Ultrahigh Energy Storage of Twisted Structures in Supramolecular Polymers

Abstract

Polymer dielectrics possess outstanding advantages for high power energy storage applications such as high breakdown strength (Eb) and efficiency (η), while both of them decrease rapidly at elevated temperature (>150 °C). Although several strategies including nanocomposites and crosslinking have been evaluated to enhance Eb and heat resistance, the discharged energy density (Ud) of polymer dielectrics is still limited by the planar conjugated structure. In this study, we introduce a novel approach to manipulate polymer morphology through supramolecular interactions, thereby influencing dielectric properties. We have predicted a range of polyurea (PU)-based polymers from different structural unit combinations and synthesized two representative polymers with high dielectric constants (K) and thermal stability. These polymers are combined with PI to form a twisted supramolecular polymer via hydrogen bonding network interactions (HNP). Both experimental results and computational simulations demonstrate that the twisted structure, induced by hydrogen bonds, disrupts the conjugated structure to widen the bandgap and increased dipole moment through the twisting of polar groups, leading to simultaneous improvements in both K and Eb. Consequently, HNP achieves an unprecedented Ud of 6.42 J/cm3 with an efficiency exceeding 90% at 200 °C. This work opens a new avenue to scalable high Ud all-polymer dielectric for high-temperature applications and also promotes the understanding of dielectric behavior on complex three-dimensional structures.

Keywords: dielectrics, machine learning, twisted supramolecular polymers, energy storage, high temperature