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Abstract
This paper proposes a hybrid metal-graphene plasmonic sensor which can simultaneously perform multi-spectral sensing in near- and mid-IR ranges. The proposed sensor consists of an array of asymmetric gold nano-antennas integrated with an unpatterned graphene sheet. The gold antennas support sharp Fano-resonances for near-IR sensing while the excitation of graphene plasmonic resonances extend the sensing spectra to the mid-IR range. Such a broadband spectral range goes far beyond previously demonstrated multi-spectral plasmonic sensors. The sensitivity and figure of merit (FOM) as well as their dependence on the thickness of the sensing layer and Fermi energy of graphene are studied systematically. This new type of sensor combines the advantages of conventional metallic plasmonic sensors and graphene plasmonic sensors and may open a new door for high-performance, multi-functional plasmonic sensing.
© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
Surface plasmons, the collective oscillations of free electrons along the surfaces of conductors, have inspired great interest to a wide spectrum of researchers in the past two decades [1]. They have been widely used in the field of sensing because their abilities of field confinement and enhancement in subwavelength scale and the sensitivity to the variation of surrounding media give the access to unprecedented label-free, highly sensitive, real-time monitoring and damage-free detection [2–8]. Specifically, refractometric plasmonic sensors can be divided into those based on surface plasmon resonances (SPRs) and those based on localized surface plasmon resonances (LSPRs). The former could offer higher bulk sensitivity [9,10] and has been widely employed in environmental surveillance, food safety analysis and medical diagnostics [11,12]. Meanwhile, the latter has attracted an increasing attention in recent years and may surpass its SPRs counterpart, considering its advantage of high surface sensitivity, simplicity in optics, smaller volumes and angle-independence [13–15].
Conventional plasmonic sensors are essentially based on the nanostructures of noble metals and working mainly at the range of visible and near-infrared (IR) frequency [16–18]. By exciting the enhanced and localized field in the vicinity of resonant nanostructures, metallic plasmons can overcome the limitation of large mismatch between IR wavelengths and biomolecular dimensions [19–21], opening up new horizons in low-cost, high-throughput and label-free optical biosensing comparing with conventional cumbersome labelled methods, i.e. fluorescence detection. Nevertheless, the disadvantage of high loss, low speed and relatively poor confinement in mid-IR range limits its further development. Recently, the rises of graphene plasmons, possessing merits of larger external tunability, stronger spatial confinement and lower loss [22–26], have reshaped the landscape of plasmonic families and become an alternative to noble metals for highly integrated plasmonic devices in the mid- and far-IR ranges [27–32]. In particular, mid-IR plasmonic biosensing with the graphene has been reported using several different structures such as graphene nanostripes and nanodisks [33–37], dielectric gratings integrated with a graphene sheet [38] and gold gratings with a graphene sheet [39], which enables sensing of materials down to nanometric thickness. Moreover, infrared spectroscopy is a powerful technique to analyze chemical information by accessing the vibrational fingerprints. The broadband, tunable graphene plasmonic resonances with deep sub-wavelength field confinements in the mid-IR can significantly enhance vibrational absorption signals of bio-molecules, providing a powerful platform to detect the vibrational modes of nanometric molecules [34].
In this paper, we go beyond pure metal plasmonic sensors or graphene plasmonic sensors and propose a hybrid metal-graphene plasmonic sensor which can simultaneously perform multi-spectral sensing in both near- and mid-IR ranges. Hybrid metal-graphene structures have been previously employed for various functional devices such as tunable metamaterials and plasmonic devices [40–44]. Plasmonic sensors based on metal-graphene hybrid structures have also been intensively investigted [45–52]. However, in such structures, they either support only metal plasmons and the graphene was used for functionalization or support only graphene plasmons and the metallic structures were used for light scattering and coupling. Here the proposed sensor comprises an array of asymmetric gold (Au) nano-antennas and an unpatterned graphene sheet. The asymmetric Au antennas support the excitation of sharp plasmonic Fano-resonances for near-IR sensing while the excited plasmons in doped graphene film extend the sensing spectra to the mid-IR range.
Multispectral plasmonic sensors have previously been studied to simultaneously monitor multiple spectral fingerprint characteristics of different chemical or biological moieties in the field of mid-IR spectroscopy [53]. The ability to monitor multiple resonance bands also allows one to correlate. Here, the ultra-broadband spectral range of our proposed sensor goes far beyond the previously demonstrated multi-spectral sensors with metallic nanostructures [53–55]. It can simultaneously perform refractive index sensing in the near infrared with the robust plasmonic resonances of metallic antennas and to detect the vibrational modes of nanometric molecules in the mid-infrared with the tunable graphene plasmons. At the same time, the proposed sensor will also expand the range of samples (or working environments) that could be monitored. For example, for materials with nanometric thickness, they can be detected in the mid-infrared with graphene plasmons. Meanwhile, for chemicals or bio-molecues in liquids that are not transparent in the mid-infrared ranges, it can still be detected in the near-infrared. This new type of sensor combines the advantages of conventional metal plasmonic sensors and graphene plasmonic sensors and may open a new door for high-performance, multi-functional plasmonic sensing.
