Advances in nano research

  • 제17권2호
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  • Pages.137-147
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  • 2024
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  • 2287-237X(pISSN)
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  • 2287-2388(eISSN)
테크노프레스 (Techno-Press)
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Quantum transport of doped rough-edged graphene nanoribbons FET based on TB-NEGF method

  • K.L. Wong (Faculty of Electrical Engineering, Universiti Teknologi Malaysia) ;
  • M.W. Chuan (Faculty of Electrical Engineering, Universiti Teknologi Malaysia) ;
  • A. Hamzah (Faculty of Electrical Engineering, Universiti Teknologi Malaysia) ;
  • S. Rusli (Faculty of Electrical Engineering, Universiti Teknologi Malaysia) ;
  • N.E. Alias (Faculty of Electrical Engineering, Universiti Teknologi Malaysia) ;
  • S.M. Sultan (Faculty of Electrical Engineering, Universiti Teknologi Malaysia) ;
  • C.S. Lim (Faculty of Electrical Engineering, Universiti Teknologi Malaysia) ;
  • M.L.P. Tan (Faculty of Electrical Engineering, Universiti Teknologi Malaysia)
  • 투고 : 2020.12.24
  • 심사 : 2024.08.01
  • 발행 : 2024.08.25
⟨ 이전 논문 다음 논문 ⟩

초록

Graphene nanoribbons (GNRs) are considered a promising alternative to graphene for future nanoelectronic applications. However, GNRs-based device modeling is still at an early stage. This research models the electronic properties of n-doped rough-edged 13-armchair graphene nanoribbons (13-AGNRs) and quantum transport properties of n-doped rough-edged 13-armchair graphene nanoribbon field-effect transistors (13-AGNRFETs) at different doping concentrations. Step-up and edge doping are used to incorporate doping within the nanostructure. The numerical real-space nearest-neighbour tight-binding (NNTB) method constructs the Hamiltonian operator matrix, which computes electronic properties, including the sub-band structure and bandgap. Quantum transport properties are subsequently computed using the self-consistent solution of the two-dimensional Poisson and Schrödinger equations within the non-equilibrium Green's function method. The finite difference method solves the Poisson equation, while the successive over-relaxation method speeds up the convergence process. Performance metrics of the device are then computed. The results show that highly doped, rough-edged 13-AGNRs exhibit a lower bandgap. Moreover, n-doped rough-edged 13-AGNRFETs with a channel of higher doping concentration have better gate control and are less affected by leakage current because they demonstrate a higher current ratio and lower off-current. Furthermore, highly n-doped rough-edged 13-AGNRFETs have better channel control and are less affected by the short channel effect due to the lower value of subthreshold swing and drain-induced barrier lowering. The inclusion of dopants enhances the on-current by introducing more charge carriers in the highly n-doped, rough-edged channel. This research highlights the importance of optimizing doping concentrations for enhancing GNRFET-based device performance, making them viable for applications in nanoelectronics.

키워드

과제정보

The authors express their deep gratitude for the outstanding support and research-friendly environment offered by Universiti Teknologi Malaysia (UTM). This research received funding from the UTM Fundamental Research (UTMFR) under cost centre number Q.J130000.3823.22H76. The authors also extend their thanks to the Research Management Centre, School of Graduate Studies, and Faculty of Electrical Engineering.

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