Multimode sensing based on optical microcavities

Yanran Wu, Bing Duan, Changhong Li, Daquan Yang

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PDF(2393 KB)
Front. Optoelectron. ›› 2023, Vol. 16 ›› Issue (3) : 29. DOI: 10.1007/s12200-023-00084-1
REVIEW ARTICLE
REVIEW ARTICLE

Multimode sensing based on optical microcavities

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Abstract

Optical microcavities have the ability to confine photons in small mode volumes for long periods of time, greatly enhancing light-matter interactions, and have become one of the research hotspots in international academia. In recent years, sensing applications in complex environments have inspired the development of multimode optical microcavity sensors. These multimode sensors can be used not only for multi-parameter detection but also to improve measurement precision. In this review, we introduce multimode sensing methods based on optical microcavities and present an overview of the multimode single/multi-parameter optical microcavities sensors. Expected further research activities are also put forward.

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Keywords

Optical microcavity / Multimode sensing / Multiparameter measurement / Sensing mechanisms

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Yanran Wu, Bing Duan, Changhong Li, Daquan Yang. Multimode sensing based on optical microcavities. Front. Optoelectron., 2023, 16(3): 29 https://doi.org/10.1007/s12200-023-00084-1

References

[1]
Zhi, Y., Yu, X., Gong, Q., Yang, L., Xiao, Y.: Single nanoparticle detection using optical microcavities. Adv. Mater. 29(12), 1604920 (2017)
CrossRef Google scholar
[2]
Vollmer, F., Yang, L.: Label-free detection with high-Q microcavities: a review of biosensing mechanisms for integrated devices. Nanophotonics 1(3–4), 267–291 (2012)
CrossRef Google scholar
[3]
Fan, X.: Advanced photonic structures for biological and chemical detection. Springer, New York (2009)
CrossRef Google scholar
[4]
Wang, K., Gao, Y.P., Jiao, R., Wang, C.: Recent progress on optomagnetic coupling and optical manipulation based on cavity-optomagnonics. Front. Phys. 17(4), 42201 (2022)
CrossRef Google scholar
[5]
Artar, A., Yanik, A.A., Altug, H.: Fabry–Pérot nanocavities in multilayered plasmonic crystals for enhanced biosensing. Appl. Phys. Lett. 95(5), 051105 (2009)
CrossRef Google scholar
[6]
Li, X., Chen, N., Zhou, X., Gong, P., Wang, S., Zhang, Y., Zhao, Y.: A review of specialty fiber biosensors based on interferometer configuration. J. BiophotonicsBiophotonics 14(6), e202100068 (2021)
CrossRef Google scholar
[7]
Rho, D., Breaux, C., Kim, S.: Label-free optical resonator-based biosensors. Sensors (Basel) 20(20), 5901 (2020)
CrossRef Google scholar
[8]
Tabassum, S., Kumar, R.: Advances in fiber-optic technology for point-of-care diagnosis and in vivo biosensing. Adv. Mater. Technol. 5(5), 1900792 (2020)
CrossRef Google scholar
[9]
Chen, C., Wang, J.: Optical biosensors: an exhaustive and comprehensive review. Analyst (Lond.) 145(5), 1605–1628 (2020)
CrossRef Google scholar
[10]
Yi, L., Li, C.: Simulation research on blood detection sensing with parity-time symmetry structure. Crystals (Basel) 11(9), 1030 (2021)
CrossRef Google scholar
[11]
Nagarajan, K., Thomas, A., Ebbesen, T.W.: Chemistry under vibrational strong coupling. J. Am. Chem. Soc. 143(41), 16877–16889 (2021)
CrossRef Google scholar
