Improving composite battery electrodes requires a delicate control of active materials and electrode formulation. The electrochemically active particles fulfill their role as energy exchange reservoirs through interacting with the surrounding… Click to show full abstract
Improving composite battery electrodes requires a delicate control of active materials and electrode formulation. The electrochemically active particles fulfill their role as energy exchange reservoirs through interacting with the surrounding conductive network. We formulate a network evolution model to interpret the regulation and equilibration between electrochemical activity and mechanical damage of these particles. Through statistical analysis of thousands of particles using x-ray phase contrast holotomography in a LiNi0.8Mn0.1Co0.1O2-based cathode, we found that the local network heterogeneity results in asynchronous activities in the early cycles, and subsequently the particle assemblies move toward a synchronous behavior. Our study pinpoints the chemomechanical behavior of individual particles and enables better designs of the conductive network to optimize the utility of all the particles during operation. Description Observations of cathode evolution The loss of capacity in a rechargeable battery can be due to changes in the electrode structure that occur with cycling. Li et al. used hard x-ray holotomography to visualize the structure of a nickel-rich LiNi0.8Mn0.1Co0.1O2 composite cathode (see the Perspective by Xiao). They were able to track the behavior of thousands of individual particles with time and thus determine the relationship between structure and performance as well as the deterioration of the cathode at a size scale that is not generally accessible. They found that damage during cycling is driven not only by each particle but also by its surrounding neighbors, although the contributions shift over time. This work suggests ways to better design electrodes to maximize their performance. —MSL Active particles in composite electrodes initially show asynchronous activity that evolves toward synchronous behavior.
               
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