Abstract
A large amount of power equipment works in closed or semi-closed environments for a long time. Carbon monoxide (CO) is the most prevalent discharge gas following a fault in the components. Based on the density functional theory of first principles, the adsorption behavior of CO gas molecules on intrinsic, Ag-doped and Au-doped hafnium disulfide (HfS2) monolayers was systematically studied at the atomic scale. Firstly, the intrinsic HfS2 monolayer, Ag-doped HfS2 (Ag-HfS2) monolayer and Au-doped HfS2 (Au-HfS2) monolayer, with different doping sites, were created. The structural stability, dopant charge transfer, substrate conductivity and energy band structure of different doping sites of the Ag-HfS2 and Au-HfS2 monolayer structures were calculated. The most stable doping structure was selected with which to obtain the best performance on the subsequent gas adsorption test. Then, the CO adsorption models of intrinsic HfS2, Ag-HfS2 and Au-HfS2 were constructed and geometrically optimized. The results show that the adsorption energy of the Ag-HfS2 monolayer for CO gas is −0.815 eV, which has good detection sensitivity and adsorption performance. The adsorption energy of CO on the Au-HfS2 monolayer is 2.142 eV, the adsorption cannot react spontaneously, and the detection sensitivity is low. The research content of this paper provides a theoretical basis for the design and research of gas sensing materials based on HfS2, promoting the development and application of HfS2 in gas sensing and other fields.
Highlights
In recent years, as people pay more attention to air pollution and public health, the requirements for high sensitivity and online detection in the field of gas sensor research have become more and more demanding [1,2]
The optimized structure of the intrinsic HfS2 monolayer is shown in Figure 2(a1,a2), where (a1)
The stability of Ag-doped HfS2 (Ag-HfS2) after doping modification is discussed, and it is concluded that Ag-Hf is the most stable doping site
Summary
As people pay more attention to air pollution and public health, the requirements for high sensitivity and online detection in the field of gas sensor research have become more and more demanding [1,2]. Liu et al designed three different defect models to simulate the common discharge fault types of power equipment [1]
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