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13.04.2024 | Review Paper

Review on data-driven approaches for improving the selectivity of MOX-sensors

verfasst von: Mohand Djeziri, Samir Benmoussa, Marc Bendahan, Jean-Luc Seguin

Erschienen in: Microsystem Technologies | Ausgabe 7/2024

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Abstract

Metal Oxide sensors, thanks to their low cost, small size and wide recovery, are increasingly used in various industrial applications for the detection of gases and gas mixtures. However, due to their operating principle, these sensors are not selective enough, thereby preventing the expansion of their fields of application. The scientific community has tackled this issue by proposing methods and algorithms to improve the selectivity of these sensors. This paper provides an overview of existing approaches for detection and identification in the general case, as well as those used in the context of gas discrimination. A discussion of the methods used and the results announced is proposed to highlight their performance and to identify promising research directions and perspectives to allow a significant advance in research in this field.

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Titel: Review on data-driven approaches for improving the selectivity of MOX-sensors
verfasst von: Mohand Djeziri
Samir Benmoussa
Marc Bendahan
Jean-Luc Seguin
Publikationsdatum: 13.04.2024
Verlag: Springer Berlin Heidelberg
Erschienen in: Microsystem Technologies / Ausgabe 7/2024
Print ISSN: 0946-7076
Elektronische ISSN: 1432-1858
DOI: https://doi.org/10.1007/s00542-024-05622-1

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