Skip to main content
SpringerLink
Log in

Sensing enhancement of nanostructure surface plasmon resonance in optical fiber ring resonator

  • Published:
Optical and Quantum Electronics Aims and scope Submit manuscript

Abstract

We propose and demonstrate a novel passive optical-fiber sensor based on surface plasmon resonance (SPR) by fabricating a configuration on metal-dielectric materials. We use a single-mode fiber to harness the transmission light. In the proposed structure, the injected refractive index on ring and fiber is controlled by the FDTD method; thus, the resonance wavelength of the fiber SPR shifts. This is the mechanism of the proposed structure. We also investigate several performance parameters such as FOM, and sensitivity and by applying silicon optical fiber can improve the sensitivity. Comparing with the reported numerical and measurements based on an optical fiber structure, the experimental results based on fiber ring resonator present good agreement and therefore the proposed structure open a new path to optical fiber sensors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

Data availability

All data included in this paper are available upon request by contact with the contact corresponding author.

References

  • Amoosoltani, N., et al.: A plasmonic nano-biosensor based on two consecutive disk resonators and unidirectional reflectionless propagation effect. IEEE Sensors J. 20(16), 9097–9104 (2020)

    Article  ADS  Google Scholar 

  • Asadi, A., Alarifi, I.M., Nguyen, H.M., Moayedi, H.: Feasibility of least-square support vector machine in predicting the effects of shear rate on the rheological properties and pumping power of MWCNT–MgO/oil hybrid nanofluid based on experimental data. J. Thermal Anal. Calorime. 143(2), 1439–1454 (2021). https://doi.org/10.1007/s10973-020-09279-6

    Article  Google Scholar 

  • Azmand, H.R., Amarachukwu, N.E., Sang-woo, S.: Active liquid flow control through a polypyrrole-coated macroporous silicon membrane toward chemical stimulation applications. Sensors Actuators Phys. 318, 112512 (2021)

    Article  Google Scholar 

  • Butt, M.A., Khonina, S.N., Kazanskiy, N.L.: Metal-insulator-metal nano square ring resonator for gas sensing applications. Waves Random Complex Media 31(1), 146–156 (2021)

    Article  ADS  MathSciNet  Google Scholar 

  • Chen, X., Wang, T., Ying, R., Cao, Z.: A fault diagnosis method considering meteorological factors for transmission networks based on p systems. Entropy (2021). https://doi.org/10.3390/e23081008

    Article  MathSciNet  Google Scholar 

  • Cheng, H., Li, T., Li, X., Feng, J., TangQin, T.D.: Facile synthesis of Co9S8 nanocages as an electrochemical sensor for luteolin detection. J. Electrochem. Soc. (2021). https://doi.org/10.1149/1945-7111/ac1813

    Article  Google Scholar 

  • Du, C., Wang, Q., Zhao, Y., Li, J.: Highly sensitive temperature sensor based on an isopropanol-filled photonic crystal fiber long period grating. Opt. Fiber Technol. 34, 12–15 (2017)

    Article  ADS  Google Scholar 

  • Enemuo, A.N., et al.: Comparative study of macroporous silicon-based photovoltaic characteristics using indium tin oxide-silicon and pn-silicon junction based devices. Microelectron. Eng. 199, 31–39 (2018)

    Article  Google Scholar 

  • Fan, Z., Ji, P., Zhang, J., Segets, D., ChenChen, D.S.: Wavelet neural network modeling for the retention efficiency of sub-15 nm nanoparticles in ultrafiltration under small particle to pore diameter ratio. J. Membr. Sci. 635, 119503 (2021). https://doi.org/10.1016/j.memsci.2021.119503

    Article  Google Scholar 

  • Foong, L.K., Moayedi, H.: Slope stability evaluation using neural network optimized by equilibrium optimization and vortex search algorithm. Eng. Comput. (2021). https://doi.org/10.1007/s00366-021-01282-1

    Article  Google Scholar 

  • Fukano, H., Kushida, Y., Taue, S.: Multimode-interference-structure optical-fiber temperature sensor with high sensitivity. IEICE Electron. Exp. 10(24), 20130812 (2013)

