Machine Learning Molecular Dynamics Simulations on Diffusion of SF6 and N2 in SF6/N2 Mixtures

Sulfur hexafluoride (SF 6 ) is widely used for an insulating and arc extinguishing medium in high voltage electrical equipment due to its excellent dielectric properties and insulation performances.However, SF 6 is a potent greenhouse gas, leading to a significant influence on the environment by the large use of SF 6 .SF 6 mixed with inert gas such as N 2 is a more promising way to reduce the use of SF 6 .The diffusion properties of SF 6 /N 2 mixtures play a crucial role in the gaseous mixture separation or replenishment, determining the proportion and uniformity of the mixtures.Combining ab initio molecular dynamics (AIMD) and machinelearning molecular dynamics (MLMD) simulations of SF 6 and N 2 dynamics in SF 6 /N 2 mixtures, we systematically illustrate the anomalous characteristics of both SF 6 and N 2 motion.At short times, both SF 6 and N 2 performs super-diffusion through the ballistic motion.At intermediate times, a combination of the SF 6 molecular flexibility and cage effect result in the larger plateau value, while N 2 molecular showed no plateau stage.At longer times, both SF 6 and N 2 gradually turns to normal diffusion.A theoretical model is also offered to quantitatively describe this abnormal diffusion.This work gives a more completely physical understanding of SF 6 and N 2 dynamics in SF 6 /N 2 mixtures, which provides important references for SF 6 /N 2 mixed electrical equipment leakage supplement.