Introducing deep traps by grafting functional groups on molecular chains of polymeric dielectric materials has been proved as an effective way to improve their electrical properties, especially suppressing the space charge injection and accumulation. However, the underlying physical mechanism of the origins and effects of deep traps on the electrical properties of polymeric dielectrics has not been fully understood. In order to explore the origins and effects of deep traps in grafted polymers, both simulations of electronic band structures as well as 3D electric potential distributions at molecular level and experiments on the macroscopic trap level distributions are carried out. The simulation and experiment results reveal that the deep traps in grafted polymers originate from the different electronic band structures of the grafted polymer compared with the pristine polymer. The deep traps would capture charge carriers and inhibit the charge transport, which leads to decreased conduction current and suppressed space charge injection and accumulation. This work provides a deep understanding of the origins of deep traps in grafted polymers and their effects on the electrical properties, which may guide the rational design of high-performance polymeric dielectric and insulation materials.

Polypropylene is considered to be the material of choice for environmentally friendly high voltage direct current cable insulation. The high power transmission of electrical energy exposes insulating materials to high temperatures and electric fields, resulting in the degradation of material properties. This paper reports that organic molecular semiconductors with strong electron affinity can effectively modulate electrical properties of polypropylene. The charge injection and transport process are analyzed by considering a combination of relations describing various conduction models in dielectrics, including the Richardson–Schottky (RS) emission and the hopping conduction. Based on the performed experiments, a modified Wiesmann–Zeller (WZ) model is proposed to simulate the electrical treeing process of polypropylene. The electrical treeing results are well verified with the simulation results, which offer a valuable tool for further analysis of the effect of intrinsic barrier height, hopping distance, and activation energy on the electrical degradation in the material. This work provides an insightful analysis of multiple charge transport mechanisms affecting the electrical degradation of the polymer, which is crucially essential for the rational design of high-performance insulation materials.

Dielectric polymers for electrostatic energy storage are used in modern electronic and electrical systems, and their performance can be significantly enhanced through doping with ultralow content nanofillers to improve energy storage performance. Understanding the underlying physical mechanisms of polymer nanocomposites is essential for designing high-performance dielectric polymers. This paper presents a conduction model that integrates Richardson–Schottky emission and hopping conduction to describe charge injection and transport in polymer composites. Phase-field simulations, incorporating electrical, thermal, and mechanical breakdown mechanisms, investigate the influence of nanofiller volume fraction, size, and dielectric constant on the dielectric response and breakdown behaviors under high temperature and electric fields. We propose the Physics-Informed Neural Networks for phase-field simulation that integrates the physical rules of charge transport, phase evolution, and boundary conditions. By embedding phase field models within the Physics-Informed Neural Networks' structure, this method demonstrates the ability to predict the breakdown strength and energy density of polymer nanocomposites. This work provides crucial guidelines for designing high-performance dielectric energy storage capacitors under extreme conditions.

High-temperature capacitive energy storage demands dielectric polymers that integrate high thermal conductivity with excellent electrical insulation to mitigate thermal runaway induced by Joule heating. However, conventional strategies for improving thermal conductivity through increased aromatic conjugation frequently exacerbate conductive losses under elevated temperatures and high electric fields. To resolve this fundamental trade-off between thermal conductivity and electrical insulation, we introduce a conjugation-decoupling strategy. This approach incorporates aliphatic segments to disrupt the π–π conjugation networks, implemented through a machine learning-assisted co-design workflow. A transfer learning model is built to establish the structure–property relationship between glass transition temperature and thermal conductivity, and subsequently guides the synthesis of three semi-aromatic polyimides that concurrently achieve a high glass transition temperature, a wide bandgap, and high thermal conductivity. The resulting semi-alicyclic polyimide film demonstrated outstanding discharge energy density (5.26 J cm−3) and η = 90% performance at 200 °C, significantly outperforming commercial Kapton polyimide film. We report a strategy for high-temperature dielectric development using an interpretable machine learning model, demonstrating a concurrent enhancement of electrical insulation and thermal conductivity, properties typically constrained by a conventional trade-off.

Cavity electromagnonic system, which simultaneously consists of cavities for photons, magnons (quanta of spin waves), and acoustic phonons, provides an exciting platform to achieve coherent energy transduction among different physical systems down to single quantum level. Here we report a dynamical phase-field model that allows simulating the coupled dynamics of the electromagnetic waves, magnetization, and strain in 3D multiphase systems. As examples of application, we computationally demonstrate the excitation of hybrid magnon-photon modes (magnon polaritons), Floquet-induced magnonic Aulter-Townes splitting, dynamical energy exchange (Rabi oscillation) and relative phase control (Ramsey interference) between the two magnon polariton modes. The simulation results are consistent with analytical calculations based on Floquet Hamiltonian theory. Simulations are also performed to design a cavity electro-magno-mechanical system that enables the triple phonon-magnon-photon resonance, where the resonant excitation of a chiral, fundamental (n = 1) transverse acoustic phonon mode by magnon polaritons is demonstrated. With the capability to predict coupling strength, dissipation rates, and temporal evolution of photon/magnon/phonon mode profiles using fundamental materials parameters as the inputs, the present dynamical phase-field model represents a valuable computational tool to guide the fabrication of the cavity electromagnonic system and the design of operating conditions for applications in quantum sensing, transduction, and communication.