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NCN Nanoelectronics: Simulation Tools for Education

Carrier Statistics Lab

This resource has a 8.3 Ranking

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Usage Stats
Overall Period: Updated 20 Aug, 2008
Users: 134
Jobs: 1071
Avg. exec. time: 17 secs
Reviews & Citations
Google/IEEE
Avg. Review: 0.0 out of 5 stars
Citations: 0

134 users, detailed statistics

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Available Versions

Supporting Documents

Version 1.01 - published on 24 Jan, 2008
Contributor(s) Abhijeet Paul, Saumitra Raj Mehrotra, Gerhard Klimeck
Purdue University, West Lafayette
At a glance Models Fermi and Maxwell-Boltzmann statistics for Silicon, Germanium, and GaAs
Screenshots
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Description

This is a simple tool that demonstrates electron and hole density distributions based on the Fermi-Dirac and Maxwell Boltzmann equations. This tool shows the dependence of carrier density, densisty of states and occupation factor on temperature and fermi level. User can choose between doped and undoped semi-conductors. Silicon, Germanium, and GaAs can be studied as a function of doping or Fermi level, and temperature.

The tool is supported by a homework assignment in which Students are asked to explore the differences between Fermi-Dirac and Maxwell-Boltzmann distributions, compute electron and hole concentrations, study temperature dependences, and study freeze-out.

Credits

The tool is supported by a homework assignment in which Students are asked to explore the differences between Fermi-Dirac and Maxwell-Boltzmann distributions, compute electron and hole concentrations, study temperature dependences, and study freeze-out.

Sponsored by

NCN@Purdue

References

Semiconductor Device Fundamentals , Robert Pierret
Physics of Semiconductor Devices, S M Sze

Cite this work

If you reference this work in a publication, please cite as follows:

  • Paul, Abhijeet; Mehrotra, Saumitra Raj; Klimeck, Gerhard (2008), "Carrier Statistics Lab," doi: 10254/nanohub-r3798.2.

    BibTex | EndNote

In addition, we would appreciate it if you would add the following acknowledgment to your publication:

  • Simulation services for results presented here were provided by the Network for Computational Nanotechnology (NCN) at nanoHUB.org

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