A multifunctional Si3N4 nanobrick metasurface for sensing

Huimin Wang , Lu Wang, Tao Wang*, Ming Shen, Xinzhao Yue, Enze Lv, Jinwei Zeng, Xuewen Shu* and Jian Wang*
Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, 430074, China. E-mail: wangtao@hust.edu.cn; xshu@hust.edu.cn; jwang@hust.edu.cn

Received 14th May 2024 , Accepted 5th August 2024

First published on 6th August 2024


Abstract

A metasurface composed of Si3N4 with a lower refractive index can result in more electromagnetic energy leaking into the surrounding environment compared with other dielectric materials, which is beneficial for sensing applications. However, the research on Si3N4 metasurfaces in the sensing field remains relatively scarce to date. We focus on two different sensing applications to highlight the potential versatility of Si3N4 nanobrick metasurfaces. On the one hand, exploiting colors corresponding to reflection spectra, colorimetric sensors in different refractive index surroundings are addressed with distinguishable color changes by naked eyes, and a sensitivity of about 104 nm per RIU at a resonance wavelength of 541 nm is obtained. On the other hand, the potential for carcinoembryonic antigen (CEA) detection is demonstrated by abnormal spectral blueshifts after specific binding of functionalized gold nanoparticles onto the Si3N4 nanobrick surface in the presence of CEA. These results open the path to the application of Si3N4 nanobrick arrays as multifunctional metasurfaces for colorimetric sensors, displays, anti-counterfeiting, and biosensors.


1. Introduction

Metasurfaces are artificial electromagnetic materials with a feature size smaller than the wavelength of the incident light.1 In recent years, metasurfaces have quickly developed due to the flexibility of various artificially designed optical functions.2–6 Besides, they have the advantages of being compatible with current CMOS (complementary metal–oxide semiconductor) nanofabrication technologies,7 easy to fabricate and integrate with flexible substrates8 and optofluidic platforms.9,10 The manipulation of light waves has been extensively investigated in these metasurfaces in terms of rays, phases,11 structural colors,12–14 and holograms.15,16 Except for exploring light-wave manipulation, there is growing interest in light–matter interactions in novel optical devices, which spans from fundamental investigations to practical applications.

Structural colors of metasurfaces are generated by the interaction of the incident light and nanostructure, and are more stable and safe in comparison with traditional dyes and pigments.13,17 Colorimetric sensors based on structural colors can be achieved by changing the surrounding environment.18–20 Especially in the visible region, dielectric metasurfaces are highly efficient and an excellent choice for colorimetric sensors due to their lossless properties. The all-dielectric metasurfaces support Mie resonances, which have the characteristic of the electromagnetic field enhancement. However, the enhanced electromagnetic fields are confined within the nanostructure and do not extend into the surrounding sensing regions, which limits the development of dielectric metasurface sensors. A metasurface composed of Si3N4 with a lower refractive index can result in more electromagnetic energy leaking into the surrounding environment compared with other dielectric materials,21,22 such as Si23–25 and Ge.26,27 This characteristic can enhance the interactions between the electromagnetic energy and analytes, which is beneficial for sensing applications. However, the research of Si3N4 metasurfaces in the sensing field remains relatively scarce to date. Besides, various analytes have unique requirements for electromagnetic energy distributions based on their sizes.28 It is crucial to investigate the interaction of different types of light and matter for the development of optical sensors.

In this study, we focused on two different applications to highlight the versatility of Si3N4 metasurfaces in the sensing field. (1) A size tuning of the nanobrick array provided different colors, which were sensitive to the refractive index changes of the surroundings. The colorimetric sensor obtained a sensitivity of about 104 nm per RIU at a resonance wavelength of 541 nm. (2) Antibody modified gold nanoparticles (AuNPs) were bound on the surface of the Si3N4 nanobrick array based on the specific recognition between the carcinoembryonic antigen (CEA) and antibodies. The interactions of the Mie resonance caused by the Si3N4 metasurface and localized surface plasmon resonance (LSPR) supported by the AuNPs resulted in blueshifts of the resonance wavelength. The potential of the Si3N4 metasurface biosensor for CEA detection was demonstrated.

