Pourasl, A. H. and Ariffin, S. H. and Ahmadi, M. and Gharaei, Niayesh and Rashid, R. and Ismail, R. (2019) Quantum capacitance model for graphene FET-based gas sensor. IEEE Sensors Journal, 19 (10). pp. 3726-3732. ISSN 1530-437X
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Official URL: http://dx.doi.org/10.1109/JSEN.2019.2896882
Abstract
Because of its extraordinary characteristics, this material has attracted researchers in various arenas. Among the numerous fields where this material can be applied is the gas sensor technology. The graphene experiences remarkable changes in its electrical and physical characteristics when exposed to different gases; and they are, therefore, the ideal candidates for gas sensing application. However, a deep understanding of the effects of gas molecules on the graphene energy band structure and its electronic properties, need to be further studied. In this paper, a new quantum capacitance model for the gas sensor employing the graphene field effect transistor platform is proposed. Hence, a general approach using the Tight-binding approximation based on the nearest neighbor incorporating Schrödinger equation is developed. Therefore, the adsorption effects of the CO, NO, and NH3 gases on the energy band structure, quantum capacitance, and I-V characteristics of the graphene FET are analytically modeled and investigated. The results indicated that, the gas adsorption can cause significant changes on the graphene band structure and quantum capacitance. The I-V characteristics evaluation indicated current decrement after gas adsorption because of the conductance decrement induced by the band gap increment. The proposed models for the capacitance were also compared with the published experimental data and a satisfactory agreement was achieved.
Item Type: | Article |
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Uncontrolled Keywords: | electrical properties, Quantum capacitance |
Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
Divisions: | Electrical Engineering |
ID Code: | 87628 |
Deposited By: | Widya Wahid |
Deposited On: | 30 Nov 2020 09:06 |
Last Modified: | 30 Nov 2020 09:06 |
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