While specialty applications of nanotechnology in the photonics and electronics areas have seen a tremendous growth in the past several years, the use of nanodielectrics in the electrical industry (high power density and high voltage) has not shown the same level of activity. In addition to a review of nanodielectrics, we discuss in this paper, our perspective on the current status, development needs and future potential to build or engineer nanostructured materials for dielectric applications in the electrical power industry. Short and long-term future research and development needs are considered from the point of view of industrial applications.

The dielectric constant (ϵ) is a critical parameter utilized in the design of polymeric dielectrics for energy storage capacitors, microelectronic devices, and high-voltage insulations. However, agile discovery of polymer dielectrics with desirable ϵ remains a challenge, especially for high-energy, high-temperature applications. To aid accelerated polymer dielectrics discovery, we have developed a machine-learning (ML)-based model to instantly and accurately predict the frequency-dependent ϵ of polymers with the frequency range spanning 15 orders of magnitude. Our model is trained using a dataset of 1210 experimentally measured ϵ values at different frequencies, an advanced polymer fingerprinting scheme and the Gaussian process regression algorithm. The developed ML model is utilized to predict the ϵ of synthesizable 11,000 candidate polymers across the frequency range 60–10¹⁵ Hz, with the correct inverse ϵ vs. frequency trend recovered throughout. Furthermore, using ϵ and another previously studied key design property (glass transition temperature, T_g) as screening criteria, we propose five representative polymers with desired ϵ and T_g for capacitors and microelectronic applications. This work demonstrates the use of surrogate ML models to successfully and rapidly discover polymers satisfying single or multiple property requirements for specific applications.

Flexible polymers that can withstand temperature and electric field extremes are critical to advanced electrical and electronic systems. High thermal stability of polymers is generally achieved through the introduction of highly conjugated aromatic structures, that lower the bandgap and thus diminish the electric field endurance. Here, we demonstrate a class of flexible all-organic polyolefins by a strategic modular structure design to eliminate the impact of conjugation on bandgap. The one such designed polymer exhibits superior operational temperature and T_g of 244 °C without compromising the bandgap (∼5 eV), exhibiting significantly suppressed electrical conductivity when subjected to a high electric field. It reveals the highest ever recorded energy density of 6.5 J cc⁻¹ at 200 °C, a 2× improvement over the best reported flexible dielectric polymers or polymer composites. The uncovered polymer design strategy introduces a platform for high performance dielectric development for extreme thermal and electric field conditions.