A Computational Framework to Efficiently Screen Antioxidants for Cross‐Linked Polyethylene Insulation

ABSTRACT Antioxidants (AOs) not only play a decisive role in processing and service reliability of cross‐linked polyethylene for power cables, but also exhibit a significant impact on their insulation performance. However, the selection of highly efficient and reliable AOs remains a huge challenge due to the low efficiency and inherent limitations of traditional experimental methods. Herein, a computational framework was proposed by integrating multidimensional descriptors (e.g., electrostatic potential, activation barrier, solubility parameter, and so on) through quantum mechanics and molecular dynamics. It is worth noting that the framework was demonstrated to provide a systematic and quantitative strategy for screening AOs, and offer microscopic insight into underlying mechanisms. Based on this framework, AO300 was identified as a highly efficient and reliable AO, in view of its strong radical‐scavenging capability, auxiliary antioxidation pathways, and minimal dielectric impact. Moreover, the screening strategy is universal, and could be expanded to other insulation materials. This work paves the way for the screening of highly efficient and reliable AOs for advanced insulation materials.