Monte Carlo Algorithm for Mobility Calculations in Thin Body Field Effect Transistors: Role of Degeneracy and Intersubband Scattering

  • V. Sverdlov
  • E. Ungersboeck
  • H. Kosina
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4818)


We generalize the Monte Carlo algorithm originally designed for small signal analysis of the three-dimensional electron gas to quasi-two-dimensional electron systems. The method allows inclusion of arbitrary scattering mechanisms and general band structure. Contrary to standard Monte Carlo methods to simulate transport, this algorithm takes naturally into account the fermionic nature of electrons via the Pauli exclusion principle. The method is based on the solution of the linearized Boltzmann equation and is exact in the limit of negligible driving fields. The theoretically derived Monte Carlo algorithm has a clear physical interpretation. The diffusion tensor is calculated as an integral of the velocity autocorrelation function. The mobility tensor is related to the diffusion tensor via the Einstein relation for degenerate statistics. We demonstrate the importance of degeneracy effects by evaluating the low-field mobility in contemporary field-effect transistors with a thin silicon body. We show that degeneracy effects are essential for the correct interpretation of experimental mobility data for field effect transistors in single- and double-gate operation mode. In double-gate structures with (100) crystal orientation of the silicon film degeneracy effects lead to an increased occupation of the higher subbands. This opens an additional channel for elastic scattering. Increased intersubband scattering compensates the volume inversion induced effect on the mobility enhancement and leads to an overall decrease in the mobility per channel in double-gate structures.


Monte Carlo Algorithm Pauli Exclusion Principle High Carrier Concentration Mobility Calculation Velocity Autocorrelation Function 
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 2008

Authors and Affiliations

  • V. Sverdlov
    • 1
  • E. Ungersboeck
    • 1
  • H. Kosina
    • 1
  1. 1.Institute for MicroelectronicsTechnical University of ViennaViennaAustria

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