• DocumentCode
    2143550
  • Title

    Statistical variations in 32nm thin-body SOI devices and SRAM cells

  • Author

    Cheng, B. ; Roy, S. ; Brown, A. ; Millar, C. ; Asenov, A.

  • Author_Institution
    Dept. of Electron.&Electr. Eng., Univ. of Glasgow, Glasgow, UK
  • fYear
    2008
  • fDate
    20-23 Oct. 2008
  • Firstpage
    389
  • Lastpage
    392
  • Abstract
    Based on 3D statistical device simulation, the impacts of key statistical variability (SV) sources (in both individual and combined forms) on device characteristics are studied in detail for a 32 nm thin-body SOI technology. The corresponding impacts on SRAM cell stability are presented as well. The simulation results indicate that thin body architectures are not only resistant to random discreet dopant induced variation, but also less sensitive to length edge roughness induced variation.
  • Keywords
    SRAM chips; semiconductor devices; silicon-on-insulator; statistical analysis; 3D statistical device simulation; SRAM cell stability; edge roughness; key statistical variability; random discreet dopant induced variation; size 32 nm; statistical variations; thin-body SOI devices; Calibration; Data mining; Doping profiles; Immune system; MOSFETs; Random access memory; Resists; Silicon; Stability; Tin;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Solid-State and Integrated-Circuit Technology, 2008. ICSICT 2008. 9th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2185-5
  • Electronic_ISBN
    978-1-4244-2186-2
  • Type

    conf

  • DOI
    10.1109/ICSICT.2008.4734546
  • Filename
    4734546