Modelling of Diffusion-Limited Growth in the Electrodeposition of Porous ZnO
Authors: Lupo Christian , Schlettwein Derck 
Published: May 2020

Electrodes of ZnO sensitized with appropriate dyes are very suitable as photoanodes in dye-sensitized solar cells (DSSCs).1 They are of particular advantage relative to established photoanodes based on nanoparticulate TiO2 since they
- can be processed at low temperature and
- provide higher electron mobility.
Processing at low temperature is beneficial in itself because it leads to lower energy consumption during preparation and, hence, helps to reach payback times. Further, it allows using plastic foils as substrates and, thereby, further improves the energy balance and allows constructing lightweight and mechanically flexible solar cells. The higher electron mobility in ZnO helps to reduce the transport resistance in films which becomes important to suppress recombination in DSSCs using reversible redox shuttles to achieve higher photovoltage and, hence, higher efficiency.
The electrodeposition of porous ZnO was optimized1 by addition of structure-directing agents (SDAs) in a reaction sequence
O2 + 2 H2O + 4 e- → 4 OH- (1)
Zn2+ + 2 OH- → [Zn(OH)2] → ZnO + H2O (2)
in which the growth rate of porous ZnO is limited by the diffusion of O2. Optimization of porosity and pore radius of ZnO essential for its application in dye-sensitized solar cells in order to enhance the cell performance can be obtained by proper choice of SDAs. Larger pores, e.g., showed a significantly decreased impedance of mass transport leading to an increased photocurrent in DSSCs. Successful application of these new ZnO films in dye-sensitized solar cells confirmed improved pathways for large complex ions as redox shuttles through the ZnO pore structure.2

Further optimization of film growth requires appropriate modelling. Simulations and experiments are presented for electrodeposition on microstructured electrode arrays (MEAs), namely, parallel band electrodes as model for planar substrates. Microelectrodes are very attractive in electrochemical applications because of easily reached high current densities and fast establishment of a steady state. In the present case of band arrays, however, the overlap of diffusion layers of adjacent electrodes has to be considered and leads to a reduced mass flux to each individual electrode band in comparison to a single electrode. A lower current density and, hence, lower rate of electrodeposition is observed. Three consecutive steps in the build-up of diffusion profiles have been established in the literature: at the beginning, each electrode band can be treated separately, then the overlap has to be considered and finally the diffusion profile can be described as planar, well comparable to a macroscopic electrode. Simulations were performed considering the detailed distribution of concentration changes in the electrolyte and also including all changes brought forward by the deposition of material (see Figure) and, hence, changes of the electrode geometry.3 The simulated current densities and the simulated shape of electrodeposited films compared very well to experimentally observed values, proving the validity of the chosen approach.
1. T. Yoshida, J. B. Zhang, D. Komatsu, S. Sawatani, H. Minoura, T. Pauporte, D. Lincot, T. Oekermann, D. Schlettwein, H. Tada, D. Wöhrle, K. Funabiki, M. Matsui, H. Miura, H. Yanagi, "Electrodeposition of Inorganic/Organic Hybrid Thin Films", Adv. Funct. Mat. (2009) 19, 17-43.
2. T. H. Q. Nguyen, R. Ruess, D. Schlettwein, "Adjusting Porosity and Pore Radius of Electrodeposited ZnO Photoanodes", J. Electrochem. Soc. (2019) 166, B3040-B3046.
3. C. Lupó, D. Schlettwein, "Modeling of Dendrite Formation as a Consequence of Diffusion-Limited Electrodeposition", J. Electrochem.
Soc. (2019) 166, D3182-D3189.
Figure: Simultaneously obtained modelling results of interdependent electrodeposition of porous ZnO (in grey) and concentration changes of O2 in the electrolyte (red for high, blue for low concentrations) after 100 s of electrodeposition under diffusion limitation.

Figure 1