Optimization of MIEC-based SOFC anodes by digital microstructure design (DMD)

Reference: 1. P. Marmet et al., Phys. Chem. Chem. Phys., 2021, 23(40), 23042–23074, doi: 10.1039/d1cp01962g.
Fully ceramic anodes such as LST-CGO offer some specific advantages compared to conventional Ni-based cermets. Ceria- and titanate-based phases are both mixed ionic and electronic conductors (MIEC), which leads to very different reaction mechanisms and associated requirements for the microstructure design compared to e.g. Ni-YSZ. In MIEC anodes, the reaction mainly takes place on the twophase boundaries of ceria (instead of the three-phase boundaries). Due to the MIEC-property of both solid phases, the transports of neither the electrons nor the oxygen ions are limited to a single phase. This leads to an effective composite conductivity (for electrons as well as for ions), which is much higher than the (hypothetical) single phase conductivity. In such a system, the charge carriers can reach the reaction sites even when the phase volume fraction(s) is/are below the percolation threshold. In this contribution, methodologies for the digital materials design (DMD) are presented to investigate the much larger design space opening for composite MIEC electrodes. Stochastic digital twins representing the 3D microstructure are constructed based on Gaussian random fields for real structures obtained from 3D-tomography. Based on stochastic parameters of digital twins, a large variation of virtual 3D microstructures is then realized using massive simultaneous cloud computing (MSCC) with GeoDict software. All relevant microstructure characteristics are determined by image analysis and/or transport simulation (e.g. the relative ionic composite conductivity and the specific pore-CGO interface area). The effect of the microstructure properties on the cell-performance is then determined with a suitable multiphysics model (see Marmet et al.1). This combination of DMDmethodologies (3D imaging and image analysis, stochastic modelling, numerical simulation) allows for a systematic and data driven optimization to provide robust design guidelines for MIEC-based anodes.