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使用作为指数转换器的单层浮动栅极、全耗尽 SOI MOSFET 进行分子感应。

Molecular sensing using monolayer floating gate, fully depleted SOI MOSFET acting as an exponential transducer.

机构信息

Center for Solid State Electronics Research, Science and Engineering of Materials, Arizona State University, Tempe, AZ 85287, USA.

出版信息

ACS Nano. 2010 Feb 23;4(2):999-1011. doi: 10.1021/nn900901f.

DOI:10.1021/nn900901f
PMID:20085285
Abstract

Field-effect transistor-based chemical sensors fall into two broad categories based on the principle of signal transduction-chemiresistor or Schottky-type devices and MOSFET or inversion-type devices. In this paper, we report a new inversion-type device concept-fully depleted exponentially coupled (FDEC) sensor, using molecular monolayer floating gate fully depleted silicon on insulator (SOI) MOSFET. Molecular binding at the chemical-sensitive surface lowers the threshold voltage of the device inversion channel due to a unique capacitive charge-coupling mechanism involving interface defect states, causing an exponential increase in the inversion channel current. This response of the device is in opposite direction when compared to typical MOSFET-type sensors, wherein inversion current decreases in a conventional n-channel sensor device upon addition of negative charge to the chemical-sensitive device surface. The new sensor architecture enables ultrahigh sensitivity along with extraordinary selectivity. We propose the new sensor concept with the aid of analytical equations and present results from our experiments in liquid phase and gas phase to demonstrate the new principle of signal transduction. We present data from numerical simulations to further support our theory.

摘要

基于信号转导原理,场效应晶体管(FET)化学传感器可分为两大类——电阻型(即压阻式)和场效应晶体管型(FET)。在本文中,我们提出了一种新型的场效应晶体管型传感器概念——全耗尽指数耦合(FDEC)传感器,该传感器采用分子单层浮栅全耗尽绝缘体上硅(SOI)MOSFET。在化学敏感表面发生分子结合时,由于涉及界面缺陷态的独特电容电荷耦合机制,器件反型通道的阈值电压会降低,从而导致反型通道电流呈指数增长。与典型的 MOSFET 型传感器相比,该器件的这种响应方向相反,在传统的 n 沟道传感器器件中,当化学敏感器件表面增加负电荷时,反型电流会减小。新的传感器结构可实现超高灵敏度和非凡的选择性。我们借助分析方程提出了新的传感器概念,并通过在液相和气相中的实验结果展示了新的信号转导原理。我们还提供了数值模拟数据来进一步支持我们的理论。

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