Importance of Incorporating Explicit 3D-Resolved Electrode Mesostructures in Li–O₂ Battery Models

Lithium–oxygen batteries are attractive for reversible energy storage because of their theoretically high capacities. Practically, high capacities are challenging to achieve due to key issues such as the transport and growth of the Li2O2 discharge product. Numerous carbon-based cathode mesostructures have been studied experimentally and computationally aiming to reach higher capacities. One-dimensional continuum models are widely used to study the discharge capacities of electrode mesostructures. Here, we investigate the capabilities and shortcomings of such models to represent different electrode mesostructures, Li2O2 growth mechanisms, and their impact on the discharge performance by comparing them to pore network models, which consider an explicit representation of the three-dimensional pore mesostructure. The continuum model can accurately predict discharge capacities when the discharge products grow through surface mechanism, but it fails to provide reasonable results when this growth includes a solution mechanism. Conversely, the pore network model results are in agreement with experiments. We attribute the better accuracy of the pore network model to a more accurate representation of the electrode mesostructures, particularly the explicit consideration of the pore interconnectivity. The pore network model allows us to reconcile, within a single theoretical framework, the scattered correlations between discharge capacity and electrode mesostructure descriptors reported in the literature.