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Straightforward bias- and frequency-dependent small-signal model extraction for single-layer graphene FETs.

Authors :
Mavredakis, Nikolaos
Pacheco-Sanchez, Anibal
Wei, Wei
Pallecchi, Emiliano
Happy, Henri
Jiménez, David
Source :
Microelectronics Journal. Mar2023, Vol. 133, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

We propose an explicit small-signal graphene field-effect transistor (GFET) parameter extraction procedure based on a charge-based quasi-static model. The dependence of the small-signal parameters on both gate voltage and frequency is precisely validated by high-frequency (up to 18 GHz) on-wafer measurements from a 300 nm device. These parameters are studied simultaneously, in contrast to other works which focus exclusively on few. Efficient procedures have been applied to GFETs for the first time to remove contact and gate resistances from the Y -parameters. The use of these methods yields straightforward equations for extracting the small-signal model parameters, which is extremely useful for radio-frequency circuit design. Furthermore, we show for the first time experimental validation vs. both gate voltage and frequency of the intrinsic GFET non-reciprocal capacitance model. Accurate models are also presented for the gate voltage-dependence of the measured unity-gain and maximum oscillation frequencies as well as of the current and power gains. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00262692
Volume :
133
Database :
Academic Search Index
Journal :
Microelectronics Journal
Publication Type :
Academic Journal
Accession number :
162062057
Full Text :
https://doi.org/10.1016/j.mejo.2023.105715