Computational Chemistry‐Driven Advances in Eco‐Friendly Insulation Gas Research: Multi‐Dimensional Prediction, Synergistic Screening, Stability Evaluation and Molecular Design

Sulphur hexafluoride has become a priority substance for greenhouse gas mitigation in electric systems. An ideal substitute should simultaneously satisfy requirements for dielectric strength, boiling point, global warming potential and chemical stability; however, these metrics are deeply coupled and mutually constraining at the molecular level. Computational chemistry, encompassing quantum‐chemical calculations and molecular dynamics simulations, is transforming this field from empirical trial and error into a computationally guided design paradigm. This review organises the theoretical methods and key advances of multi‐tiered performance prediction, synergistic screening, stability evaluation and molecular design. Multi‐level prediction frameworks for core performance are converging into integrated synergistic computation, while screening combined with Pareto multi‐objective optimisation has enabled a multi‐dimensional global optimisation. Stability assessments have elucidated the mechanisms of self‐decomposition and interfacial reactions. Molecular design has progressed from functional‐group hybridisation and H/F substitution at the single‐molecule level to synergistic component optimisation in gas mixtures. Computational chemistry has demonstrated the capacity to accelerate full‐chain engineering translation, compressing the cycle from molecular discovery to prototype validation. Looking forward, the progressive integration of artificial intelligence technologies is poised to propel this field towards a new paradigm defined by the synergy of computational prediction and intelligent empowerment.