Open Access
Add to BibSonomy
Abstract
Hyperbolic metamaterials (HMMs) have attracted increasing attentions because of their unique dispersion properties and the flexibility to control the dispersion by changing the components and fractions of the composed materials. In this work, for the first time, we demonstrate a plasmonic sensor based on a side-polished few-mode-fiber coated with a layered of HMM, which is composed of alternating layers of Ag and TiO2. To optimize the sensor performance, the effects of the metal filling fraction (ρ) and the number of bilayers (Nbi) on the HMM dispersion are thoroughly engineered with the effective medium theory and the finite element method. It is found that the HMM with ρ=0.7 and Nbi = 3 can provide the average sensitivity of 5114.3 nm/RIU (RIU: refractive index unit), and the highest sensitivity 9000 nm/RIU in the surrounding refractive index (SRI) ranging from 1.33 to 1.40 RIU. The corresponding figure of merit (FOM) reaches a maximum of 230.8 RIU-1 which is much higher than that of the conventional silver film based SPR sensor. The influence of ρ and Nbi on the sensitivity are well explained from the aspects of the electrical field distribution and the dispersion relationship. This work opens a gate to significantly improve fiber plasmonic sensors performance by engineering the HMM dispersion, which is expected to meet the emergent demand in the biological, medical and clinical applications.
© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
The surface plasmon resonance (SPR) is an optical phenomenon occurred at an interface between a metal and a dielectric when the wave vectors of the incident light and the surface plasmon wave are matched, and it will result a resonance dip in the transmittance spectra [1]. The wavelength with the lowest transmittance, usually called the resonant wavelength, is highly sensitive to the change of surrounding refractive index (SRI) [2]. Since the SPR technology shows merits in the high-sensitivity and label-free detection [3], it has been intensively involved in medical detection [4], food safety [5], drug screening [6], and environmental monitoring [7]. However, a huge challenge still exists in the SPR sensors when applied in detecting the analytes with ultralow concentration or the small molecules with the molecular weight less than 500 Da [8–10]. In order to address this challenge, various methods have been proposed to improve the performance of the SPR sensors, such as adding a layer of nanomaterials with a high refractive index or large surface areas (e.g. Si, ITO, WS2, MoS2, MoSe2, graphene oxide, etc.) on the metal layer [11–18] and engineering the metal layer to periodic strips or pillar arrays [19–21]. The essence of the mentioned examples to obtain higher sensitivities is to engineer the dispersion of the surface plasmon by the method of covering the metal film with nanomaterials or patterning the metal layer. However, the former method has suffered a limited sensitivity improvement due to the small dispersion modification exerted by the added material; while the latter one needs complicated fabrication process with expensive equipment like electron beam lithography or focused ion beam.
Recent investigations have demonstrated that the hyperbolic metamaterial (HMM), which possesses a hyperbolic dispersion with the parallel and perpendicular component having opposite signs [22], has been employed in plasmonic sensors and promoted remarkable improvement in the sensor performances [23–26]. For instance, the biosensors constructed by metallic diffraction grating-coupled HMM can effectively improve the sensitivity (S) and figure of merit (FOM) to a very high level of 30000 nm/RIU and 590 RIU−1, respectively [24]. The Kretschmann configuration coupled with nanorod HMM structure can also achieve the comparable improvement [25]. However, the above reported sensors are all based on a prism or grating coupling configuration and operated in the form of spatial light path, which would bring problems to the miniaturization and integration [20]. These drawbacks can be easily overcome by employing a side-polished fiber (SPF) as the waveguide to fabricate an SPR sensor, because the SPF has the advantages of low cost, easy fabrication and integration, and its planar and smooth surface provides an ideal platform for HMM deposition [27,28].