2. Experimental

2.1. Materials and reagents

CEA, secondary antibody of CEA (Ab2), and primary antibody of CEA (Ab1) were from Beijing Key-Bio Biotech Co. Ltd. (Beijing, China). Bovine serum albumin (BSA) and phosphate-buffered saline (PBS) were purchased from Sigma-Aldrich (Shanghai, China). Silane-PEG–COOH (2000 Da) was purchased from Shanghai Ponsure Biotech, Inc. (Shanghai, China). N-(3-dimethylaminopropyl)-N′-ethylcarbodiimide hydrochloride (EDC) and N-hydroxysuccinimide (NHS) were purchased from Shanghai Macklin Biochemical Co., Ltd. (Shanghai, China).

2.2. Fabrication of the Si3N4 metasurface

The Si3N4 metasurface was fabricated as previously described.12 Briefly, a 350-nm-thick Si3N4 film was deposited on a quartz glass substrate using the plasma-enhanced chemical vapor deposition (PECVD) technology, followed by a 30-nm-thick Cr film deposition through the electron beam evaporation (EBE) technology as shown in Fig. 1. Nanobrick patterns were subsequently obtained using the electron beam lithography (EBL) technology with an AR-P 6200.09 photoresist. The inductively coupled plasma (ICP) technology was then used twice to etch Cr with Cl2 gas, and Si3N4 with CF4 and H2 gases, successively. Finally, any remaining Cr was removed using a Cr etching solution.
image file: d4tc01992j-f1.tif
Fig. 1 Fabrication process of the Si3N4 metasurface.

2.3. Surface functionalization of the Si3N4 metasurface

Fig. 2 summarizes the procedure of a biomolecule-functionalized surface of the Si3N4 nanobrick array for CEA detection. Prior to the linker deposition, the Si3N4 metasurface was exposed to acetone and isopropanol, successively, followed by rinsing with deionized water and blow-drying under nitrogen. Initially, the Si3N4 metasurface was hydroxylated with an oxygen plasma (for 2 min). The Si3N4 metasurface was then immersed in silane-PEG–COOH toluene solution (1 μg mL−1) for 16 h. Subsequently, the Si3N4 metasurface was incubated in a solution containing EDC (400 mM) and NHS (100 mM) in equal volumes for 30 min to activate the carboxylic group. The Si3N4 metasurface was immediately incubated in 10 μg mL−1 Ab1 solution for over 10 h at 4 °C. The Ab1 modified Si3N4 metasurface was immersed in a BSA solution (30 μg mL−1) for 30 min to prevent nonspecific binding. Then, the unbound and weakly attached Ab1 and BSA were removed by rinsing with PBS. The Ab1 modified Si3N4 metasurface was immersed in CEA solution for 45 min. Finally, the functionalized metasurface was incubated in the Ab2 modified AuNP (AuNP–Ab2) solution for 45 min after rinsing with PBS as previously described.29 The surface functionalization of the Si3N4 metasurface was completed.
image file: d4tc01992j-f2.tif
Fig. 2 Schematic representation of biomolecule immobilization on the Si3N4 metasurface for CEA detection. The representation of the Si3N4 nanobrick, AuNPs, and biomolecules is not drawn to scale, and the actual number of biomolecules and AuNPs per Si3N4 nanobrick is believed to be significantly higher than depicted.

2.4. Optical measurement and numerical simulations

The schematic of the simplified experimental setup is shown in Fig. S1 (ESI), which is composed of a metallographic microscope (MV5000) coupled to a charge coupled device (CCD) camera and a spectrometer (PG2000pro). The Si3N4 metasurface was placed in a container made of polydimethylsiloxane (PDMS). The colors of Si3N4 metasurfaces were observed using a 5× microscope objective lens. The colors and their corresponding reflection spectra were recorded using the CCD and spectrometer, respectively. The bulk sensitivity of the Si3N4 metasurface was determined in the air, water, 50% glycerol–water mixture, and glycerol solution, and the refractive indexes of the solutions at 28 °C were 1, 1.33, 1.39, and 1.47, respectively.

The stepwise molecule binding was investigated by monitoring the corresponding reflection spectra. The Si3N4 metasurface was rinsed with PBS before each analysis step. All reflection spectra were obtained at the normal incidence and were not background-subtracted. A 20× microscope objective lens was used for measurements of reflection spectra.

