Graphene/MoS₂ Thin Film Based Two Dimensional Barristors With Tunable Schottky Barrier for Sensing Applications
In this work, a large-area MoS 2 /graphene barristor device, with an electrically tunable Schottky barrier height, has been studied for detection of various gaseous analytes. The Schottky barrier height could be modulated by over 0.65 eV, allowing the drain current to be tuned by many orders of magn...
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Published in: | IEEE sensors journal Vol. 21; no. 23; pp. 26549 - 26555 |
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Main Authors: | , , , , |
Format: | Journal Article |
Language: | English |
Published: |
New York
IEEE
01-12-2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects: | |
Online Access: | Get full text |
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Summary: | In this work, a large-area MoS 2 /graphene barristor device, with an electrically tunable Schottky barrier height, has been studied for detection of various gaseous analytes. The Schottky barrier height could be modulated by over 0.65 eV, allowing the drain current to be tuned by many orders of magnitude. Using diluted NO 2 and NH 3 gases as analytes, the performance of the barristor device was compared with individual MoS 2 and graphene based planar FETs, where the barristor device outperformed its counterparts in terms of response magnitude and limit of detection. Due to the atomically thin nature of MoS 2 and graphene, electric field applied to one material could not be fully screened from the other one, which allowed both materials to act as a composite structure when analyte molecules interacted with the barristor device. This apparently reversed the dopant behavior of NO 2 and NH 3 , while increasing the device sensitivity through subthreshold operation. Both conductance and capacitance based measurements are presented to highlight the charge transfer and barrier height modulation, to support the unique sensing mechanism observed in the 2D barristor device. A lower limit of detection in low ppb is established for NO 2 and low ppm for NH 3 , which could be further tuned by altering gate-drain bias conditions. |
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ISSN: | 1530-437X 1558-1748 |
DOI: | 10.1109/JSEN.2021.3120792 |