In this paper, we propose and numerically investigate a novel plasmonic sensor based on an SPF coated with HMM that is composed of multiple bilayers of silver and titanium-dioxide (Ag/TiO2) structure. Our design integrates the advantages of SPF and HMM, resulting in a high-performance sensor with a compact all-fiber configuration. Using the effective medium theory (EMT) and resonant coupling conditions, we obtain that the sensor is more sensitive in the long wavelength range. Further, a finite element method was used to comprehensively optimize its metal filling fraction (ρ) and the number of the bilayers (Nbi). According to the maximum FOM, the best parameters were selected when ρ=0.7 and Nbi=3, respectively. With the optimized parameters, the highest average S value of 5114.3 nm/RIU and FOM of 182.0 RIU−1 can be achieved in the range of 1.33∼1.40 RIU. The performance improvement is analyzed in detail from the both perspectives of the dispersion relationship and electrical field enhancement. The proposed method to construct a fiber plasmonic sensor based on a layered HMM, which integrates the highly flexible opportunity to tune the dispersion and subsequently greatly improved performance, will lay a keystone in the development of high-performance fiber plasmonic sensors.
2. Calculation based on effective medium theory
The proposed sensor is constructed by coating the HMM layers on the surface of the side-polished few-mode fiber (HMM-SP-FMF). The few-mode fiber has a residual fiber thickness (RFT) of 72 μm. The over-coated HMM are composed of multiple periodic bilayers of silver and titanium-dioxide, and the thickness of each bilayer is 30 nm. The parameters used in the simulation are consistent with those of the commercial few-mode step-index fiber (FMF, OFS), which has a core/cladding diameter of 19/125 μm. The schematic diagram and the cross-sectional view of the HMM-SP-FMF sensor are shown in Figs. 1(a) and (b), respectively. The x-axis is set along the fiber direction, and the y and z-axis are perpendicular to the fiber direction as shown in Fig. 1(a). The refractive indices of the fiber core and cladding are 1.449 and 1.444, respectively, neglecting the dispersion of optical fiber.
Fig. 1. (a) Schematic diagram and (b) the cross-sectional view of the proposed side-polished fiber based plasmonic sensor coated with a layered hyperbolic metamaterial (HMM-SP-FMF). SPF, side-polished fiber; HMM, hyperbolic metamaterial; RFT, residual fiber thickness.
The hyperbolic properties of the multilayer metal-dielectric films can be illustrated with the EMT. Because the thickness of the Ag/TiO2 bilayer is 30 nm and much smaller than the operating wavelength, usually a few hundred nanometers, thus satisfying the long wave limit, the criteria of EMT can be used to evaluate the components of the equivalent dielectric tensor of the HMM [29], as follows:
Fig. 2. (a) The effective permittivity of Ag/TiO2 HMM calculated by EMT. The blue line and the red line represent the permittivity component of εx and εz with ρ=0.7; the solid lines represent the real part, and the dotted lines represent the imaginary part; The non-hyperbolic and hyperbolic domain are plotted in purple and yellow background, respectively. (b) The real part relation curve between kx and kz for ρ=0.7, with colored lines representing different wavelengths.
In order to make EMT suitable for to calculate the dispersion, we have simplified the sensing region of the optical fiber into a two-dimensional total-reflection model. Because the surface plasmon wave propagates along the interface between metal and dielectric, the resonant condition is determined by the parallel component εx, which can be obtained by the EMT from Eq. (1). Therefore, the coupling condition formula can be expressed as:
From Ref. [32], the wavelength sensitivity of the sensor can be calculated by the following approximate formula:
Fig. 3. (a) The relationship between wavelength and the effective refractive index kx/k0. Different colors represent the effective refractive index with different ρ, Ag represents ρ=1, and ncsinθ represents the incident light. (b) The resonant wavelengths in achieved in (a) at different metal filling fractions. (c) The sensitivity of HMM in different ρ. Different colored lines represent different metal filling fractions (ρ), and Ag represents ρ=1. The Roman numerals (I ∼ VI) in the three sub-figures represent the corresponding resonant wavelength points.
