Skip to main content
SpringerLink
Log in

Numerical and Analytical Modeling of Plasmonic Filter with High Q-Factor Based on “Nanostructured Resonator”

  • Published:
Plasmonics Aims and scope Submit manuscript

Abstract

In this paper, to achieve high-quality filters, nanostructured plasmon resonators are proposed. The structure of proposed resonator is based on metal-dielectric-metal configuration and is designed in the range of 1550-nm telecommunication wavelength. To evaluate the proposed structure, finite-difference time-domain method and analytical method of coupled mode theory have been used. To obtain optimal results, the effects of the number of waveguides as well as the radius of circular and ring waveguides were investigated. The appropriate results will be obtained by considering a strong coupling between the incoming light and the surface plasmon. In addition, two transient and static wave structures have been used to evaluate the structure. The simulation results show that besides filtering behavior of the structure, it is possible to control the surface plasmon propagation speed in the proposed structure. Therefore, it is expected that the proposed structure will be used in many parts of a telecommunication link such as multiplexers.

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

Similar content being viewed by others

Availability of Data and Material

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

References

  1. Jamalpoor K, Zarifkar A, Alighanbari A (2019) A GaAs-based plasmonic source employing a nanoscale vertical cavity. Opt Quant Electron 51(5):1–9

    Article  CAS  Google Scholar 

  2. Jamalpoor K, Zarifkar A (2018) Utilising graphene antidots for implementation of a broadband terahertz absorber. Micro & Nano Letters 13(12):1712–1715

    Article  CAS  Google Scholar 

  3. Jamalpoor K, Zarifkar A, Miri M (2017) Application of graphene second-order nonlinearity in THz plasmons excitation. Photonics Nanostruct Fundam Appl 26:80–84

  4. Jamalpoor K, Zarifkar A (2017) Analytical investigation of surface plasmon excitation on a graphene sheet using four-wave mixing. Appl Opt 56(3):434–438

    Article  CAS  Google Scholar 

  5. Liang GQ, Chong YD (2013) Optical resonator analog of a two-dimensional topological insulator. Phys Rev Lett 110(20):203904

  6. Salzenstein P, Diallo S, Zarubin M (2018) Electrically driven thermal annealing set-up dedicated to high quality factor optical resonator fabrication. Journal of Power Technologies 98(2):198–201

    CAS  Google Scholar 

  7. Jali MH et al (2019) Optical characterization of different waist diameter on microfiber loop resonator humidity sensor. Sensors and Actuators A Phys 285:200–209

  8. Ghadrdan M, Mansouri-Birjandi MA (2017) Low-threshold ultrafast all-optical switch implemented with metallic nanoshells in the photonic crystal ring resonator. Superlattice Microst 111:789–795

  9. Papageorge AT, Kollár AJ, Lev BL (2016) Coupling to modes of a near-confocal optical resonator using a digital light modulator. Opt Express 24(11):11447–11457

    Article  CAS  Google Scholar 

  10. Nurmohammadi T, Abbasian K, Yadipour R (2018) Ultra-fast all-optical plasmonic switching in near infra-red spectrum using a Kerr nonlinear ring resonator. Optics Communications 410:142–147

    Article  CAS  Google Scholar 

  11. Srivastava YK et al (2017) MoS2 for ultrafast all-optical switching and modulation of THz Fano metaphotonic devices. Adv Opt Mater 5(23):1700762

  12. Li C et al (2017) Multiple Fano resonances based on plasmonic resonator system with end-coupled cavities for high-performance nanosensor. IEEE Photonics J 9(6):1–9

  13. Jankovic N, Cselyuszka N (2018) Multiple Fano-like MIM plasmonic structure based on triangular resonator for refractive index sensing. Sensors 18(1):287

    Article  Google Scholar 

  14. Hosseinbeig A, Pirooj A, Zarrabi FB (2017) A reconfigurable subwavelength plasmonic fano nano-antenna based on split ring resonator. J Magn Magn Mater 423:203–207