2. Results and discussion
Figure 1 depicts the schematic illustration and geometric parameters of our proposed structure. A periodic array of asymmetric Au nano-antennas are integrated on top of an unpatterned monolayer graphene sheet and a homogeneous semi-infinite substrate. The Au nano-antennas are surrounded by a cover layer with the refractive index $n$ and the thickness $d$. The period of a unit cell is $P = 350~nm$ and the separation distance between two asymmetric antennas in a unit cell is $G = 100~nm$. Two antennas are designed to have same geometric parameters $H = W = 50~nm$, except that the length of the short antenna is $L_{1} = 200~nm$ and the long one is $L_{2} = 250~nm$.
Fig. 1. Schematic of linearly polarized waves impinging at a Au nano-antenna/graphene hybrid structure at normal incidence in a Cartesian coordinate system. The polarized state of incident wave is x-polarization. The structure has a multilayer configuration, consisting of a cover layer, a periodic array of asymmetric Au nano-antennas, an unpatterned monolayer graphene sheet and a semi-infinite substrate. $P = 350~nm$ denotes the period of a unit cell and $G = 100~nm$ is the gap of two Au antennas. $W =50~nm$ and $H = 50~nm$ denote the width and height of Au antennas. $L_{1} = 200~nm, L_{2} = 250~nm$ are the length of two Au antennas, respectively. The inset is top view.
The numerical simulations are conducted using a fully three-dimensional finite element technique (in COMSOL Multiphysics). In simulations, the structure is impinged upon a linearly polarized (x-polarized) wave at normal incidence. The substrate is assumed to be lossless with a refractive index of 1.4 (i.e. CaF$_2$) in the IR range. The permittivity of Au is described by the Drude model with plasma frequency $\omega _{p} = 1.37 \times 10^{16}~s^{-1}$. Providing the increased scattering by surface and grain boundary effects in the thin film, the damping constant $\omega _{\tau }= 1.23 \times 10^{14}~s^{-1}$ is three times larger than the bulk value. The monolayer graphene sheet is modelled as a conductive surface [56–58] and the transition boundary is used for it with $0.34~nm$ thickness. The maximum computational mesh size for graphene is set to be $4~nm$ in the 2D plane. Optical conductivity of graphene can be derived within the random-phase approximation (RPA) in the local limit, which consists of contributions from the intra-band transition and the inter-band transition [59,60].
Fig. 2. Simulated spectra of transmission, reflection and absorption for unpatterned graphene integrated with asymmetric Au nano-antennas with the refractive index of cover layer $n=1$ in: (a) Near-IR range; (b) Mid-IR range.
To explain different resonant modes in near- and mid-IR ranges, Figs. 3(a), 3(b) and 3(c) map the distribution of local electric field in the z-direction at $1.06~\mu m$, $6.32~\mu m$ and $7.18~\mu m$, respectively. The fields are normalized to the field amplitude of the incident light ($E_{0}$) and plotted in the x-y plane that is $5~nm$ below the graphene sheet. As shown in Fig. 3(a), the energy is most trapped in two asymmetric Au antennas and is comparable to each other. Opposite plasmonic oscillations of two Au antennas result in opposite electric current distributions, which leads to a Fano resonance in the near-IR range. Graphene sheet in this area is nothing but an absorptive layer. While in the mid-IR range, as depicted in Figs. 3(b) and 3(c), the resonances can be attributed to the excitation of dipolar plasmonic modes since the energy is mainly distributed in the graphene sheet. This is different from the excitation of plasmonic waves in continuous graphene by guided-mode resonances using gratings, where the light is generally polarized perpendicular to the metal or dielectric grating bars [62,63]. The former relies on the scattering of the metal antennas to excite localized resonances and the latter relies on the periodical gratings to realize wavevector matching between light in free space and plasmonic modes in graphene. The near-field distributions of Au plasmonic resonances in the near-IR and graphene plasmonic resonances in the mid-IR are also presented (Figs. 3(d)–3(f)). The field is plotted at the centre of the gap (y=0). As can be seen from the field distributions, graphene plasmons show stronger spatial confinement of electromagnetic field compared to metal plasmons.
Fig. 3. (a,b,c) Distribution of local electric fields in z-direction. The field is normalized to the field amplitude of the incident light ($E_{0}$) and plotted at the x-y plane that is $5~nm$ below the graphene sheet. (d,e,f) Profile of near-field enhancement distribution. The field is normalized to $E_{0}$ and plotted at the x-z plane that is at the centre of the gap (y = 0). (a) and (d) are plotted at absorption peak of near-IR frequency ($1.06~\mu m$). (b) and (e) are plotted at absorption peak of mid-IR frequency ($6.32~\mu m$). (c) and (f) are plotted at absorption peak of mid-IR frequency ($7.18~\mu m$).