3. Simulation based on finite element method
After qualitatively analyzing the relationship between the sensitivity and the metal filling fractions ρ, we adopt the finite element method to quantitatively calculate the transmission spectra of the sensors and further analyze their sensitivity (S), full width at half maximum (FWHM), FOM (FOM = S/FWHM), and depth of resonance dip (DRD) [1]. The transmission spectra of the sensors are obtained using the following equation [33]:
3.1 Mode selection
Although the few-mode fiber usually guides several modes simultaneously, to simplify the following operation, only an appropriate mode is selected for the parameter optimization. The dispersion characteristics of the core modes LP01, LP11a, LP11b, LP21a, and LP21b are analyzed at Nbi=3, ρ=0.5, RFT=72 μm, and SRI=1.33. The electrical field amplitude of different modes at the wavelength of 820 nm are shown in F 4(a), and a sharp peak can be seen in the vicinity of the HMM surface, indicating that plasmon resonance exists in these modes. The transmission spectra for different modes of the sensor are plotted in Fig. 4(b), where the black line represents the superposition, which is the average of all the five modes of LP01, LP11a, LP11b, LP21a, and LP21b. Since the superimposed mode and its composing modes show similar resonant wavelength shifts when SRI is changed from 1.33 to 1.34 RIU; while their FWHMs are 33, 55, 27, 54, 42 and 40 nm, respectively. Further study shows that the three modes of LP11a, LP21a and LP21b modes cannot be selected in some combination of ρ and Nbi parameters (for example, when the ρ is less than 0.5, or when the Nbi is small) because the loss spectrum range is too wide to find out the resonance point. The resonant wavelength deviation of LP11b and LP01 with the superimposed spectrum is 1 nm, but the FWHM of LP01 mode is closer to superposition. In addition, as the fundamental mode, LP01 mode can be easily extracted from all the calculated modes, facilitating the subsequent optimization and comparison process. Therefore, the LP01 mode is selected for the subsequent numerical investigation.
Fig. 4. (a) The electrical field amplitude along the z-axis for the modes of LP01, LP11a, LP11b, LP21a, and LP21b modes at their resonant wavelengths for Nbi=3, ρ=0.5, RFT=72 μm and SRI=1.33, the right insets are their corresponding contour maps. Note that the coordinate system is the same to that depicted in Fig. 1. (b) Transmission spectra of the LP01, LP11a, LP11b, LP21a, and LP21b modes and their superposition (black line) at SRI=1.33 and 1.34, respectively.
3.2 Optimization of the HMM
By varying the ρ and Nbi, the dispersion of the HMM was tuned to find the best design for the HMM-SP-FMF sensor. The transmission spectra under different ρ for Nbi=3 when the SRI increases from 1.33 (Fig. 5(a)) to 1.34 (Fig. 5(b)). For a given Nbi, the resonant wavelength increases from 690 to 971 nm with the decreased ρ, as shown in Fig. 5(a) or (b), accompanying with an increase of the depth of the resonance dip. Figures 5(d) and (e) show that as the Nbi increases from 1 to 4, the resonant wavelength shifts approximately from 541 to 693 nm while the resonance depth keeps decreasing. The coupling coefficients between SP modes and core modes can be verified by the DRD of the plasmon resonance transmission. Furthermore, when Nbi is 5 the DRD comes to zero. This can be attributed tothe low coupling efficiency between surface plasmon mode and LP mode and limited leakage of the electric field from the fiber core [34]. To summarize, it is found that the resonant wavelengths could be regulated over a few hundred nanometers by both changing the ρ and varying the Nbi. Furthermore, the S and FOM can be calculated, and the results are presented in Fig. 5(c) and (f), which shows that with the increase of ρ, the S of sensor decreases while FOM increases. The highest S and FOM are 3700 nm/RIU and 161.1 RIU−1 when the ρ are 0.3 and 0.7. Obviously, the sensitivity of the HMM-SP-FMF sensor is higher than that of the 40 nm Ag-SPR sensor in both simulation and theoretical calculation. The sensitivity obtained in the simulation is similar to that calculated by EMT, with an average error within 5%. There are two main reasons for the error: first, the change of refractive index in the simulation is at least 0.01 RIU, and it is close to infinitesimal in the calculation by EMT; second, the Eq. (7) used to calculate the sensitivity is an approximate formula. The S increases first when Nbi increases from 1 to 3, and remains constant thereafter. Meanwhile, the change trend of FOM is the same as S. Since the FOM is defined as the ratio of the sensing sensitivity to the FWHM, there is a trade-off between the sensitivity and FWHM of the SPR spectrum. Therefore, it is necessary to optimize the parameters of the ρ and Nbi of HMM for achieving the highest FOM for the HMM-SP-FMF sensors.
