Journal article
Carbon SH-SAW-Based Electronic Nose to Discriminate and Classify Sub-ppm NO2
University of Alcalá1
Universidad Autónoma de Madrid2
Instituto de Cerámica y Vidrio3
Center for Intelligent Drug Delivery and Sensing Using Microcontainers and Nanomechanics, Department of Health Technology, Technical University of Denmark4
Department of Health Technology, Technical University of Denmark5
Universidad Nacional Autónoma de México6
CSIC7
In this research, a compact electronic nose (e-nose) based on a shear horizontal surface acoustic wave (SH-SAW) sensor array is proposed for the NO2 detection, classification and discrimination among some of the most relevant surrounding toxic chemicals, such as carbon monoxide (CO), ammonia (NH3), benzene (C6H6) and acetone (C3H6O).
Carbon-based nanostructured materials (CBNm), such as mesoporous carbon (MC), reduced graphene oxide (rGO), graphene oxide (GO) and polydopamine/reduced graphene oxide (PDA/rGO) are deposited as a sensitive layer with con-trolled spray and Langmuir–Blodgett techniques. We show the potential of the mass loading and elastic effects of the CBNm to enhance the detection, the classification and the discrimination of NO2 among different gases by using Machine Learning (ML) techniques (e.g., PCA, LDA and KNN).
The small dimensions and low cost make this analytical system a promising candidate for the on-site discrimination of sub-ppm NO2.
Language: | English |
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Publisher: | MDPI |
Year: | 2022 |
Pages: | 1261 |
ISSN: | 14243210 and 14248220 |
Types: | Journal article |
DOI: | 10.3390/s22031261 |
ORCIDs: | Badillo-Ramirez, Isidro , 0000-0001-8024-2541 , 0000-0003-2554-3119 and 0000-0001-6937-9838 |