Researchers Jie Yang and Wei Tan, affiliated with the University of Michigan, have developed a comprehensive computational model to study the fracture behavior of silicon particles used in lithium-ion batteries. Their work, published in the Journal of Power Sources, aims to understand and mitigate the degradation of silicon-based anodes, which are promising for next-generation energy storage technologies.
The study focuses on the lithiation and delithiation processes in silicon particles, which involve the insertion and extraction of lithium ions during battery charging and discharging cycles. These processes can induce significant stresses and strains in the silicon particles, leading to cracking and fracturing. To tackle this, Yang and Tan developed a multiphysics model that couples mass transport, deformation, phase field, and fatigue damage. This model allows for a detailed investigation of the factors influencing the failure behavior of silicon particles.
The researchers systematically analyzed the effects of particle diameter, charge rate, and pre-existing notches on the failure behavior of silicon particles. They found that increasing the charge rate, particle diameter, or the length of pre-existing notches leads to higher cracking rates and faster fracturing of the particles. Based on these findings, they developed a validated contour map of silicon particle fracture behaviors, which can serve as a practical tool for predicting and understanding failure mechanisms in silicon-based anodes.
Furthermore, the study examined the influence of pre-existing notch length and charge rate on fatigue damage. The results indicated that longer pre-existing notches and higher charge rates can shorten the cyclic life of the particles. To address this issue, the researchers introduced nanopores into the silicon particles and investigated their impact on fracture behaviors. They discovered that nanopores can reduce expansion, dissipate global tensile stresses, and elongate the crack propagation path, thereby alleviating particle fracture.
The developed computational framework establishes a predictive relationship between stress diffusion coupling theory and particle-level degradation. This work provides valuable insights for the design and manufacturing of failure-resistant silicon-based anodes, which are crucial for improving the performance and longevity of lithium-ion batteries. The practical applications of this research extend to the energy sector, particularly in the development of advanced energy storage technologies for electric vehicles and grid storage systems.
Source: Yang, J., & Tan, W. (2023). Fully Coupled Multiphysics Modelling of Fracture Behaviour in Silicon Particles During Lithiation Delithiation Using the Phase Field Method. Journal of Power Sources.
This article is based on research available at arXiv.