High-temperature polymer composite capacitors with high energy density designed via machine learning

Polymer dielectrics are the primary energy storage media in electrostatic capacitors, which are essential components in power electronics for electric vehicles and renewable energy systems. Composite approach has been intensively explored to enhance the energy density (U_d) and breakdown strength (E_b) of polymers at high temperatures, but finding fillers with both a large bandgap (E_g) and high electronic affinity (E_a) remains challenging. Here, assisted by a generative machine learning approach, we discover and synthesize organic fillers of both a large E_g (~5.5 eV) and high E_a (~4.5 eV). These fillers enable polyimide composite films to deliver a U_d of 5.1 J cm⁻³ at discharge efficiency of 90% and 2 × 10⁵ charge–discharge cycles at 250 °C. Moreover, we fabricate high-quality, kilometre-scale composite films using roll-to-roll processing and demonstrate that industrial capacitors incorporating these metalized composite films exhibit stable discharge and self healing in harsh environments.