Prediction of Volumetric, Specific Energy and Power Density of High-Capacity Thin Layer Battery Electrodes By Using a Novel Multi-Scale Modelling Framework

In this work, a novel modelling approach is presented, which is able to directly relate the microstructure of the active layer of thin-film batteries to the battery cell macroscopic behaviour. A general pore-scale model has been developed by mimicking the layer fabrication process. Five different electrode structures were reconstructed taking into account the interaction between the deposited particles during the layer formation. In each simulation 10⁸particles were deposited with 5 different sticking rules. Fig.1. captures the beginning of the layer formation. Fig.1a) shows weak interaction between the particles, i.e. the layer is mainly governed by random deposition, and b) strong attractive forces, i.e. every particle sticks to the nearest neighbour. The different colours correspond to the deposition of 1000 particles, while white spaces correspond to open pores.

Instead of simulating each type of reconstructed layer, the renormalization group theory is applied to analyse the effect of thickness on the properties of the active layer. It is shown, that in spite of the very different morphology, all these reconstructed layers belong to the same universality class and can be described by a general non-linear scaling law. The simulation results imply that porosity and specific surface area depend on the thickness of the electrode, which is not commonly considered in battery models. The general expression derived is incorporated into a macrohomogeneous model and the charge-discharge performance is simulated. The volumetric and specific energy and power densities are calculated and finally, the simulation results are compared with measured data at different thicknesses.

The developed method offers an efficient tool not only to predict, but to design high power and high capacity batteries for automotive applications and/or scale down dimensions for microelectronics and MEMS. It can be used for fast screening of novel manufacturing technologies as well as for deeper understanding of the effect of microscale structure on the macroscopic behaviour of battery cells.