First-principles analysis of Ti3C2Tx MXene as a promising candidate for SF6 decomposition characteristic components sensor
First-principles analysis of Ti3C2Tx MXene as a promising candidate for SF6 decomposition characteristic components sensor
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Ti3C2TX MXene 作为 SF6 分解特征成分传感器有希望的候选者的第一性原理分析
DOI:
10.1016/j.apsusc.2021.152020
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发表时间:
2021-11
影响因子:
6.7
通讯作者:
Ju Tang
中科院分区:
文献类型:
--
作者:
Fuping Zeng;Xiaoxuan Feng;Xiaoyue Chen;Qiang Yao;Yulong Miao;Liangjun Dai;Yi Li;Ju Tang
SF6decomposition characteristic components detection is currently one of the effective technical means for SF6gas insulation equipment condition monitoring, and sensors are the key to achieving this goal. In this paper, two-dimensional MXene is used as a sensing material, combined with DFT method to study the adsorption behaviour of Ti3C2Txwith different termination groups (O, F, OH) on the main decomposition characteristic components of SF6such as H2S, SO2, SOF2and SO2F2.The most stable structure, α-model Ti3C2Txwas obtained and various gas adsorption structures were constructed and geometrically optimized. The most stable adsorption structures of different Ti3C2Txsurfaces were obtained by comparing the adsorption energy. The electron density, band structure and density of states of the adsorption system were further analyzed. The results show that target gases adsorb spontaneously on Ti3C2O2and Ti3C2(OH)2, while on Ti3C2F2external energy is required to form stable adsorption structures. Charge transfer induced by gas adsorption gradually decreases at the order of Ti3C2(OH)2, Ti3C2O2and Ti3C2F2. Hydroxyl groups terminated Ti3C2TxMXene performed better sensing ability over oxygen and fluorine terminated ones. And 2D Ti3C2(OH)2is a promising candidate for SF6decomposition characteristic components sensor, surpassing graphene and transition metal dichalcogenides.
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DOI:
10.3390/s16111830
发表时间:
2016-11-01
期刊:
Sensors (Basel, Switzerland)
影响因子:
--
作者:
Zhang X;Huang R;Gui Y;Zeng H
通讯作者:
Zeng H
影响因子:
3.3
作者:
Mardirossian, Narbe;Head-Gordon, Martin
通讯作者:
Head-Gordon, Martin
影响因子:
16.6
作者:
Cepellotti, Andrea;Fugallo, Giorgia;Marzari, Nicola
通讯作者:
Marzari, Nicola
影响因子:
2.8
作者:
Enyashin, A. N.;Ivanovskii, A. L.
通讯作者:
Ivanovskii, A. L.
影响因子:
4.9
作者:
Cui, Heping;Zheng, Kai;Chen, Xianping
通讯作者:
Chen, Xianping