In order to evaluate the overall performance of the proposed dual-area sensor, we adopt the widely used bulk figure of merit (FOM) [64,65]
Herein, FWHM represents the full width at half maximum bandwidth of the resonance. $S$ denotes the linear regression slope for the refractive index dependence. It can be obtained from $S = \partial \lambda /\partial n$ and has units of nanometers per refractive index unit ($nm/RIU$). It is worth mentioning that the definition of $S$ here refers to bulk sensitivity.As shown in Fig. 4, we calculate the transmittance of proposed structure with a cover layer for different refractive indices. The thickness of the cover layer here is $t = 400~nm$. For the near-IR range, the position of the dip redshifts from $1.083~\mu m$ to $1.303~\mu m$ when the refractive index increases from 1 to 1.4 (Fig. 4(a)), while the value of the transmittance dip remains at $\sim 10\%$. Since the lineshape of the resonance is asymmetric, the FWHM here refers to the half of the bandwidth of the peak and the dip. To make it intuitive, Fig. 4(b) extracts the positions of transmittance dips from Fig. 4(a) to plot as a function of refractive indices. The red line is a linear fitting through the data points. The slope of Fano resonance is $550~nm/RIU$ and the bulk FOM is 16.18. For the mid-IR range, the larger transmittance dip redshifts from $6.32~\mu m$ to $7.24~\mu m$ when the refractive index changes from 1 to 1.4, as illustrated in Fig. 4(c). The slope of graphene plasmonic resonance is $2300~nm/RIU$ and the bulk FOM is $28.75$, which is comparable to the previous high-sensitivity work [38].
Fig. 4. (a,c) Calculated transmittance of the asymmetric Au nano-antenna/graphene hybrid structure with a $400~nm$-thick cover layer for different values of refractive index in both (a) near-IR and (c) mid-IR frequencies. (b,d) Wavelengths of the transmittance dips as a function of refractive index of the cover layer. The square dots in (b) represent positions of dip extracted from (a) and square dots in (d) represent positions of dip extracted from (c). The red and blue curves are the linear regression of the corresponding data.
In essence, bulk sensitivity represents the measurement of all accessible electric field regions from the surface of sensors to the infinite. In other words, using bulk FOM to correctly evaluate the sensors requires a large thickness of the cover layer [66–68]. Nevertheless, in the field of biosensing, this condition may be difficult to satisfy since scales of biomoleculars, such as proteins, DNA and viruses [69,70] are usually small ($<10~nm$). Hence, it is necessary to quantify the performance of sensors for the varying thickness of the cover layer. To correlate the plasmonic spectral shift to the thickness of the cover layer, many previous works redefine the sensitivity $S$[71,72]:
where $d$ denotes the thickness of the cover layer and $l_{d}$ denotes the exponential decay length. $l_{d}$ describes how fast the electric field decaying away from the surface.To assess the FOM of the proposed sensor with respect to the thickness of the cover layer, we calculate the spectra of transmittance with varying thicknesses. Figures 5(a) and 5(b) show positions of transmittance dips as a function of refractive indices for different thicknesses of the cover layer in both near- and mid-IR ranges. As expected, slope of linear regression curves decreases when the thickness of the cover layer reduces. In the near-IR range, the sensitivity (slope of the curve) is $530~nm/RIU$ when the thickness of cover layer is $d=200~nm$. This is slightly smaller than the bulk sensitivity (about $550~nm/RIU$). It decreases to $250~nm/RIU$ for $d=40~nm$ and $80~nm/RIU$ for $d=10~nm$. In the mid-IR range, the sensitivity (slope of the curve) is $2300~nm/RIU$ when the thickness of the cover layer is $d=200~nm$ and $2100~nm/RIU$ when the thickness of cover layer reduces to $d=40~nm$. With a thickness of only $d=10~nm$, the sensitivity can still keep as high as $1025~nm/RIU$ which is about half of that for $d=200~nm$. The high surface sensitivity in the mid-IR range for ultra-thin cover layers down to nanometric thickness can be attributed to the extremely strong spatial confinement of graphene plasmons in the near field.
Fig. 5. (a,b) Positions of transmittance dips as a function of refractive index for different thicknesses of the cover layer, ranging from $2~nm$ to $200~nm$. From the top red line to the bottom blue line, the slopes are $530~nm/RIU$, $250~nm/RIU$, $170~nm/RIU$, $80~nm/RIU$ and $7.5~nm/RIU$ for (a), while the slopes are $2300~nm/RIU$, $2100~nm/RIU$, $1775~nm/RIU$, $1025~nm/RIU$ and $250~nm/RIU$ for (b). (c,d) Calculated FOM with varied thickness of cover layer using Eq. 2 and Eq. 3. The square dots are simulated data from (a) and (b). (c) Near-IR range with surface sensitivity $S = 554.22~nm/RIU$ and decay length $l_{d} = 133.68~nm$ ; (d) Mid-IR range with $S = 2304.40~nm/RIU$ and $l_{d} = 33.85~nm$.
