AI-Enhanced GWO-FDTD Co-Design of Multi-Band Plasmonic Nanorings for Multiplexed Biosensing

محورهای موضوعی : فصلنامه نانوساختارهای اپتوالکترونیکی

Mohsen Nasrolahi ¹ , Ali Farmani ² , Ashkan Horri ³ , Hossein Hatami ⁴

1 - Department of Electrical Engineering, Technical and Vocational University (TVU), Tehran, Iran
2 - Department of Electrical Engineering, Lorestan univesity, Khramabad, Iran
3 - Department of Electrical Engineering, Arak Branch, Islamic Azad univesity, Arak, Iran
4 - Department of Mechanics Engineering, Lorestan univesity, Khoramabad, Iran

تاریخ دریافت : 1404/05/08 تاریخ پذیرش : 1404/05/08 تاریخ انتشار : 1404/05/08

کلید واژه: Ring resonator, Plasmonics sensor, FDTD,

چکیده مقاله :

In this paper, we explore the notable advancements in optical biosensors that have emerged over the past decade. This analysis includes innovative fabrication techniques and the growing areas of application. A historical overview of the development of optical biosensors since the 1970s is also presented, drawing from key literature. We further categorize biosensors and their typical architectures, highlighting new developments that may shape the current decade. Additionally, we discuss significant and creative application domains from the last ten years, illustrating the versatility of these sensors. The paper concludes by addressing the challenges and future possibilities of emerging technologies in optical biosensing for the current decade. By utilizing the GWO algorithm, researchers and engineers can efficiently explore the design space, identify optimal solutions, and enhance the performance of plasmonic nanoring resonators for various applications such as biosensing, optical communications, and photonics devices. When applied to the design of nanoring resonators, the grey wolf optimization algorithm can be used to optimize the parameters such as the dimensions of the nanoring, the material properties, and the operating conditions to achieve specific resonant frequencies or other desired characteristics. By iteratively updating the positions of a population of virtual wolves based on their fitness in the solution space, the algorithm can efficiently search for the best set of parameters for the nanoring resonator design.

چکیده انگلیسی:

In this paper, we explore the notable advancements in optical biosensors that have emerged over the past decade. This analysis includes innovative fabrication techniques and the growing areas of application. A historical overview of the development of optical biosensors since the 1970s is also presented, drawing from key literature. We further categorize biosensors and their typical architectures, highlighting new developments that may shape the current decade. Additionally, we discuss significant and creative application domains from the last ten years, illustrating the versatility of these sensors. The paper concludes by addressing the challenges and future possibilities of emerging technologies in optical biosensing for the current decade. By utilizing the GWO algorithm, researchers and engineers can efficiently explore the design space, identify optimal solutions, and enhance the performance of plasmonic nanoring resonators for various applications such as biosensing, optical communications, and photonics devices. When applied to the design of nanoring resonators, the grey wolf optimization algorithm can be used to optimize the parameters such as the dimensions of the nanoring, the material properties, and the operating conditions to achieve specific resonant frequencies or other desired characteristics. By iteratively updating the positions of a population of virtual wolves based on their fitness in the solution space, the algorithm can efficiently search for the best set of parameters for the nanoring resonator design.

منابع و مأخذ:

