Quantum mechanical and machine learning models are used to analyze the properties of silicon composite materials and their impact on anode performance. The analysis focuses on addressing challenges related to significant volume expansion during lithiation and provides valuable insights into the Gibbs free energy, chemical potentials, and relative stability of Li0 and Li+ species. Furthermore, the study explores how Li+ ions behave in the primary and secondary phases of the anode, assessing the impact of their formation on ion diffusion. This work highlights the fundamental significance of secondary phases in shaping microstructural features that impact anode properties, elucidating their contribution to the Li diffusion pathway tortuosity, which is the primary cause of the fracture of Si anodes in Li-ion batteries.