Electrostatic capacitors play a crucial role as energy storage devices in modern electrical systems. Energy density, the figure of merit for electrostatic capacitors, is primarily determined by the choice of dielectric material. Most industry-grade polymer dielectrics are flexible polyolefins or rigid aromatics, possessing high energy density or high thermal stability, but not both. Here, we employ artificial intelligence (AI), established polymer chemistry, and molecular engineering to discover a suite of dielectrics in the polynorbornene and polyimide families. Many of the discovered dielectrics exhibit high thermal stability and high energy density over a broad temperature range. One such dielectric displays an energy density of 8.3 J cc⁻¹ at 200 °C, a value 11 × that of any commercially available polymer dielectric at this temperature. We also evaluate pathways to further enhance the polynorbornene and polyimide families, enabling these capacitors to perform well in demanding applications (e.g., aerospace) while being environmentally sustainable. These findings expand the potential applications of electrostatic capacitors within the 85–200 °C temperature range, at which there is presently no good commercial solution. More broadly, this research demonstrates the impact of AI on chemical structure generation and property prediction, highlighting the potential for materials design advancement beyond electrostatic capacitors.

静电电容器作为现代电气系统中的储能装置发挥着至关重要的作用。能量密度（静电电容器的品质因数）主要取决于介电材料的选择。大多数工业级聚合物电介质是柔性聚烯烃或刚性芳香族化合物，具有高能量密度或高热稳定性，但不是两者兼而有之。在这里，我们利用人工智能 (AI)、成熟的聚合物化学和分子工程来发现聚降冰片烯和聚酰亚胺家族中的一套电介质。许多已发现的电介质在较宽的温度范围内表现出高热稳定性和高能量密度。一种这样的电介质在200℃下显示出8.3J cc ^-1的能量密度，该值是该温度下任何市售聚合物电介质的能量密度的11倍。我们还评估了进一步增强聚降冰片烯和聚酰亚胺系列的途径，使这些电容器能够在要求苛刻的应用（例如航空航天）中表现良好，同时具有环境可持续性。这些发现扩大了静电电容器在 85-200 °C 温度范围内的潜在应用，目前在该温度范围内还没有良好的商业解决方案。更广泛地说，这项研究展示了人工智能对化学结构生成和性能预测的影响，凸显了静电电容器之外的材料设计进步的潜力。