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Dynamic bonds transform ion transport mechanisms in polymeric covalent adaptable networks

  • Amirkabir University of Technology
  • Department of Chemistry and Materials Innovation Factory
  • University of Liverpool

Research output: Contribution to journalArticlepeer-review

3   Link opens in a new tab Citations (SciVal)

Abstract

This study unravels the mechanisms by which dynamic covalent bonds facilitate ion transport in poly(ethylene oxide)-based covalent adaptable networks (CANs), designed for solid polymer electrolytes. Our findings reveal how CANs differ fundamentally from traditional static PEO networks in their ion conductivity behavior. Through molecular dynamics simulations, we show that dynamic bonding creates temporary “corridors” for lithium-ion movement via reversible bond breaking and reformation, without altering the network topology. Unlike static networks, which rely on structural loosening for ion diffusion, dynamic bonding uniquely enhances ion transport by inducing local bond rearrangements that create transient structural fluctuations, increasing ion mobility up to 2.8-fold in dense networks. Importantly, these transient structural changes do not alter the overall pore distribution in the network. Instead, the dynamic reactions transform blocked pathways – previously dead-ends – into reversible gates that open and close, effectively regulating ion transport. This mechanism provides a pathway to improve ion conductivity while preserving mechanical integrity.

Original languageEnglish
JournalMaterials Horizons
Early online date13 Aug 2025
DOIs
Publication statusE-pub ahead of print - 13 Aug 2025

Data Availability Statement

The data supporting this article have been included as part of the SI.

Atomistic simulation details, coarse-grain mapping, polymerization modelling details, residence time calculation, mean-squared displacement (MSD) analysis, exchange bond reaction kinetics, diffusion coefficient and conductivity calculations for TFSI. See DOI: https://doi.org/10.1039/d5mh00433k

Acknowledgements

The authors acknowledge Seyyed Mohammad Mousavifard for implementing dynamic reactions in PolySMart and developing the reverse mapping algorithm.

Funding

Farhad Sharif and Mohammad Rezayani have been financially supported by Iran National Science Foundation (INSF) grant no. 4030458. This work made use of the facilities of the N8 Centre of Excellence in Computationally Intensive Research (N8 CIR) provided and funded by the N8 research partnership and EPSRC (Grant No. EP/T022167/1). The Centre is coordinated by the Universities of Durham, Manchester, and York.

FundersFunder number
Engineering and Physical Sciences Research CouncilEP/T022167/1

ASJC Scopus subject areas

  • General Materials Science
  • Mechanics of Materials
  • Process Chemistry and Technology
  • Electrical and Electronic Engineering

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