围内进行调整。为此，涂层必须满足规定的要求，特别是在成分和厚度方面。电沉积层厚度分布的数值模拟是工艺和电解液设计的挑战之一，尤其是对形状复杂的零件。目前使用的模型都是基于大量的简化假设。例如，没有充分考虑熔池、阳极和阴极的反应动力学。这是由于特定沉积过程所需的物理参数，如反应的扩散系数和速率常数通常是未知的。然而，必须特别考虑这些反应，特别是对于碱性电解液，因为这里添加的络合剂反应地结合自由金属离子，而这些络合剂不能用于成层过程。通过充分考虑镀液反应，有可能以所需的精度预测涂层厚度分布。为此，该项目将在以前自己研究的基础上建立一个包含这些扩展的数值模型，并将开发出有效的数学解的必要方法。所需物理参数的确定是通过数值模拟和适当的实验方法相结合的方法完成的。这种方法为其他或新的电解液提供了良好的转移性。作为一个例子，实验、模型和软件在相关的柠檬酸-镍电解液上进行了校准，随后在柠檬酸-钴体系上进行了验证。数值模型的开发使用了现代数学和数值方法(例如自适应有限元)，因此对于各种电解液，即使在具有可接受的计算时间的复杂形状的组件上，预测层厚度分布的精度也是可能的。

Surface properties can be adjusted within wide limits by electroplating. For this purpose, the coatings must meet defined requirements, especially with respect to their composition and thickness. The numerical simulation of the layer-thickness distribution of electrodeposited layers is one of the challenging tasks of process and electrolyte design, especially on complexly shaped components. Currently used models are based on a large number of simplifying assumptions. For example, the reaction kinetics in the bath, at the anode, and at the cathode are not fully taken into account. This is due to the fact that the necessary physical parameters, such as diffusion coefficients and rate constants of the reactions, for the specific deposition process are generally unknown. However, these reactions must be considered especially for alkaline electrolytes, since the complexing agents added here reactively bind free metal ions and these are not available for the layer-formation process. By taking the bath reactions fully into account, it is possible to predict the coating thickness distribution with the required accuracy. For this purpose, a numerical model containing these extensions will be set up in the project based on previous, own research, and the necessary methods for an efficient mathematical solution will be developed. The determination of the necessary physical parameters is done by numerical modeling in combination with adapted experimental methods. This approach opens up good transferability to other or new electrolytes. As an example, the experiments, the models, and the software are calibrated on a relevant citric acid–nickel electrolyte and subsequently validated on the citric acid–cobalt system. The numerical model development uses modern mathematical and numerical methods (e.g. adaptive FEM) so that an increased accuracy of the prediction of the layer thickness distribution is possible for a variety of electrolytes even on complexly shaped components with acceptable computation times.