    Article  Google Scholar 

  • Gao, Y., et al.: Cavity-enhanced thermo-optic bistability and hysteresis in a graphene-on-Si 3 N 4 ring resonator. Opt. Lett. 42(10), 1950–1953 (2017)

    Article  ADS  Google Scholar 

  • Ghabussi, A., Habibi, M., NoormohammadiArani, O., Shavalipour, A., Moayedi, H., Safarpour, H.: Frequency characteristics of a viscoelastic graphene nanoplatelet–reinforced composite circular microplate. JVC/J. Vib. Control 27(1–2), 101–118 (2021a). https://doi.org/10.1177/1077546320923930

    Article  MathSciNet  Google Scholar 

  • Ghabussi, A., Ashrafi, N., Shavalipour, A., Hosseinpour, A., Habibi, M., Moayedi, H., Babaei, B., Safarpour, H.: Free vibration analysis of an electro-elastic GPLRC cylindrical shell surrounded by viscoelastic foundation using modified length-couple stress parameter. Mech. Based Des. Struct. Mach. 49(5), 738–762 (2021b). https://doi.org/10.1080/15397734.2019.1705166

    Article  Google Scholar 

  • Gupta, S., Deep, K., Heidari, A.A., Moayedi, H., Chen, H.: Harmonized salp chain-built optimization. Eng. Comput. 37(2), 1049–1079 (2021). https://doi.org/10.1007/s00366-019-00871-5

    Article  Google Scholar 

  • Huang, Z., Wang, T., Liu, W., Valencia-Cabrera, L., Pérez-Jiménez, M.J., Li, P., Geem, Z.W.: A fault analysis method for three-phase induction motors based on spiking neural P systems. Complexity 2021, 1–19 (2021). https://doi.org/10.1155/2021/2087027

    Article  Google Scholar 

  • Ji, B., Zhang, F., Song, X., Tang, Y.: A novel potassium-ion-based dual-ion battery. Adv. Mater. 29(19), 1700519 (2017). https://doi.org/10.1002/adma.201700519

    Article  Google Scholar 

  • Li, S., et al.: Colloidal crystal cladding fiber based on side-polished fiber and its temperature sensing. Opt. Quantum Electron. 49(2), 66 (2017)

    Article  Google Scholar 

  • Li, H., Tang, J., Kang, Y., Zhao, H., Fang, D., FangWei, X.Z.: Optical properties of quasi-type-II structure in GaAs/GaAsSb/GaAs coaxial single quantum-well nanowires. Appl. Phys. Lett. 113(23), 233104 (2018). https://doi.org/10.1063/1.5053844

    Article  Google Scholar 

  • Li, X., Feng, Y., Liu, B., Yi, D., Yang, X., ZhangBai, W.P.: Influence of NbC particles on microstructure and mechanical properties of AlCoCrFeNi high-entropy alloy coatings prepared by laser cladding. J. Alloy. Compd. 788, 485–494 (2019). https://doi.org/10.1016/j.jallcom.2019.02.223

    Article  Google Scholar 

  • Li, X., Sheng, X., Guo, Y., Lu, X., Wu, H., ChenGu, Y.J.: Multifunctional HDPE/CNTs/PW composite phase change materials with excellent thermal and electrical conductivities. J. Mater. Sci. Technol. 86, 171–179 (2021). https://doi.org/10.1016/j.jmst.2021.02.009

    Article  Google Scholar 

  • Lim, J., Yang, Q., Jones, B.E., Jackson, P.R.: Strain and temperature sensors using multimode optical fiber Bragg gratings and correlation signal processing. IEEE Trans. Instrum. Meas. 51, 622–627 (2002)

    Article  Google Scholar 

  • Liu, C., Deng, F., Heng, Q., Cai, X., ZhuLiserre, R.M.: Crossing thyristor branches based hybrid modular multilevel converters for DC line faults. IEEE Trans. Ind. Electron. 1982, 1 (2020). https://doi.org/10.1109/TIE.2020.3026277

    Article  Google Scholar 

  • Lu, C., Zhu, R., Yu, F., Jiang, X., Liu, Z., DongOu, L.Z.: Gear rotational speed sensor based on FeCoSiB/Pb(Zr, Ti)O3 magnetoelectric composite. Measure. J. Int. Measure. Confeder. 168, 108409 (2021). https://doi.org/10.1016/j.measurement.2020.108409