    Article  CAS  Google Scholar 

  15. Zhang X, Cui TJ (2020) Deep-subwavelength and high-Q trapped mode induced by symmetry-broken in toroidal plasmonic resonator. IEEE Trans Antennas Propag

  16. Negahdari R, Rafiee E, Emami F (2019) Realization of all-optical plasmonic MIM split square ring resonator switch. Opt Quant Electron 51(7):235

    Article  Google Scholar 

  17. Kewes G et al (2018) Heuristic modeling of strong coupling in plasmonic resonators. ACS Photonics 5(10):4089–4097

  18. Khani S, Danaie M, Rezaei P (2019) Design of a single-mode plasmonic bandpass filter using a hexagonal resonator coupled to graded-stub waveguides. Plasmonics 14(1):53–62

    Article  CAS  Google Scholar 

  19. Lin J et al (2020) Tailoring the lineshapes of coupled plasmonic systems based on a theory derived from first principles. Light Sci Appl 9(1):1–11

  20. Chou Chao CT et al (2020) Highly sensitive and tunable plasmonic sensor based on a nanoring resonator with silver nanorods. Nanomaterials 10(7):1399

  21. Huang ZQ, Yi SH, Chen HX, He XQ (2019) Parameter analysis of damaged region for laminates with matrix defects. J Sandw Struct Mater 425695259

  22. Gao N et al (2021) Elastic wave modulation of double-leaf ABH beam embedded mass oscillator. Appl Acoust 173:107694

  23. Yang Y, Chen H, Zou X, Shi X, Liu W, Feng, L.,... Chen, Z. (2020) Flexible carbon-fiber/semimetal bi nanosheet arrays as separable and recyclable plasmonic photocatalysts and photoelectrocatalysts. ACS Appl Mater Interfaces 12(22):24845–24854

    Article  CAS  Google Scholar 

  24. Sheng H, Wang S, Zhang Y, Yu D, Cheng X, Lyu, W.,... Xiong, Z. (2021) Near-online tracking with co-occurrence constraints in blockchain-based edge computing. IEEE Internet Things J 8(4):2193–2207

    Article  Google Scholar 

  25. Chen Z, Zhang H, He X, Fan G, Li X, He, Z.,... Zhang, L. (2021) Fabrication of cellulosic paper containing zeolitic imidazolate framework and its application in removal of anionic dye from aqueous solution. BioResources 16(2):2644–2654

    Article  CAS  Google Scholar 

  26. Zhang M, Zhang L, Tian S, Zhang X, Guo J, Guan X, Xu P (2020) Effects of graphite particles/Fe3+ on the properties of anoxic activated sludge. Chemosphere (Oxford) 253:126638

  27. Tong X, Ou X, Wu N, Wang H, Li J, Tang Y (2021) High oxidation potential ≈6.0 V of concentrated electrolyte toward high-performance dual-ion battery. Adv Energy Mater 2100151

  28. Wang M, Tang Y (2018) A review on the features and progress of dual-ion batteries. Adv Energy Mater 8(19):1703320

    Article  Google Scholar 

  29. Du X, Li J, Niu G, Yuan J, Xue K, Xia, M.,... Tang, J. (2021) Lead halide perovskite for efficient optoacoustic conversion and application toward high-resolution ultrasound imaging. Nat Commun 12(1):3348

    Article  CAS  Google Scholar 

  30. Shi C, Zhang X, Zhang X, Chen P, Xu L (2021) Ultrasonic desulfurization of amphiphilic magnetic-Janus nanosheets in oil-water mixture system. Ultrason Sonochem 76

  31. Cheng H, Li T, Li X, Feng J, Tang, T, Qin D (2021) Facile synthesis of Co9S8 nanocages as an electrochemical sensor for luteolin detection. J Electrochem Soc

  32. Chen H et al (2020) Multi-population differential evolution-assisted Harris hawks optimization: Framework and case studies. Futur Gener Comput Syst 111:175–198

    Article  Google Scholar 

  33. Wang M, Chen H (2020) Chaotic multi-swarm whale optimizer boosted support vector machine for medical diagnosis. Appl Soft Comput 88:105946

