Proceedings of nanoGe Fall Meeting 2021 (NFM21)
DOI: https://doi.org/10.29363/nanoge.nfm.2021.141
Publication date: 23rd September 2021
Increasing the structural complexity of (photo)electrodes is a possible approach to obtain higher activities and selectivities in – for example – CO2 reduction or oxygen evolution. Many synthesis methods produce random, porous morphologies in which the chemical and physical conditions may vary significantly with respect to the bulk, affecting activity and selectivity towards the desired product.
Here, we use a combined experimental-numerical technique to obtain, digitalize and quantitatively characterize morphologically complex (photo)electrodes. The material is digitally reconstructed starting from a physical sample investigated by means of the FIB-SEM nanotomography technique, with resolution of up to 4 nm in the three dimensions. The obtained image stacks are processed to obtain a digitalized representation of the morphology, which subsequently can be quantitatively characterized and used in pore-level transport simulations.
We present quantitative morphological characterization of the catalyst layer of five CO2 reduction gas diffusion electrodes. We calculated and compared roughness factor, specific area, connected volume, volume fraction profile, opening size distribution, chord length distribution, and two points correlation, providing a range of parameters difficult or impossible to obtain through experimental methods giving quantitative insight on electrode morphologies.
The digitalized morphologies can be meshed and used as geometrical domain in simulations for the characterization of transport properties and the extraction of effective physical properties (e.g. effective diffusivity or absorption coefficient) or in direct coupled pore-scale simulations for the characterization of operando physical and chemical conditions within the pores. The presented methodology is widely applicable, and will allow to shine some light on the link between morphology and physical properties of materials.
The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie-Skłodowska-Curie grant agreement No. 861151 and under SELECTCO2 grant agreement No. 851441.
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