2016
DOI: 10.1109/tnano.2015.2493543
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Computationally Efficient Multiple-Independent-Gate Device Model

Abstract: Abstract-Nanowire Field Effect Transistors (FETs) with multiple independent gates around a silicon channel feature ultimate gate control and are regarded as promising candidates for next generation transistors. Being inherently more complex than conventional gate-all-around nanowire FETs, they require longer simulation times, especially with numerical simulations. We present a new model enabling the efficient computation of voltages and current in modular semiconductor structures with an arbitrary number of in… Show more

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Cited by 8 publications
(1 citation statement)
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References 34 publications
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“…The reason is that the analytical expression for the drain current corresponding to the thermionic emission with a shifted Fermi level and including energy-independent transmission can be used at small bias, when the contribution of thermally excited electrons in the total current is large enough [24]. The analytical current calculations on the basis of drift-diffusion model do not properly take into account the effect of SB tunneling and BTBT on the electron transport [25], [26]. The empirical continuous compact dc model based on a set of empirical fitting parameters is reliable in the framework of experimental data [27], but it cannot be used for predictions.…”
Section: Introductionmentioning
confidence: 99%
“…The reason is that the analytical expression for the drain current corresponding to the thermionic emission with a shifted Fermi level and including energy-independent transmission can be used at small bias, when the contribution of thermally excited electrons in the total current is large enough [24]. The analytical current calculations on the basis of drift-diffusion model do not properly take into account the effect of SB tunneling and BTBT on the electron transport [25], [26]. The empirical continuous compact dc model based on a set of empirical fitting parameters is reliable in the framework of experimental data [27], but it cannot be used for predictions.…”
Section: Introductionmentioning
confidence: 99%