Probing and Interpreting the Porosity and Tortuosity Evolution of Li-O2 Cathodes on Discharge through a Combined Experimental and Theoretical Approach.

Li-O2 batteries offer a high theoretical discharge capacity due to the formation of light discharged species such as Li2O2, which fill the porous positive electrode. However, in practice, it is challenging to reach the theoretical capacity and completely utilize the full electrode pore volume during discharge. With the formation of discharge products, the porous medium evolves, and the porosity and tortuosity factor of the positive electrode are altered through shrinkage and clogging of pores. A pore shrinks as solid discharge products accumulate, the pore clogging when it is filled (or when access is blocked). In this study, we investigate the structural evolution of the positive electrode through a combination of experimental and computational techniques. Pulsed field gradient nuclear magnetic resonance results show that the electrode tortuosity factor changes much faster than suggested by the Bruggeman relation (an equation that empirically links the tortuosity factor to the porosity) and that the electrolyte solvent affects the tortuosity factor evolution. The latter is ascribed to the different abilities of solvents to dissolve reaction intermediates, which leads to different discharge product particle sizes: on discharging using 0.5 M LiTFSI in dimethoxyethane, the tortuosity factor increases much faster than for discharging in 0.5 M LiTFSI in tetraglyme. The correlation between a discharge product size and tortuosity factor is studied using a pore network model, which shows that larger discharge products generate more pore clogging. The Knudsen diffusion effect, where collisions of diffusing molecules with pore walls reduce the effective diffusion coefficients, is investigated using a kinetic Monte Carlo model and is found to have an insignificant impact on the effective diffusion coefficient for molecules in pores with diameters above 5 nm, i.e., most of the pores present in the materials investigated here. As a consequence, pore clogging is thought to be the main origin of tortuosity factor evolution.

Local Distortions and Dynamics in Hydrated Y-Doped BaZrO3.

Y-doped BaZrO3 is a promising proton conductor for intermediate temperature solid oxide fuel cells. In this work, a combination of static DFT calculations and DFT based molecular dynamics (DFT-MD) was used to study proton conduction in this material. Geometry optimizations of 100 structures with a 12.5% dopant concentration allowed us to identify a clear correlation between the bending of the metal-oxygen-metal angle and the energies of the simulated cells. Depending on the type of bending, two configurations, designated as inward bending and outward bending, were defined. The results demonstrate that a larger bending decreases the energy and that the lowest energies are observed for structures combining inward bending with protons being close to the dopant atoms. These lowest energy structures are the ones with the strongest hydrogen bonds. DFT-MD simulations in cells with different yttrium distributions provide complementary microscopic information on proton diffusion as they capture the dynamic distortions of the lattice caused by thermal motion. A careful analysis of the proton jumps between different environments confirmed that the inward and outward bending states are relevant for the understanding of proton diffusion. Indeed, intra-octahedral jumps were shown to only occur starting from an outward configuration while the inward configuration seems to favor rotations around the oxygen. On average, in the DFT-MD simulations, the hydrogen bond lengths are shorter for the outward configuration which facilitates the intra-octahedral jumps. Diffusion coefficients and activation energies were also determined and compared to previous theoretical and experimental data, showing a good agreement with previous data measuring local proton motion.

Stochasticity of Pores Interconnectivity in Li-O2 Batteries and its Impact on the Variations in Electrochemical Performance.

While large dispersions in electrochemical performance have been reported for lithium oxygen batteries in the literature, they have not been investigated in any depth. The variability in the results is often assumed to arise from differences in cell design, electrode structure, handling and cell preparation at different times. An accurate theoretical framework turns out to be needed to get a better insight into the mechanisms underneath and to interpret experimental results. Here, we develop and use a pore network model to simulate the electrochemical performance of three-dimensionally resolved lithium-oxygen cathode mesostructures obtained from TXM nanocomputed tomography. We apply this model to the 3D reconstructed object of a Super P carbon electrode and calculate discharge curves, using identical conditions, for four different zones in the electrode and their reversed configurations. The resulting galvanostatic discharge curves show some dispersion, (both in terms of capacity and overpotential) which we attribute to the way pores are connected with each other. Based on these results, we propose that the stochastic nature of pores interconnectivity and the microscopic arrangement of pores can lead, at least partially, to the variations in electrochemical results observed experimentally.

Impact of Li2O2 Particle Size on Li-O2 Battery Charge Process: Insights from a Multiscale Modeling Perspective.

We report a comprehensive multiscale model describing charge processes of Li-O2 batteries. On the basis of a continuum approach, the present model combines mathematical descriptions of mass transport of soluble species (O2, Li+, LiO2) and elementary reaction kinetics, which are assumed to be dependent on the morphology of the Li2O2 formed during discharge. The simulated charge curves are in agreement with previously reported experimental studies. The model along with the assumed reaction mechanisms provides physical explanations for the two-step charge profiles. Furthermore, it suggests that these charge profiles depend on the size of the Li2O2 particles, which are determined by the applied current density during discharge. Therefore, the model underlines the strong link between discharge and charge processes.