Simulation and inverse modeling of TEOS deposition processes using a fast level set method

C. Heitzinger, J. Fugger, O. Häberlen, S. Selberherr

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

Deposition and etching of silicon trenches is an important manufacturing step for state of the art memory cells. Understanding and simulating the transport of gas species and surface evolution enables to achieve void-less filling of deep trenches, to predict the resulting profiles, and thus to optimize process parameters with respect to manufacturing throughput and the quality of the resulting memory cells. For the simulation of the SiO2 deposition process from TEOS (Tetraethoxysilane), the level set method was used in addition to physical models. The level set algorithm devised minimizes computational effort while ensuring high accuracy by intertwining narrow banding and extending the speed function. In order to make the predictions of the simulation more accurate, model parameters were extracted by comparing the step coverages of the deposited layers in the simulation with those of SEM (scanning electron microscope) images.

Original languageEnglish (US)
Title of host publication2002 International Conference on Simulation of Semiconductor Processes and Devices, SISPAD 2002
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages191-194
Number of pages4
ISBN (Electronic)4891140275
DOIs
StatePublished - 2002
Externally publishedYes
EventInternational Conference on Simulation of Semiconductor Processes and Devices, SISPAD 2002 - Kobe, Japan
Duration: Sep 4 2002Sep 6 2002

Publication series

NameInternational Conference on Simulation of Semiconductor Processes and Devices, SISPAD
Volume2002-January

Other

OtherInternational Conference on Simulation of Semiconductor Processes and Devices, SISPAD 2002
Country/TerritoryJapan
CityKobe
Period9/4/029/6/02

Keywords

  • Computational modeling
  • Etching
  • Filling
  • Inverse problems
  • Level set
  • Manufacturing processes
  • Predictive models
  • Scanning electron microscopy
  • Silicon
  • Virtual manufacturing

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Modeling and Simulation

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