Fig. 5. (a) The dependence of transmittance spectrum on Nbi=3 and SRI=1.33; (b) The dependence of transmittance spectrum on Nbi=3 and SRI=1.34; (c) The dependence of S and FOM on ρ when Nbi is fixed at 3, and the 40 nm Ag-SPR sensor; (d) The dependence of transmittance spectrum on ρ=0.7 for SRI=1.33, and (e) The dependence of transmittance spectrum on ρ=0.7 and SRI=1.34; (f) The dependence of S and FOM on Nbi when ρ is fixed at 0.7. Note that in (a) and (b) the different colored lines represent different ρ; in (d) and (e) the different colored lines represent different Nbi; in (c) and (f) black bar indicates sensitivity, red bar indicates FOM, and gray bar with pattern indicates sensitivity calculated using EMT.
To make a comprehensive comparison and thus find the optimized parameters, we summarize the influences of Nbi and ρ on the performance of sensor including S, FWHM, FOM, and DRD in Fig. 6. As shown in Fig. 6(a), the DRD decreases with the increase of Nbi until it finally reaches 0. At fixed Nbi, the DRD is reduced with the increase of ρ. The maximum DRD is 1, suggesting the coupling efficiency between SP mode and core mode can arrive 100%. Figure 6(b) shows the variation of FWHM with the ρ and Nbi. With the increase of Nbi from 1 to 6, the FWHM first increases and then decreases. At fixed Nbi, the FWHM gradually decreases with the increase of ρ, except that Nbi was 1. Figure 6(c) depicts the change of sensitivity with the ρ and Nbi. The general trend is that the sensitivity first increases and then remains unchanged as the ρ and Nbi increase, with maximum sensitivity reaching 4000 nm/RIU. A wide FWHM, however, results in low sensing resolution and poor performance. Therefore, as a comprehensive optimization parameter, FOM is adopted to compare the performance of sensors. As shown in Fig. 6(d), the value of FOM is influenced by the ρ and Nbi. The FOM has a maximum value of 161.1 RIU−1 when the ρ and Nbi are 0.7 and 3, respectively.
Fig. 6. The dependence of (a) DRD, (b) FWHM, (c) S, and (d) FOM on the ρ and Nbi in the case of SRI changing from 1.33 to 1.34, with the colors of the columns representing the different ρ.
Figure 7(a) and (b) shows the spectra of HMM-SP-FMF (ρ = 0.7, Nbi = 3) and Ag-SPR (Ag thickness: 40 nm [27]) at different SRI. The resonant wavelength has an exponential growth with SRI, shifting from 690 to 1048 nm as the SRI increases from 1.33 to 1.40. Likewise, the resonant wavelengths of the spectra in Fig. 7(b) increase exponentially with increase of SRI, but they are in a shorter wavelength range (483-749 nm). The comparison of their sensitivity and FOM is shown in Fig. 7(c) and (d), the average sensitivity of HMM and Ag-SPR sensors is 5114.3 and 3800 nm/RIU, and the average FOM is 182.0 and 155.0 RIU−1, respectively. At high SRI region of 1.39 to 1.40, the resonant wavelength of HMM-SP-FMF sensor shifts from 958 to 1048 nm, which corresponds to an S of 9000 nm/RIU and an FOM of 230.8 RIU−1. Therefore, compared to the Ag-SPR sensor, the advantage of the HMM-SP-FMF sensor is that the HMM composed of alternative Ag/TiO2 has a higher effective refractive index than pure Ag film, which makes the surface plasmon wave satisfy the resonant condition at a longer wavelength, therefore results in a higher sensitivity and FOM for HMM-SPR sensor. Note that the comparison is based on the equivalent SRI for the Ag-SPR and HMM-SPR sensor.
Fig. 7. Transmission spectra and the sensing performance for the HMM-SP-FMF and the Ag-SPR sensor. The transmission spectra of (a) the HMM-SP-FMF (ρ=0.7, Nbi = 3) and (b) Ag-SPR. (c) Comparison of the sensitivities; (d) Comparison of the FOMs.
