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As a novel class of porous crystalline solids, covalent organic frameworks (COFs) based electrolyte can combine the advantages of both inorganic and polymer electrolytes, leading to such as higher structural stability to inhibit lithium dendrites and better processing facility for improving interfacial contact. However, the ionic components of Li salt tend to be closely associated in the form of ion pairs or even ionic aggregates in the channel of COFs due to strong coulombic interactions, thus resulting in slow ionic diffusion dynamics and low ionic conductivity. Herein, we successfully designed and synthesized a novel single-ion conducting nitrogen hybrid conjugated skeleton (NCS) as all solid electrolyte, whose backbone is consisted with triazine and piperazine rings. A loose bonding between the triazine rings and cations would lower the energy barrier during ions transfer, and electrostatic forces with piperazine rings could “anchor” anions to increase the selectivity during ions transfer. Thus, the NCS-electrolyte exhibits excellent room temperature lithium-ion conductivity up to 1.49 mS·cm−1 and high transference number of 0.84 without employing any solvent, which to the best of our knowledge is one of the highest COF-based electrolytes so far. Moreover, the fabricated all-solid-state lithium metal batteries demonstrate highly attractive properties with quite stable cycling performance over 100 cycles with 82% capacity reservation at 0.5 C.

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Publication history
Copyright
Acknowledgements

Publication history

Received: 30 April 2022
Revised: 06 July 2022
Accepted: 18 July 2022
Published: 14 September 2022
Issue date: January 2023

Copyright

© Tsinghua University Press 2022

Acknowledgements

Acknowledgements

We thank the financial support from the Natural Science Foundation of Shandong (Nos. ZR2020JQ21 and ZR2021ZD24), National Natural Science Foundation of China (Nos. 51873231 and 22138013), Taishan Scholar Project (No. tsqn201909062), and the Technology Foundation of Shandong Energy Group Co., LTD. (YKZB2020-176, YKKJ2019AJ08JG-R63). This work was partially carried out at the City University of Hong Kong for MD simulations. We greatly thank Pro. Jian LU give us assistance on NMR data unscrambling and analyzing.

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