    Article  Google Scholar 

  • Luo, G., Siong Teh, K., Xia, Y., Luo, Y., Li, Z., WangJiang, S.Z.: A novel three-dimensional spiral CoNi LDHs on Au@ErGO wire for high performance fiber supercapacitor electrodes. Mater. Lett. 236, 728–731 (2019). https://doi.org/10.1016/j.matlet.2018.11.038

    Article  Google Scholar 

  • Mahmoud, A.S., Kalantar, B., Al-Najjar, H.A.H., Moayedi, H., Halin, A.A., Mansor, S.: Object-oriented approach for urbanization growth by using remote sensing and GIS techniques: a case study in Hilla City, Babylon Governorate, Iraq (2021) Urban Book Series, pp. 39–57. https://doi.org/10.1007/978-3-030-71945-6_3

  • Moayedi, H., Mosavi, A.: Suggesting a stochastic fractal search paradigm in combination with artificial neural network for early prediction of cooling load in residential buildings. Energies 14(6), 1649 (2021a). https://doi.org/10.3390/en14061649

    Article  Google Scholar 

  • Moayedi, H., Mosavi, A.: Synthesizing multi-layer perceptron network with ant lion biogeography-based dragonfly algorithm evolutionary strategy invasive weed and league champion optimization hybrid algorithms in predicting heating load in residential buildings. Sustainability 13(6), 3198 (2021b). https://doi.org/10.3390/su13063198

    Article  Google Scholar 

  • Moayedi, H., Mosavi, A.: Double-target based neural networks in predicting energy consumption in residential buildings. Energies 14(5), 1331 (2021c). https://doi.org/10.3390/en14051331

    Article  Google Scholar 

  • Moayedi, H., Mosavi, A.: An innovative metaheuristic strategy for solar energy management through a neural networks framework. Energies 14(4), 1196 (2021d). https://doi.org/10.3390/en14041196

    Article  Google Scholar 

  • Moayedi, H., Mosavi, A.: Electrical power prediction through a combination of multilayer perceptron with water cycle ant lion and satin bowerbird searching optimizers. Sustainability 13(4), 2336 (2021e). https://doi.org/10.3390/su13042336

    Article  Google Scholar 

  • Moayedi, H., Mosavi, A.: A water cycle-based error minimization technique in predicting the bearing capacity of shallow foundation. Eng. Comput. (2021f). https://doi.org/10.1007/s00366-021-01289-8

    Article  Google Scholar 

  • Moayedi, H., Rezaei, A.: The feasibility of PSO–ANFIS in estimating bearing capacity of strip foundations rested on cohesionless slope. Neural Comput. Appl. 33(9), 4165–4177 (2021). https://doi.org/10.1007/s00521-020-05231-9

    Article  Google Scholar 

  • Moayedi, H., Mu’azu, M.A., Kok Foong, L.: Swarm-based analysis through social behavior of grey wolf optimization and genetic programming to predict friction capacity of driven piles. Eng. Comput. 37(2), 1277–1293 (2021). https://doi.org/10.1007/s00366-019-00885-z

    Article  Google Scholar 

  • Moayedi, H., Gör, M., Kok Foong, L., Bahiraei, M.: Imperialist competitive algorithm hybridized with multilayer perceptron to predict the load-settlement of square footing on layered soils. Measurement J. Int. Measure. Conf. 172, 108837 (2021a). https://doi.org/10.1016/j.measurement.2020.108837

    Article  Google Scholar 

  • Moayedi, H., Ghareh, S., Foong, L.K.: Quick integrative optimizers for minimizing the error of neural computing in pan evaporation modeling. Eng. Comput. (2021b). https://doi.org/10.1007/s00366-020-01277-4

    Article  Google Scholar 

  • Moayedi, H., Hajibaba, S., Afarideh, H., Ghergherehchi, M., Mohamadian, M.: Optimization of beta radioluminescent batteries with different radioisotopes: a theoretical study. Nuclear Sci. Eng. 195(6), 614–625 (2021c). https://doi.org/10.1080/00295639.2020.1848199

