首页> 外文期刊>Applied Physics Letters >Computational study of heterojunction graphene nanoribbon tunneling transistors with p-d orbital tight-binding method
【24h】

Computational study of heterojunction graphene nanoribbon tunneling transistors with p-d orbital tight-binding method

机译:p-d轨道紧密结合法计算异质结石墨烯纳米带隧穿晶体管的计算研究

获取原文
获取原文并翻译 | 示例
           

摘要

The graphene nanoribbon (GNR) tunneling field effect transistor (TFET) has been a promising candidate for a future low power logic device due to its sub-60 mV/dec subthreshold characteristic and its superior gate control on the channel electrons due to its one-dimensional nature. Even though many theoretical studies have been carried out, it is not clear that GNR TFETs would outperform conventional silicon metal oxide semiconductor field effect transistors (MOSFETs). With rigorous atomistic simulations using the p/d orbital tight-binding model, this study focuses on the optimization of GNR TFETs by tuning the doping density and the size of GNRs. It is found that the optimized GNR TFET can operate at a half of the supply voltage of silicon nanowire MOSFETs in the ballistic limit. However, a study on the effects of edge roughness on the performance of the optimized GNR TFET structure reveals that experimentally feasible edge roughness can deteriorates the on-current performance if the off-current is normalized with the low power requirement specified in the international technology roadmap for semiconductors.
机译:石墨烯纳米带(GNR)隧穿场效应晶体管(TFET)由于其低于60 mV / dec的亚阈值特性以及对沟道电子的优异栅极控制能力而成为未来低功耗逻辑器件的有希望的候选者。尺寸性质。尽管已经进行了许多理论研究,但不清楚GNR TFET是否会胜过传统的硅金属氧化物半导体场效应晶体管(MOSFET)。利用p / d轨道紧密结合模型进行严格的原子模拟,本研究着重于通过调整GNR的掺杂密度和尺寸来优化GNR TFET。发现优化的GNR TFET可以在弹道极限内以硅纳米线MOSFET的电源电压的一半工作。但是,对边缘粗糙度对优化的GNR TFET结构性能的影响的研究表明,如果通过国际技术路线图中指定的低功耗要求对截止电流进行归一化,则实验上可行的边缘粗糙度会降低导通电流性能。用于半导体。

著录项

  • 来源
    《Applied Physics Letters》 |2014年第24期|243113.1-243113.4|共4页
  • 作者单位

    Network for Computational Nanotechnology, Purdue University, West Lafayette, Indiana 47907, USA;

    Integrated Systems Laboratory, Gloriastrasse 35, ETH Zuerich, 8092 Zuerich, Switzerland;

    Department of Electrical and Computer Engineering, The University of Alabama in Huntsville, Huntsville, Alabama 35899, USA;

    Network for Computational Nanotechnology, Purdue University, West Lafayette, Indiana 47907, USA;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号