1. Adato, R., Yanik, A. A., Amsden, J. J., Kaplan, D. L., Omenetto, F. G., Hong, M. K., Erramilli, S., & Altug, H. (2009). Ultra-sensitive vibrational spectroscopy of protein monolayers with plasmonic nanoantenna arrays. Proc. Natl. Acad. Sci. U. S. A., 106, 19227.
2. Homola, J. (2008). Surface plasmon resonance sensors for detection of chemical and biological species. Chem. Rev., 108(2), 462–493. https://doi.org/10.1021/cr068107d
3. Anker, J. N., Hall, W. P., Lyandres, O., Shah, N. C., Zhao, J., & van Duyne, R. P. (2008). Biosensing with plasmonic nanosensors. Nat. Mater., 7(6), 442–453. https://doi.org/10.1038/nmat2162
4. Grover, R. (2003). Indium phosphide based optical micro-ring resonators. https://www.researchgate.net/publication/234216409_Indium_phosphide_based_optical_micro-ring_resonators
5. Rafizadeh, D. (1997). Experimental realization of nanofabricated semiconductor waveguide-coupled microcavity ring and disk optical resources. https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=Experimental+realization+of+nanofabricated+semiconductor+waveguide-coupled+microcavity+ring+and+disk+optical+resources%2C%E2%80%9D+Ph.D.+dissertation%2C+Northwestern+Univ.%2C+Evanston%2C+&btnG=
6. Geuzebroek, D. (2005). Flexible optical network components based on densely integrated microring resonators. https://research.utwente.nl
7. Tan, F. (2004). Integrated optical filters based on microring resonators. https://research.utwente.nl/en/publications/integrated-optical-filters-based-on-microring-resonators
8. Maier, S. A. (2007). Plasmonics: fundamentals and applications. J. Appl. Phys., 98(1), 011101. https://faculty.washington.edu/seattle/gis129/575%20copy/spr-books/Plasmonics.pdf
9. Zhang, J., & Wu, Y. (2023). Enhanced sensitivity in plasmonic ring resonators with hollow nanocylinders. Opt. Express, 31(5), 7890–7900. https://doi.org/10.1016/j.micrna.2022.207469
10. Chen, S., Autore, M., Li, J., Li, P., Alonso-Gonzalez, P., Yang, Z., Martin-Moreno, L., Hillenbrand, R., & Nikitin, A. Y. (2017). Acoustic graphene plasmon nanoresonators for field-enhanced infrared molecular spectroscopy. ACS Photonics, 4(12), 3089–3097. https://doi.org/10.1021/acsphotonics.7b00654
11. Liu, N., Mesch, M., Weiss, T., Hentschel, M., & Giessen, H. (2010). Infrared perfect absorber and its application as plasmonic sensor. Nano Lett., 10(7), 2342–2348. https://doi.org/10.1021/nl9041033
12. Ge, L., Feng, L., & Schwefel, H. G. L. (2017). Optical microcavities: New understandings and developments. Photonics Research, 5(6), OM1-OM3. https://doi.org/10.1364/PRJ.5.000OM1
13. Vollmer, F., & Arnold, S. (2008). Whispering-gallery-mode biosensing: label-free detection down to single molecules. Nat. Methods, 5(7), 591–596. https://doi.org/10.1038/nmeth.1221
14. Baaske, M., & Vollmer, F. (2016). Optical observation of single atomic ions interacting with plasmonic nanorods in aqueous solution. Nature Photonics, 10, 733-739. https://doi.org/10.1038/nphoton.2016.177
15. Hedhy, M., Ouerghi, F., Zeng, S., & AbdelMalek, F. (2024). Improved sensitivity of a sensor based on metallic nano-cylinder coated with graphene. Plasmonics, 19(4), 2053–2060. https://doi.org/10.1007/s11468-023-02139-7
16. Chen, H., Liao, L., Zhao, X., Fan, H., Zhang, H., Ren, K., & Jia, D. (2024). High-sensitivity electrocardiogram sensor based on Fano resonance in a double-stub-assisted plasmonic micro-ring resonator. Optics and Laser Technology, 169, 109874. https://doi.org/10.1016/j.optlastec.2023.109874