Using Eq. 2 and Eq. 3, the FOM with varied thicknesses of the cover layer is calculated in Figs. 5(c) and 5(d). Herein, for the near-IR frequency, the surface sensitivity is $S = 554.22~nm/RIU$ and the decay length is about $l_{d} = 133.68~nm$. The saturation value of FOM is $\sim 16.30$ for thicknesses above $250~nm$. For the mid-IR frequency, the surface sensitivity is $S = 2304.40~nm/RIU$ and the decay length is about $l_{d} = 33.85~nm$. The decay length in the mid-IR range is about one fourth of that in the near-IR. The saturation value of FOM is $\sim 28.81$ for thicknesses above $120~nm$. The fitting curves also depict that even for thickness reduced to few nanometers, the sensor is still capable of working in the mid-IR range.
One of the most attractive properties of graphene plasmons is the electrical tunability. Though graphene just behaves as an absorptive layer in the near-IR range and the Fano resonances of metallic antennas depend weakly on the Fermi energy of graphene, the resonance wavelength of graphene plasmons in the mid-IR range can be easily varied by changing its Fermi energy. Figure 6 shows the near- and mid-infrared (IR) transmission spectra of the hybrid metal-graphene plasmonic sensor when the Fermi energies of graphene are $0.6~eV$ and $0.4~eV$, respectively. In the near-IR range, the position of the transmittance dip in the near-IR range remains almost the same when the Fermi energy of graphene changes from $0.6~eV$ to $0.4~eV$. The reason is that graphene is an absorptive layer in the near-IR range. The reduction of the Fermi energy increases the absorption of graphene which damps the Fano resonance of the metallic antennas but almost doesn’t shift the resonance wavelength. In the contrast, the resonance wavelength of graphene plasmons in the mid-IR range can be easily varied by changing its Fermi engergy. As shown in Fig. 6(b), the plasmonic resonances of graphene redshift to longer wavelengths as the Fermi energy decreases from $0.6~eV$ to $0.4~eV$. At the same time, the conductivity of graphene declines and the graphene plasmon becomes more lossy, which results in a larger resonant lineshape. Figures 7(a) and 7(b) show the dependence of the wavelength of the transmittive dip on the refractive index of the surrounding media with different Fermi energies of graphene for near-IR range and mid-IR range, respectively. The change of Fermi energy has little influence on resonance wavelength and bulk sensitivity (slope of regression lines) in the near-IR range and the two lines almost overlap with each other. In the mid-IR range, the redshift of the resonances can be clearly seen from the separation of two lines in Fig. 7(b) and the bulk sensitivity is $2600~nm/RIU$ at $0.4~eV$ compared to that of $2300~nm/RIU$ at $0.6~eV$.
Fig. 6. Spectra of transmittance with different Fermi energy of graphene for (a) Near-IR range and (b) Mid-IR range.
Fig. 7. (a,b) Bulk sensitivity for different Fermi energy of graphene with a $400~nm$-thick cover. (c,d) Calculated FOM for varied thickness of cover layer with different Fermi energy of graphene. (a,c) Near-IR range; (b,d) Mid-IR range.
In Figs. 7(c) and 7(d), the sensitivity as well as FOM of the plasmonic sensor are studied for both near- and mid-IR ranges with varied thicknesses of the cover layer. Our simulations show that the thickness of the cover layer have little influence on the FWHM of both the near-IR and middle-IR resonances in the studied range (data not shown here). So we choose to regard FWHM for each resonance as a constant for simplicity when we compare the FOM of the sensors with different thickness of surrounding media. In the near-IR range, the Fermi energy has little influence on the sensitivity and its dependence on the thickness of the cover layer, but the increase of Fermi energy slightly increases FOM due to the reduced absorption of the structure and thus increased quality factor of Fano resonances. In the mid-IR range, the variation of graphene’s Fermi energy has much larger influence on the performance of the plasmonic sensor. Besides the shift of resonance (working) wavelength, the reduction of Fermi energy from $0.6~eV$ to $0.4~eV$ leads to a smaller FOM, which can be mainly attributed to the increased FWHM and reduced quality factor of the plasmonic resonance of graphene.
3. Conclusion
In summary, we have proposed a hybrid metal-graphene plasmonic sensor for simultaneously multi-spectral sensing in both near- and mid-IR ranges. The proposed refractive index sensor consists of an asymmetric gold (Au) nano-antenna array and an unpatterned graphene film. It can be fabricated with the standard nanofabrication process using CVD grown monolayer graphene with high-resolution electron-beam lithography and a lift-off process to fabricate the Au antennas [24]. Sensing of this structure is based on spectra shifts of plasmonic resonances. In the near-IR range, the excitation of high-Q Fano resonances in asymmetric gold nano-antennas provides highly sensitive and robust sensing. In the mid-IR range, the excitation of low-loss, extremely confined and electrically tunable graphene plasmons enables highly sensitive sensing for media down to nanometric thickness over a broad spectrum, which can be adjusted to detect specific vibrational fingerprints and is particularly important for biosensing. The sensitivity and FOM of our proposed sensor are comparable to previously reported near-IR sensors based on metallic localized surface plasmon resonances and mid-IR plasmonic sensors with graphene. This new type of sensor may open a new door for high-performance plasmonic sensing.
