The morphology of copper electrodes significantly affects the performance of electrochemical CO₂ reduction devices. Porous morphologies are important to increase the active reaction sites and to tune the selectivity towards desired products, but it can also limit the mass transport through the pore space. A better understanding of morphology-induced performance limitations or enhancements in porous electrodes is needed.

We used a coupled experimental-numerical approach to quantitatively characterize morphologically-complex porous electrodes (micrometer thick macroporous films with mesoporous structural details). We utilized a 3D-microscopy method, FIB-SEM tomography [1] with a high resolution of 4x4x4 nm³, to obtain a grey value array representing the photoelectrode morphology. The digital structure was segmented based on trainable machine-learning algorithms to subsequently quantify performance-related morphological parameters.

We applied this method to a hierarchically structured indium−tin oxide (ITO) electrode, covered by electrodeposited copper. The ITO scaffold has a macroporous inverse opal (IO) architecture and a mesoporous skeleton to increase the effective surface area [2]. Various samples with IO film thickness of 10 – 30 μm and pore diameters of 0.5 – 2 μm were scanned.

The digitalized electrode morphologies were then used in direct pore-level simulations to understand the mass transport within the macro- and mesopores. The diffusive transport of reactants and products in the electrolyte were investigated with a finite volume solver on a meshed representation of the exact geometries. Local current densities at the solid-liquid interface and pH distributions in the pore space were determined for the different film thickness and pore diameters.

The FIB-SEM tomography, with its nanometer-scale resolution, and the advanced pore-level simulations allowed for direct linking of the multi-physical transport to the morphological parameters of the porous ITO/Cu films. This study lays the ground for the optimization of the CO₂ reduction efficiency by tuning the morphological parameters on digitally modified electrode representations (e.g. modified pore diameters, pore distribution and film thickness).

References

[1]         M. Cantoni and L. Holzer, “Advances in 3D focused ion beam tomography,” MRS Bull., vol. 39, no. 4, pp. 354–360, 2014.

[2]         D. Mersch et al., “Wiring of Photosystem II to Hydrogenase for Photoelectrochemical Water Splitting,” 2015.