Search

Unraveling the reaction paths and structural evolutions during charging/discharging processes are critical for the development and tailoring of silicon anodes for high‐capacity batteries. However, a mechanistic understanding is still lacking due to the complex phase transformations between crystalline (c‐) and amorphous (a‐) phases involved in electrochemical cycles. In this study, by employing a newly developed machine learning potential, the key experimental phenomena not only reproduce, including voltage curves and structural evolution pathways, but also provide atomic scale mechanisms associated with these phenomena. The voltage plateaus of both the c‐Si and a‐Si lithiation processes are predicted with the plateau value difference close to experimental measurements, revealing the two‐phase reaction mechanism and reaction path differences. The observed voltage hysteresis between lithiation and delithiation mainly originates from the transformation between the c‐Li15‐δSi4 and a‐Li15‐δSi4 phases. Furthermore, stress accumulation is simulated along different reaction paths, indicating a better cycling stability of the a‐Si anode due to the lower stress concentration. Overall, the study provides a theoretical understanding of the thermodynamics of the complex structural evolutions in Si anodes during (de)lithiation processes, which may play a role in optimizations for battery performances. [ABSTRACT FROM AUTHOR]