Funding
National Natural Science Foundation of China (11304389, 11674396); Hunan Provincial Science and Technology Department (2017RS3039, 2018JJ1033); National University of Defense Technology (ZK18-03-05).
Disclosures
There are no conflicts to declare.
References
1. C. L. Wong and M. Olivo, “Surface plasmon resonance imaging sensors: a review,” Plasmonics 9(4), 809–824 (2014). [CrossRef]
2. 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.
3. A. G. Brolo, “Plasmonics for future biosensors,” Nat. Photonics 6(11), 709–713 (2012). [CrossRef]
4. N. Lindquist, P. Nagpal, K. Mcpeak, D. Norris, and S. Oh, “Engineering metallic nanostructures for plasmonics and nanophotonics,” Rep. Prog. Phys. 75(3), 036501 (2012). [CrossRef]
5. 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]
6. B. Špačková, P. Wrobel, M. Bocková, and J. Homola, “Optical biosensors based on plasmonic nanostructures: a review,” Proc. IEEE 104(12), 2380–2408 (2016). [CrossRef]
7. G. A. Lopez, M.-C. Estevez, M. Soler, and L. M. Lechuga, “Recent advances in nanoplasmonic biosensors: applications and lab-on-a-chip integration,” Nanophotonics 6(1), 123–136 (2017). [CrossRef]
8. J. Zheng, W. Yang, J. Wang, J. Zhu, L. Qian, and Z. Yang, “An ultranarrow spr linewidth in the uv region for plasmonic sensing,” Nanoscale 11(9), 4061–4066 (2019). [CrossRef]
9. M. Svedendahl, S. Chen, A. Dmitriev, and M. Kall, “Refractometric sensing using propagating versus localized surface plasmons: a direct comparison,” Nano Lett. 9(12), 4428–4433 (2009). [CrossRef]
10. S. J. Zalyubovskiy, M. Bogdanova, A. Deinega, Y. Lozovik, A. D. Pris, K. H. An, W. P. Hall, and R. A. Potyrailo, “Theoretical limit of localized surface plasmon resonance sensitivity to local refractive index change and its comparison to conventional surface plasmon resonance sensor,” J. Opt. Soc. Am. A 29(6), 994–1002 (2012). [CrossRef]
11. J. Homola, “Surface plasmon resonance sensors for detection of chemical and biological species,” Chem. Rev. 108(2), 462–493 (2008). [CrossRef]
12. B. Chocarro-Ruiz, A. Fernández-Gavela, S. Herranz, and L. M. Lechuga, “Nanophotonic label-free biosensors for environmental monitoring,” Curr. Opin. Biotechnol. 45, 175–183 (2017). [CrossRef]
13. M. A. Otte, B. Sepulveda, W. Ni, J. P. Juste, L. M. Liz-Marzán, and L. M. Lechuga, “Identification of the optimal spectral region for plasmonic and nanoplasmonic sensing,” ACS Nano 4(1), 349–357 (2010). [CrossRef]
14. F. Mazzotta, T. W. Johnson, A. B. Dahlin, J. Shaver, S.-H. Oh, and F. Hook, “Influence of the evanescent field decay length on the sensitivity of plasmonic nanodisks and nanoholes,” ACS Photonics 2(2), 256–262 (2015). [CrossRef]
15. Y.-S. Lin and W. Chen, “A large-area, wide-incident-angle, and polarization-independent plasmonic color filter for glucose sensing,” Opt. Mater. 75, 739–743 (2018). [CrossRef]
16. M. Ren, C. Pan, Q. Li, W. Cai, X. Zhang, Q. Wu, S. Fan, and J. Xu, “Isotropic spiral plasmonic metamaterial for sensing large refractive index change,” Opt. Lett. 38(16), 3133–3136 (2013). [CrossRef]
17. B. Liu, S. Chen, J. Zhang, X. Yao, J. Zhong, H. Lin, T. Huang, Z. Yang, J. Zhu, S. Liu, C. Lienau, L. Wang, and B. Ren, “A plasmonic sensor array with ultrahigh figures of merit and resonance linewidths down to 3 nm,” Adv. Mater. 30(12), 1706031 (2018). [CrossRef]
18. C. Xiong, H. Li, H. Xu, M. Zhao, B. Zhang, C. Liu, and K. Wu, “Coupling effects in single-mode and multimode resonator-coupled system,” Opt. Express 27(13), 17718–17728 (2019). [CrossRef]
19. F. Neubrech, A. Pucci, T. W. Cornelius, S. Karim, A. García-Etxarri, and J. Aizpurua, “Resonant plasmonic and vibrational coupling in a tailored nanoantenna for infrared detection,” Phys. Rev. Lett. 101(15), 157403 (2008). [CrossRef]
