Abstract The growing demand for high-energy-density lithium-ion batteries in portable electronics, electric vehicles, and grid storage has accelerated the introduction of silicon-graphite blended electrodes in commercially available lithium-ion cells. Despite their commercial adoption and higher energy density, the widespread deployment of silicon-graphite (Si-Gr) composites is hindered by rapid degradation phenomena which limit both their calendar and cycle life. In this work, a novel diagnostic framework that enables the quantification and separation of silicon and graphite active material losses in blended electrodes is presented, based on differential voltage and incremental capacity analysis. Expanding upon the established methods for graphite electrodes, a novel silicon-specific IC diagnostic marker is proposed for the detection of silicon active material loss. The proposed method was validated using synthetic datasets generated from the ‘alawa mechanistic modelling toolbox, simulating a broad range of degradation mode combinations and cell architectures. The results of this work underscore the potential of diagnostic decoupling in composite anode electrodes using derivative analysis and lay the groundwork for scalable health-monitoring strategies in next-generation high-energy lithium-ion batteries.
Darikas et al. (Mon,) studied this question.