Theoretical analysis of Ni atom-doped MXene for improving the catalytic degradation performance of SF6

Long Wang, Xiangyu Wang, Yiming Yan,Hao Qiu,Xinnuo Guo,Ju Tang,Fuping Zeng

Computational and Theoretical Chemistry(2023)

引用 0|浏览5
暂无评分
摘要
The strong greenhouse effect of SF6 will directly affect the whole habitat. Finding a suitable catalyst for the efficient degradation of SF6 is one of the main means to reduce SF6 emissions. In this paper, two-dimensional MXene doped with Ni atoms was used as catalytic material, and Density Functional Theory (DFT) was combined to investigate the influence properties of different terminal modifications of Ti3C2Tx (T = F, OH, O) on the catalytic degradation of SF6. The adsorption and decomposition processes of SF6 gas molecules on the surface of Ni-doped Ni-MXene material were calculated, and the adsorption energy transferred electron number and density of states (DOS) of the adsorption system were analyzed. The results show that: the adsorption energy of SF6 gas molecules on the surface of Ni-MXene is -6 eV and the number of transferred electrons is more than 0.5 e, in which the adsorption energy under the F-terminal group increases by 1 eV and the number of transferred electrons increases by 0.5 e compared with the undoped case, and the catalytic effect is improved; the molecular structure of SF6 changes significantly during the adsorption process, and the S-F bond was elongated to 2 angstrom and the S-F bond length away from the material was elongated by 0.2 angstrom, which made the SF6 molecule easier to be decomposed; according to the results of DOS calculations, the F atoms in the SF6 molecule had obvious electronic orbital interactions with both the Ni atoms on the surface of the Ni-MXene material and the MXene material itself, indicating that both showed the catalytic activity for SF6 during the adsorption process. The conclusions of this paper have some theoretical guidance for the efficient catalytic degradation of SF6.
更多
查看译文
关键词
MXene,Catalytic degradation,DFT,Ni,SF6
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要