Extended from the electrochemo-mechanical single particle model, an electrochemo-mechanical impedance model for porous electrode in LIB, which considers the effect of the contact stress, is proposed in this work. A modified coefficient ζ which links the mechanical properties of the electrode and particle material is introduced to describe the effect of contact stress. First, we find that the contact stress can weaken the stress-induced semicircle in the low-frequency range through analyzing the Faradaic part of the impedance. Second, considering the contact stress is determined by the mechanical bonding between electrode layer and the current collector, we introduce a pseudo-elastic boundary condition to analyze the bonding effect. For rigid substrate, namely the in-plane deformation is totally restricted, the effect of the contact stress is strong. For free substrate, namely the in-plane deformation is not restricted, the contact stress is not induced thus its effect on impedance disappears. Finally, we discuss the interaction effect of stress and the ionic transport in the electrolyte and find that the interaction is strong for silicon-based material, which indicates the stress effect needs to be considered when interpreting the impedance data in this case.
Lithium plating on the negative electrode of Li-ion batteries remainsa great concern for durability, reliability, and safety in operation under low temperatures and fast charging conditions. High-accuracy detection of Li-plating is critically needed for field operations. To detect the lithium plating is to track its multiphysics footprint since Li plating often is a localized event while the driving force from chemical, electrical, thermal, and mechanical origins could vary with time and locality which makes the detection and characterization challenging. Here, we summarize the multiphysical footprints of lithium plating and the corresponding state-of-the-art detection methods. By assessing and comparing these methods, the combination of capacity/voltage differential, R-Q mapping and Arrhenius outlier tracking could be promising and effective for battery diagnosis, prognosis, and management. We analyze the origins of quantitative error in sample preparation, overly simplified assumption, and dynamic evolution of the plated Li, and recommend the in-situ and quantitative chemical analysis methods, such as in-situ nuclear magnetron resonance, electron paramagnetic resonance, X-ray, and neutron. In addition, we propose four conjectures on the capacity plunge, Li plating, pore clogging, electrolyte drainage, and rapid SEI growth, can be aligned and unified to one scenario basically triggered by Li plating.
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