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基于石墨烯电解质门控场效应晶体管的大规模传感器系统。

Large-scale sensor systems based on graphene electrolyte-gated field-effect transistors.

机构信息

Department of Electrical Engineering & Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

出版信息

Analyst. 2016 Apr 25;141(9):2704-11. doi: 10.1039/c5an02328a.

Abstract

This work reports a novel graphene electrolyte-gated field-effect transistor (EGFET) array architecture along with a compact, self-contained, and inexpensive measurement system that allows DC characterization of hundreds of graphene EGFETs as a function of VDS and VGS within a matter of minutes. We develop a reliable graphene EGFET fabrication process capable of producing 100% yield for a sample size of 256 devices. Large sample size statistical analysis of graphene EGFET electrical performance is performed for the first time. This work develops a compact piecewise DC model for graphene EGFETs that is shown capable of fitting 87% of IDSvs. VGS curves with a mean percent error of 7% or less. The model is used to extract variations in device parameters such as mobility, contact resistance, minimum carrier concentration, and Dirac point. Correlations in variations are presented. Lastly, this work presents a framework for application-specific optimization of large-scale sensor designs based on graphene EGFETs.

摘要

本工作报道了一种新型的石墨烯电解质门控场效应晶体管(EGFET)阵列结构,以及一种紧凑、自包含且廉价的测量系统,可在数分钟内实现数百个石墨烯 EGFET 的 DC 特性测试,包括 VDS 和 VGS 的函数关系。我们开发了一种可靠的石墨烯 EGFET 制造工艺,可在 256 个器件的样本大小下实现 100%的产量。这是首次对石墨烯 EGFET 的电性能进行大规模样本的统计学分析。本工作为石墨烯 EGFET 开发了一种紧凑的分段式 DC 模型,该模型能够拟合 87%的 IDSvs. VGS 曲线,平均误差百分比在 7%或以下。该模型用于提取器件参数的变化,如迁移率、接触电阻、最小载流子浓度和狄拉克点。还给出了参数变化之间的相关性。最后,本工作提出了一种基于石墨烯 EGFET 的大规模传感器设计的特定应用优化框架。

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