Multiscale simulation process and application to additives in porous composite battery electrodes

Abstract

Structure-resolving simulation of porous materials in electrochemical cells such as fuel cells and lithium ion batteries allows for correlating electrical performance with material morphology. In lithium ion batteries characteristic length scales of active material particles and additives range several orders of magnitude. Hence, providing a computational mesh resolving all length scales is not reasonably feasible and requires alternative approaches. In the work presented here a virtual process to simulate lithium ion batteries by bridging the scales is introduced. Representative lithium ion battery electrode coatings comprised of μm-scale graphite particles as active material and a nm-scale carbon/polymeric binder mixture as an additive are imaged with synchrotron radiation computed tomography (SR-CT) and sequential focused ion beam/scanning electron microscopy (FIB/SEM), respectively. Applying novel image processing methodologies for the FIB/SEM images, data sets are binarized to provide a computational grid for calculating the effective mass transport properties of the electrolyte phase in the nanoporous additive. Afterwards, the homogenized additive is virtually added to the micropores of the binarized SR-CT data set representing the active particle structure, and the resulting electrode structure is assembled to a virtual half-cell for electrochemical microheterogeneous simulation. Preliminary battery performance simulations indicate non-negligible impact of the consideration of the additive.