  Nanostructured Si is the most promising high-capacity anode material to
substantially increase the energy density of Li-ion batteries. Among the
remaining challenges is its low rate capability as compared to conventional
materials. To understand better what controls the diffusion of Li in the
amorphous Li-Si alloy, we use a novel machine-learning potential trained on
more than 40,000 ab-initio calculations and nanosecond-scale molecular dynamics
simulations, to visualize for the first time the delithiation of entire LiSi
nanoparticles. Our results show that the Si host is not static but undergoes a
dynamic rearrangement from isolated atoms, to chains, and clusters, with the Li
diffusion strongly governed by this Si rearrangement. We find that the Li
diffusivity is highest when Si segregates into clusters, so that Li diffusion
proceeds via hopping between the Si clusters. The average size of Si clusters
and the concentration range over which Si clustering occurs can thus function
as design criteria for the development of rate-improved anodes based on
modified Si.