3.3 Comparison and discussion
Concerning the key performances of S, FWHM, and FOM, Table 1 summarizes the results of fiber SPR sensors from previous reports, including various fiber types (single-mode [27], multimode [28] [31], plastic [36] and photonic crystal fiber [35]) and various plasmon excited configurations (fiber-Bragg grating [39], long-period fiber grating [38] and long-range SPR sensors [20]). The HMM-SP-FMF sensor proposed in this paper has great advantages in sensitivity and FOM compared with various fiber SPR sensors listed in the table. Moreover, due to the simplicity and good repeat-ability of the fabrication method in this work, the performance can be further improved when combined with other optical fiber structures.
Table 1. Comparison of various fiber SPR sensors
To further analyze our results, the electric field amplitude and loss with different ρ and Nbi are calculated and presented in Figs. 8. For the convenience to compare, the electric field is normalized and the position where the resonance appears is magnified. In Fig. 8(a), the ρ is ranging from 0.3 to 0.7, the amplitude of electric field increases with the decrease of ρ and the corresponding to the peak of resonance fraction is 1 and 0.18, respectively. Therefore, a smaller ρ can produce a deeper evanescence penetration and higher field intensity to the SRI, thus improving the S of the sensor [40]. When ρ is in the range of 0.3∼0.7, Fig. 8(b) shows that a smaller ρ is accompanied by a higher loss (calculated with the formula αloss = 8.686×(2π/λ)×Im(neff)×107(dB/cm) [41]), which leads to the spectrum broadening and thus larger FWHM. As a result, a smaller ρ has a higher S and a broader FWHM. As shown in Fig. 8(c), for different Nbi, the amplitude of electric field decreases significantly with the increase of Nbi, and when Nbi = 5, there is no sharp peak near the surface of HMM. Therefore, with the increase of Nbi, the electric field amplitude decreases with the increase of Nbi and eventually disappears. It can also seen from the Fig. 8(d) that when Nbi is 5, the loss is almost zero, indicating the resonance cannot be achieved. With the increase of Nbi, the resonant wavelength is red shifted with decreasement of the loss and FWHM. Therefore, for a fixed ρ, the evanescent wave cannot penetrate the material when Nbi reaches a certain value, and the loss will be reduced to zero, thus no plasmon resonance will be occurred.
Fig. 8. (a) (c) the electrical field amplitude along the z-axis, and a local enlarged view of 9.45-9.7 μm on the Z-position is shown in the right; (b) (d) Loss spectra of the LP01 mode. (a) (c) For different ρ; (d) For different Nbi.
4. Conclusion
In summary, we numerically demonstrated a high-performance fiber plasmonic sensor by engineering the dispersion of hyperbolic metamaterials. This paper focuses on the investigation of the influences of ρ and Nbi on the dispersion properties and hence on the sensor performance. By optimizing the optimal parameter combination corresponding to different ρ and Nbi, which can be selected according to their own requirements. The optimized HMM provides a small FWHM, high S and FOM. In the SRI ranging from 1.33 to 1.40, the highest average S obtained are 5114.3 nm/RIU and the best average FOM obtained is 182.0 RIU−1 with ρ=0.7 and Nbi=3, respectively. For the high SRI region from 1.39 to 1.40, the S can reach up to 9000 nm/RIU, corresponding to the FOM of 230.8 RIU−1. The greatly improved plasmonic sensors show prospect in the detection of analyte with ultra-low molecular-weights or low concentrations. Moreover, the easy fabrication of the layered HMM as well as the mode-multiplexing advantages brought by the optical fiber are fully integrated into the sensing system, the HMM-SP-FMF sensors would find great practical applications in bio-chemical, environmental, and food safety assessing with high sensitivities and high figure of merits.
Funding
Fundamental Research Funds for the Central Universities (21618404, 21619102); Scientific Research Fund of Tianhe District, Guangzhou (2018AY003); National Natural Science Foundation of China (61575084, 61805108, 61904067); Guangdong Basic and Applied Basic Research Foundation (2017A010101013, 2020A1515011498); Science & Technology Project of Guangzhou (201605030002, 201704030105, 201707010500, 201807010077).