20. C. Wu, A. B. Khanikaev, R. Adato, N. Arju, A. A. Yanik, H. Altug, and G. Shvets, “Fano-resonant asymmetric metamaterials for ultrasensitive spectroscopy and identification of molecular monolayers,” Nat. Mater. 11(1), 69–75 (2012). [CrossRef]
21. R. Adato and H. Altug, “In-situ ultra-sensitive infrared absorption spectroscopy of biomolecule interactions in real time with plasmonic nanoantennas,” Nat. Commun. 4(1), 2154–2163 (2013). [CrossRef]
22. A. Grigorenko, M. Polini, and K. Novoselov, “Graphene plasmonics,” Nat. Photonics 6(11), 749–758 (2012). [CrossRef]
23. Z. Fei, A. Rodin, W. Gannett, S. Dai, W. Regan, M. Wagner, M. Liu, A. McLeod, G. Dominguez, and M. Thiemens, “Electronic and plasmonic phenomena at graphene grain boundaries,” Nat. Nanotechnol. 8(11), 821–825 (2013). [CrossRef]
24. P. Alonso-Gonzalez, A. Y. Nikitin, F. Golmar, A. Centeno, A. Pesquera, S. Velez, J. Chen, G. Navickaite, F. Koppens, A. Zurutuza, F. Casanova, L. E. Hueso, and R. Hillenbrand, “Controlling graphene plasmons with resonant metal antennas and spatial conductivity patterns,” Science 344(6190), 1369–1373 (2014). [CrossRef]
25. A. Woessner, M. Lundeberg, Y. Gao, A. Principi, P. Alonso-Gonzalez, M. Carrega, K. Watanabe, T. Taniguchi, G. Vignale, M. Polini, J. Hone, and H. R. F. L. Koppens, “Highly confined low-loss plasmons in graphene–boron nitride heterostructures,” Nat. Mater. 14(4), 421–425 (2015). [CrossRef]
26. H. Hu, F. Zhai, D. Hu, Z. Li, B. Bai, X. Yang, and Q. Dai, “Broadly tunable graphene plasmons using an ion-gel top gate with low control voltage,” Nanoscale 7(46), 19493–19500 (2015). [CrossRef]
27. L. Ju, B. Geng, J. Horng, C. Girit, M. Martin, Z. H H. Bechtel, X. Liang, A. Zettl, Y. Shen, and F. Wang, “Graphene plasmonics for tunable terahertz metamaterials,” Nat. Nanotechnol. 6(10), 630–634 (2011). [CrossRef]
28. J. Chen, M. Badioli, P. Alonsogonzalez, S. Thongrattanasiri, F. Huth, J. Osmond, M. Spasenovi, A. Centeno, A. Pesquera, P. Godignon, Z. E. Amaia, N. Camara, F. Garcia de Abajo, R. Hillenbr, and F. Koppens, “Optical nano-imaging of gate-tunable graphene plasmons,” Nature 487(7405), 77–81 (2012). [CrossRef]
29. H. Yan, T. Low, W. Zhu, Y. Wu, M. Freitag, X. Li, F. Guinea, P. Avouris, and F. Xia, “Damping pathways of mid-infrared plasmons in graphene nanostructures,” Nat. Photonics 7(5), 394–399 (2013). [CrossRef]
30. Z. Fang, S. Thongrattanasiri, A. Schlather, Z. Liu, L. Ma, Y. Wang, P. M. Ajayan, P. Nordlander, N. J. Halas, and F. J. García de Abajo, “Gated tunability and hybridization of localized plasmons in nanostructured graphene,” ACS Nano 7(3), 2388–2395 (2013). [CrossRef]
31. Q. Hong, F. Xiong, W. Xu, Z. Zhu, K. Liu, X. Yuan, J. Zhang, and S. Qin, “Towards high performance hybrid two-dimensional material plasmonic devices: strong and highly anisotropic plasmonic resonances in nanostructured graphene-black phosphorus bilayer,” Opt. Express 26(17), 22528–22535 (2018). [CrossRef]
32. M. Zhang, X.-X. Wang, W.-Q. Cao, J. Yuan, and M.-S. Cao, “Electromagnetic functions of patterned 2d materials for micro–nano devices covering ghz, thz, and optical frequency,” Adv. Opt. Mater. 7(19), 1900689 (2019). [CrossRef]
33. B. Vasić, G. Isić, and R. Gajić, “Localized surface plasmon resonances in graphene ribbon arrays for sensing of dielectric environment at infrared frequencies,” J. Appl. Phys. 113(1), 013110 (2013). [CrossRef]
34. D. Rodrigo, O. Limaj, D. Janner, D. Etezadi, F. J. G. De Abajo, V. Pruneri, and H. Altug, “Mid-infrared plasmonic biosensing with graphene,” Science 349(6244), 165–168 (2015). [CrossRef]
35. H. Hu, X. Yang, F. Zhai, D. Hu, R. Liu, K. Liu, Z. Sun, and Q. Dai, “Far-field nanoscale infrared spectroscopy of vibrational fingerprints of molecules with graphene plasmons,” Nat. Commun. 7(1), 12334 (2016). [CrossRef]
