Targeting the Right Metrics for an Efficient Solvent-Free Formulation of PEO:LiTFSI:Li6PS5Cl Hybrid Solid Electrolyte

材料科学 电解质 溶剂 化学工程 锂(药物) 有机化学 电极 物理化学 工程类 内分泌学 医学 化学
作者
Ronan Chometon,Michaël Deschamps,Romain Dugas,Elisa Quemin,Benjamin Hennequart,Marc Deschamps,Jean‐Marie Tarascon,Christel Laberty‐Robert
出处
期刊:ACS Applied Materials & Interfaces [American Chemical Society]
卷期号:15 (50): 58794-58805 被引量:5
标识
DOI:10.1021/acsami.3c11542
摘要

Hybrid solid electrolytes (HSEs) aim to combine the superior ionic conductivity of inorganic fillers with the scalable process of polymer electrolytes in a unique material for solid-state batteries. Pursuing the goal of optimizing the key metrics (σion ≥ 10–4 S·cm–1 at 25 °C and self-standing property), we successfully developed an HSE based on a modified poly(ethylene oxide):LiTFSI organic matrix, which binds together a high loading (75 wt %) of Li6PS5Cl particles, following a solvent-free route. A rational study of available formulation parameters has enabled us to understand the role of each component in conductivity, mixing, and mechanical cohesion. Especially, the type of activation mechanism (Arrhenius or Vogel–Fulcher–Tammann (VFT)) and its associated energy are proposed as a new metric to unravel the ionic pathway inside the HSE. We showed that a polymer-in-ceramic approach is mandatory to obtain enhanced conduction through the HSE ceramic network, as well as superior mechanical properties, revealed by the tensile test. Probing the compatibility of phases, using electrochemical impedance spectroscopy (EIS) alongside 7Li nuclear magnetic resonance (NMR), reveals the formation of an interphase, the quantity and resistivity of which grow with time and temperature. Finally, electrochemical performances are evaluated by assembling an HSE-based battery, which displays comparable stability as pure ceramic ones but still suffers from higher polarization and thus lower capacity. Altogether, we hope these findings provide valuable knowledge to develop a successful HSE, by placing the optimization of the right metrics at the core of the formulation.
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