Multimode sensing based on optical microcavities

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.

Key words： Optical microcavity; Multimode sensing; Multiparameter measurement; Sensing mechanisms

References

1 Zhi, Y., Yu, X., Gong, Q., Yang, L., Xiao, Y.: Single nanoparticle detection using optical microcavities. Adv. Mater. 29(12), 1604920 (2017)

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)

3 Fan, X.: Advanced photonic structures for biological and chemical detection. Springer, New York (2009)

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)

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)

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)

7 Rho, D., Breaux, C., Kim, S.: Label-free optical resonator-based biosensors. Sensors (Basel) 20(20), 5901 (2020)

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)

9 Chen, C., Wang, J.: Optical biosensors: an exhaustive and comprehensive review. Analyst (Lond.) 145(5), 1605–1628 (2020)

10 Yi, L., Li, C.: Simulation research on blood detection sensing with parity-time symmetry structure. Crystals (Basel) 11(9), 1030 (2021)

11 Nagarajan, K., Thomas, A., Ebbesen, T.W.: Chemistry under vibrational strong coupling. J. Am. Chem. Soc. 143(41), 16877–16889 (2021)

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)

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)

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)

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)

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)

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)

18 Lyu, S., Wu, Z., Shi, X., Wu, Q.: Optical fiber biosensors for protein detection: a review. In Photonics 9(12), 987 (2022)

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)

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)

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)

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)

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)

24 Qiao, Q., Xia, J., Lee, C., Zhou, G.: Applications of photonic crystal nanobeam cavities for sensing. Micromachines (Basel) 9(11), 541 (2018)

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)

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)

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)

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)

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)

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)

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)

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)

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)

34 Jiang, X., Qavi, A.J., Huang, S.H., Yang, L.: Whispering-gallery sensors. Matter 3(2), 371–392 (2020)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

55 Malik, P., Pathania, M., Rathaur, V.K.: Overview of artificial intelligence in medicine. J. Family Med. Prim. Care 8(7), 2328 (2019)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

71 Yang, D., Tian, H., Ji, Y.: Nanoscale low crosstalk photonic crystal integrated sensor array. IEEE Photonics J. 6(1), 1–7 (2014)

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)

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)

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)

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)

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).

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)

78 Yi, L., Li, C.: Light enhanced absorption of graphene based on parity-time symmetry structure. Faguang Xuebao 43(1), 119–128 (2022)

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)

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)

81 Le Cun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521(7553), 436–444 (2015)

82 Jordan, M.I., Mitchell, T.M.: Machine learning: trends, perspectives, and prospects. Science 349(6245), 255–260 (2015)

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)

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)

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)

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)

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)