[12]
Li, T.E., Cui, B., Subotnik, J.E., Nitzan, A.: Molecular polaritonics: chemical dynamics under strong light-matter coupling. Annu. Rev. Phys. Chem. Rev. Phys. Chem. 73(1), 43–71 (2022)
CrossRef Google scholar
[13]
Dong, H., Zhang, C., Liu, X., Yao, J., Zhao, Y.S.: Materials chemistry and engineering in metal halide perovskite lasers. Chem. Soc. Rev. 49(3), 951–982 (2020)
CrossRef Google scholar
[14]
Wang, K., Wang, H., Wu, X.Y., Zhang, Y., Yang, D., Jiao, R., Wang, C.: Ultrasound sensing using packaged microsphere cavity in the underwater environment. Sensors (Basel) 22(11), 4190 (2022)
CrossRef Google scholar
[15]
Xu, X., Chen, W., Zhao, G., Li, Y., Lu, C., Yang, L.: Wireless whispering-gallery-mode sensor for thermal sensing and aerial mapping. Light Sci. Appl. 7(1), 62 (2018)
CrossRef Google scholar
[16]
Liu, N., Shi, L., Zhu, S., Xu, X., Yuan, S., Zhang, X.: Whispering gallery modes in a single silica microparticle attached to an optical microfiber and their application for highly sensitive displacement sensing. Opt. Express 26(1), 195–203 (2018)
CrossRef Google scholar
[17]
Chen, L.H., Chan, C.C., Menon, R., Balamurali, P., Wong, W.C., Ang, X.M., Hu, P.B., Shaillender, M., Neu, B., Zu, P., Tou, Z.Q., Poh, C.L., Leong, K.C.: Fabry–Perot fiber-optic immunosensor based on suspended layer-by-layer (chitosan/polystyrene sulfonate) membrane. Sens. Actuators B Chem. 188, 185–192 (2013)
CrossRef Google scholar
[18]
Lyu, S., Wu, Z., Shi, X., Wu, Q.: Optical fiber biosensors for protein detection: a review. In Photonics 9(12), 987 (2022)
CrossRef Google scholar
[19]
Vollmer, F., Arnold, S., Keng, D.: Single virus detection from the reactive shift of a whispering-gallery mode. Proc. Natl. Acad. Sci. U.S.A. 105(52), 20701–20704 (2008)
CrossRef Google scholar
[20]
Baaske, M.D., Vollmer, F.: Optical observation of single atomic ions interacting with plasmonic nanorods in aqueous solution. Nat. Photonics 10(11), 733–739 (2016)
CrossRef Google scholar
[21]
Dantham, V.R., Holler, S., Barbre, C., Keng, D., Kolchenko, V., Arnold, S.: Label-free detection of single protein using a nanoplasmonic-photonic hybrid microcavity. Nano Lett. 13(7), 3347–3351 (2013)
CrossRef Google scholar
[22]
Yang, D.Q., Duan, B., Liu, X., Wang, A.Q., Li, X.G., Ji, Y.F.: Photonic crystal nanobeam cavities for nanoscale optical sensing: a review. Micromachines (Basel) 11(1), 72 (2020)
CrossRef Google scholar
[23]
Xia, J., Qiao, Q., Zhou, G., Chau, F.S., Zhou, G.: Opto-mechanical photonic crystal cavities for sensing application. Appl. Sci. (Basel) 10(20), 7080 (2020)
CrossRef Google scholar
[24]
Qiao, Q., Xia, J., Lee, C., Zhou, G.: Applications of photonic crystal nanobeam cavities for sensing. Micromachines (Basel) 9(11), 541 (2018)
CrossRef Google scholar
[25]
Wu, Y., Duan, B., Song, J., Tian, H., Chen, J.H., Yang, D., Huang, S.: Simultaneous temperature and pressure sensing based on a single optical resonator. Opt. Express 31(12), 18851–18861 (2023)
CrossRef Google scholar
[26]
Yang, D.Q., Chen, J.H., Cao, Q.T., Duan, B., Chen, H.J., Yu, X.C., Xiao, Y.F.: Operando monitoring transition dynamics of responsive polymer using optofluidic microcavities. Light Sci. Appl. 10(1), 128 (2021)
CrossRef Google scholar
[27]
Liao, J., Yang, L.: Optical whispering-gallery mode barcodes for high-precision and wide-range temperature measurements. Light Sci. Appl. 10(1), 32 (2021)
CrossRef Google scholar
[28]