17. Korani, N., Mohammadi, S., Hocini, A., & Danaie, M. (2024). A tunable graphene dual mode absorber for efficient terahertz radiation absorption and sensing applications. Diamond and Related Materials, 149, 111554. https://doi.org/10.1016/j.diamond.2024.111554
18. Nguyen, A. V. T., Dao, T. D., Trinh, T. T. T., Choi, D.-Y., Yu, S.-T., Park, H., & Yeo, S.-J. (2020). Sensitive detection of influenza a virus based on a CdSe/CdS/ZnS quantum dot-linked rapid fluorescent immunochromatographic test. Biosensors and Bioelectronics, 155, 112090. https://doi.org/10.1016/j.bios.2020.112090
19. Moon, G., Lee, J., Lee, H., Yoo, H., Ko, K., Im, S., & Kim, D. (2022). Machine learning and its applications for plasmonics in biology. Cell Reports Physical Science, 3(9), 101042. https://doi.org/10.1016/j.xcrp.2022.101042
20. Nasrolahi, M., Farmani, A., Horri, A., & Hatami, H. (2025). Grey wolf optimization algorithm in conjunction with the FDTD method to analyze the nanostructure predicated on a plasmonic demultiplexer. Plasmonics. https://doi.org/10.1007/s11468-025-03016-1
21. S., N., Muthuswamy, J., Alsalman, O., & Patel, S. K. (2025). Graphene-based machine learning-optimized surface plasmon resonance biosensor design for skin cancer detection. Plasmonics. https://doi.org/10.1007/s11468-024-02734-2
22. Zhao, X., et al. (2023). Graphene-based tunable dual-band absorbers. Appl. Phys. Lett., 122(10), 101901. https://doi.org/10.1007/s11082-019-1882-0
23. Amoosoltani, N., Mehrabi, K., Zarifkar, A., Farmani, A., & Yasrebi, N. (2021). Double-ring resonator plasmonic refractive index sensor utilizing dual-band unidirectional reflectionless propagation effect. Plasmonics, 16(4), 1277-1285. https://doi.org/10.1007/s11468-021-01395-9
24. Moon, G., Lee, J., Lee, H., Yoo, H., Ko, K., Im, S., & Kim, D. (2022). Machine learning and its applications for plasmonics in biology. Cell Reports Physical Science, 3(9), 101042. https://doi.org/10.1016/j.xcrp.2022.101042
25. Das, P., & Varshney, G. (2023). Analysis of a Thin Tunable Silicon-Based Metamaterial Absorber for Sensing Applications. Silicon, 15(13), 5647–5658. https://doi.org/10.1007/s12633-023-02388-5
26. Li, L., Du, F., Zong, X., Cui, L., & Liu, Y. (2022). Plasmonic crystals fabricated by nanosphere lithography for advanced biosensing. Applied Optics, 61(23), 6924-6930. https://doi.org/10.1364/AO.464826
27. Farmani, A. (2019). Three-dimensional FDTD analysis of a nanostructured plasmonic sensor in the near-infrared range. Journal of the Optical Society of America B, 36(2), 401-407. https://doi.org/10.1364/JOSAB.36.000401
28. Farmani, A., Mir, A., & Sharifpour, Z. (2018). Broadly tunable and bidirectional terahertz graphene plasmonic switch based on enhanced Goos-Hänchen effect. Applied Surface Science, 453, 358-364. https://doi.org/10.1016/j.apsusc.2018.05.092
29. Khani, S., Farmani, A., & Mir, A. (2021). Reconfigurable and scalable 2,4-and 6-channel plasmonics demultiplexer utilizing symmetrical rectangular resonators containing silver nano-rod defects with FDTD method. Scientific Reports, 11(1), 13628. https://doi.org/10.1038/s41598-021-93167-y
