Understanding and Mapping Sensitivity in MoS(2) Field-Effect-Transistor-Based Sensors

理解和绘制基于 MoS2 场效应晶体管的传感器的灵敏度图

阅读:3

Abstract

Sensors based on two-dimensional (2D) field-effect transistors (FETs) are extremely sensitive and can detect charged analytes with attomolar limits of detection (LOD). Despite some impressive LODs, the operating mechanisms and factors that determine the signal-to-noise ratio in 2D FET-based sensors remain poorly understood. These uncertainties, coupled with an expansive design space for sensor layout and analyte positioning, result in a field with many reported highlights but limited collective progress. Here, we provide insight into sensing mechanisms of 2D molybdenum disulfide (MoS(2)) FETs by realizing precise control over the position and charge of an analyte using a customized atomic force microscope (AFM), with the AFM tip acting as an analyte. The sensitivity of the MoS(2) FET channel is revealed to be nonuniform, manifesting sensitive hotspots with locations that are stable over time. When the charge of the analyte is varied, an asymmetry is observed in the device drain-current response, with analytes acting to turn the device off leading to a 2.5× increase in the signal-to-noise ratio (SNR). We developed a numerical model, applicable to all FET-based charge-detection sensors, that confirms our experimental observation and suggests an underlying mechanism. Further, extensive characterization of a set of different MoS(2) FETs under various analyte conditions, coupled with the numerical model, led to the identification of three distinct SNRs that peak with dependence on the layout and operating conditions used for a sensor. These findings reveal the important role of analyte position and coverage in determining the optimal operating bias conditions for maximal sensitivity in 2D FET-based sensors, which provides key insights for future sensor design and control.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。