Silicon (Si)-based anodes, where Si serves as the active material, have garnered significant attention due to their potential to achieve high electric capacity in lithium-ion batteries (LIBs). A key challenge with Si-based anodes is their susceptibility to create in-plane cracks caused by stresses from the manufacturing process and cyclic charging, which ultimately shortens battery life and reduces the overall electrochemical capacity. To address this issue, a refined microstructural design of the active material layer is in pressing need to enhance both the performance and longevity of LIBs. We successfully applied the Oyane failure criterion, which models ductile failure under stress triaxiality, to simulate crack initiation and propagation in the binder matrix containing Si particles in the finite element modeling. Given the non-linear plastic deformation of the binder, this criterion was formulated based on cumulative strain increments. The computational results of microcrack formation within the active material layer under uniaxial tension were then validated by the experimental observations. Furthermore, we developed several models with varied particle arrangements, comparing each simulated crack path to actual microstructural images obtained via scanning electron microscopy. The findings confirm the accuracy of the model, underlying its promising application in optimizing the microstructure of Si-based anodes for enhanced LIB performance and durability.

As lithium-ion batteries (LIBs) become increasingly widespread, ensuring their safety has become a primary concern. Particularly, battery aging has been reported to significantly impact major battery safety behaviors, including the internal short circuit (ISC) and thermal runaway (TR). Over the past decade, despite considerable research into the thermal hazards of aged batteries, the complexity of battery aging and TR mechanisms, along with the challenges posed by extreme experimental conditions, necessitates a systematic understanding. Aiming to provide a comprehensive review of safety issues related to aged batteries, this paper begins by exploring the fundamental aging mechanisms and factors that accelerate aging. It then investigates how aging affects battery safety issues, including swelling and off-gassing behaviors. Furthermore, we discuss the impact of aging on TR problems induced by abusive conditions, covering safety issues from internal sources to external abusive scenarios. This review offers valuable insights into understanding and predicting the thermal hazards of aged LIBs, which provides guidelines for designing and manufacturing safer LIBs and accurate and rapid battery safety prognostics in the future.

The accurate representation of lithium plating and aging phenomena has posed a persistent challenge within the battery research community. Empirical evidence underscores the pivotal role of cell structure in influencing aging behaviors and lithium plating within lithium-ion batteries (LIBs). Available lithium-ion plating models often falter in detailed description when integrating the structural intricacies. To address this challenge, this study proposes an innovative hierarchical model that intricately incorporates the layered rolling structure in cells. Notably, our model demonstrates a remarkable capacity to predict the non-uniform distribution of current density and overpotential along the rolling direction of LIBs. Subsequently, we delve into an insightful exploration of the structural factors that influence lithium plating behavior, leveraging the foundation laid by our established model. Furthermore, we easily update the hierarchical model by considering aging factors. This aging model effectively anticipates capacity fatigue and lithium plating tendencies across individual layers of LIBs, all while maintaining computational efficiency. In light of our findings, this model yields novel perspectives on capacity fatigue dynamics and local lithium plating behaviors, offering a substantial advancement compared to existing models. This research paves the way for more efficient and tailored LIB design and operation, with broad implications for energy storage technologies.