The effect of randomness in the distribution of impurity atoms on FET thresholds

Keyes, Robert W.

doi:10.1007/bf00896619

Cited by 163 publications

(74 citation statements)

References 11 publications

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“…Statistical fluctuations of the channel dopant number were predicted by Keyes [82] as a fundamental physical limitation of MOSFETs down-scaling. Entering into the nanometer regime results in a decreasing number of channel impurities whose random distribution leads to significant fluctuations of the threshold voltage and off-state leakage current.…”

Section: 2mentioning

confidence: 99%

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 When velocity overshoot becomes important, drift diffusion model is no longer valid and hydrodynamic model must be used.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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Section: 2mentioning

confidence: 99%

Monte Carlo Device Simulations

Raleva¹,

Shaik

Hathwar

et al. 2011

Applications of Monte Carlo Method in Science and Engineering

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“…The short-range Coulomb force can be further defined as (22) where coul ij F is given by Eq. (20) and ij R is called the reference force.…”

Section: The P 3 M Methodsmentioning

confidence: 99%

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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“…In particular, DG MOSFET with an intrinsic channel is considered to be the best candidate for device downscaling, as it possesses advantages such as (a) absence of the dopant fluctuation effect, which contributes to the variations of the threshold voltage and drive current [2][3][4][5][6][7][8][9][10] and (b) enhanced carrier mobility owing to the absence of depletion charges which can significantly contribute to the effective electric field, thus degrading the mobility [11]. However, intrinsic channel DG MOSFETs need to rely solely on gate work function to achieve multiple threshold voltages on a chip due to the absence of body doping, which is an efficient tool to adjust the threshold voltage in DG MOSFETs with doped channels [11,12].…”

Section: Introductionmentioning

confidence: 99%

Threshold Voltage Control through Layer Doping of Double Gate MOSFETs

Joseph¹,

George²,

Mathew³

2010

JSTS:Journal of Semiconductor Technology and Science

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Abstract-Double Gate MOSFETs (DG MOSFETs) with doping in one or two thin layers of an otherwise intrinsic channel are simulated to obtain the transport characteristics, threshold voltage and leakage current. Two different device structures-one with doping on two layers near the top and bottom oxide layers and another with doping on a single layer at the centre-are simulated and the variation of device parameters with a change in doping concentration and doping layer thickness is studied. It is observed that an n-doped layer in the channel reduces the threshold voltage and increases the drive current, when compared with a device of undoped channel. The reduction in the threshold voltage and increase in the drain current are found to increase with the thickness and the level of doping of the layer. The leakage current is larger than that of an undoped channel, but less than that of a uniformly doped channel. For a channel with p-doped layer, the threshold voltage increases with the level of doping and the thickness of the layer, accompanied with a reduction in drain current. The devices with doped middle layers and doped gate layers show almost identical behavior, apart from the slight difference in the drive current. The doping level and the thickness of the layers can be used as a tool to adjust the threshold voltage of the device indicating the possibility of easy fabrication of ICs having FETs of different threshold voltages, and the rest of the channel, being intrinsic having high mobility, serves to maintain high drive current in comparison with a fully doped channel.

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The effect of randomness in the distribution of impurity atoms on FET thresholds

Cited by 163 publications

References 11 publications

Monte Carlo Device Simulations

Monte Carlo Device Simulations

Quantum and Coulomb Effects in Nano Devices

Threshold Voltage Control through Layer Doping of Double Gate MOSFETs

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