High-throughput data-driven interface design of high-energy-density polymer nanocomposites

Abstract

Understanding the interface effect in dielectric nanocomposites is crucial to the enhancement of their performance. In this work, a data-driven interface design strategy based on high-throughput phase-field simulations is developed to study the interface effect and then optimize the permittivity and breakdown strength of nanocomposites. Here, we use two microscopic features that are closely related to the macroscopic dielectric properties, the thickness and permittivity of the interface phases, to evaluate the role of interfaces in experimental configuration, and thus provide quantitative design schemes for the interfacial phases. Taking the polyvinyl difluoride (PVDF)BaTiO3 nanocomposite as an example, the calculation results demonstrate that the interfacial polarization could account for up to 83.6% of the increase in the experimentally measured effective permittivity of the nanocomposite. Based on the interface optimized strategy, a maximum enhancement of ∼156% in the energy density could be achieved by introducing an interface phase with d/r = 0.55 and εinterface/εfiller=0.036, compared to the pristine nanocomposite. Overall, the present work not only provides fundamental understanding of the interface effect in dielectric nanocomposites, but also establishes a powerful data-driven interface design framework for such materials that could also be easily generalized and applied to study interface issues in other functional nanocomposites, such as solid electrolytes and thermoelectrics.

Keywords

• Interface
• Polymer nanocomposites
• Energy storage
• Data-driven
• Phase-field simulation