• DocumentCode
    1690734
  • Title

    Tracking the composition of growing silicon-germanium alloys: an industrial application of particle filters

  • Author

    Marrs, Alan

  • Author_Institution
    DERA, Malvern, UK
  • fYear
    1999
  • fDate
    6/21/1905 12:00:00 AM
  • Firstpage
    42552
  • Lastpage
    42556
  • Abstract
    This paper describes the use of a particle filter to perform in-situ monitoring of growing silicon-germanium (SiGe) alloys. Silicon (Si) technology is revolutionising the design of both civil and military systems through the production of complex integrated circuits at low unit cost. The electronic and optical properties of SiGe devices are sensitive to the composition, thickness and strain-state of the alloys, and if the additional gains of lower power and higher speed are to be had, these layer parameters must be accurately controlled in manufacture. Spectroscopic ellipsometry represents a nondestructive measurement process that can indirectly monitor changes in alloy composition. The highly nonlinear measurement model required to associate ellipsometry measurements with changes in composition makes the use of an extended Kalman filter for composition tracking impractical. We present the development of a tracking solution based upon the particle filter. Its performance for a real SiGe alloy with a complex composition profile is compared with results obtained from off-line analysis using secondary ion mass spectroscopy. The results show that the particle filter can be successfully used for real-time in-situ analysis in an industrial application where standard Kalman filter based tracking algorithms fail
  • Keywords
    chemical vapour deposition; CVD; Markov random walk model; SiGe; alloy composition changes; complex composition profile; composition tracking; discrete time estimation problem; dynamic state estimation; growing SiGe alloys; highly nonlinear measurement model; in-situ monitoring; industrial application; inverse problem; nondestructive measurement process; particle filters application; real-time in-situ analysis; recursive Bayesian estimation; spectroscopic ellipsometry; state space model; target tracking analogy;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Target Tracking: Algorithms and Applications (Ref. No. 1999/090, 1999/215), IEE Colloquium on
  • Conference_Location
    London
  • Type

    conf

  • DOI
    10.1049/ic:19990508
  • Filename
    827253