In this paper, the Ir-modified MoS₂ monolayer is suggested as a novel gas sensor alternative for detecting the characteristic decomposition products of SF₆, including H₂S, SO₂, and SOF₂. The corresponding adsorption properties and sensing behaviors were systematically studied using the density functional theory (DFT) method. The theoretical calculation indicates that Ir modification can enhance the surface activity and improve the conductivity of the intrinsic MoS₂. The physical structure formation, the density of states (DOS), deformation charge density (DCD), molecular orbital theory analysis, and work function (WF) were used to reveal the gas adsorption and sensing mechanism. These analyses demonstrated that the Ir-modified MoS₂ monolayer used as sensing material displays high sensitivity to the target gases, especially for H₂S gas. The gas sensitivity order and the recovery time of the sensing material to decomposition products were reasonably predicted. This contribution indicates the theoretical possibility of developing Ir-modified MoS₂ as a gas sensor to detect characteristic decomposition gases of SF₆.

Hexagonal-Boron nitride nanotubes (h-BN) decorated with transition metals have been widely studied due to their enhanced physicochemical properties. In this paper, Pt cluster-modified h-BN is proposed as a sensitive material for a novel gas sensor for the online malfunction monitoring of oil-immersed transformers. The inner oil is ultimately decomposed to various gases during the long-term use of oil-immersed transformers. Exposure to excessively high temperatures produces the alkanes CH₄ and C₂H₆, whereas different degrees of discharge generate H₂ and C₂H₂. Therefore, the identification of H₂, CH_4, and C₂H₂ gas efficiently measures the quality of transformers. Based on the density functional theory, the most stable h-BN doped with 1–4 Pt atoms is employed to simulate its adsorption performance and response behavior to these typical gases. The adsorption energy, charge transfer, total density of states, projected density of states, and orbital theory of these adsorption systems are analyzed and the results show high consistency. The adsorption ability for these decomposition components are ordered as follows: C₂H₂ > H₂ > CH₄. Pt cluster-modified h-BN shows good sensitivity to C₂H₂, H₂, with decreasing conductivity in each system, but is insensitive to CH₄ due to its weak physical sorption. The conductivity change of Pt_n-h-BN is considerably larger upon H₂ than that upon C₂H₂, but is negligible upon CH₄. Our calculations suggest that Pt cluster modified h-BN can be employed in transformers to estimate their operation status.

Moisture is detrimental to the performance of epoxy resin material for electrical equipment in long-term operation and insulation. Therefore, moisture absorption is one of the critical indicators for insulation of the material. However, some relevant test methods, e.g., the direct weighing method, are time-consuming, and it usually takes months to complete a test. For this, it is necessary to have some modification to save the test time. Firstly, the study analyzes the present prediction method (according to ISO 62:2008). Under the same accuracy, the time required is reduced from 104 days to 71 days. Subsequently, the Langmuir curve-fitting method for water absorption of epoxy resin is analyzed, and the initial values of diffusion coefficient, bonding coefficient, and de-bonding coefficient are determined based on the results of molecular simulation, relevant experiment, and literature review. With the optimized prediction model, it takes only 1.5 days (reduced by 98% as compared with the standard prediction method) to determine the moisture absorbability. Then, the factors influencing the prediction accuracy are discussed. The results have shown that the fluctuation of balance at the initial stage will affect the test precision significantly. Accordingly, this study proposes a quantitative characterization method for initial trace moisture based on the terahertz method, by which the trace moisture in epoxy resin is represented precisely through the established terahertz time-domain spectroscopy system. When this method is used to predict the moisture absorbability, the experimental time may be further shortened by 33% to 1 day. For the whole water absorption cycle curve, the error is less than 5%.