The rapidly growing demands on energy storage technologies over the last decade have imposed further requirements for the high energy/power density, safety, and durability of lithium-ion batteries (LIBs). Si/C composite materials have attracted enormous research interest as the most promising candidates for the anodes of next-generation lithium-ion batteries, owing to their high energy density and mechanical buffering property. However, the major disadvantage of materials with ultra-high capacities, such as Si-based materials, is the significant volume change during cycling, which further leads to mechanical and electrochemical degradation. A comprehensive computational model is indispensable in the developing process of the excellent performance of anode material due to the low realizability, inconvenience, and high cost of experiments, which also provides powerful tools for fabrication guidance of novel Si/C composites designs. Further, the fundamental mechanism of Li diffusion and complex failure behaviors in various Si/C composite materials remains unclear, with our understanding limited by experimental techniques and continuum modeling methodologies. Thus, DFT simulation is firstly used to investigate the Li diffusion behavior in Si/C composite materials, which indicates the underlying mechanism and provides a quantitative description of the diffusivity. A multiphysics modeling framework is then established. The relationship between mechanical failure and electrochemical performance in Si/C core-shell particles is revealed using this model. Further, based on this multiphysics model, the contact behavior of two Si/C core-shell particles is studied, and five representative nanostructures are compared, providing design guidance on Si/C core-shell and related structures. Finally, the model is extended into a multi-scale one, which can describe the multiphysics behavior both at the particle level and cell level. This study explores the multiphysics behavior of Si/C anodes material from the atomic level to cell level using DFT modeling and FEA methodology, systematically revealing the coupling mechanism among various physical fields, as well as providing efficient and powerful tools in the design, development, and evaluation of high energy density lithium-ion batteries.
