As an insulating medium, sulfur hexafluoride (SF6) is extensively applied to electrical insulation equipment to ensure its normal operation. However, both partial discharge and overheating may cause SF6 to decompose, and then the insulation strength of electrical equipment will be reduced. The adsorption properties and sensing mechanisms of four SF6 decomposed components (HF, SO2, SOF2 and SO2F2) upon an Au-modified InN (Au-InN) monolayer were studied in this work based on first-principles theory. Meanwhile, the adsorption energy (Ead), charge transfer (QT), deformation charge density (DCD), density of states (DOS), frontier molecular orbital and recovery property were calculated. It can be observed that the structures of the SO2, SOF2 and SO2F2 molecules changed significantly after being adsorbed. Meanwhile, the Ead and QT of these three adsorption systems are relatively large, while that of the HF adsorption system is the opposite. These phenomena indicate that Au-InN monolayer has strong adsorption capacity for SO2, SOF2 and SO2F2, and the adsorption can be identified as chemisorption. In addition, through the analysis of frontier molecular orbital, it is found that the conductivity of Au-InN changed significantly after adsorbing SO2, SOF2 and SO2F2. Combined with the analysis of the recovery properties, since the recovery time of SO2 and SO2F2 removal from Au-InN monolayer is still very long at 418 K, Au-InN is more suitable as a scavenger for these two gases rather than as a gas sensor. Since the recovery time of the SOF2 adsorption system is short at 418 K, and the conductivity of the system before and after adsorption changes significantly, Au-InN is an ideal SOF2 gas-sensing material. These results show that Au-InN has broad application prospects as an SO2, SOF2 and SO2F2 scavenger and as a resistive SOF2 sensor, which is of extraordinary meaning to ensure the safe operation of power systems. Our calculations can offer a theoretical basis for further exploration of gas adsorbent and resistive sensors prepared by Au-InN.
Optimization of a Low-Power Chemoresistive Gas Sensor: Predictive Thermal Modelling and Mechanical Failure Analysis
