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Characterization and modeling of dual material double gate tunnel field effect transistor using superposition approximation method
Author(s) -
Maria Jossy A.,
Vigneswaran T.,
Malarvizhi S.,
Nagarajan K. K.
Publication year - 2018
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4860
Subject(s) - tunnel field effect transistor , superposition principle , transistor , subthreshold conduction , quantum tunnelling , field effect transistor , voltage , subthreshold slope , poisson's equation , materials science , physics , optoelectronics , quantum mechanics
Summary Tunnel field effect transistors are used for ultra‐low power application since it is challenging to operate CMOS at very low supply voltage. As tunnel field effect transistor has a very low subthreshold slope due to band to band tunneling (BTBT) mechanism, it has the potential to operate at very low operating voltage. It is necessary that the devices utilized in implantable bio‐medical applications and Internet of Everything (IoE) need to consume very low power. This work presents an analysis of Dual Material Double Gate Tunnel Field effect transistor (DMDG‐TFET). An analytical two dimensional (2D) model has been developed to obtain the analytical expressions for drain current. The 2D Poisson's equation has been used to calculate surface potential in the silicon channel using the superposition approximation, as it considers the short channel effects in the calculation of the current when compared to parabolic approximation. To validate the model, analytical results have been confirmed by comparing with the Sentaurus TCAD simulation results. A reduced subthreshold slope of 31.2 mV/decade is obtained in this paper. It shows that DMDG TFET is a promising candidate for ultra‐low power applications. The subthreshold swing obtained using superposition approximation is more optimized than that of parabolic approximation technique.