Impacts of core gate thickness and Ge content variation on the performance of Si_1−xGe_x source/drain Si–nanotube JLFET

Abstract

In this paper, we investigate the impacts of variation in the core gate thickness and germanium content on the performance of a Si_1−xGe_x source/drain Si-nanotube junctionless field-effect transistor. A SiGe source/drain structure is combined with a core gate inside the nanotube to address and suppress the stringent issue of short-channel effects (SCEs). The effect of gate length, bias voltages, and Ge content on the subthreshold current, threshold voltage, and SCEs has also been studied by developing a compact analytical model including the quantum confinement effect. Our results highlight the utility of core gate and Si_1−xGe_x source/drain to provide an additional degree of freedom to control SCEs in the nanoscale regime.

Appendices

Appendix 1

$$ A_{n} = \frac{{\left( {V_{{\text{bi}}} + V_{{\text{ds}}} - V_{i} (r)} \right) - \left( {V_{{\text{bi}}} - V_{i} (r)} \right)\exp ( - \lambda_{n} L_{\text{g}} )}}{{2\sinh (\lambda_{n} L_{\text{g}} )J_{0} (\lambda_{n} r)}} $$

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$$ B_{n} = \frac{{V_{{\text{bi}}} - V_{i} (r) - A_{n} J_{0} (\lambda_{n} r)}}{{J_{0} (\lambda_{n} r)}} $$

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$$ C_{n} = - \frac{{\left( {V_{{\text{bi}}} + V_{{\text{ds}}} - V_{i} (r)} \right) - \left( {V_{{\text{bi}}} - V_{i} (r)} \right)\exp ( - \lambda_{n} L_{\text{g}} )}}{{2\sinh (\lambda_{n} L_{\text{g}} )J_{0} (\lambda_{n} r)}} $$

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$$ D_{n} = C_{n} - A_{n} \exp (\lambda_{n} L_{\text{g}} ) + B_{n} \exp ( - \lambda_{n} L_{\text{g}} ) $$

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Appendix 2

$$ \left( {k_{2} } \right)^{\prime }_{{L_{\text{g}} }} = 2\cosh \left( {\lambda_{n} L_{\text{g}} } \right)\left( {2V_{{\text{bi}}} + V_{{\text{ds}}} } \right) $$

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$$ \begin{array}{l} \left( {k_{1} k_{3} } \right)^{\prime }_{{L_{\text{g}} }} = 2\left( {\sinh^{2} \left( {\lambda_{n} L_{\text{g}} } \right) - 2\sinh \left( {\lambda_{n} L_{\text{g}} } \right) - 2} \right) \\ \times \;\left( {V_{{\text{bi}}}^{\text{2}} + V_{{\text{bi}}} V_{{\text{ds}}} } \right)\cosh \left( {\lambda_{n} L_{\text{g}} } \right) \\ + \;4\left( {V_{{\text{bi}}}^{\text{2}} + V_{{\text{bi}}} V_{{\text{ds}}} } \right)\sinh \left( {\lambda_{n} L_{\text{g}} } \right) \\ \times \;\left( {\sinh \left( {\lambda_{n} L_{\text{g}} } \right) - 1} \right)\cosh \left( {\lambda_{n} L_{\text{g}} } \right) \\ \end{array} $$

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$$ \left( {k_{2} } \right)^{\prime }_{{V_{{\text{ds}}} }} = 2\sinh \left( {\lambda_{n} L_{\text{g}} } \right) $$

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$$ \left( {k_{1} k_{3} } \right)^{\prime }_{{_{{V_{{\text{ds}}} }} }} = 2\left( {V_{{\text{bi}}} \sinh \left( {\lambda_{n} L_{\text{g}} } \right) - 2\left( {V_{{\text{bi}}} + V_{{\text{ds}}} } \right)} \right) $$

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