Mandin, Philippe, Cense, J.M., Fabian, Cesimiro, Gbado, C., and Lincot, D. (2007) Electrodeposition process modeling using continuous and discrete scales. Computers & Chemical Engineering, 31 (8). pp. 980-992.

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Abstract

Chemical bath electro deposition process is used in many industrial applications to obtain a thin layer material on a target surface. Numerous metal, magnetic or semi-conductor materials, such as oxide, chalcogenure or alloys are obtained in electrochemical cells at laboratory scale. Some of these materials are interesting to be produced at industrial scale, for example for electronics, fuel cells or photovoltaic applications. In industrial electrochemical cells, dimension is larger and many parameters such as hydrodynamics or electro active specie transport are heterogeneous. There are many industrial electrochemical techniques in which the electrode moves with respect to the solution. These systems, like the rotating electrodes, are called hydrodynamic electrochemical processes. It is also interesting to notice that micronic structure, such as roughness, columnar structure or porosity of material deposit is local flow dependent. Then, it appears, that the material deposit composition and structural quality need integrated information from the micronic scale to the industrial scale, using, of course, the laboratory scale measurements.

The aim of the present work is to model and to numerically simulate the hydrodynamics, electrochemical and chemical coupled phenomena, which are occurring during the chemical bath electro deposition process for laboratory and industrial configurations. Experimental measurements obtained at laboratory scale with zinc oxide thin layer deposit are used to identify transport or kinetic data input which are conserved during the scale-up. Flow and chemical species concentration field properties are calculated in the working electrode surface vicinity taking into account homogeneous and heterogeneous reactions. The numerical method used is the finite volume method. In addition, using a Monte Carlo method, micronic information is calculated such as the roughness and the porosity of the thin layer material obtained.

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