期刊
SENSORS AND ACTUATORS A-PHYSICAL
卷 360, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.sna.2023.114548
关键词
DFT calculation; Sc -doping; MoTe 2 monolayer; Adsorption and sensing performances; SF6 decomposition gases; SO2; H2S; SOF2
This study investigates the adsorption performance of MoTe2 and Sc-doped MoTe2 on four gases (SO2, H2S, SO2F2, SOF2) from SF6 decomposition based on Density Functional Theory (DFT). The results show that Sc-MoTe2 has superior adsorption performance for these gases compared to intrinsic MoTe2, providing insights into the sensing mechanism of gases in MoTe2 and laying the foundation for developing a MoTe2-based sensor for detecting SF6 decomposition gases.
SF6 is widely used in insulation and arc extinguishing due to its excellent insulation performance. The detection of its decomposed gases can help us to effectively identify the types of internal malfunctions in gas-insulated switchgear (GIS). Based on the Density functional theory (DFT), the adsorption performance of intrinsic MoTe2 and Sc-doped MoTe2 (Sc-MoTe2) on four gases (SO2, H2S, SO2F2, SOF2) from SF6 decomposition were studied in this paper. The calculation results indicate that the intrinsic MoTe2 monolayers have weak adsorption capacity and low adsorption energy (Ead) for SF6 decomposition gas products, which are all physical adsorption and with small transfer charge. However, the adsorption ability of MoTe2 monolayer film to SF6 decomposition gas products is significantly enhanced after doping the Sc atom. The adsorption energy is changed into chemical adsorption, and the amount of transferred charge in the adsorption process is significantly increased. Therefore, the adsorption performance of Sc-MoTe2 for four gas products (SO2, H2S, SO2F2, SOF2) from SF6 decomposition are obviously superior to intrinsic MoTe2. The results are helpful to further explain the sensing mechanism of gases in MoTe2, and establish a foundation for the sensor based on MoTe2 to detect SF6 decomposition gases.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据