A simple model for quantisation effects in heavily-doped silicon MOSFETs at inversion conditions

Dort, M.J. van; Woerlee, P.H.; Walker, Andrew

doi:10.1016/0038-1101(94)90005-1

Cited by 260 publications

(103 citation statements)

References 8 publications

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“…Second method is used in finding the threshold voltages accounting of DIBL effect, and first method finding ones accounting of VDQC model(is referenced to Van Dort Quantum Correction model) [5] and body effect. Figure 2 shows V th with and without DIBL effect when the drain voltage is 0.1V, 1.0V and 2.0V under the condition of the constant voltage scaling.…”

Section: Simulations and Discussionmentioning

confidence: 99%

Analysis of Threshold Voltage in Nano-Channel Length MOSFETs

Tyagi¹,

Kumar²,

Kumar³

2015

International Journal of Advanced Research in Computer and Comm

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This paper presents the simulation results of threshold voltage for Si-based nano channel length MosFet. Simulation results will in between of 180 to 30 nm length of Si-based n-channel MosFet according to constant theory of voltage scaling. The structure of this MosFet is lightly doped drain which reduces to electric field magnitude and effect on short channel at drain region. In this paper, we analyzed the threshold voltage of these type devices and this analysis will provide some applicable limitations inside at ICs and used for basis data at VLSI Circuit design methodology.

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Section: Simulations and Discussionmentioning

confidence: 99%

Analysis of Threshold Voltage in Nano-Channel Length MOSFETs

Tyagi¹,

Kumar²,

Kumar³

2015

International Journal of Advanced Research in Computer and Comm

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“…The high levels of substrate doping, needed in nanodevices to prevent the punch-through effect, and which enhance the quasi-two-dimensional (Q2D) nature of the carrier transport in the inversion layer, were found responsible for the increased threshold voltage and decreased channel mobility. A simple analytical model that accounts for this effect was proposed by van Dort and coworkers [62,63]. Vasileska and Ferry [64] confirmed these findings by investigating the doping dependence of the threshold voltage in MOS capacitors.…”

Section: Quantum Correctionsmentioning

confidence: 85%

Monte Carlo Device Simulations

Raleva¹,

Shaik

Hathwar

et al. 2011

Applications of Monte Carlo Method in Science and Engineering

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As semiconductor devices are scaled into nanoscale regime, first velocity saturation starts to limit the carrier mobility due to pronounced intervalley scattering, and when the device dimensions are scaled to 100 nm and below, velocity overshoot (which is a positive effect) starts to dominate the device behavior leading to larger ON-state currents. Alongside with the developments in the semiconductor nanotechnology, in recent years there has been significant progress in physical based modeling of semiconductor devices. First, for devices for which gradual channel approximation can not be used due to the two-dimensional nature of the electrostatic potential and the electric fields driving the carriers from source to drain, drift-diffusion models have been exploited. These models are valid, in general, for large devices in which the fields are not that high so that there is no degradation of the mobility due to the electric field. The validity of the drift-diffusion models can be extended to take into account the velocity saturation effect with the introduction of field-dependent mobility and diffusion coefficients. When velocity overshoot becomes important, drift diffusion model is no longer valid and hydrodynamic model must be used. The hydrodynamic model has been the workhorse for technology development and several high-end commercial device simulators have appeared including Silvaco, Synopsys, Crosslight, etc. The advantages of the hydrodynamic model are that it allows quick simulation runs but the problem is that the amount of the velocity overshoot depends upon the choice of the energy relaxation time. The smaller is the device, the larger is the deviation when using the same set of energy relaxation times. A standard way in calculating the energy relaxation times is to use bulk Monte Carlo simulations. However, the energy relaxation times are material, device geometry and doping dependent parameters, so their determination ahead of time is not possible. To avoid the problem of the proper choice of the energy relaxation times, a direct solution of the Boltzmann Transport Equation (BTE) using the Monte Carlo method is the best method of choice. That is why the focus of this review paper is on explaining basic Monte Carlo device simulator and then the focus will be shifted on the inclusion of various higher order effects that explain particular physical phenomena or processes.The Monte Carlo book chapter is organized as follows. First, the idea behind the Monte Carlo technique is outlined by revoking the path integral method for the solution of the BTE. This approach naturally leads to the free-flight-scatter sequence that is used in solving the BTE using the Monte Carlo method. Various scattering mechanisms relevant for different materials are given to completely specify the collision integral in the BTE. A discussion followed with the presentation of a generic flow-chart for implementing bulk Monte Carlo code is presented. Note that bulk Monte Carlo approach is suitable for the characterization of ma...

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“…The finite inversion layer thickness was estimated experimentally by Hartstein and Albert [38]. The high levels of substrate doping, needed in nano-devices to prevent the punch-through effect, that lead to quasi-two-dimensional (Q2D) nature of the carrier transport, were found responsible for the increased threshold voltage and decreased channel mobility, and a simple analytical model that accounts for this effect was proposed by van Dort and co-workers [39,40]. Later on, Vasileska and Ferry [ 41 ] confirmed these findings by investigating the doping dependence of the threshold voltage in MOS capacitors.…”

Section: The Role Of Quantum-mechanical Space Quantization Effects Onmentioning

confidence: 98%

Quantum and Coulomb Effects in Nano Devices

Vasileska¹,

Khan²,

Ahmed³

et al. 2011

Nano-Electronic Devices

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In state of the art devices, it is well known that quantum and Coulomb effects play significant role on the device operation. In this paper we demonstrate that a novel effective potential approach in conjunction with a Monte Carlo device simulation scheme can accurately capture the quantummechanical size quantization effects. We also demonstrate, via proper treatment of the short-range Coulomb interactions, that there will be significant variation in device design parameters for devices fabricated on the same chip due to the presence of unintentional dopant atoms at random locations within the channel.

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A simple model for quantisation effects in heavily-doped silicon MOSFETs at inversion conditions

Cited by 260 publications

References 8 publications

Analysis of Threshold Voltage in Nano-Channel Length MOSFETs

Analysis of Threshold Voltage in Nano-Channel Length MOSFETs

Monte Carlo Device Simulations

Quantum and Coulomb Effects in Nano Devices

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