| Issue |
EPJ Web Conf.
Volume 143, 2017
EFM16 – Experimental Fluid Mechanics 2016
|
|
|---|---|---|
| Article Number | 02068 | |
| Number of page(s) | 4 | |
| Section | Contributions | |
| DOI | https://doi.org/10.1051/epjconf/201714302068 | |
| Published online | 12 May 2017 | |
https://doi.org/10.1051/epjconf/201714302068
Graphene field-effect transistor application for flow sensing
1 Gdańsk University of Technology, Faculty of Electrical and Control Engineering, 80-233 Gdańsk, Poland
2 Rzeszów University of Technology, Faculty of Electrical and Computer Engineering, 35-959 Rzeszów, Poland
3 AGH University of Science and Technology, Faculty of Geology, Geophysics and Environmental Protection, 30-059 Kraków, Poland
4 AGH University of Science and Technology, Faculty of Physics and Applied Computer Science, 30-059 Kraków, Poland
* Corresponding author: maciej.luszczek@pg.gda,pl
Published online: 12 May 2017
Microflow sensors offer great potential for applications in microfluidics and lab-on-a-chip systems. However, thermal-based sensors, which are commonly used in modern flow sensing technology, are mainly made of materials with positive temperature coefficients (PTC) and suffer from a self-heating effect and slow response time. Therefore, the design of novel devices and careful selection of materials are required to improve the overall flow sensor performance. In this work we propose graphene field-effect transistor (GFET) to be used as microflow sensor. Temperature distribution in graphene channel was simulated and the analysis of heat convection was performed to establish the relation between the fluidic flow velocity and the temperature gradient. It was shown that the negative temperature coefficient (NTC) of graphene could enable the self-protection of the device and should minimize sensing error from currentinduced heating. It was also argued that the planar design of the GFET sensor makes it suitable for the real application due to supposed mechanical stability of such a construction.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.