Li-excess cathode materials are expected to have great potential for applications in lithium-ion batteries owing to their high energy density. In addition to the extensive studies on the anionic redox activity in lithium-ion batteries, their Li-ion diffusion properties have also attracted much interest. Using ab initio calculations, herein, we systematically explored Li diffusion properties in both stoichiometric and Li-excess phases of spinel lithium manganese oxide (LMO). Our results showed that there is a type of structural unit (six Mn ions forming a cation ring for Li-ions to pass through during migration) that acts as “gate sites” and the Li-excess configuration could introduce two types of fast Li-ion migration channels to enhance the Li-ion diffusivity. The first type of fast channels resulted from the decreased repulsive coulombic interactions between the cations at the gate site and the mobile Li-ions due to the substitution of Mn³⁺ by Li⁺. The second type of fast channels originated because the excess Li could induce more gate sites with symmetrical distribution of Mn⁴⁺ surrounding the Li diffusion channel, which is proved to be able to enhance the Li-ion mobility. Interestingly, it was also found that in slow Li diffusion channels for both stoichiometric and Li-excess LMO, a simultaneous polaron hopping process around the gate sites would be coupled with the Li migration process, which accounts for the high energy barriers for Li-ion diffusion.

Li is an ideal anode material for use in state‐of‐the‐art secondary batteries. However, Li‐dendrite growth is a safety concern and results in low coulombic efficiency, which significantly restricts the commercial application of Li secondary batteries. Unfortunately, the Li‐deposition (growth) mechanism is poorly understood on the atomic scale. Here, machine learning is used to construct a Li potential model with quantum‐mechanical computational accuracy. Molecular dynamics simulations in this study with this model reveal two self‐healing mechanisms in a large Li‐metal system, viz. surface self‐healing, and bulk self‐healing. It is concluded that self‐healing occurs rapidly in nanoscale; thus, minimizing the voids between the Li grains using several comprehensive methods can effectively facilitate the formation of dendrite‐free Li.