Trifluoromethanesulfonyl fluoride (CF3SO2F) is a promising alternative to SF6, a potent greenhouse gas prevalent in electrical grids, but understanding its decomposition pathways and products is crucial for evaluating its environmental feasibility. Here, the authors investigate its thermal decomposition using machine learning-driven molecular dynamics, revealing temperature- and gas pressure-dependent bond-breaking pathways and determining and experimentally validating its decomposition products.
- Anyang Wang
- Zeyuan Li
- Jun Wang
