A general purpose device simulator coupling Poisson and Monte Carlo transport with applications to deep submicron MOSFETs

Venturi, F.; Smith, Randall K.; Sangiorgi, E.; Pinto, M.R.; Riccò, B.

doi:10.1109/43.29590

Cited by 93 publications

(17 citation statements)

References 11 publications

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“…handle quantization in the inversion layer or other physical effects. For example in the MC family some models based on the free-electron gas [4][5][6] neglect quantization, while others adopt quantum corrections [7][8][9]. Models based on a multi-subband description of the carrier gas [10][11][12] and approaches based on the solution of the Wigner equation [13,14] instead, explicitly incorporate quantum mechanical effects.…”

Section: Introductionmentioning

confidence: 99%

A comparison of advanced transport models for the computation of the drain current in nanoscale nMOSFETs

Palestri

Alexander

Asenov

et al. 2009

Solid-State Electronics

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Section: Introductionmentioning

confidence: 99%

A comparison of advanced transport models for the computation of the drain current in nanoscale nMOSFETs

Palestri

Alexander

Asenov

et al. 2009

Solid-State Electronics

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“…A 2D Poisson equation was then solved in the silicon channel and the gate oxide to update the electrostatic potential (a nonlinear Poisson equation was solved to improve the outer-loop convergence [28]). The iteration between the quantum-transport equation and the Poisson equation was repeated until the self-consistency was achieved.…”

Section: Simulation Approachmentioning

confidence: 99%

Control of Short-Channel Effects in Nano DG MOSFET Using Gaussian-Channel Doping Profile

Charmi¹

2016

Transactions on Electrical and Electronic Materials

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This article investigates the use of the Gaussian-channel doping profile for the control of the short-channel effects in the double-gate MOSFET whereby a two-dimensional (2D) quantum simulation was used. The simulations were completed through a self-consistent solving of the 2D Poisson equation and the Schrodinger equation within the non-equilibrium Green's function (NEGF) formalism. The impacts of the p-type-channel Gaussian-doping profile parameters such as the peak doping concentration and the straggle parameter were studied in terms of the drain current, on-current, off-current, sub-threshold swing (SS), and drain-induced barrier lowering (DIBL). The simulation results show that the short-channel effects were improved in correspondence with incremental changes of the straggle parameter and the peak doping concentration.

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“…Remark 1: The reason of a nonlinear Poisson equation applied here is that, during the outer self-consistent iteration loop, the fluctuation of n ( r ) may undermine the iteration convergence, according to [93]. The use of the Fermi-Dirac integral will average or normalize this kind of fluctuations and thus lead to efficient convergence.…”

Section: Numerical Implementation and Device Simulationmentioning

confidence: 99%

Modeling and simulation of electronic structure, material interface and random doping in nano-electronic devices

Chen

Wei

2010

Journal of Computational Physics

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The miniaturization of nano-scale electronic devices, such as metal oxide semiconductor field effect transistors (MOSFETs), has given rise to a pressing demand in the new theoretical understanding and practical tactic for dealing with quantum mechanical effects in integrated circuits. Modeling and simulation of this class of problems have emerged as an important topic in applied and computational mathematics. This work presents mathematical models and computational algorithms for the simulation of nano-scale MOSFETs. We introduce a unified twoscale energy functional to describe the electrons and the continuum electrostatic potential of the nano-electronic device. This framework enables us to put microscopic and macroscopic descriptions in an equal footing at nano scale. By optimization of the energy functional, we derive consistently-coupled Poisson-Kohn-Sham equations. Additionally, layered structures are crucial to the electrostatic and transport properties of nano transistors. A material interface model is proposed for more accurate description of the electrostatics governed by the Poisson equation. Finally, a new individual dopant model that utilizes the Dirac delta function is proposed to understand the random doping effect in nano electronic devices. Two mathematical algorithms, the matched interface and boundary (MIB) method and the Dirichlet-to-Neumann mapping (DNM) technique, are introduced to improve the computational efficiency of nano-device simulations. Electronic structures are computed via subband decomposition and the transport properties, such as the I-V curves and electron density, are evaluated via the non-equilibrium Green's functions (NEGF) formalism. Two distinct device configurations, a double-gate MOSFET and a four-gate MOSFET, are considered in our three-dimensional numerical simulations. For these devices, the current fluctuation and voltage threshold lowering effect induced by the discrete dopant model are explored. Numerical convergence and model well-posedness are also investigated in the present work.

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A general purpose device simulator coupling Poisson and Monte Carlo transport with applications to deep submicron MOSFETs

Cited by 93 publications

References 11 publications

A comparison of advanced transport models for the computation of the drain current in nanoscale nMOSFETs

A comparison of advanced transport models for the computation of the drain current in nanoscale nMOSFETs

Control of Short-Channel Effects in Nano DG MOSFET Using Gaussian-Channel Doping Profile

Modeling and simulation of electronic structure, material interface and random doping in nano-electronic devices

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