• DocumentCode
    2471104
  • Title

    Modeling and analysis of circuit performance of ballistic CNFET

  • Author

    Paul, Bipul ; Fujita, Shinobu ; Okajima, Masaki ; Lee, Thomas

  • Author_Institution
    Center for Integrated Syst., Stanford Univ., CA
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    717
  • Lastpage
    722
  • Abstract
    With the advent of carbon nanotube technology, evaluating circuit and system performance using these devices is becoming extremely important. In this paper, we propose a quasi-analytical device model for intrinsic ballistic CNFET, which can be used in any conventional circuit simulator like SPICE. This simple quasi-analytical model is seen to be effective in a wide variety of CNFET structures as well as for a wide range of operating conditions in the digital circuit application domain. We also provide an insight how the parasitic fringe capacitance in state-of-the-art CNFET geometries impacts the overall performance of CNFET circuits. We show that unless the device width can be significantly reduced, the effective gate capacitance of CNFET will be strongly dominated by the parasitic fringe capacitances and the superior performance of intrinsic CNFET over silicon MOSFET cannot be achieved in circuit
  • Keywords
    SPICE; carbon nanotubes; field effect transistors; semiconductor device models; CNFET structures; SPICE; ballistic CNFET; ballistic carbon nanotube FET; carbon nanotube technology; circuit compatible model; circuit performance; digital circuit application; effective gate capacitance; parasitic capacitance; parasitic fringe capacitance; Carbon nanotubes; Circuit analysis; Circuit optimization; Circuit simulation; Circuits and systems; Digital circuits; Geometry; Parasitic capacitance; Performance analysis; SPICE; Ballistic carbon nanotube FET (CNFET); Design; Performance; circuit compatible model; circuit performance; parasitic capacitance;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Design Automation Conference, 2006 43rd ACM/IEEE
  • Conference_Location
    San Francisco, CA
  • ISSN
    0738-100X
  • Print_ISBN
    1-59593-381-6
  • Type

    conf

  • DOI
    10.1109/DAC.2006.229334
  • Filename
    1688890