Deep-learning powered whispering gallery mode sensor based on multiplexed imaging at fixed frequency

During the last decades the whispering gallery mode based sensors have become a prominent solution for label-free sensing of various physical and chemical parameters. At the same time, the widespread utilization of the approach is hindered by the restricted applicability of the known configurations...

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Autores principales:	Saetchnikov Anton V., Tcherniavskaia Elina A., Saetchnikov Vladimir A., Ostendorf Andreas
Formato:	article
Lenguaje:	EN
Publicado:	Institue of Optics and Electronics, Chinese Academy of Sciences 2020
Materias:	optical microresonator sensing machine learning whispering gallery mode multiplexing Optics. Light QC350-467
Acceso en línea:	https://doaj.org/article/10f70d43f74a4783a489ca0f627ac354
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spelling	oai:doaj.org-article:10f70d43f74a4783a489ca0f627ac3542021-11-10T09:45:13ZDeep-learning powered whispering gallery mode sensor based on multiplexed imaging at fixed frequency2096-457910.29026/oea.2020.200048https://doaj.org/article/10f70d43f74a4783a489ca0f627ac3542020-11-01T00:00:00Zhttp://www.oejournal.org/article/doi/10.29026/oea.2020.200048https://doaj.org/toc/2096-4579During the last decades the whispering gallery mode based sensors have become a prominent solution for label-free sensing of various physical and chemical parameters. At the same time, the widespread utilization of the approach is hindered by the restricted applicability of the known configurations for ambient variations quantification outside the laboratory conditions and their low affordability, where necessity on the spectrally-resolved data collection is among the main limiting factors. In this paper we demonstrate the first realization of an affordable whispering gallery mode sensor powered by deep learning and multi-resonator imaging at a fixed frequency. It has been shown that the approach enables refractive index unit (RIU) prediction with an absolute error at 3×10-6 level for dynamic range of the RIU variations from 0 to 2×10-3 with temporal resolution of several milliseconds and instrument-driven detection limit of 3×10-5. High sensing accuracy together with instrumental affordability and production simplicity places the reported detector among the most cost-effective realizations of the whispering gallery mode approach. The proposed solution is expected to have a great impact on the shift of the whole sensing paradigm away from the model-based and to the flexible self-learning solutions.Saetchnikov Anton V.Tcherniavskaia Elina A.Saetchnikov Vladimir A.Ostendorf AndreasInstitue of Optics and Electronics, Chinese Academy of Sciencesarticleoptical microresonatorsensingmachine learningwhispering gallery modemultiplexingOptics. LightQC350-467ENOpto-Electronic Advances, Vol 3, Iss 11, Pp 200048-1-200048-9 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	optical microresonator sensing machine learning whispering gallery mode multiplexing Optics. Light QC350-467
spellingShingle	optical microresonator sensing machine learning whispering gallery mode multiplexing Optics. Light QC350-467 Saetchnikov Anton V. Tcherniavskaia Elina A. Saetchnikov Vladimir A. Ostendorf Andreas Deep-learning powered whispering gallery mode sensor based on multiplexed imaging at fixed frequency
description	During the last decades the whispering gallery mode based sensors have become a prominent solution for label-free sensing of various physical and chemical parameters. At the same time, the widespread utilization of the approach is hindered by the restricted applicability of the known configurations for ambient variations quantification outside the laboratory conditions and their low affordability, where necessity on the spectrally-resolved data collection is among the main limiting factors. In this paper we demonstrate the first realization of an affordable whispering gallery mode sensor powered by deep learning and multi-resonator imaging at a fixed frequency. It has been shown that the approach enables refractive index unit (RIU) prediction with an absolute error at 3×10-6 level for dynamic range of the RIU variations from 0 to 2×10-3 with temporal resolution of several milliseconds and instrument-driven detection limit of 3×10-5. High sensing accuracy together with instrumental affordability and production simplicity places the reported detector among the most cost-effective realizations of the whispering gallery mode approach. The proposed solution is expected to have a great impact on the shift of the whole sensing paradigm away from the model-based and to the flexible self-learning solutions.
format	article
author	Saetchnikov Anton V. Tcherniavskaia Elina A. Saetchnikov Vladimir A. Ostendorf Andreas
author_facet	Saetchnikov Anton V. Tcherniavskaia Elina A. Saetchnikov Vladimir A. Ostendorf Andreas
author_sort	Saetchnikov Anton V.
title	Deep-learning powered whispering gallery mode sensor based on multiplexed imaging at fixed frequency
title_short	Deep-learning powered whispering gallery mode sensor based on multiplexed imaging at fixed frequency
title_full	Deep-learning powered whispering gallery mode sensor based on multiplexed imaging at fixed frequency
title_fullStr	Deep-learning powered whispering gallery mode sensor based on multiplexed imaging at fixed frequency
title_full_unstemmed	Deep-learning powered whispering gallery mode sensor based on multiplexed imaging at fixed frequency
title_sort	deep-learning powered whispering gallery mode sensor based on multiplexed imaging at fixed frequency
publisher	Institue of Optics and Electronics, Chinese Academy of Sciences
publishDate	2020
url	https://doaj.org/article/10f70d43f74a4783a489ca0f627ac354
work_keys_str_mv	AT saetchnikovantonv deeplearningpoweredwhisperinggallerymodesensorbasedonmultiplexedimagingatfixedfrequency AT tcherniavskaiaelinaa deeplearningpoweredwhisperinggallerymodesensorbasedonmultiplexedimagingatfixedfrequency AT saetchnikovvladimira deeplearningpoweredwhisperinggallerymodesensorbasedonmultiplexedimagingatfixedfrequency AT ostendorfandreas deeplearningpoweredwhisperinggallerymodesensorbasedonmultiplexedimagingatfixedfrequency
_version_	1718440076578390016

Deep-learning powered whispering gallery mode sensor based on multiplexed imaging at fixed frequency

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