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

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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.