30. Xue, J., Zhang, Y., Guang, Z., Hu, J., Zhao, F., Liu, Y., & Shao, L. (2025). MoS2 surface plasmon resonance based high-resolution THz biosensor using a dual D-shaped channel micro-structured fiber. Optics & Laser Technology, 180, 111387. https://doi.org/10.1016/j.optlastec.2024.111387
31. Liu, H., Duan, S., Chen, C., Cui, H., Gao, P., Dai, Y., Gao, Z., Wang, X., & Zhou, T. (2024). Graphene-enabled chiral metasurface for terahertz wavefront manipulation and multiplexing holographic imaging. Optical Materials, 147, 114654. https://doi.org/10.1016/j.optmat.2023.114654
32. Zhao, X., Yuan, C., Zhu, L., & Yao, J. (2016). Graphene-based tunable terahertz plasmon-induced transparency metamaterial. Nanoscale, 8(33), 15273-15280. https://doi.org/10.1039/C5NR07114C
33. Butt, M. A. (2024). Plasmonic sensors based on a metal-insulator-metal waveguide - what do we know so far? Sensors, 24(22), 7158. https://doi.org/10.3390/s24227158
34. Kazanskiy, N. L., Khonina, S. N., & Butt, M. A. (2020). Plasmonic sensors based on metal-insulator-metal waveguides for refractive index sensing applications: A brief review. Physica E: Low-dimensional Systems and Nanostructures, 117, 113798. https://doi.org/10.1016/j.physe.2019.113798
35. Butt, M. A., Kazanskiy, N. L., & Khonina, S. N. (2022). Advances in Waveguide Bragg Grating Structures, Platforms, and Applications: An Up-to-Date Appraisal. Biosensors, 12, 497. https://doi.org/10.3390/bios12070497
36. Fallahi, V., Kordrostami, Z., & Hosseini, M. (2024). Sensitivity and quality factor improvement of photonic crystal sensors by geometrical optimization of waveguides and micro-ring resonators combination. Scientific Reports, 14(1), 2001. https://doi.org/10.1038/s41598-024-52363-2
37. Danaie, M., & Kaatuzian, H. (2010). Design of a photonic crystal differential phase comparator for a Mach-Zehnder switch. Journal of Optics, 13(1), 015504. https://doi.org/10.1088/2040-8978/13/1/015504
38. Zhang, J.; Hong, Q.; Zou, J.; He, Y.; Yuan, X.; Zhu, Z.; Qin, S. Fano-Resonance in Hybrid Metal-Graphene Metamaterial and Its Application as Mid-Infrared Plasmonic Sensor. Micromachines 2020, 11, 268. https://doi.org/10.3390/mi11030268
39. Mansuri, M., Mir, A., & Farmani, A. (2021). A tunable nonlinear plasmonic multiplexer/demultiplexer device based on nanoscale ring resonators. Photonic Network Communications, 42(3), 209-218. https://doi.org/10.1007/s11107-021-00953-9
40. Wang, Q., Ouyang, Z., Lin, M., & Zheng, Y. (2021). High-quality graphene-based tunable absorber based on double-side coupled-cavity effect. Nanomaterials, 11(11), 2824. https://doi.org/10.3390/nano11112824
41. Sadeghzadeh, M., Mohammadi, A., & Jalali, T. (2025). FDTD study of plasmon-exciton coupling for bio-nanosensors. Results in Chemistry, 16, 102450. https://doi.org/10.1016/j.rechem.2025.102450
42. Butt, M. A., Kazanskiy, N. L., & Khonina, S. N. (2023). A Review on Photonic Sensing Technologies: Status and Outlook. Biosensors, 13(5), 568. https://doi.org/10.3390/bios13050568
43. Butt, M. A., Kazanskiy, N. L., & Khonina, S. N. (2020). Nanodots decorated asymmetric metal-insulator-metal waveguide resonator structure based on Fano resonances for refractive index sensing application. Laser Physics, 30(7), 076204. https://doi.org/10.1088/1555-6611/ab9090
44. Huaiqing, L., Gao, Y., Zhu, B., Ren, G., & Jian, S. (2015). A T-shaped high resolution plasmonic demultiplexer based on perturbations of two nanoresonators. Optics Communications, 334, 164–169. https://doi.org/10.1016/j.optcom.2014.08.039
