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A chip to wafer scale, CMOS compatible method of graphene device fabrication has been established, which can be integrated into the back end of the line (BEOL) of conventional semiconductor process flows. In this paper, we present…

Applied Physics · Physics 2022-11-23 A. D. Smith , S. Vaziri , S. Rodriguez , M. Östling , M. C. Lemme

Establishing a reliable communication interface between the brain and electronic devices is of paramount importance for exploiting the full potential of neural prostheses. Current microelectrode technologies for recording electrical…

A small-signal equivalent circuit for graphene field-effect transistors is proposed considering the explicit contribution of effects at the metal-graphene interfaces by means of contact resistances. A methodology to separate the contact…

We present a compact physics-based model of the current-voltage characteristics of graphene field-effect transistors, of especial interest for analog and radio-frequency applications where bandgap engineering of graphene could be not…

Mesoscale and Nanoscale Physics · Physics 2011-10-27 David Jimenez , Oana Moldovan

We present a graphene-based phase shifter for radio-frequency (RF) phase-array applications. The core of the designed phase-shifting system consists of a graphene field-effect transistor (GFET) used in a common source amplifier…

Mesoscale and Nanoscale Physics · Physics 2021-03-16 A. Medina-Rull , F. Pasadas , E. G. Marin , A. Toral-Lopez , J. Cuesta , A. Godoy , D. Jiménez , F. G. Ruiz

In this letter, we analyze the carrier transit delay in graphene field-effect transistors (GFETs). GFETs are fabricated at the wafer-scale on sapphire substrate. For a device with a gate length of 210 nm, a current gain cut-off frequency fT…

Mesoscale and Nanoscale Physics · Physics 2015-06-03 Han Wang , Allen Hsu , Dong Seup Lee , Ki Kang Kim , Jing Kong , Tomas Palacios

We introduce a new method for hardware non-uniform random number generation based on the transfer characteristics of graphene field-effect transistors (GFETs) which requires as few as two transistors and a resistor (or transimpedance…

Emerging Technologies · Computer Science 2020-10-29 Nathaniel Joseph Tye , James Timothy Meech , Bilgesu Arif Bilgin , Phillip Stanley-Marbell

We obtain the output and transfer characteristics of graphene field-effect transistors by using the charge-control model for the current, based on the solution of the Boltzmann equation in the field-dependent relaxation time approximation.…

Mesoscale and Nanoscale Physics · Physics 2015-05-20 Brett W. Scott , Jean-Pierre Leburton

We present an analytical device model for a graphene bilayer field-effect transistor (GBL-FET) with a graphene bilayer as a channel, and with back and top gates. The model accounts for the dependences of the electron and hole Fermi energies…

Mesoscale and Nanoscale Physics · Physics 2015-05-13 V. Ryzhii , M. Ryzhii , A. Satou , T. Otsuji , N. Kirova

Graphene Field-Effect Transistors (GFETs) are increasingly employed as biochemical sensors due to their exceptional electronic properties, surface sensitivity, and potential for miniaturization. A critical challenge in deploying GFETs is…

A novel nanoelectronic device is constructed by graphyne that is robustly connected between graphene electrodes, where graphyne is composed of hexagonal carbon rings and carbon chains. Owing to similarities between the bond lengths and unit…

Mesoscale and Nanoscale Physics · Physics 2013-07-17 Young I. Jhon , Myung S. Jhon

A new compact modeling approach is presented which describes the full current-voltage (I-V) characteristic of high-performance (aggressively scaled-down) tunneling field-effect-transistors (TFETs) based on homojunction direct-bandgap…

Mesoscale and Nanoscale Physics · Physics 2015-11-02 Ramon B. Salazar , Hesameddin Ilatikhameneh , Rajib Rahman , Gerhard Klimeck , Joerg Appenzeller

This paper presents a circuit performance benchmarking using the large-signal model of graphene field effect transistor reported in Part I of this two-part paper. To test the model, it has been implemented in a circuit simulator.…

Mesoscale and Nanoscale Physics · Physics 2016-09-07 Francisco Pasadas , David Jiménez

Graphene is a promising material for applications as a channel in graphene field-effect transistors (GFETs) which may be used as a building block for optoelectronics, high-frequency devices and sensors. However, these devices require gate…

A low complexity computational model of the current-voltage characteristics for graphene nano-ribbon (GNR) field effect transistors (FET), able to simulate a hundred of points in few seconds using a PC, is presented. For quantum capacitance…

Mesoscale and Nanoscale Physics · Physics 2008-07-15 David Jimenez

Extended Floating Gate Field Effect Transistors (EGFETs) are CMOS-compatible floating gate devices capable of detecting charges on their sensing area by the relative shifts in current-voltage (I-V) characteristics. The I-V shifts are…

Signal Processing · Electrical Eng. & Systems 2023-07-24 Yunsoo Park , Santosh Pandey

A graphene field effect transistor, where the active area is made of monolayer large-area graphene, is simulated including a full 2D Poisson equation and a drift-diffusion model with mobilities deduced by a direct numerical solution of the…

Applied Physics · Physics 2021-09-01 Giovanni Nastasi , Vittorio Romano

We develop an analytical device model for graphene bilayer field-effect transistors (GBL-FETs) with the back and top gates. The model is based on the Boltzmann equation for the electron transport and the Poisson equation in the weak…

Mesoscale and Nanoscale Physics · Physics 2015-05-19 V. Ryzhii , M. Ryzhii , A. Satou , T. Otsuji , V. Mitin

An analytical circuit model able to predict the input impedance of reconfigurable graphene plasmonic dipoles is presented. A suitable definition of plasmonic characteristic impedance, employing natural currents, is used to for consistent…

Optics · Physics 2015-06-18 Michele Tamagnone , Julien Perruisseau-Carrier

Graph Transformers (GTs) have shown strong empirical performance, yet current architectures vary widely in their use of attention mechanisms, positional embeddings (PEs), and expressivity. Existing expressivity results are often tied to…

Machine Learning · Computer Science 2025-11-12 Timo Stoll , Luis Müller , Christopher Morris