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Predictive 3-D Modeling of Parasitic Gate Capacitance in Gate-all-Around Cylindrical Silicon Nanowire MOSFETs

机译:全方位栅极圆柱形硅纳米线MOSFET中寄生栅极电容的预测3-D建模

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In this paper, an analytical model for parasitic gate capacitances in gate-all-around cylindrical silicon nanowire MOSFETs (SNWTs) is developed for the first time. A practical 3-D architecture of SNWTs with surrounding-gate cylindrical channel and source/drain extension regions is taken into account in the parasitic gate capacitance modeling. The parasitic gate capacitances of the SNWT are divided into four parts: 1) outer fringe capacitance $C_{rm of}$; 2) inner fringe capacitance $C_{rm if}$; 3) overlap capacitance $C_{rm ov}$; and 4) sidewall capacitance $C_{rm side}$. The 3-D capacitance system is calculated by useful methods such as the equivalent transformation and inversion of Schwarz–Christoffel mapping. The obtained model agrees well with the results of 3-D electrostatic numerical simulations. The results show that the proportion of parasitic gate capacitances in the total capacitance is increased in this gate-all-around architecture due to the ultrasmall dimension of the SNWT channel; thus, the proportion of the intrinsic capacitance is reduced. Among the capacitances, $C_{rm of}$ is found to be the largest contributor to the total parasitic gate capacitance in FO1 delay calculation, and $C_{rm side}$ manifests itself as a nonnegligible parasitic capacitance. The developed capacitance model can be easily incorporated into a compact core model of SNWTs for further device/circuit design optimizations with various device parameters.
机译:本文首次建立了全方位栅圆柱形硅纳米线MOSFET(SNWT)中寄生栅电容的分析模型。在寄生栅极电容建模中,考虑了具有环绕栅圆柱形沟道和源极/漏极扩展区的SNWTs的实用3-D架构。 SNWT的寄生栅极电容分为四个部分:1)外部边缘电容$ C_ {rm of} $; 2)内部边缘电容$ C_ {rm if} $; 3)重叠电容$ C_ {rm ov} $; 4)侧壁电容$ C_ {rm side} $。 3-D电容系统是通过有用的方法计算的,例如Schwarz-Christoffel映射的等效变换和反演。所获得的模型与3-D静电数值模拟的结果非常吻合。结果表明,由于SNWT通道的尺寸极小,因此在这种全栅结构中,寄生栅极电容在总电容中所占的比例有所增加。因此,固有电容的比例减小。在电容中,在FO1延迟计算中,$ C_ {rm of} $是总寄生栅极电容的最大贡献者,而$ C_ {rm side} $则表现为不可忽略的寄生电容。所开发的电容模型可以轻松地集成到SNWT的紧凑型核心模型中,以进一步优化具有各种器件参数的器件/电路设计。

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