Duan, B., Zou, H., Chen, J.H., Ma, C.H., Zhao, X., Zheng, X., Wang, C., Liu, L., Yang, D.: High-precision whispering gallery microsensors with ergodic spectra empowered by machine learning. Photon. Res. 10(10), 2343–2348 (2022)
CrossRef Google scholar
[29]
Chen, Z., Guo, Z., Mu, X., Li, Q., Wu, X., Fu, H.Y.: Packaged microbubble resonator optofluidic flow rate sensor based on Bernoulli Effect. Opt. Express 27(25), 36932–36940 (2019)
CrossRef Google scholar
[30]
Zhan, X., Liu, Y., Yang, K.L., Luo, D.: State-of-the-art development in liquid crystal biochemical sensors. Biosensors (Basel) 12(8), 577 (2022)
CrossRef Google scholar
[31]
Mathew, J., Schneller, O., Polyzos, D., Havermann, D., Carter, R.M., MacPherson, W.N., Hand, D.P., Maier, R.R.J.: In-fiber Fabry–Perot cavity sensor for high-temperature applications. J. Lightwave Technol. 33(12), 2419–2425 (2015)
CrossRef Google scholar
[32]
Johari, M.A.M., Khudus, M.I.M.A., Jali, M.H.B., Al Noman, A., Harun, S.W.: Effect of size on single and double optical microbottle resonator humidity sensors. Sens. Actuators A Phys. 284, 286–291 (2018)
CrossRef Google scholar
[33]
Zhang, Y.N., Zhu, N., Gao, P., Zhao, Y.: Magnetic field sensor based on ring WGM resonator infiltrated with magnetic fluid. J. Magn. Magn. Mater. 493, 165701 (2020)
CrossRef Google scholar
[34]
Jiang, X., Qavi, A.J., Huang, S.H., Yang, L.: Whispering-gallery sensors. Matter 3(2), 371–392 (2020)
CrossRef Google scholar
[35]
Baaske, M.D., Foreman, M.R., Vollmer, F.: Single-molecule nucleic acid interactions monitored on a label-free microcavity biosensor platform. Nat. Nanotechnol. Nanotechnol. 9(11), 933–939 (2014)
CrossRef Google scholar
[36]
Swaim, J.D., Knittel, J., Bowen, W.P.: Detection of nanoparticles with a frequency locked whispering gallery mode microresonator. Appl. Phys. Lett. 102(18), 183106 (2013)
CrossRef Google scholar
[37]
Zhu, J., Ozdemir, S.K., Xiao, Y., Li, L., He, L., Chen, D., Yang, L.: On-chip single nanoparticle detection and sizing by mode splitting in an ultrahigh-Q microresonator. Nat. Photonics 4(1), 46–49 (2010)
CrossRef Google scholar
[38]
Li, B.B., Clements, W.R., Yu, X.C., Shi, K., Gong, Q., Xiao, Y.F.: Single nanoparticle detection using split-mode microcavity Raman lasers. Proc. Natl. Acad. Sci. U.S.A. 111(41), 14657–14662 (2014)
CrossRef Google scholar
[39]
Jin, M., Tang, S.J., Chen, J.H., Yu, X.C., Shu, H., Tao, Y., Chen Antony, K., Gong, Q., Wang, X., Xiao, Y.F.: 1/f-noise-free optical sensing with an integrated heterodyne interferometer. Nat. Commun. Commun. 12(1), 1973 (2021)
CrossRef Google scholar
[40]
Yi, X., Xiao, Y.F., Li, Y., Liu, Y.C., Li, B.B., Liu, Z.P., Gong, Q.: Polarization-dependent detection of cylinder nanoparticles with mode splitting in a high-Q whispering-gallery microresonator. Appl. Phys. Lett. 97(20), 203705 (2010)
CrossRef Google scholar
[41]
Xu, Y., Tang, S.J., Yu, X.C., Chen, Y.L., Yang, D., Gong, Q., Xiao, Y.F.: Mode splitting induced by an arbitrarily shaped Rayleigh scatterer in a whispering-gallery microcavity. Phys. Rev. A (Coll. Park) 97(6), 063828 (2018)
CrossRef Google scholar
[42]
Kohler, L., Mader, M., Kern, C., Wegener, M., Hunger, D.: Tracking Brownian motion in three dimensions and characterization of individual nanoparticles using a fiber-based high-finesse micro-cavity. Nat. Commun. Commun. 12(1), 1–7 (2021)
CrossRef Google scholar
[43]