Disclosures
The authors declare no conflicts of interest.
References
1. J. N. Anker, W. P. Hall, O. Lyandres, N. C. Shah, J. Zhao, and R. P. Van Duyne, “Biosensing with plasmonic nanosensors,” in Nanoscience and Technology: A Collection of Reviews from Nature Journals (World Scientific, 2010), pp. 308–319.
2. S. Zeng, D. Baillargeat, H.-P. Ho, and K.-T. Yong, “Nanomaterials enhanced surface plasmon resonance for biological and chemical sensing applications,” Chem. Soc. Rev. 43(10), 3426–3452 (2014). [CrossRef]
3. P. Mao, Y. Luo, C. Chen, S. Peng, X. Feng, J. Tang, J. Fang, J. Zhang, H. Lu, and J. Yu, “Design and optimization of surface plasmon resonance sensor based on multimode fiber,” Opt. Quantum Electron. 47(6), 1495–1502 (2015). [CrossRef]
4. C. Ribaut, M. Loyez, J.-C. Larrieu, S. Chevineau, P. Lambert, M. Remmelink, R. Wattiez, and C. Caucheteur, “Cancer biomarker sensing using packaged plasmonic optical fiber gratings: Towards in vivo diagnosis,” Biosens. Bioelectron. 92, 449–456 (2017). [CrossRef]
5. F. Fathi, H. Mohammadzadeh-Aghdash, Y. Sohrabi, P. Dehghan, and J. E. N. Dolatabadi, “Kinetic and thermodynamic studies of bovine serum albumin interaction with ascorbyl palmitate and ascorbyl stearate food additives using surface plasmon resonance,” Food Chem. 246, 228–232 (2018). [CrossRef]
6. K. Stembera, S. Vogel, A. Buchynskyy, J. A. Ayala, and P. Welzel, “A surface plasmon resonance analysis of the interaction between the antibiotic moenomycin A and penicillin-binding protein 1b,” ChemBioChem 3(6), 559–565 (2002). [CrossRef]
7. M. S. Rahman, M. S. Anower, M. R. Hasan, M. B. Hossain, and M. I. Haque, “Design and numerical analysis of highly sensitive Au-MoS2-graphene based hybrid surface plasmon resonance biosensor,” Opt. Commun. 396, 36–43 (2017). [CrossRef]
8. O. V. Gnedenko, Y. V. Mezentsev, A. A. Molnar, A. V. Lisitsa, A. S. Ivanov, and A. I. Archakov, “Highly sensitive detection of human cardiac myoglobin using a reverse sandwich immunoassay with a gold nanoparticle-enhanced surface plasmon resonance biosensor,” Anal. Chim. Acta 759, 105–109 (2013). [CrossRef]
9. L. Guo, J. A. Jackman, H.-H. Yang, P. Chen, N.-J. Cho, and D.-H. Kim, “Strategies for enhancing the sensitivity of plasmonic nanosensors,” Nano Today 10(2), 213–239 (2015). [CrossRef]
10. R. Karlsson and R. Stahlberg, “Surface plasmon resonance detection and multispot sensing for direct monitoring of interactions involving low-molecular-weight analytes and for determination of low affinities,” Anal. Biochem. 228(2), 274–280 (1995). [CrossRef]
11. H. Wang, H. Zhang, J. Dong, S. Hu, W. Zhu, W. Qiu, H. Lu, J. Yu, H. Guan, and S. Gao, “Sensitivity-enhanced surface plasmon resonance sensor utilizing a tungsten disulfide (WS 2) nanosheets overlayer,” Photonics Res. 6(6), 485–491 (2018). [CrossRef]
12. A. Lahav, A. Shalabaney, and I. S. Abdulhalim, “Surface plasmon sensor with enhanced sensitivity using top nano dielectric layer,” J. Nanophotonics 3(1), 031501 (2009). [CrossRef]
