  The increased energy and power density required in modern electronics poses a
challenge for designing new dielectric polymer materials with high energy
density while maintaining low loss at high applied electric fields. Recently,
an advanced computational screening method coupled with hierarchical modelling
has accelerated the identification of promising high energy density materials.
It is well known that the dielectric response of polymeric materials is largely
influenced by their phases and local heterogeneous structures as well as
operational temperature. Such inputs are crucial to accelerate the design and
discovery of potential polymer candidates. However, an efficient computational
framework to probe temperature dependence of the dielectric properties of
polymers, while incorporating effects controlled by their morphology is still
lacking. In this paper, we propose a scalable computational framework based on
reactive molecular dynamics with a valence-state aware polarizable charge
model, which is capable of handling practically relevant polymer morphologies
and simultaneously provide near-quantum accuracy in estimating dielectric
properties of various polymer systems. We demonstrate the predictive power of
our framework on high energy density polymer systems recently identified
through rational experimental-theoretical co-design. Our scalable and automated
framework may be used for high-throughput theoretical screenings of
combinatorial large design space to identify next-generation high energy
density polymer materials.
