(3) For the delithiaton of c-Li15Si4, XRD characterization revealed that the c-Li15Si4 phase was converted into a-Li2.0Si. Moreover, Car-Parrinello molecular dynamics (CPMD) calculation suggested that a-Li2.0Si has lower amorphization energy than a-Li3Si, and a-Li2.0Si as an important phase during electrochemical reaction. However, Grey et al. proposed that the a-Si phase was directly formed by aggregation and growth of Si atoms when removing Li atoms, without any intermediate a-LixSi phases. Ogata et al. Molecular dynamics (MD) simulation is the main theoretical tool for studying the detailed lithiation/delithiation processes of Si anode. However, the ability of MD simulations has traditionally been limited by the dilemma of accuracy and efficiency. Thanks to the development in the area of artificial intelligence, machine learning potentials have made it possible to perform MD with ab initio accuracy for system sizes much larger than what was possible using traditional ab initio MD. This opens up a lot of new opportunities for efficiently simulating complex transition processes . In the present work, we use deep potential (DP) MD simulation to study the lithiation/delithiation processes of Si anode, evaluate reaction paths, characterize the microstructure evolution, and estimate the charging/discharging voltage curves. Our results reproduce the voltage plateau difference between c-Si and a-Si and the voltage hysteresis that have been observed in experiments. At the same time, they provide the atomic scale details of the two-phase process at the initial stage of the lithiation, and the difference of reaction paths between lithiation and delithiation. Thus, our results provide deep insights into the mechanism of lithiation/delithiation processes and the evolution of the electrochemical properties for the Si anode, which should be helpful for the further optimization of Si-anode materials.