Atomistic Simulation of Decanano MOSFETs

  • A. Asenov
  • A. R. Brown
  • S. Kaya
Part of the Springer Series in MATERIALS SCIENCE book series (SSMATERIALS, volume 72)


The application of 3D statistical atomistic simulation techniques to the study of intrinsic parameter fluctuations in aggressively scaled MOSFETs introduced by discreteness of charge and atomicity of matter is presented. The most commonly studied source of such fluctuations is random dopant induced effects, associated with random placement and a varying number of dopant atoms in semiconductors. We describe an efficient implementation of the atomistic simulation approach, which has been used to investigate the threshold voltage standard deviation and lowering in uniformly doped MOSFETs, and in fluctuation-resistant architectures utilising epitaxial layers and delta-doping. Threshold voltage fluctuations due to random dopants in the polysilicon gate have also been considered. The influence of a single trapped charge on the channel conductivity in decanano MOSFETs is studied in the atomistic framework as well. Quantum effects are taken into consideration in our simulations, using the density gradient formalism. The granular nature of the Si/SiO2 interface resulting in random interface roughness is also taken into account, and is shown to lead to significant fluctuations in MOSFETs in the decanano regime. Imperfect definition of line edges in lithography processes due to the molecular structure of the resist and the granularity of the gate material is accounted for in line edge roughness simulations. We point out the importance of various challenges that lie ahead in understanding and simulating a truly atomistic MOSFET.


Threshold Voltage Oxide Thickness Atomistic Simulation Short Channel Effect Polysilicon Gate 
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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© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • A. Asenov
  • A. R. Brown
  • S. Kaya

There are no affiliations available

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