Small-Signal Model for 2D-Material Based FETs Targeting Radio-Frequency Applications: The Importance of Considering Nonreciprocal Capacitances

Pasadas, Francisco; Wei, Wei; Pallecchi, Emiliano; Happy, H.; Jiménez, David

doi:10.1109/ted.2017.2749503

Cited by 27 publications

(50 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Table 2 describes the QS small-signal parameters describing the device at the considered bias point. For convenience, the equivalent circuit of the complete QS small-signal model of GFETs 25 has been depicted in Fig. 8.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Non-Quasi-Static Effects in Graphene Field-Effect Transistors Under High-Frequency Operation

Pasadas

Jiménez

2020

IEEE Trans. Electron Devices

Self Cite

View full text Add to dashboard Cite

We have investigated the non-quasi-static (NQS) effects in graphene field-effect transistors (GFETs), which are relevant for GFET operation at high frequencies as a result of significant carrier inertia. A small-signal NQS model is derived from the analytical solution of drift-diffusion equation coupled with the continuity equation, which can be expressed in terms of modified Bessel functions of the first kind. The NQS model can be conveniently simplified to provide an equivalent circuit of lumped elements ready to be used in standard circuit simulators. Taking into account only first-order NQS effects, accurate GFET based circuit simulations up to several times the cut-off frequency (fT) can be performed. Notably, it reduces to the quasi-static (QS) approach when the operation frequency is below  fT/4. To validate the NQS model, we have compared its outcome against simulations based on a multisegment approach consisting of breaking down the channel length in N equal segments described by the QS model each one.

show abstract

Section: Resultsmentioning

confidence: 99%

“…7. It has been analytically calculated using the derivation carried out by the authors in 25 , with the small-signal parameters given in Table 2 and considering RsW = RdW = 100Ωµm and Rg = 10Ω. According to Fig.…”

Section: Resultsmentioning

confidence: 99%

Non-Quasi-Static Effects in Graphene Field-Effect Transistors Under High-Frequency Operation

Pasadas

Jiménez

2020

IEEE Trans. Electron Devices

Self Cite

View full text Add to dashboard Cite

show abstract

“…There is very little research about extracting the parasitic resistances only by RF measurement. A methodology proposed by Francisco give a direct parameter extraction process only by RF measurements, based on the assumption that both drain and source resistances are the same, namely

R_{s} = R_{d} = R_{c}

. However, in fact, the drain resistance is not always equal to the source resistance, because of the fabrication error and the nonuniformity of graphene channel.…”

Section: Gfets’ Small‐signal Model and Parameters Extractionmentioning

confidence: 99%

“…While, in ref. , the real parts of the Z parameters are given by

r e a l true(Z_{11} true) = R_{g} + R_{s} + \frac{A}{4}

r e a l true(Z_{12} true) = R_{s} + \frac{A}{2}

r e a l true(Z_{21} true) = R_{s} + \frac{A}{2}

r e a l true(Z_{22} true) = R_{d} + R_{s} + A

…”

Section: Gfets’ Small‐signal Model and Parameters Extractionmentioning

confidence: 99%

See 1 more Smart Citation

Extracting Small‐Signal Model Parameters of Graphene‐Based Field‐Effect Transistors

Wang

Miao

Peng

et al. 2018

Physica Status Solidi (a)

View full text Add to dashboard Cite

This paper is aimed at extracting the intrinsic and extrinsic model parameter values of a small signal model based only on S‐parameter measurements. An analytically derived method to extract parasitic resistances and then obtain the all intrinsic parameters according to the previous method are proposed. Experiment results show the extracted model parameters can fit the test data well for our device, which illustrate the validity and accuracy of the extraction method. In addition, the authors analyze the huge differences of small‐signal parameters between graphene‐based field‐effect transistors (FETs) and traditional MOSFETs in saturation, and then point out the specific direction of improving the radio frequency performance of graphene‐based field‐effect transistors.

show abstract

Compact Modeling Technology for the Simulation of Integrated Circuits Based on Graphene Field‐Effect Transistors

et al. 2022

Self Cite

View full text Add to dashboard Cite

In this study, we report the progress made towards the definition of a modular compact modeling technology for graphene field-effect transistors (GFET) that enables the electrical analysis of arbitrary GFET-based integrated circuits. A set of primary models embracing the main physical principles defines the ideal GFET response under DC, transient (time domain), AC (frequency domain), and noise (frequency domain) analysis. Other set of secondary models accounts for the GFET non-idealities, such as extrinsic-, short-channel-, trapping/detrapping-, self-heating-, and non-quasi static-effects, which could have a significant impact under static and/or dynamic operation. At both device and circuit levels, significant consistency is demonstrated between the simulation output and experimental data for relevant operating conditions. Additionally, we provide a perspective of the challenges during the scale up of the GFET modeling technology towards higher technology readiness levels while drawing a collaborative scenario among fabrication technology groups, modeling groups, and circuit designers.Received: ((will be filled in by the editorial staff))Revised: ((will be filled in by the editorial staff))

show abstract

Small-Signal Model for 2D-Material Based FETs Targeting Radio-Frequency Applications: The Importance of Considering Nonreciprocal Capacitances

Cited by 27 publications

References 43 publications

Non-Quasi-Static Effects in Graphene Field-Effect Transistors Under High-Frequency Operation

Non-Quasi-Static Effects in Graphene Field-Effect Transistors Under High-Frequency Operation

Extracting Small‐Signal Model Parameters of Graphene‐Based Field‐Effect Transistors

Compact Modeling Technology for the Simulation of Integrated Circuits Based on Graphene Field‐Effect Transistors

Contact Info

Product

Resources

About