13. R. Tabassum and B. D. Gupta, “Influence of oxide overlayer on the performance of a fiber optic SPR sensor with Al/Cu layers,” IEEE J. Sel. Top. Quantum Electron. 23(2), 81–88 (2017). [CrossRef]
14. S. Singh and B. Gupta, “Simulation of a surface plasmon resonance-based fiber-optic sensor for gas sensing in visible range using films of nanocomposites,” Meas. Sci. Technol. 21(11), 115202 (2010). [CrossRef]
15. Y. Chen, S. Hu, H. Wang, Y. Zhi, Y. Luo, X. Xiong, J. Dong, Z. Jiang, W. Zhu, and W. Qiu, “MoS2 Nanosheets Modified Surface Plasmon Resonance Sensors for Sensitivity Enhancement,” Adv. Opt. Mater. 7(13), 1900479 (2019). [CrossRef]
16. Y. Luo, S. Hu, H. Wang, Y. Chen, J. Dong, Z. Jiang, X. Xiong, W. Zhu, W. Qiu, and H. Lu, “Sensitivity-enhanced surface plasmon sensor modified with MoSe 2 overlayer,” Opt. Express 26(26), 34250–34258 (2018). [CrossRef]
17. X. Xiong, Y. Chen, H. Wang, S. Hu, Y. Luo, J. Dong, W. Zhu, W. Qiu, H. Guan, and H. Lu, “Plasmonic interface modified with graphene oxide sheets overlayer for sensitivity enhancement,” ACS Appl. Mater. Interfaces 10(41), 34916–34923 (2018). [CrossRef]
18. Y. Wang, J. Dong, Y. Luo, J. Tang, H. Lu, J. Yu, H. Guan, J. Zhang, and Z. Chen, “Indium Tin Oxide Coated Two-Mode Fiber for Enhanced SPR Sensor in Near-Infrared Region,” IEEE Photonics J. 9, 1–9 (2017). [CrossRef]
19. C. J. Alleyne, A. G. Kirk, R. C. McPhedran, N.-A. P. Nicorovici, and D. Maystre, “Enhanced SPR sensitivity using periodic metallic structures,” Opt. Express 15(13), 8163–8169 (2007). [CrossRef]
20. H. Zhang, Y. Chen, X. Feng, X. Xiong, S. Hu, Z. Jiang, J. Dong, W. Zhu, W. Qiu, and H. Guan, “Long-range surface plasmon resonance sensor based on side-polished fiber for biosensing applications,” IEEE J. Sel. Top. Quantum Electron. 25(2), 1–9 (2019). [CrossRef]
21. B. Liu, S. Chen, J. Zhang, X. Yao, J. Zhong, H. Lin, T. Huang, Z. Yang, J. Zhu, and S. Liu, “A plasmonic sensor array with ultrahigh figures of merit and resonance linewidths down to 3 nm,” Adv. Mater. 30(12), 1706031 (2018). [CrossRef]
22. S. V. Zhukovsky, A. Andryieuski, J. E. Sipe, and A. V. Lavrinenko, “From surface to volume plasmons in hyperbolic metamaterials: general existence conditions for bulk high-k waves in metal-dielectric and graphene-dielectric multilayers,” Phys. Rev. B 90(15), 155429 (2014). [CrossRef]
23. A. I. Aristov, M. Manousidaki, A. Danilov, K. Terzaki, C. Fotakis, M. Farsari, and A. V. Kabashin, “3D plasmonic crystal metamaterials for ultra-sensitive biosensing,” Sci. Rep. 6(1), 25380 (2016). [CrossRef]
24. K. V. Sreekanth, Y. Alapan, M. ElKabbash, E. Ilker, M. Hinczewski, U. A. Gurkan, A. De Luca, and G. Strangi, “Extreme sensitivity biosensing platform based on hyperbolic metamaterials,” Nat. Mater. 15(6), 621–627 (2016). [CrossRef]
25. A. Kabashin, P. Evans, S. Pastkovsky, W. Hendren, G. Wurtz, R. Atkinson, R. Pollard, V. Podolskiy, and A. Zayats, “Plasmonic nanorod metamaterials for biosensing,” Nat. Mater. 8(11), 867–871 (2009). [CrossRef]
26. A. K. Sharma and G. J. Mohr, “On the performance of surface plasmon resonance based fibre optic sensor with different bimetallic nanoparticle alloy combinations,” J. Phys. D: Appl. Phys. 41(5), 055106 (2008). [CrossRef]
