Predictors for gases of high electrical strength

We present an efficient method of predicting the electric strength (ES) of insulating gases in comparison to sulfur hexafluoride. Different molecular properties (descriptors) of a comprehensive set of 67 predominantly electronegative or electron attaching molecules were calculated ab-initio by means of density functional theory (DFT). For the same list of molecules, we compiled a data set of experimental values for the ES and descriptors. We analyzed the data by statistical methods and observed strong correlations between the ES and certain predictors, which are simple functions of selected DFT-calculated descriptors. In addition, we applied the same statistical method to the boiling point of the gas, and we observed strong correlations as well. We demonstrate our method by predicting the ES for a few unreported molecules.