Shao, L., Jiang, X., Yu, X., Li, B., Clements, W.R., Vollmer, F., Wang, W., Xiao, Y., Gong, Q.: Detection of single nanoparticles and lentiviruses using microcavity resonance broadening. Adv. Mater. 25(39), 5616–5620 (2013)
CrossRef Google scholar
[44]
Madugani, R., Yang, Y., Le, V.H., Ward, J.M., Chormaic, S.N.: Linear laser tuning using a pressure-sensitive microbubble resonator. IEEE Photonics Technol. Lett. 28(10), 1134–1137 (2016)
CrossRef Google scholar
[45]
Liu, S., Sun, W., Wang, Y., Yu, X., Xu, K., Huang, Y., Xiao, S., Song, Q.: End-fire injection of light into high Q silicon microdisks. Optica 5(5), 612–616 (2018)
CrossRef Google scholar
[46]
Zhang, X., Liu, L., Xu, L.: Ultralow sensing limit in optofluidic micro-bottle resonator biosensor by self referenced differentialmode detection scheme. Appl. Phys. Lett. 104(3), 033703 (2014)
CrossRef Google scholar
[47]
Li, M., Wu, X., Liu, L., Fan, X., Xu, L.: Self-referencing optofluidic ring resonator sensor for highly sensitive biomolecular detection. Anal. Chem. 85(19), 9328–9332 (2013)
CrossRef Google scholar
[48]
Luo, R., Jiang, H., Liang, H., Chen, Y., Lin, Q.: Self-referenced temperature sensing with a lithium niobate microdisk resonator. Opt. Lett. 42(7), 1281–1284 (2017)
CrossRef Google scholar
[49]
Savchenkov, A.A., Matsko, A.B., Ilchenko, V.S., Yu, N., Maleki, L.: Whispering-gallery-mode resonators as frequency references. II. Stabilization. J. Opt. Soc. Am. B 24(12), 2988–2997 (2007)
CrossRef Google scholar
[50]
Guo, Z., Lu, Q., Zhu, C., Wang, B., Zhou, Y., Wu, X.: Ultra-sensitive biomolecular detection by external referencing optofluidic microbubble resonators. Opt. Express 27(9), 12424–12435 (2019)
CrossRef Google scholar
[51]
Zhao, X., Zhou, Y., Li, Y., Guo, J., Liu, Z., Luo, M., Guo, Z., Yang, X., Zhang, M., Wang, Y., Wu, X.: Ultrasensitive optofluidic coupled Fabry–Perot capillary sensors. Opt. Express 30(25), 45070–45081 (2022)
CrossRef Google scholar
[52]
Dong, Y., Sun, P., Zeng, X., Wang, J., Li, Y., Wang, M., Wang, H.: Displacement sensing in a multimode SNAP microcavity by an artificial neural network. Opt. Express 30(15), 27015–27027 (2022)
CrossRef Google scholar
[53]
Zhou, Y., Yuan, Z., Gong, X., Birowosuto, M.D., Dang, C., Chen, Y.C.: Dynamic photonic barcodes for molecular detection based on cavity-enhanced energy transfer. Adv. Photonics 2(6), 066002 (2020)
CrossRef Google scholar
[54]
Kumagai, Y., Takubo, K., Kawada, K., Aoyama, K., Endo, Y., Ozawa, T., Hirasawa, T., Yoshio, T., Ishihara, S., Fujishiro, M., Tamaru, J., Mochiki, E., Ishida, H., Tada, T.: Diagnosis using deep-learning artificial intelligence based on the endocytoscopic observation of the esophagus. Esophagus 16(2), 180–187 (2019)
CrossRef Google scholar
[55]
Malik, P., Pathania, M., Rathaur, V.K.: Overview of artificial intelligence in medicine. J. Family Med. Prim. Care 8(7), 2328 (2019)
CrossRef Google scholar
[56]
Suganyadevi, S., Seethalakshmi, V., Balasamy, K.: A review on deep learning in medical image analysis. Int. J. Multimed. Inf. Retr. 11(1), 19–38 (2022)
CrossRef Google scholar
[57]
He, J., Baxter, S.L., Xu, J., Xu, J., Zhou, X., Zhang, K.: The practical implementation of artificial intelligence technologies in medicine. Nat. Med. 25(1), 30–36 (2019)
CrossRef Google scholar
[58]
Lu, J., Niu, R., Wan, S., Dong, C.H., Le, Z., Qin, Y., Hu, Y., Hu, W., Zou, C.L., Ren, H.: Experimental demonstration of multimode microresonator sensing by machine learning. IEEE Sens. J. 21(7), 9046–9053 (2021)
