Numerical simulation of submicron semiconductor devices by Kazutaka Tomizawa

Cover of: Numerical simulation of submicron semiconductor devices | Kazutaka Tomizawa

Published by Artech House in Boston .

Written in English

Read online

Subjects:

  • Semiconductors -- Data processing.,
  • Semiconductors -- Mathematical models.,
  • Monte Carlo method.,
  • Electron transport.,
  • Microstructure.

Edition Notes

Includes bibliographical references and index.

Book details

StatementKazutaka Tomizawa.
SeriesThe Artech House materials science library
Classifications
LC ClassificationsQC611 .T66 1993
The Physical Object
Paginationxiv, 341 p. :
Number of Pages341
ID Numbers
Open LibraryOL1399471M
ISBN 100890066205
LC Control Number93007153

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Describes the basic theory of carrier transport, develops numerical algorithms in FORTRAN used for transport problems or device simulations, and presents real-world House Materials Science Library: Numerical Simulation of Submicron Semiconductor Devices (Hardcover)Brand: Kazutaka Tomizawa.

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By (author): Kazutaka Tomizawa. This chapter covers different methods of semiconductor device modeling for electronic circuit simulation. It presents a discussion on physics-based analytical modeling approach to predict device operation at specific conditions such as applied bias (e.g., voltages and currents); environment (e.g., temperature, noise); and physical characteristics (e.g., geometry, doping levels).

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Numerical simulation of submicron semiconductor devices. Responsibility -- carrier scattering-- Monte Carlo transport calculation-- Monte Carlo device simulation-- balance equation method for device simulation.

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With simplified models and comprehensive numerical techniques, the relative importance (on the device behavior) of several physical effects, such as velocity overshoot, intracollisional.

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In this article, we deal with the three-dimensional numerical simulation of semiconductor devices using the Viscous-Hydrodynamic (VHD) transport model.

A reformulation of the VHD system using entropy variables allows to end up with a quasi-linear form that is symmetric and for which a stability result (in form of Clausius–Duhem inequality) is.

{25} K. Tomizawa, Numerical Simulation of Submicron Semiconductor Devices, Artech House, Boston, ]] Google Scholar {26} W. Wagner, Stochastic models and Monte Carlo algorithms for Boltzmann type equations, in: Monte Carlo and Quasi-Monte Carlo MethodsSpringer, Berlin,pp.

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