27. J. Zhao, S. Cao, C. Liao, Y. Wang, G. Wang, X. Xu, C. Fu, G. Xu, J. Lian, and Y. Wang, “Surface plasmon resonance refractive sensor based on silver-coated side-polished fiber,” Sens. Actuators, B 230, 206–211 (2016). [CrossRef]
28. J. H. Ahn, T. Y. Seong, W. M. Kim, T. S. Lee, I. Kim, and K.-S. Lee, “Fiber-optic waveguide coupled surface plasmon resonance sensor,” Opt. Express 20(19), 21729–21738 (2012). [CrossRef]
29. C. Cortes, W. Newman, S. Molesky, and Z. Jacob, “Quantum nanophotonics using hyperbolic metamaterials,” J. Opt. 14(6), 063001 (2012). [CrossRef]
30. T. Siefke, S. Kroker, K. Pfeiffer, O. Puffky, K. Dietrich, D. Franta, I. Ohlídal, A. Szeghalmi, E. B. Kley, and A. Tünnermann, “Materials pushing the application limits of wire grid polarizers further into the deep ultraviolet spectral range,” Adv. Opt. Mater. 4(11), 1780–1786 (2016). [CrossRef]
31. S. Shukla, N. K. Sharma, and V. Sajal, “Sensitivity enhancement of a surface plasmon resonance based fiber optic sensor using ZnO thin film: a theoretical study,” Sens. Actuators, B 206, 463–470 (2015). [CrossRef]
32. J. Homola, I. Koudela, and S. S. Yee, “Surface plasmon resonance sensors based on diffraction gratings and prism couplers: sensitivity comparison,” Sens. Actuators, B 54(1-2), 16–24 (1999). [CrossRef]
33. J. Dong, Y. Zhang, Y. Wang, F. Yang, S. Hu, Y. Chen, W. Zhu, W. Qiu, H. Guan, and H. Lu, “Side-polished few-mode fiber based surface plasmon resonance biosensor,” Opt. Express 27(8), 11348–11360 (2019). [CrossRef]
34. R. B. Schasfoort, Handbook of surface plasmon resonance,2nd Edition, 2nd ed. (The Royal Society of Chemistry, 2017).
35. T. Huang, “Highly sensitive SPR sensor based on D-shaped photonic crystal fiber coated with indium tin oxide at near-infrared wavelength,” Plasmonics 12(3), 583–588 (2017). [CrossRef]
36. K. Gasior, T. Martynkien, M. Napiorkowski, K. Zolnacz, P. Mergo, and W. Urbanczyk, “A surface plasmon resonance sensor based on a single mode D-shape polymer optical fiber,” J. Opt. 19(2), 025001 (2017). [CrossRef]
37. H.-T. Yan, Q. Liu, Y. Ming, W. Luo, Y. Chen, and Y.-q. Lu, “Metallic grating on a D-shaped fiber for refractive index sensing,” IEEE Photonics J. 5(5), 4800706 (2013). [CrossRef]
38. P. Pilla, V. Malachovská, A. Borriello, A. Buosciolo, M. Giordano, L. Ambrosio, A. Cutolo, and A. Cusano, “Transition mode long period grating biosensor with functional multilayer coatings,” Opt. Express 19(2), 512–526 (2011). [CrossRef]
39. Y. Liu, C. Meng, A. P. Zhang, Y. Xiao, H. Yu, and L. Tong, “Compact microfiber Bragg gratings with high-index contrast,” Opt. Lett. 36(16), 3115–3117 (2011). [CrossRef]
40. A. Shalabney and I. Abdulhalim, “Sensitivity-enhancement methods for surface plasmon sensors,” Laser Photonics Rev. 5(4), 571–606 (2011). [CrossRef]
41. J. Liang, L. Ren, N. Chen, and C. Zhou, “Broadband, low-loss, dispersion flattened porous-core photonic bandgap fiber for terahertz (THz)-wave propagation,” Opt. Commun. 295, 257–261 (2013). [CrossRef]