CrossRef Google scholar
[59]
Hu, D., Zou, C.L., Ren, H., Lu, J., Le, Z., Qin, Y., Guo, S., Dong, C., Hu, W.: Multi-parameter sensing in a multimode self-interference microring resonator by machine learning. Sensors (Basel) 20(3), 709 (2020)
CrossRef Google scholar
[60]
Zhang, Y., Lu, J., Le, Z., Dong, C.H., Zheng, H., Qin, Y., Yu, P., Hu, W., Zou, C.L., Ren, H.: Proposal of unsupervised gas classification by multimode microresonator. IEEE Photonics J. 13(2), 5800111 (2021)
CrossRef Google scholar
[61]
Chugh, S., Gulistan, A., Ghosh, S., Rahman, B.M.A.: Machine learning approach for computing optical properties of a photonic crystal fiber. Opt. Express 27(25), 36414–36425 (2019)
CrossRef Google scholar
[62]
An, G., Omodaka, K., Hashimoto, K., Tsuda, S., Shiga, Y., Takada, N., Kikawa, T., Yokota, H., Akiba, M., Nakazawa, T.: Glaucoma diagnosis with machine learning based on optical coherence tomography and color fundus images. J. Healthc. Eng. 1 (2019)
CrossRef Google scholar
[63]
Chen, H., Wang, Z., Wang, Y., Yu, C., Niu, R., Zou, C.L., Lu, J., Dong, C.H., Ren, H.: Machine learning-assisted high-accuracy and large dynamic range thermometer in high-Q microbubble resonators. Opt. Express 31(10), 16781–16794 (2023)
CrossRef Google scholar
[64]
Saetchnikov, A.V., Tcherniavskaia, E.A., Skakun, V.V., Saetchnikov, V.A., Ostendorf, A.: Reusable dispersed resonators-based biochemical sensor for parallel probing. IEEE Sens. J. 19(17), 7644–7651 (2019)
CrossRef Google scholar
[65]
Saetchnikov, A.V., Tcherniavskaia, E.A., Saetchnikov, V., Ostendorf, A.: Design and application of distributed microresonator-based systems for biochemical sensing. Opt. Sens. Detect. VI. SPIE 11354, 321–326 (2020)
CrossRef Google scholar
[66]
Saetchnikov A. V., Tcherniavskaia E. A., Saetchnikov V. A., and Ostendorf, A.: Deep-learning powered whispering gallery mode sensor based on multiplexed imaging at fixed frequency. (2020)
CrossRef Google scholar
[67]
Shah, S., Yu, C.N., Zheng, M., Kim, H., Eggleston, M.S.: Microparticle-based biochemical sensing using optical coherence tomography and deep learning. ACS Nano 15(6), 9764–9774 (2021)
CrossRef Google scholar
[68]
Tian, X., Li, L., Chew, S.X., Gunawan, G., Nguyen, L., Yi, X.: Cascaded optical microring resonator based auto-correction assisted high resolution microwave photonic sensor. J. Light-wave Technol. 39(24), 7646–7655 (2021)
CrossRef Google scholar
[69]
Liu, Y., Jing, Z., Liu, Q., Li, A., Lee, A., Cheung, Y., Zhang, Y., Peng, W.: All-silica fiber-optic temperature-depth-salinity sensor based on cascaded EFPIs and FBG for deep sea exploration. Opt. Express 29(15), 23953–23966 (2021)
CrossRef Google scholar
[70]
Yang, D., Tian, H., Ji, Y.: Nanoscale photonic crystal sensor arrays on monolithic substrates using side-coupled resonant cavity arrays. Opt. Express 19(21), 20023–20034 (2011)
CrossRef Google scholar
[71]
Yang, D., Tian, H., Ji, Y.: Nanoscale low crosstalk photonic crystal integrated sensor array. IEEE Photonics J. 6(1), 1–7 (2014)
CrossRef Google scholar
[72]
Kavungal, V., Farrell, G., Wu, Q., Mallik, A.K., Shen, C., Semenova, Y.: Packaged inline cascaded optical micro-resonators for multi-parameter sensing. Opt. Fiber Technol. Fiber Technol. 50, 50–54 (2019)
CrossRef Google scholar
[73]