  34. Xu Y et al (2019) Enhanced Moth-flame optimizer with mutation strategy for global optimization. Inf Sci 492:181–203

    Article  Google Scholar 

  35. Zhao X et al (2019) Chaos enhanced grey wolf optimization wrapped ELM for diagnosis of paraquat-poisoned patients. Comput Biol Chem 78:481–490

    Article  CAS  Google Scholar 

  36. Li C et al (2018) Developing a new intelligent system for the diagnosis of tuberculous pleural effusion. Comput Methods Programs Biomed 153:211–225

    Article  Google Scholar 

  37. Wang M et al (2017) Toward an optimal kernel extreme learning machine using a chaotic moth-flame optimization strategy with applications in medical diagnoses. Neurocomputing 267:69–84

    Article  Google Scholar 

  38. Xia J et al (2017) Ultrasound-based differentiation of malignant and benign thyroid nodules: an extreme learning machine approach. Comput Methods Programs Biomed 147:37–49

    Article  Google Scholar 

  39. Shen L et al (2016) Evolving support vector machines using fruit fly optimization for medical data classification. Knowl-Based Syst 96:61–75

    Article  Google Scholar 

  40. Chen H-L et al (2016) An efficient hybrid kernel extreme learning machine approach for early diagnosis of Parkinson′ s disease. Neurocomputing 184:131–144

    Article  Google Scholar 

  41. Hu L et al (2015) An efficient machine learning approach for diagnosis of paraquat-poisoned patients. Comput Biol Med 59:116–124

    Article  Google Scholar 

  42. Xu X, Chen H (2014) Adaptive computational chemotaxis based on field in bacterial foraging optimization. Soft Comput 18(4):797–807

  43. Zhang Y et al (2020) Boosted binary Harris hawks optimizer and feature selection. Engineering with Computers 25:26

    Google Scholar 

  44. Zhang Y et al (2020) Towards augmented kernel extreme learning models for bankruptcy prediction: algorithmic behavior and comprehensive analysis. Neurocomputing. https://doi.org/10.1016/j.neucom.2020.10.038

  45. Zhao D et al (2020) Chaotic random spare ant colony optimization for multi-threshold image segmentation of 2D Kapur entropy. Knowl-Based Syst p 106510

  46. Tu J et al (2021) Evolutionary biogeography-based whale optimization methods with communication structure: Towards measuring the balance. Knowl-Based Syst 212:106642

  47. Shan W et al (2020) Double adaptive weights for stabilization of moth flame optimizer: balance analysis, engineering cases, and medical diagnosis. Knowl-Based Syst p 106728

  48. Yu C et al (2021) SGOA: Annealing-behaved grasshopper optimizer for global tasks. Eng Comput p 1–28

  49. Hu J et al (2020) Orthogonal learning covariance matrix for defects of grey wolf optimizer: insights, balance, diversity, and feature selection. Knowl-Based Syst p 106684

  50. Zhao X et al (2014) Feature selection based on improved ant colony optimization for online detection of foreign fiber in cotton. Appl Soft Comput 24:585–596

    Article  CAS  Google Scholar 

  51. Yu H et al (2020) Dynamic Gaussian bare-bones fruit fly optimizers with abandonment mechanism: method and analysis. Eng Comput p 1–29

Download references

Acknowledgements

The authors would like to thank the reviewers for their thoughtful comments.

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

Contributions

All authors contributed equally.

Corresponding author

Correspondence to Abdolkarim Afroozeh.

Ethics declarations

Ethics Approval

Not applicable.

Consent to Participate

Not applicable.

Consent for Publication

Not applicable.

Conflict of Interest

The authors declare no competing interests.

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. Numerical and Analytical Modeling of Plasmonic Filter with High Q-Factor Based on “Nanostructured Resonator”. Plasmonics 17, 371–379 (2022). https://doi.org/10.1007/s11468-021-01527-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11468-021-01527-1

Keywords

Search

Navigation