45. Saha, N., Brunetti, G., Kumar, A., & others. (2022). Highly sensitive refractive index sensor based on polymer Bragg grating: A case study on extracellular vesicles detection. Biosensors, 12(6), 415. https://doi.org/10.3390/bios12060415
46. Yesilkoy, F., et al. (2019). Ultrasensitive hyperspectral imaging and biodetection enabled by dielectric metasurfaces. Nat. Photonics, 13(6), 390–396. https://doi.org/10.1038/s41566-019-0394-6
47. Wu, Q., Xiao, Y., Zhao, G., & Song, Q. (2024). Evolutionary processes and applications of microfiber resonant Rings: A systematic exploration for sensitivity enhancement. Optics and Laser Technology, 174, 110567. https://doi.org/10.1016/j.optlastec.2024.110567
48. Taflove, A., & Hagness, S. C. (2005). Computational electrodynamics: the finite-difference time-domain method. Artech House.
49. Lyu, J., Huang, L., Chen, L., Zhu, Y., & Zhuang, S. (2024). Review on the terahertz metasensor: from featureless refractive index sensing to molecular identification. Photonics Research, 12(2), 194. https://doi.org/10.1364/prj.508136
50. Zhang, Z., Yang, J., He, X., Zhang, J., Huang, J., Chen, D., & Han, Y. (2018). Plasmonic refractive index sensor with high figure of merit based on concentric-rings resonator. Sensors, 18(1), 116. https://doi.org/10.3390/s18010116
51. Bhalla, N., Pan, Y., Yang, Z., & Payam, A. F. (2020). Opportunities and challenges for biosensors and nanoscale analytical tools for pandemics: COVID-19. ACS Nano, 14(7), 7783-7807. https://doi.org/10.1021/acsnano.0c04421
52. Khani, S., & Hayati, M. (2022). Optical sensing in single-mode filters based on surface plasmon H-shaped cavities. Optics Communications, 505, 127534. https://doi.org/10.1016/j.optcom.2021.127534
53. Li, Z., Sun, X., Ma, C., Li, J., Li, X., Guan, B.-O., & Chen, K. (2021). Ultra-narrow-band metamaterial perfect absorber based on surface lattice resonance in a WS2 nanodisk array. Optics Express, 29, 27084-27091. https://doi.org/10.1364/OE.434349
54. Špačková, B., Wrobel, P., Bocková, M., & Homola, J. (2016). Optical biosensors based on plasmonic nanostructures: A review. Proceedings of the IEEE, 104(12), 2380-2408. https://doi.org/10.1109/JPROC.2016.2624340
55. Khani, S., Danaie, M., & Rezaei, P. (2020). Realization of a plasmonic optical switch using improved nano-disk resonators with Kerr-type nonlinearity: A theoretical and numerical study on challenges and solutions. Optics Communications, 477, 126359. https://doi.org/10.1016/j.optcom.2020.126359
56. Danaie, M., & Shahzadi, A. (2019). Design of a high-resolution metal-insulator-metal plasmonic refractive index sensor based on a ring-shaped Si resonator. Plasmonics, 14. https://doi.org/10.1007/s11468-019-00926-9
57. Guo, R., Gao, H., Liu, T., & Cheng, Z. (2022). Ultra-thin mid-infrared silicon grating coupler. Optics Letters, 47, 1226-1229. https://doi.org/10.1364/OL.449140
58. Alipour, A., Mir, A., & Farmani, A. (2020). Analytical modeling and design of a graphene metasurface sensor for thermo-optical detection of terahertz plasmons. IEEE Sensors Journal. https://doi.org/10.1109/JSEN.2020.303557710
59. Farmani, A., Mir, A., & Sharifpour, Z. (2018). Broadly tunable and bidirectional terahertz graphene plasmonic switch based on enhanced Goos-Hänchen effect. Applied Surface Science, 453, 358-364. https://doi.org/10.1016/j.apsusc.2018.05.092
