Adsorption of CO, H₂S and CH₄ molecules on SnS₂ monolayer: a first-principles study

ABSTRACT

The adsorption of CO, H₂S and CH₄ on the intrinsic SnS₂ monolayer and SnS₂ monolayer with S-vacancy were studied by the first principle method. The most stable adsorption geometry was determined, and the electronic structure and differential charge were calculated. The results show that the band gap value of SnS₂ monolayer with S-vacancy decreases and the surface activity increases. Compared with the intrinsic SnS₂ monolayer, from the adsorption energy, electron transfer and adsorption distance of CO, H₂S and CH₄ on SnS₂ monolayer with S-vacancy, it can be seen that the S vacancy system is more sensitive to these gases. The results show that the SnS₂ monolayer with S-vacancy is more sensitive to three gases, which provides a new design idea for SnS₂ based gas sensor.

As seen from the graphical abstract, the gas molecules (CO, H₂S, CH₄) on SnS₂ monolayer with S vacancy has stronger adsorption energy than the intrinsic SnS₂ surface, and the adsorption properties of H₂S gas molecule on SnS₂ monolayer with S-vacancy surface has the strongest adsorption energy −0.77 eV. It indicate that SnS₂ monolayer with S-vacancy can be used as a promising gas detection material.

Statement of article significance: First-principles studies were performed to investigate the electronic structures and adsorptive property of SnS₂ monolayer and SnS₂ monolayer with S-Vacancy with adsorbents CH₄, CO and H₂S molecules. The adsorption order of the three gases on the intrinsic surface is H₂S > CH₄ > CO. The adsorption order of the three gases on SnS₂ monolayer with S-vacancy is H₂S > CO > CH₄. In addition, the results indicate that the adsorption energy of H₂S on SnS₂ monolayer with S-vacancy is strong. The work provides a new design idea for SnS₂ based gas sensor.

GRAPHICAL ABSTRACT

KEYWORDS:

• SnS₂
• vacancy
• first principle
• adsorption
• gas sensor

Acknowledgments

This work was supported by the Key Projects of NSFC-Henan Joint Fund (U1704255), the National Natural Science Foundation of China (Grant Nos. 21603109), the Henan Joint Fund of the National Natural Science Foundation of China (grant number U1404216), Natural Science Foundation of Liaoning and Doctor Start-up Fund of Liaoning under Grant (20170520155), the Fundamental Research Funds for the Universities of Henan Province (200303). Computational resources have been provided by the Henan Polytechnic University high-performance grid computing platform.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the Key Projects of NSFC-Henan Joint Fund (U1704255), the National Natural Science Foundation of China (grant number 11804081), Natural Science Foundation of Henan Province (11804081), Key Research Project for the Universities of Henan Province (19A140009, 19B430003, 20A430016), the Doctoral Foundation of Henan Polytechnic University (B2018-38).