Numerical simulations were performed using the COMSOL Multiphysics software. The refractive indexes of the quartz glass and Si3N4 were 1.46 and 2, respectively, and the refractive index of gold was obtained from experimental data.30 Floquet periodic boundary conditions were applied in horizontal directions, and a perfect match layer was used in the vertical direction. The incident light was the normal incident transverse magnetic wave.

3. Results and discussion

3.1. Colorimetric sensing

The scanning electron microscope (SEM) images in Fig. 3(a) show the top and tilt views of the metasurface, and the regularly distributed Si3N4 nanobricks have vertical sidewalls. One of the periodic nanobrick cells of the Si3N4 metasurface is shown in Fig. 3(b). H, L, and P represent the height, length, and period of each nanobrick, respectively. The H was fixed at 350 nm, and f = L/P represents the duty cycle of the Si3N4 metasurface. As shown in Fig. 3(c), the wavelength of the reflectance peak is 536 nm when the parameters of P = 360 nm, f = 0.6, and n = 2 (close to Si3N4) are used in the simulations. The coupling of individual meta-atoms to the surface lattice modes can produce far-field observable colors in Fig. 3(d). The reflectance peak resulted from the magnetic dipole resonance, which was typically characterized by the ring-shaped electric field distribution. The Si3N4 metasurface due to a moderate refractive index induces a stronger magnetic dipole resonance than TiO2 (n = 2.5) at the same resonance wavelength in Fig. 3(c). The full width at half maximum (FWHM) of reflectance spectra decreased, and electric field enhancements were greater when the refractive indexes decreased from 2.5 to 2. The improvements were beneficial for enhancing the spectrum resolution and sensing performance. The ratio of sensitivity to FWHM, known as the figure of merit (FOM), was used to comprehensively evaluate the sensing performance of the sensors.31 The FOM increases as the refractive index of the nanobrick decreases in Fig. S2 (ESI). Therefore, the Si3N4 metasurface with a lower refractive index had superior sensing performance.
image file: d4tc01992j-f3.tif
Fig. 3 (a) SEM images of the Si3N4 metasurface from top and tilt views. (b) Single cell of the Si3N4 nanobrick metasurface. (c) Reflectance spectra of dielectric metasurfaces with nanobricks with different refractive indices ranging from n = 2 to n = 2.5. Insets show the enhanced electric field distributions in the xz cross-section (pictures from top to down are for n = 2, n = 2.23, and n = 2.5, respectively). The color bar in the insets represents the enhanced electric field. P and H are fixed at 360 nm and 350 nm, respectively. The duty cycles (f) of nanobricks with n = 2, 2.23, and 2.5 are 0.6, 0.52, and 0.45, respectively. (d) Near-field distribution of the magnetic dipole resonance in the x–z cross section. The white lines are the x–z cross-section of Si3N4 nanobricks. The color bar represents electric field enhancement.

The reflection spectra of Si3N4 metasurfaces were simulated, and the corresponding colors were calculated from the spectral data and color matching functions defined by the International Commission on Illumination (CIE). The chromaticity coordinates ((x = X/(X + Y + Z)), y = Y/(X + Y + Z)) in the CIE 1931 color space were calculated based on tristimulus values X, Y, and Z.32,33 Further, X, Y, and Z could be calculated using the following equations:

 
image file: d4tc01992j-t1.tif(1)
where S(λ) is the simulated reflection spectra, [x with combining macron](λ), ȳ(λ), and [z with combining macron](λ) are the standard observer functions defined by CIE, I(λ) is the relative spectral power distribution of the incident light, and image file: d4tc01992j-t2.tif is a normalizing constant. The results with different values of P and f are shown in Fig. S3 (ESI), where a size tuning of the nanobrick array provides different colors. Green light, which was a very sensitive color to human eyes, was generated with f = 0.6.