Mallik, A.K., Farrell, G., Ramakrishnan, M., Kavungal, V., Liu, D., Wu, Q., Semenova, Y.: Whispering gallery mode micro resonators for multi-parameter sensing applications. Opt. Express 26(24), 31829–31838 (2018)
CrossRef Google scholar
[74]
Zhang, C., Fu, S., Tang, M., Liu, D.: Parallel Fabry-Perot inter-ferometers fabricated on multicore-fiber for temperature and strain discriminative sensing. Opt. Express 28(3), 3190–3199 (2020)
CrossRef Google scholar
[75]
Ma, Z., Chen, J., Wei, H., Zhang, L., Wang, Z., Chen, Z., Pang, F., Wang, T.: Compound Fabry-Pérot interferometer for simultaneous high-pressure and high-temperature measurement. Opt. Express 29(15), 24289–24299 (2021)
CrossRef Google scholar
[76]
Ye, L., Liu, X., Pei, D., Peng, J., Liu, S., Guo, K., Li, X., Chen, X., Zhang, X., Yang, D.: Simultaneous detection of relative humidity and temperature based on silicon on-chip cascaded photonic crystal nanobeam cavities. Crystals (Basel) 11(12), 1559 (2021).
CrossRef Google scholar
[77]
Wang, J., Chew, S.X., Song, S., Li, L., Nguyen, L., Yi, X.: Onchip simultaneous measurement of humidity and temperature using cascaded photonic crystal microring resonators with error correction. Opt. Express 30(20), 35608–35623 (2022)
CrossRef Google scholar
[78]
Yi, L., Li, C.: Light enhanced absorption of graphene based on parity-time symmetry structure. Faguang Xuebao 43(1), 119–128 (2022)
CrossRef Google scholar
[79]
Tan, T., Yuan, Z., Zhang, H., Yan, G., Zhou, S., An, N., Peng, B., Soavi, G., Rao, Y., Yao, B.: Multispecies and individual gas molecule detection using Stokes solitons in a graphene overmodal microresonator. Nat. Commun.Commun. 12(1), 6716 (2021)
CrossRef Google scholar
[80]
Guo, Y., Li, Z., An, N., Guo, Y., Wang, Y., Yuan, Y., Zhang, H., Tan, T., Wu, C., Peng, B., Soavi, G., Rao, Y., Yao, B.: A monolithic graphene-functionalized microlaser for multispecies gas detection. Adv. Mater. 34(51), 2207777 (2022)
CrossRef Google scholar
[81]
Le Cun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436–444 (2015)
CrossRef Google scholar
[82]
Jordan, M.I., Mitchell, T.M.: Machine learning: trends, perspectives, and prospects. Science 349(6245), 255–260 (2015)
CrossRef Google scholar
[83]
Li, Z., Zhang, H., Nguyen, B.T.T., Luo, S., Liu, P.Y., Zou, J., Shi, Y., Cai, H., Yang, Z., Jin, Y., Hao, Y., Zhang, Y., Liu, A.Q.: Smart ring resonator-based sensor for multicomponent chemical analysis via machine learning. Photon. Res. 9(2), B38–B44 (2021)
CrossRef Google scholar
[84]
Ho, C.S., Jean, N., Hogan, C.A., Blackmon, L., Jeffrey, S.S., Holodniy, M., Banaei, N., Saleh, A.A.E., Ermon, S., Dionne, J.: Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning. Nat. Commun.Commun. 10(1), 4927 (2019)
CrossRef Google scholar
[85]
Djurhuus, M.S., Werzinger, S., Schmauss, B., Clausen, A.T., Zibar, D.: Machine learning assisted fiber Bragg grating-based temperature sensing. IEEE Photonics Technol. Lett. 31(12), 939–942 (2019)
CrossRef Google scholar
[86]
Hu, D., Zou, C.L., Ren, H., Lu, J., Le, Z., Qin, Y., Guo, S., Dong, C., Hu, W.: Multi-parameter sensing in a multimode self-interference micro-ring resonator by machine learning. Sensors (Basel) 20(3), 709 (2020)
CrossRef Google scholar
[87]
Zhang, Y., Lu, J., Le, Z., Dong, C.H., Zheng, H., Qin, Y., Yu, P., Hu, W., Zou, C.L., Ren, H.: Proposal of unsupervised gas classification by multimode microresonator. IEEE Photonics J. 13(2), 1–11 (2021)
CrossRef Google scholar

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