60. Lu, Y., Rhee, J., Jang, W., & Lee, Y. (2010). Active manipulation of plasmonic electromagnetically-induced transparency based on magnetic plasmon resonance. Optics Express, 18, 20912-20917. https://doi.org/10.1364/OE.18.020912
61. Farmani, A., Miri, M., & Sheikhi, M. H. (2017). Analytical modeling of highly tunable giant lateral shift in total reflection of light beams from a graphene containing structure. Optics Communications, 391, 68-76. https://doi.org/10.1016/j.optcom.2017.01.018
62. Arellano Vidal, C. L., & Govan, J. E. (2024). Machine learning techniques for improving nanosensors in agroenvironmental applications. Agronomy, 14(2), 341. https://doi.org/10.3390/agronomy14020341
63. Divya, J., Selvendran, S., Raja, A. S., & Sivasubramanian, A. (2022). Surface plasmon based plasmonic sensors: A review on their past, present and future. Biosensors and Bioelectronics: X, 11, 100175. https://doi.org/10.1016/j.biosx.2022.100175
64. Sun, X., Mojahedi, M., & Aitchison, J. S. (2016). Hybrid plasmonic waveguide-based ultra-low insertion loss transverse electric-pass polarizer. Optics Letters, 41(17), 4020-4023. https://doi.org/10.1364/OL.41.004020
65. Wang, Y., et al. (2021). Wearable plasmonic-metasurface sensor for noninvasive and universal molecular fingerprint detection on biointerfaces. Sci. Adv., 7(4), eabe4553. https://doi.org/10.1126/sciadv.abe4553
66. Dmitriev, P. A., Lassalle, E., Ding, L., Pan, Z., Neo, D. C. J., Valuckas, V., Paniagua-Dominguez, R., Yang, J. K. W., Demir, H. V., & Kuznetsov, A. I. (2023). Hybrid dielectric-plasmonic nanoantenna with multiresonances for subwavelength photon sources. ACS Photonics, 10(3), 582-594. https://doi.org/10.1021/acsphotonics.2c01332
67. Wang, S., Zhu, Y., Luo, S., Zhu, E., & Chen, S. (2021). Compact hybrid plasmonic slot waveguide sensor with a giant enhancement factor for surface-enhanced Raman scattering application. Optics Express, 29, 24765-24778. https://doi.org/10.1364/OE.431274
68. Nasrolahi, M., Farmani, A., Horri, A., & Hatami, H. (2024). FDTD analysis of a high-sensitivity refractive index sensing based on Fano resonances in a plasmonic planar split-ring resonators. Journal of Optical and Photonic Nanostructures, 9(3), 91-115. https://doi.org/10.30495/jopn.2024.33499.1321
69. Farmani, A., & Mir, A. (2019). Graphene sensor based on surface plasmon resonance for optical scanning. IEEE Photonics Technology Letters, 31(8), 643-646. https://doi.org/10.1109/LPT.2019.2904618
70. Butt, M. A., Khonina, S. N., & Kazanskiy, N. L. (2021). Recent advances in photonic crystal optical devices: A review. Optics & Laser Technology, 142, 107265. https://doi.org/10.1016/j.optlastec.2021.107265
71. Farmani, A., Miri, M., & Sheikhi, M. H. (2017). Analytical modeling of highly tunable giant lateral shift in total reflection of light beams from a graphene containing structure. Optics Communications, 391, 68-76. https://doi.org/10.1016/j.optcom.2017.01.018
72. Farmani, A., Mir, A., & Sharifpour, Z. (2018). Broadly tunable and bidirectional terahertz graphene plasmonic switch based on enhanced Goos-Hänchen effect. Applied Surface Science, 453, 358-364. https://doi.org/10.1016/j.apsusc.2018.05.092
73. Butt, M. A., Khonina, S. N., & Kazanskiy, N. L. (2021). Recent advances in photonic crystal optical devices: A review. Optics & Laser Technology, 142, 107265. https://doi.org/10.1016/j.optlastec.2021.107265