The potential of the Si3N4 metasurface as a colorimetric sensor was explored. The experimentally fabricated Si3N4 metasurfaces were with f = 0.6 and P from 340 nm to 390 nm. Each of the fabricated Si3N4 metasurfaces had an area of 160 μm × 160 μm for the easy color observation. Fig. 4(a) shows the bright-field microscope images of the fabricated Si3N4 metasurfaces under different environmental conditions, where the color changes with the refractive indexes of the surroundings. For instance, the color of the Si3N4 metasurface with P = 360 nm changed from green to orange, and then to grayish purple and purple, which was a significant color change. The reflection spectra are measured and the main reflectance peaks are shown in Fig. 4(b), where redshifts are observed with the increases of the refractive indexes of the environments. The reflection spectra of the Si3N4 metasurface with P = 360 nm and f = 0.6 in different environments are shown in Fig. 4(c). Significant redshifts of the main reflectance peak were observed with the increase of the surrounding refractive index. The redshifts of reflectance peaks in the visible region resulted in the color change which can be observed by naked eyes, which showed the colorimetric properties of the proposed metasurface. The positions of reflectance peaks in air and glycerol solutions were at 541 nm and 590 nm, respectively, resulting in a sensitivity of about 104 nm per RIU. Furthermore, we compare sensitivities between the Si3N4 nanobrick metasurface and other different nanostructures in Table 1. In comparison with sensors based on Au nanospheres,34,35 TiO2 nanoblocks,36 and gold grating covered with graphene,37 the Si3N4 nanobrick metasurface had a higher sensitivity at a similar resonance wavelength, which showed superiority in the sensing application.


image file: d4tc01992j-f4.tif
Fig. 4 (a) The colorimetric properties of Si3N4 metasurfaces in different environments. The size of each color pixel is 160 μm × 160 μm in the experiment. (b) The positions of the main reflectance peaks detected using a spectrometer in different environments. P changes from 340 to 390 nm and f is fixed at 0.6. (c) Experimental reflection spectra of the Si3N4 metasurface in different environments when P is 360 nm.
Table 1 Sensitivity comparisons between our work and the other nanostructures
Nanostructure Resonance wavelength (nm) Sensitivity (nm per RIU)
Au nanospheres34 532 80
Au nanospheres35 520 85
TiO2 nanoblocks36 560 ∼83
Gold grating covered with graphene37 520 ∼80
Our work 541 ∼104


3.2. Biosensing for CEA

CEA is a tumor biomarker used for diagnosing various cancers, such as breast carcinoma and lung cancer.38,39 The potential of the Si3N4 metasurface as a biosensor for CEA detection was further explored. As shown in Table S1 (ESI), the results of energy dispersive X-ray spectroscopy show that the contents of the C element significantly increase after the silane-PEG–COOH modification in comparison with the bare Si3N4 metasurface. Silane-PEG–COOH was successfully bound to the Si3N4 metasurface for the covalent immobilization of Ab1. The reflection spectra are characterized in different linker depositions, which are shown in Fig. 5. Periods P of Si3N4 metasurfaces are 340 nm and 390 nm in Fig. 5(a) and (b), respectively, and their values of f are 0.8. Different structural parameters significantly affected the resonance wavelengths of the reflection spectra of Si3N4 metasurfaces. We treated the reflection spectra of Si3N4 metasurfaces modified by silane-PEG–COOH (metasurface/silane-PEG–COOH) as an initial reference. The resonance wavelengths of metasurface/silane-PEG–COOH are 549.52 nm and 583.66 nm in Fig. 5(a) and (b), respectively. We observed the redshifts of the resonance wavelengths after Ab1 and 500 ng mL−1 CEA biofunctionalization procedures. After silane-PEG–COOH, Ab1, and CEA were modified on Si3N4 metasurfaces (metasurface/silane-PEG–COOH/Ab1/CEA), the resonance wavelengths of Si3N4 metasurfaces changed to 550.9 nm and 584.59 nm in Fig. 5(a) and (b), respectively. The linker-molecular chains of the surface modification induced an increase of the surrounding refractive index, leading to dielectric environment-sensitive responses. After the AuNP–Ab2 modification on the metasurface/silane-PEG–COOH/Ab1/CEA (metasurface/silane-PEG–COOH/Ab1/CEA/AuNP–Ab2), the reflectance peaks have blueshifts and then 500 ng mL−1 CEA can be detected in Fig. 5(a) and (b). The resonance wavelengths of metasurface/silane-PEG–COOH/Ab1/CEA/AuNP–Ab2 are 548.59 nm and 582.74 nm in Fig. 5(a) and (b), respectively. These results revealed that the proposed Si3N4 metasurface had the ability to detect CEA. The abnormal slight spectral buleshifts could not result in a readily recognizable color difference, so the proposed Si3N4 metasurface could not be used as a colorimetric biosensor based on current detection methods.
image file: d4tc01992j-f5.tif
Fig. 5 Experimental reflection spectra for metasurface/silane-PEG–COOH (green), metasurface/silane-PEG–COOH/Ab1 (yellow), metasurface/silane-PEG–COOH/Ab1/CEA (purple), and metasurface/silane-PEG–COOH/Ab1/CEA/AuNP–Ab2 (blue). The concentration of CEA is 500 ng mL−1. Insets show enlarged diagrams of the parts of reflectance peaks. The experimental measurement environment is PBS. Structure parameters: (a) P = 340 nm and (b) P = 390 nm.

