Decoupling Ionic Conductivity from Structural Rigidity Constraints of Solid Polymer Electrolytes through Microphase Separation Regulation
Source abstract
Abstract
Solid polymer electrolytes (SPEs) are pivotal for solid-state batteries due to their high safety, structural versatility, and processability. However, the inherent trade-off between ionic conductivity and mechanical strength, arising from insufficient segmental relaxation and excessive chain flexibility, remains a fundamental challenge. To overcome this limitation, we engineered a bicontinuous microphase separated poly(ether-urethane) electrolyte by leveraging the equilibrium between thermodynamic driving forces and intermolecular interactions to decouple segmental relaxation from chain rigidity. Bicontinuous microphase structure facilitates rapid ion transport (1.1 × 10 –3 S·cm –1 ) through continuous amorphous soft domains, while the hard segments ensure mechanical integrity (789% elongation at break, 13 MPa tensile strength). Consequently, the Li||Li symmetric cell demonstrates stable plating/stripping for 2,500 h and the Li||LiNi 0.8 Co 0.1 Mn 0.1 O 2 (NCM811) full cell retains 81% capacity over 300 cycles at 0.5 C. Our work establishes explicit microphase structure-electrochemical property correlations, providing a scalable design paradigm to break the conductivity-rigidity compromise in SPEs.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Advanced Battery Materials and Technologies · Fuel Cells and Related Materials · Thermal Expansion and Ionic Conductivity
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
State Key Laboratory of Molecular Engineering of Polymers, Department of Macromolecular Science, Institute of Fiber Materials and Devices, Collaborative Innovation Center of Chemistry for Energy Materials
Fudan University
The Dow Chemical Company, 936 Zhangheng Road, Shanghai 201203, China
Funding
Shanghai Municipal Commission of Economy and Infomatization, AI for Science Program
References (32)
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