Improved performance of sub-10-nm band-to-band tunneling n-i-n graphene nanoribbon field-effect transistors using underlap engineering: A quantum simulation study

Journal of Physics and Chemistry of Solids(2022)

引用 10|浏览1
暂无评分
摘要
In this study, we investigated the effect of underlapping on improving the performance of sub-10-nm band-to-band tunneling (BTBT) double-gate (DG) armchair-edge graphene nanoribbon field-effect transistors (GNRFETs). BTBT was adopted as an operating regime in n-i-n GNRFETs, where p-type doping is not required unlike the conventional p-i-n tunnel FETs. The quantum model employed was based on self-consistently solving the non-equilibrium Green's function and Poisson's equation while considering ballistic transport. Quantum simulation studies were conducted to analyze the impacts of underlapping on direct source-to-drain tunneling and BTBT, which are the dominant quantum mechanical mechanisms in n-i-n GNRFETs that operate in the BTBT regime, where the ambipolar property is induced by thermionic emission. The underlap-induced dilation in the potential barrier dramatically improved the device switching performance according to atomistic simulations. The computational investigation also considered how increasing the underlap length boosted the performance and scaling capacity of the BTBT GNRFETs. Nanodevices with sub-10-nm gate length and an underlap structure exhibited an improved sub-thermionic swing factor, reduced leakage current, and higher current ratios. Despite the slightly reduced on-current due to the underlap-induced dilation in BTBT windows, the recorded improvements in terms of the subthreshold swing, leakage current, and current ratio mean that the sub-10-nm DG BTBT n-i-n GNRFETs with an underlap configuration can potentially be used as steep ultra-scaled transistors for ultra-low power applications.
更多
查看译文
关键词
Armchair GNR,Ballistic transport,Quantum simulation,Underlap,FETs,Band-to-band tunneling,Ultra-scaling,Sub-thermionic subthreshold swing,Ultra-low power applications
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要