Sodium-ion technology is a reliable alternative to lithium-ion for large-scale energy storage because of the abundance of sodium sources and related low cost. In this work, we report about a simple fabrication of self-standing electrodes based on electrospun carbon nanofiber (CNF) loaded with Na 3 V 2 (PO 4 ) 3 with NASICON framework, which is a promising cathode material that has shown good electrochemical performance when its electrical conductivity is enhanced by a conductive medium. The proposed method is simple, low cost, potentially scalable to fabricate and load cathode support with active materials. The electrochemical tests confirmed the stable cycling performances and the high C-rate capability of the NVP/ CNFs composites, with hundreds of cycles without major degradation of performances. Our work demonstrates that stable, self-supported, long-term performing NIB electrodes, ready to use without addition of any performance enhancer, can be obtained by using fast and cost-efficient procedures suitable to be scaled-up at an industrial level.

The coupling of thick and dense cathodes with anode‐free lithium metal configuration is a promising path to enable the next generation of high energy density solid‐state batteries. In this work, LiCoO2 (30 µm)/LiPON/Ti is considered as a model system to study the correlation between fundamental electrode properties and cell electrochemical performance, and a physical model is proposed to understand the governing phenomena. The first cycle loss is demonstrated to be constant and independent of both cathode thickness and anode configuration, and only ascribed to the diffusion coefficient's abrupt fall at high lithium contents. Subsequent cycles achieve close to 100% coulombic efficiency. The examination of the effect of cathode thickness demonstrate a nearly linear correlation with areal specific capacity for sub‐100 µm LiCoO2 and 0.1 mA cm−2 current density. These findings bring new insights to better understand the energy density limiting factors and to suggest potential optimization approaches.