36. O. V. Shapoval and A. I. Nosich, “Bulk refractive-index sensitivities of the thz-range plasmon resonances on a micro-size graphene strip,” J. Phys. D: Appl. Phys. 49(5), 055105 (2016). [CrossRef]
37. C. Cen, H. Lin, C. Liang, J. Huang, X. Chen, Y. Yi, Y. Tang, Z. Yi, X. Ye, J. Liu, and S. Xiao, “A tunable plasmonic refractive index sensor with nanoring-strip graphene arrays,” Sensors 18(12), 4489–4504 (2018). [CrossRef]
38. T. Wenger, G. Viola, J. Kinaret, M. Fogelström, and P. Tassin, “High-sensitivity plasmonic refractive index sensing using graphene,” 2D Mater. 4(2), 025103 (2017). [CrossRef]
39. T. Wu, Y. Luo, and L. Wei, “Mid-infrared sensing of molecular vibrational modes with tunable graphene plasmons,” Opt. Lett. 42(11), 2066–2069 (2017). [CrossRef]
40. M. M. Jadidi, A. B. Sushkov, R. L. Myers-Ward, A. K. Boyd, K. M. Daniels, D. K. Gaskill, M. S. Fuhrer, H. D. Drew, and T. E. Murphy, “Tunable terahertz hybrid metal–graphene plasmons,” Nano Lett. 15(10), 7099–7104 (2015). [CrossRef]
41. T. Liu, H. Wang, Y. Liu, L. Xiao, C. Zhou, Y. Liu, C. Xu, and S. Xiao, “Independently tunable dual-spectral electromagnetically induced transparency in a terahertz metal–graphene metamaterial,” J. Phys. D: Appl. Phys. 51(41), 415105 (2018). [CrossRef]
42. M.-L. Zhai and D.-M. Li, “Tunable resonators based on hybrid metal–graphene structures at mid-infrared frequencies using an improved leapfrog wcs-fdtd method,” J. Electromagn. Waves Appl. 32(14), 1791–1800 (2018). [CrossRef]
43. F. F. Mahani and A. Mokhtari, “Performance improvement of organic solar cells using a hybrid color filter electrode of graphene-aluminum nanorings,” J. Nanoelectron. Optoelectron. 13(12), 1917–1923 (2018). [CrossRef]
44. M. Salemizadeh, F. F. Mahani, and A. Mokhtari, “Tunable mid-infrared graphene-titanium nitride plasmonic absorber for chemical sensing applications,” J. Opt. Soc. Am. B 36(10), 2863–2870 (2019). [CrossRef]
45. L. Wu, H. Chu, W. Koh, and E. Li, “Highly sensitive graphene biosensors based on surface plasmon resonance,” Opt. Express 18(14), 14395–14400 (2010). [CrossRef]
46. J. C. Reed, H. Zhu, A. Y. Zhu, C. Li, and E. Cubukcu, “Graphene-enabled silver nanoantenna sensors,” Nano Lett. 12(8), 4090–4094 (2012). [CrossRef]
47. Y. Du, Y. Zhao, Y. Qu, C.-H. Chen, C.-M. Chen, C.-H. Chuang, and Y. Zhu, “Enhanced light–matter interaction of graphene–gold nanoparticle hybrid films for high-performance sers detection,” J. Mater. Chem. C 2(23), 4683–4691 (2014). [CrossRef]
48. Y. Zhao and Y. Zhu, “Graphene-based hybrid films for plasmonic sensing,” Nanoscale 7(35), 14561–14576 (2015). [CrossRef]
49. Y. Zhao, W. Zeng, Z. Tao, P. Xiong, Y. Qu, and Y. Zhu, “Highly sensitive surface-enhanced raman scattering based on multi-dimensional plasmonic coupling in au–graphene–ag hybrids,” Chem. Commun. 51(5), 866–869 (2015). [CrossRef]
50. S. Zeng, S. Valiyaveedu, J. Shang, T. Yu, C. K. Chen, Y. Feng, D. Baillargeat, P. Coquet, H. P. Ho, A. Kabashin, and K. T. Yong, “Graphene–gold metasurface architectures for ultrasensitive plasmonic biosensing,” Adv. Mater. 27(40), 6163–6169 (2015). [CrossRef]
51. N. M. Y. Zhang, K. Li, P. P. Shum, X. Yu, S. Zeng, Z. Wu, Q. J. Wang, K. T. Yong, and L. Wei, “Hybrid graphene/gold plasmonic fiber-optic biosensor,” Adv. Mater. Technol. 2(2), 1600185 (2017). [CrossRef]
52. R. Alharbi, M. Irannejad, and M. Yavuz, “A short review on the role of the metal-graphene hybrid nanostructure in promoting the localized surface plasmon resonance sensor performance,” Sensors 19(4), 862–877 (2019). [CrossRef]
53. K. Chen, R. Adato, and H. Altug, “Dual-band perfect absorber for multispectral plasmon-enhanced infrared spectroscopy,” ACS Nano 6(9), 7998–8006 (2012). [CrossRef]
