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3D Block-Structured Grid Algorithms for the Numerical Simulation of Chemical Vapor Deposition in Horizontal Reactors

  • L. Kadinski
  • P. Kaufmann
  • C. Lindner
  • F. Durst
Part of the Lecture Notes in Computational Science and Engineering book series (LNCSE, volume 21)

Abstract

In this paper an advanced numerical approach for the simulation of epitaxial growth in metalorganic chemical vapor deposition (MOCVD) reactors is presented. The mathematical model is based on the conservation equations for momentum and heat transfer combined with mass transfer

The heat conduction includes thermal solid/fluid interactions between the gas and solid parts of the reactor. The radiation heat transfer is coupled with convection and conduction. The radiation heat transfer modelling approach is based on the exchange of radiative heat fluxes between the internal solid surfaces in the computational domain using diffuse view-factors. The calculation of view factors is based on a double contour integral method. A shadowing algorithm is implemented for the calculation of view factors in complex geometries

The model is implemented in a finite volume numerical solution procedure, incompressible or low Mach number flow on block-structured non-orthogonal grids for three-dimensional laminar flows

In order to demonstrate the ability of the present method to analyse complex problems, investigations for horizontal MOCVD reactor configurations are presented. The simulated temperature distribution is compared with well-known temperature measurements and good agreement with them is achieved

The growth of GaAs from trimethyl gallium (TMGa), arsine, and hydrogen was considered where the deposition process is assumed to be in the transport-limited regime. The predicted deposition rates in the reactor fairly well compare with the available experimental results from literature

Keywords

View Factor Metalorganic Chemical Vapor Deposition Horizontal Reactor Growth Rate Distribution MOCVD Reactor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • L. Kadinski
    • 1
  • P. Kaufmann
    • 1
  • C. Lindner
    • 1
  • F. Durst
    • 1
  1. 1.Institute of Fluid MechanicsUniversity of Erlangen-NürnbergErlangenGermany

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