62
Views
0
CrossRef citations to date
0
Altmetric
Articles

Bipolar Hydrodynamical Model for Charge Transport in Graphene Nanoribbons

ORCID Icon & ORCID Icon
Pages 80-100 | Published online: 20 Jun 2022
 

Abstract

A hydrodynamical model for charge transport in narrow strips of graphene is here presented. The model takes into account the interactions with the well-known lattice vibrations and with the edge of the strip. The remarkable result is the modulation of the charge current due to the swapping of charge carriers between the conduction and the valence bands, controlled by the Fermi energy variation and by the thickness of the ribbon. The numerical test shows a behavior comparable with that one obtained by solving directly the Boltzmann equation but with a considerable reduction of the computational time.

Acknowledgments

The authors acknowledge the support from INdAM (GNFM) and from Università degli Studi di Catania, Piano della Ricerca 2020/2022 Linea di intervento 2 “QICT” and “Progetto Giovani GNFM 2020”. V. D. Camiola acknowledges the financial support from the project AIM, Mobilità dei Ricercatori Asse I del PON R & I 2014-2020, proposta AIM1893589. G. Nastasi acknowledges the financial support from the project PON R & I 2014–2020 “Asse IV - Istruzione e ricerca per il recupero - REACT-EU, Azione IV.4 - Dottorati e contratti di ricerca su tematiche dell’innovazione”, project: “Modellizzazione, simulazione e design di transistori innovativi”.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 944.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.