    Article  Google Scholar 

  • Moayedi, H.: Two novel predictive networks for slope stability analysis using a combination of genetic programming and artificial neural network techniques. (2021) 109: 91–108. https://doi.org/10.1007/978-3-030-60839-2_6

  • Ni, T., Liu, D., Xu, Q., Huang, Z., Liang, H., Yan, A.: Architecture of cobweb-based redundant TSV for clustered faults. IEEE Trans. Very Large Scale Integr. Syst. 28(7), 1736–1739 (2020). https://doi.org/10.1109/TVLSI.2020.2995094

    Article  Google Scholar 

  • Ni, T., Yang, Z., Chang, H., Zhang, X., Lu, L., YanWen, A.X.: A novel TDMA-based fault tolerance technique for the TSVs in 3D-ICs using honeycomb topology. IEEE Trans. Emerg. Top. Comput. 9(2), 724–734 (2021). https://doi.org/10.1109/TETC.2020.2969237

    Article  Google Scholar 

  • Qian, W., et al.: High-sensitivity temperature sensor based on an alcohol filled photonic crystal fiber loop mirror. Opt. Lett. 36(9), 1548–1550 (2011)

    Article  ADS  Google Scholar 

  • Reyes-Vera, E., Cordeiro, C.M.B., Torres, P.: Highly sensitive temperature sensor using a Sagnac loop interferometer based on a sidehole photonic crystal fiber filled with metal. Appl. Opt. 56(2), 156–162 (2017)

    Article  ADS  Google Scholar 

  • Sakr, M.A.H., Omar, A.E., Saad, A.M., Moayedi, H.: Geotechnical parameters modelling and the radiation safety of expansive clayey soil treated with waste marble powder: a case study at west Gulf of Suez, Egypt. Environ. Earth Sci. 80(7), 263 (2021). https://doi.org/10.1007/s12665-021-09573-y

    Article  Google Scholar 

  • Senosiain, I., Diaz, A.G., Sevilla, J.: High sensitivity temperature sensor based on side-polished optical fiber. IEEE Trans. Instrum. Meas. 50(6), 1656–1660 (2001)

    Article  Google Scholar 

  • Seo, S.-W., Azmand, H.R., Enemuo, A.N.: Hollow core waveguide sensor array based on a macroporous silicon membrane structure. J. Lightwave Technol. 37(9), 2036–2041 (2019)

    Article  ADS  Google Scholar 

  • Seo, S.-W., Azmand, H.R., Song, Y.: A fiber optic sensor platform for smart hydrogel event detection. Opt. Fiber Technol. 58, 102246 (2020)

    Article  Google Scholar 

  • Shen, H., Zhang, M., Wang, H., Guo, F., Susilo, W.: A cloud-aided privacy-preserving multi-dimensional data comparison protocol. Inf. Sci. 545, 739–752 (2021). https://doi.org/10.1016/j.ins.2020.09.052

    Article  MathSciNet  Google Scholar 

  • Shi, X., et al.: Dual Fano resonance control and refractive index sensors based on a plasmonic waveguide-coupled resonator system. Opt. Commun. 427, 326–330 (2018)

    Article  ADS  Google Scholar 

  • Sui, T., Marelli, D., Sun, X., Fu, M.: Multi-sensor state estimation over lossy channels using coded measurements. Automatica 111, 108561 (2020). https://doi.org/10.1016/j.automatica.2019.108561

    Article  MathSciNet  MATH  Google Scholar 

  • Szunerits, S., Boukherroub, R.: Electrochemical investigation of gold/silica thin film interfaces for electrochemical surface plasmon resonance studies. Electrochem. Commun. 8(3), 439–444 (2006)

    Article  Google Scholar 

  • Tavousi, A., Rakhshani, M.R., Mansouri-Birjandi, M.A.: High sensitivity label-free refractometer based biosensor applicable to glycated hemoglobin detection in human blood using all-circular photonic crystal ring resonators. Opt. Commun. 429, 166–174 (2018)

