Files-Optimizing Multilayer Graphite-Silicon Anodes: A computational approach to enhancing lithium-Ion battery performance.

This dataset contains the results of a computational screening of multilayer anodes for lithium-ion batteries. The anode architecture consists of an outer graphite layer in direct contact with the electrolyte and an inner graphite–silicon composite layer, evaluated by finite-element simulations and multivariate statistical analysis. The study explores silicon contents of 10, 20, and 30 percent, layer thickness configurations of 30–30 µm, 20–40 µm, and 10–50 µm (outer–inner, total 60 µm), and graphite particle sizes of 2.5, 5, and 7.5 µm. Cells are configured with an NMC622 cathode and LiPF6 in 3:7 EC:EMC electrolyte. COMSOL Multiphysics simulations, organized with a JMP design of experiments, provide the response variables: capacity loss percentage, solid electrolyte interphase (SEI) thickness, potential drop across the SEI, and electrolyte consumption over 2,000 simulated cycles. The best region observed corresponds to the 30–30 µm configuration with 2.5 µm graphite and 20–30 percent silicon in the composite layer, which lowers potential drop, electrolyte consumption, and SEI growth relative to modeled single-layer 100 percent graphite and homogeneous silicon–graphite anodes. These results support dual-layer designs as a practical way to leverage silicon’s high specific capacity while preserving electrochemical stability and illustrate the value of simulation-driven optimization for forecasting long-life behavior.