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

Nikolaos Mavredakis*, Anibal Pacheco-Sanchez, Wei Wei, Emiliano Pallecchi, Henri Happy, David Jiménez

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

4 Citations (Scopus)
1 Downloads (Pure)

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.

Original languageEnglish
Article number105715
Number of pages7
JournalMicroelectronics Journal
Volume133
DOIs
Publication statusPublished - 1 Mar 2023

Keywords

  • Bias- and frequency-dependence
  • Graphene transistor (GFET)
  • RF circuit Design
  • Small-signal compact model

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