Developing Computational Tools for Modeling Fracture of Electrode Particles Used in Lithium-Ion Batteries (RPA Pilot/ Seed Project)

Layered lithium transition-metal oxide materials are the most promising candidates for lithium ion battery (LIB) positive electrodes. In particular, lithium nickel manganese cobalt oxide (NMC) has received considerable attention due to its greater specific capacity compared to conventional lithium cobalt oxide. However, severe structural degradation in the form of microcracking of the constituent particles during the manufacturing process and the thousands of charge-discharge cycles can greatly affect the electrochemical performance of the NMC positive electrode, hence the life of the battery. Computational models have been developed and applied to study the cracking behavior of NMC cathode at both particle and battery cell levels. However, the current computational models in the literature assume solid particle or solid cell, which does not apply to NMC particles which have an agglomerate structure. To fully understand the microcracking behavior of NMC particles, it is critical to develop an agglomerate level computational model which can take into account the particle level microstructural effects. The goal of this project is to develop predictive computational tools to model the cracking of NMC particles in LIB applications. The proposed research will result in an experimentally validated and computationally efficient model for making accurate predictions about the fracture of NMC particles. The specific objectives of this project include the development of (1) an effective approach for particles system generation, and (2) a validated computational model for particle fracture modeling under mechanical loading. The computational model to be developed in this research will be beneficial to the development of the next-generation high capacity LIBs.