Frank McLarnon’s contribution in developing advanced optical and spectroscopic techniques over the past few decades have led to a deep understanding of how electrochemical processes occur. As we become more proficient in visualizing processes that occur in batteries in situ, we are challenged with offering hypotheses that explain the observables and help link the microscopic and spectroscopic information to the electrochemical performance. Continuum-scale mathematical models provide an ideal means of providing this link and is a useful way to test hypothesis.

In this talk, we will examine the role of continuum models in testing hypothesis and predicting performance, working with concert with experimental observations. We will use a few examples systems to establish the role of models. We will examine the growth of lithium dendrites and link the experimentally observed growth morphology to mechanical and electrochemical processes to help determine ways to stop dendrites. We will also examine the role of the experimentally determined 3D microstructure of porous battery cathodes in determine the performance limitations in cells. These examples will serve to highlight the critical role modeling plays in enhancing our understanding.

The figure below shows an example of such an approach where in situ x-ray tomography information (top panel) of dendrite growth provides critical information on the morphology change of the dendrite during deposition in polymer electrolytes. Using a continuum-scale model, we have shown that the change in shape of the dendrite is closely linked to the increasing compressive stress at the peak of the dendrite that retards deposition (bottom panel). Such a model can then be used to provide guidance on how materials can be tuned to prevent dendrite growth. More details of this work can be found at J. of Electrochem. Soc., 163 (10) A2216 (2016).