54. M. E. Stewart, N. H. Mack, V. Malyarchuk, J. A. Soares, T.-W. Lee, S. K. Gray, R. G. Nuzzo, and J. A. Rogers, “Quantitative multispectral biosensing and 1d imaging using quasi-3d plasmonic crystals,” Proc. Natl. Acad. Sci. 103(46), 17143–17148 (2006). [CrossRef]
55. Z. Liu, G. Liu, S. Huang, X. Liu, P. Pan, Y. Wang, and G. Gu, “Multispectral spatial and frequency selective sensing with ultra-compact cross-shaped antenna plasmonic crystals,” Sens. Actuators, B 215, 480–488 (2015). [CrossRef]
56. S. Thongrattanasiri, F. H. Koppens, and F. J. G. de Abajo, “Complete optical absorption in periodically patterned graphene,” Phys. Rev. Lett. 108(4), 047401 (2012). [CrossRef]
57. A. Vakil and N. Engheta, “Transformation optics using graphene,” Science 332(6035), 1291–1294 (2011). [CrossRef]
58. Y. Yao, M. A. Kats, P. Genevet, N. Yu, Y. Song, J. Kong, and F. Capasso, “Broad electrical tuning of graphene-loaded plasmonic antennas,” Nano Lett. 13(3), 1257–1264 (2013). [CrossRef]
59. L. Falkovsky and S. Pershoguba, “Optical far-infrared properties of a graphene monolayer and multilayer,” Phys. Rev. B 76(15), 153410 (2007). [CrossRef]
60. L. Falkovsky and A. Varlamov, “Space-time dispersion of graphene conductivity,” Eur. Phys. J. B 56(4), 281–284 (2007). [CrossRef]
61. K. S. Novoselov, A. K. Geim, S. Morozov, D. Jiang, Y. Zhang, S. Dubonos, I. Grigorieva, and A. Firsov, “Electric field effect in atomically thin carbon films,” Science 306(5696), 666–669 (2004). [CrossRef]
62. W. Gao, J. Shu, C. Qiu, and Q. Xu, “Excitation of plasmonic waves in graphene by guided-mode resonances,” ACS Nano 6(9), 7806–7813 (2012). [CrossRef]
63. W. Gao, G. Shi, Z. Jin, J. Shu, Q. Zhang, R. Vajtai, P. M. Ajayan, J. Kono, and Q. Xu, “Excitation and active control of propagating surface plasmon polaritons in graphene,” Nano Lett. 13(8), 3698–3702 (2013). [CrossRef]
64. L. J. Sherry, S.-H. Chang, G. C. Schatz, R. P. Van Duyne, B. J. Wiley, and Y. Xia, “Localized surface plasmon resonance spectroscopy of single silver nanocubes,” Nano Lett. 5(10), 2034–2038 (2005). [CrossRef]
65. N. Verellen, P. Van Dorpe, C. Huang, K. Lodewijks, G. A. Vandenbosch, L. Lagae, and V. V. Moshchalkov, “Plasmon line shaping using nanocrosses for high sensitivity localized surface plasmon resonance sensing,” Nano Lett. 11(2), 391–397 (2011). [CrossRef]
66. G. Vecchi, V. Giannini, and J. G. Rivas, “Shaping the fluorescent emission by lattice resonances in plasmonic crystals of nanoantennas,” Phys. Rev. Lett. 102(14), 146807 (2009). [CrossRef]
67. M. Otte, B. Sepulveda, W. Ni, J. Juste, L. Liz-Marzan, and L. Lechuga, “Identification of the optimal spectral region for plasmonic and nanoplasmonic sensing,” ACS Nano 4(1), 349–357 (2010). [CrossRef]
68. G. K. Joshi, P. J. McClory, B. B. Muhoberac, A. Kumbhar, K. A. Smith, and R. Sardar, “Designing efficient localized surface plasmon resonance-based sensing platforms: Optimization of sensor response by controlling the edge length of gold nanoprisms,” J. Phys. Chem. C 116(39), 20990–21000 (2012). [CrossRef]
69. P. R. Griffiths and J. A. De Haseth, Fourier Transform Infrared Spectrometry, 2nd Edition (John Wiley & Sons, Inc.,2006).
70. A. A. Yanik, M. Huang, O. Kamohara, A. Artar, T. W. Geisbert, J. H. Connor, and H. Altug, “An optofluidic nanoplasmonic biosensor for direct detection of live viruses from biological media,” Nano Lett. 10(12), 4962–4969 (2010). [CrossRef]
71. L. S. Jung, C. T. Campbell, T. M. Chinowsky, M. N. Mar, and S. S. Yee, “Quantitative interpretation of the response of surface plasmon resonance sensors to adsorbed films,” Langmuir 14(19), 5636–5648 (1998). [CrossRef]
72. J. Li, J. Ye, C. Chen, L. Hermans, N. Verellen, J. Ryken, H. Jans, V. Wim, V. Moshchalkov, L. Lagae, and P. Dorpe, “Biosensing using diffractively coupled plasmonic crystals: the figure of merit revisited,” Adv. Opt. Mater. 3(2), 176–181 (2015). [CrossRef]
