Analytical Modeling of Electrical Characteristics of Low Bandgap Graphene Nanoribbon FET
Md. Shofiqul Islam1, Tanvir Muntasir2, Shuvomoy Das Gupta3
1Md. Shofiqul Islam, Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia.
2Tanvir Muntasir, Department of Electrical and Computer Engineering, Iowa State University, Ames, Iowa, USA.
3Shuvomoy Das Gupta, Department of Electrical and Computer Engineering, University of Toronto, Ontario, Canada.
Manuscript received on September 04, 2015. | Revised Manuscript received on September 10, 2015. | Manuscript published on September 30, 2015. | PP: 23-28 | Volume-2 Issue-10, September 2015. | Retrieval Number: J03380921015
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In this paper analytical modeling for the electrical characteristics of low bandgap graphene nanoribbon field effect transistor (GNR-FET) has been presented. This analytical modeling is based on the two-dimensional Poisson’s equation in the weak nonlocality approximation. At first, analytical formula for spatial distribution of electric potential along the channel of low bandgap GNR-FET has been derived. Then using the channel potential, an expression of drain current of low bandgap GNR-FET is developed. The potential distribution and current are expressed in terms of device parameters and applied voltages. Spatial potential has been investigated with different levels of gate voltage, gate length and drain voltage. Similarly, the current has been investigated with different applied voltages. It shows that drain current is controlled by applied voltages hence the device might be applicable in digital and analog circuits. This work of analytical modeling would be helpful for analyzing the device and optimizing the parameters to improve its performance.
Keywords: Analytical modeling, graphene nanoribbon, GNR-FET, spatial potential, low bandgap.