Photonic chip breath analyzer

Gallego Martínez, Elieser Ernesto; Matías Maestro, Ignacio; Ruiz Zamarreño, Carlos

Photonic chip breath analyzer

dc.contributor.author	Gallego Martínez, Elieser Ernesto
dc.contributor.author	Matías Maestro, Ignacio
dc.contributor.author	Ruiz Zamarreño, Carlos
dc.contributor.department	Ingeniería Eléctrica, Electrónica y de Comunicación	es_ES
dc.contributor.department	Ingeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritza	eu
dc.contributor.department	Institute of Smart Cities - ISC	en
dc.contributor.funder	Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
dc.date.accessioned	2025-06-04T08:18:12Z
dc.date.available	2025-06-04T08:18:12Z
dc.date.issued	2025-06-03
dc.date.updated	2025-06-04T08:09:20Z
dc.description.abstract	This work introduces a novel single-package optical sensing device for multiple gas sensing, which is suitable for breath analysis applications. It is fabricated on a coverslip substrate via a sputtering technique and uses a planar waveguide configuration with lateral incidence of light. It features three sequentially ordered strips of different materials, which serve to increase the multivariate nature of the response of the device to different gases. For the proof-of-concept, the selected materials are indium tin oxide (ITO), tin oxide (SnO2), and chromium oxide III (Cr2O3), while the selected gases are nitric oxide (NO), acetylene (C2H2), and ammonia (NH3). The sensing mechanism is based on the hyperbolic mode resonance (HMR) effect, with the first-order resonance obtained for each strip located in the near infrared region. The multivariate response of the resonances and the correlation with the concentration of each gas allow training a machine learning (ML) model based on a nonlinear autoregressive neural network, enabling the accurate prediction of the concentration of each gas. The obtained limit of detection for all the gases was in the order of a few parts per billion. This innovative approach coined as the multivariate optical resonances spectroscopy demonstrates the potential of HMR-based optical sensors in combination with ML techniques for ultra-sensitive multi-gas detection applications using a single device.	en
dc.description.sponsorship	This work was supported by the Agencia Estatal de Investigación research projects, Spain (Grant Nos. PID2019-106231RB-I00 and PDC2023-145831-I00), and by the Institute Smart Cities of the Public University of Navarra Ph.D. student grants, Spain (Grant No. 401).
dc.format.mimetype	application/pdf	en
dc.identifier.citation	Gallego Martínez, E. E., Matías, I. R., Ruiz Zamarreño, C. (2025). Photonic chip breath analyzer. Photonic Sensors, 15(3), 1-17. https://doi.org/10.1007/s13320-025-0771-3.
dc.identifier.doi	10.1007/s13320-025-0771-3
dc.identifier.issn	1674-9251
dc.identifier.uri	https://academica-e.unavarra.es/handle/2454/54205
dc.language.iso	eng
dc.publisher	SpringerOpen
dc.relation.ispartof	Photonic Sensors (2025), vol. 15, núm. 3, 250317
dc.relation.projectID	info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-106231RB-I00/ES/
dc.relation.projectID	info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PDC2023-145831-I00/ES/
dc.relation.publisherversion	https://doi.org/10.1007/s13320-025-0771-3
dc.rights	© The Author(s) 2025. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License.
dc.rights.accessRights	info:eu-repo/semantics/openAccess
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/
dc.subject	Gas sensor	en
dc.subject	Hyperbolic mode resonance	en
dc.subject	Multivariate optical resonances spectroscopy	en
dc.title	Photonic chip breath analyzer	en
dc.type	info:eu-repo/semantics/article
dc.type.version	info:eu-repo/semantics/publishedVersion
dspace.entity.type	Publication
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