    Article  ADS  Google Scholar 

  • Tong, X., Zhang, F., Ji, B., Sheng, M., Tang, Y.: Carbon-coated porous aluminum foil anode for high-rate, long-term cycling stability, and high energy density dual-ion batteries. Adv. Mater. 28(45), 9979–9985 (2016). https://doi.org/10.1002/adma.201603735

    Article  Google Scholar 

  • Wang, P., et al.: Fiber-tip high-temperature sensor based on multimode interference. Opt. Lett. 38(22), 4617–4620 (2013)

    Article  ADS  Google Scholar 

  • Wang, X., Yang, H.-J., Wang, S.-S., Liao, Y.-P., Wang, J.: Seawater temperature measurement based on a high-birefringence elliptic fiber sagnac loop. IEEE Photon. Technol. Lett. 27(16), 1772–1775 (2015)

    Article  ADS  Google Scholar 

  • Wang, T., Liu, W., Zhao, J., Guo, X., Terzija, V.: A rough set-based bio-inspired fault diagnosis method for electrical substations. Int. J. Electr. Power Energy Syst. 119, 105961 (2020a). https://doi.org/10.1016/j.ijepes.2020.105961

    Article  Google Scholar 

  • Wang, T., Wei, X., Wang, J., Huang, T., Peng, H., SongPérez-Jiménez, X.M.J.: A weighted corrective fuzzy reasoning spiking neural P system for fault diagnosis in power systems with variable topologies. Eng. Appl. Artif. Intell. 92, 103680 (2020b). https://doi.org/10.1016/j.engappai.2020.103680

    Article  Google Scholar 

  • Xu, F., Moayedi, H., Foong, L.K., Moghadam, M.J., Zangeneh, M.: Laboratory and numerical analysis of geogrid encased stone columns. Measure. J. Int. Measure. Conf. 169, 108369 (2021). https://doi.org/10.1016/j.measurement.2020.108369

    Article  Google Scholar 

  • Yan, J., Meng, Y., Yang, X., Luo, X., Guan, X.: Privacy-preserving localization for underwater sensor networks via deep reinforcement learning. IEEE Trans. Inf. Forensics Secur. 16, 1880–1895 (2021). https://doi.org/10.1109/TIFS.2020.3045320

    Article  Google Scholar 

  • Yang, H.U., et al.: Optical dielectric function of silver. Phys. Rev. B 91(23), 235137 (2015)

    Article  ADS  Google Scholar 

  • Yang, F., Moayedi, H., Mosavi, A.: Predicting the degree of dissolved oxygen using three types of multi-layer perceptron-based artificial neural networks. Sustainability. 13(17), 9898 (2021). https://doi.org/10.3390/su13179898

    Article  Google Scholar 

  • Zhang, X., Sun, X., Lv, T., Weng, L., Chi, M., Shi, J., Zhang, S.: Preparation of PI porous fiber membrane for recovering oil-paper insulation structure. J. Mater. Sci. Mater. Electron. 31(16), 13344–13351 (2020). https://doi.org/10.1007/s10854-020-03888-5

    Article  Google Scholar 

  • Zhang, H., Yuan, C., Yang, G., Wu, L., Peng, C., Ye, W., Shen, Y., Moayedi, H.: A novel constitutive modelling approach measured under simulated freeze–thaw cycles for the rock failure. Eng. Comput. 37(1), 779–792 (2021). https://doi.org/10.1007/s00366-019-00856-4

    Article  Google Scholar 

  • Zhao, Y., Chen, M.-Q., Lv, R.-Q., Wang, P., Feng, X.: Small and practical optical fiber fluorescence temperature sensor. IEEE Trans. Instrum. Meas. 65(10), 2406–2411 (2016)

    Article  Google Scholar 

Download references

Funding

This research did not receive any specific grant from funding agencies.

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, University of Larestan, Lar, Iran

    Abdolkarim Afroozeh

Authors
  1. Abdolkarim Afroozeh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Abdolkarim Afroozeh.

Ethics declarations

Conflict of interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Afroozeh, A. Sensing enhancement of nanostructure surface plasmon resonance in optical fiber ring resonator. Opt Quant Electron 53, 719 (2021). https://doi.org/10.1007/s11082-021-03345-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11082-021-03345-5

Keywords

Search

Navigation