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Abstract:
The rise in global carbon dioxide levels necessitates efficient, low-pollution energy technologies. Solid Oxide Fuel Cells (SOFCs) are promising energy converters, and their electrical performance is strongly influenced by the electrode microstructure. This study presents a comprehensive multiscale, experimentally grounded optimization pipeline for SOFC electrodes to maximize the electrical power density, integrating microscale and macroscale approaches. The methodology combines tomography-based microstructure characterization, computational homogenization, multiphysics simulations, model order reduction, and machine-learning-based surrogate modeling. Anode samples with fine, medium, and coarse grain sizes are analyzed using high-dimensional morphological descriptors to characterize microstructure morphology. Partial least squares discriminant analysis reduces the descriptor space to enable efficient surrogate modeling and generation of artificial microstructures by interpolation in the reduced space. Effective conductivities and permeability are computed by first-order homogenization and incorporated into a macroscopic fuel cell model to predict the power density. The proposed framework links microstructural information to macroscopic electrical performance within a nested optimization loop, enabling systematic exploration of physically realistic microstructural variants. Using a Ni-YSZ anode as a case study, the approach identifies the most suitable microstructure characteristics within an experimentally limited design space and provides a flexible optimization framework that can be adapted to different databases, models, and objective functions.

Keywords:
Optimization pipeline, Solid oxide fuel cells, Electrode microstructure, Multiscale modeling, Multiphysics modeling, Surrogate modeling

Abstract:
This study presents a comprehensive 3D and time-dependent simulation of a planar solid oxide fuel cell (SOFC), focusing on the intricate interplay between microstructural characteristics and multiphysics phenomena. The simulation framework integrates detailed microstructural models with advanced multiphysics simulations to capture the coupled effects of electrochemical reactions as well as mass transport and heat transfer within the 3D representative volume elements (RVE) of SOFC porous electrodes generated, and their effective properties are estimated. The energy conversion performances of a SOFC unit are predicted using finite element analysis to solve the governing equations for the coupled phenomena over time. This approach enables us to elucidate the impact of microstructural features such as pore size distribution, tortuosity, and phase connectivity on the overall cell performance. The results demonstrate critical insights into the transient behaviour of the SOFC under various operating conditions, highlighting the importance of microstructural optimisation for enhancing efficiency. This work bridges the gap between microstructural analysis and macroscopic performance prediction, providing valuable guidelines for the design and development of high-performance SOFCs