Nature Communications (Aug 2024)

Revealing and reconstructing the 3D Li-ion transportation network for superionic poly(ethylene) oxide conductor

  • Cheng-Dong Fang,
  • Ying Huang,
  • Yi-Fan Sun,
  • Peng-Fei Sun,
  • Ke Li,
  • Shu-Yang Yao,
  • Min-Yi Zhang,
  • Wei-Hui Fang,
  • Jia-Jia Chen

DOI
https://doi.org/10.1038/s41467-024-51191-2
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 11

Abstract

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Abstract Understanding the Li-ions conduction network and transport dynamics in polymer electrolyte is crucial for developing reliable all-solid-state batteries. In this work, advanced nano- X-ray computed tomography combined with Raman spectroscopy and solid state nuclear magnetic resonance are used to multi-scale qualitatively and quantitatively reveal ion conduction network of poly(ethylene) oxide (PEO)-based electrolyte (from atomic, nano to macroscopic level). With the clear mapping of the microstructural heterogeneities of the polymer segments, aluminium-oxo molecular clusters (AlOC) are used to reconstruct a high-efficient conducting network with high available Li-ions (76.7%) and continuous amorphous domains via the strong supramolecular interactions. Such superionic PEO conductor (PEO-LiTFSI-AlOC) exhibites a molten-like Li-ion conduction behaviour among the whole temperature range and delivers an ionic conductivity of 1.87 × 10−4 S cm−1 at 35 °Ϲ. This further endows Li electrochemical plating/stripping stability under 50 μA cm−2 and 50 μAh cm−2 over 2000 h. The as-built Li|PEO-LiTFSI-AlOC|LiFePO4 full batteries show a high rate performance and a capacity retention more than 90% over 200 cycling at 250 μA cm−2, even enabling a high-loading LiFePO4 cathode of 16.8 mg cm−2 with a specific capacity of 150 mAh g−1 at 50 °Ϲ.