An electronic nose using a single graphene FET and machine learning for water, methanol, and ethanol
Open Access
- 18 May 2020
- journal article
- research article
- Published by Springer Science and Business Media LLC in Microsystems & Nanoengineering
- Vol. 6 (1), 1-13
- https://doi.org/10.1038/s41378-020-0161-3
Abstract
The poor gas selectivity problem has been a long-standing issue for miniaturized chemical-resistor gas sensors. The electronic nose (e-nose) was proposed in the 1980s to tackle the selectivity issue, but it required top-down chemical functionalization processes to deposit multiple functional materials. Here, we report a novel gas-sensing scheme using a single graphene field-effect transistor (GFET) and machine learning to realize gas selectivity under particular conditions by combining the unique properties of the GFET and e-nose concept. Instead of using multiple functional materials, the gas-sensing conductivity profiles of a GFET are recorded and decoupled into four distinctive physical properties and projected onto a feature space as 4D output vectors and classified to differentiated target gases by using machine-learning analyses. Our single-GFET approach coupled with trained pattern recognition algorithms was able to classify water, methanol, and ethanol vapors with high accuracy quantitatively when they were tested individually. Furthermore, the gas-sensing patterns of methanol were qualitatively distinguished from those of water vapor in a binary mixture condition, suggesting that the proposed scheme is capable of differentiating a gas from the realistic scenario of an ambient environment with background humidity. As such, this work offers a new class of gas-sensing schemes using a single GFET without multiple functional materials toward miniaturized e-noses.Keywords
This publication has 46 references indexed in Scilit:
- A Survey on Gas Sensing TechnologySensors, 2012
- Highly sensitive methanol chemical sensor based on undoped silver oxide nanoparticles prepared by a solution methodMicrochimica Acta, 2012
- Development of SiC-FET methanol sensorSensors and Actuators B: Chemical, 2011
- Charged-impurity scattering in grapheneNature Physics, 2008
- Higher-Order Chemical SensingChemical Reviews, 2008
- A self-consistent theory for graphene transportProceedings of the National Academy of Sciences of the United States of America, 2007
- Detection of individual gas molecules adsorbed on grapheneNature Materials, 2007
- Data analysis for electronic nose systemsMicrochimica Acta, 2006
- Automated odor-sensing system based on plural semiconductor gas sensors and computerized pattern recognition techniquesAnalytica Chimica Acta, 1987
- Analysis of discrimination mechanisms in the mammalian olfactory system using a model noseNature, 1982