There were Ab1, CEA, and Ab2 between Si3N4 nanobricks and AuNPs, and their thicknesses could be treated as 15 nm.29,40,41 The average diameter of AuNPs was 12 nm as described in our previous work.29,42 Therefore, the overall sensing volume was in the range of approximately 27 nm above the surface of the Si3N4 nanobricks when biosensing for CEA was conducted. The model of Si3N4 nanobricks covered with a 15-nm-thick dielectric (metasurface/dielectric) was used to simulate Si3N4 nanobricks modified by Ab1, CEA, and Ab2. Furthermore, on the surface of metasurface/dielectric, 10 AuNPs (marked as metasurface/dielectric/AuNPs), and 20 AuNPs (marked as metasurface/dielectric/more AuNPs) were randomly placed to simulate the actual situation of AuNPs on the Si3N4 metasurface. As shown in Fig. S4 (ESI), colors correspond to simulated reflection spectra for the Si3N4 metasurface, metasurface/dielectric/AuNPs, and metasurface/dielectric/more AuNPs at periods from 340 nm to 390 nm. The duty cycles (f) in Fig. S4(a) and (b) (ESI) are 0.6 and 0.8, respectively. Colors only had a slight change when simulation models changed from the Si3N4 metasurface through metasurface/dielectric/AuNPs to metasurface/dielectric/more AuNPs, which was in agreement with the experimental results.

To illustrate the underlying physics, numerical simulations based on the finite element method were performed to model resonance responses between the Si3N4 metasurface and AuNPs. The scattering cross section could be decomposed into electric dipole (ED), magnetic dipole (MD), electric quadrupole (EQ), and magnetic quadrupole (MQ) components, as outlined in the multipole scattering theory.43 When considering a harmonic excitation, exp(iωt), the total scattering cross-section could be represented as

 
image file: d4tc01992j-t3.tif(2)
where c, ω, A, M, Qαβ, and Mαβ represent the speed of light in a vacuum, angular frequency, ED moment, MD moment, EQ moment, and MQ moment, respectively. The reflection spectrum and multipole expansion for metasurface/dielectric are shown in Fig. 6(a) and (b), respectively. The resonance peak at 562 nm was primarily dominated by the MD and EQ components. The reflection spectrum and multipole expansion for AuNPs are shown in Fig. 6(c) and (d), respectively. AuNPs could support LSPR, which resulted from the ED component. The reflection spectrum and multipole expansion for metasurface/dielectric with top AuNPs (metasurface/dielectric/AuNPs) are shown in Fig. 6(e) and (f), respectively. The addition of AuNPs enhanced the MD resonance. The resonance peak at 559 nm of metasurface/dielectric/AuNPs had a blueshift of 3 nm in comparison with metasurface/dielectric, which was in excellent agreement with experiment results.


image file: d4tc01992j-f6.tif
Fig. 6 Simulated reflection spectra for metasurface/dielectric (a), AuNPs (c), and metasurface/dielectric/AuNPs (e). Multipole expansions for metasurface/dielectric (b), AuNPs (d), and metasurface/dielectric/AuNPs (f). The thickness of the dielectric layer is 15 nm and the diameter of the AuNPs is 12 nm. The simulated environment is PBS.

Reflection spectra of the Si3N4 metasurface and metasurface/dielectric with a top 12-nm-thick gold film (metasurface/dielectric/GF) were further simulated with f values ranging from 0.5 to 0.7 and P from 340 nm to 390 nm, and the corresponding colors are calculated in Fig. S5 to S7 (ESI). The reflection spectra showed significant differences, leading to observable color changes between the Si3N4 metasurface and metasurface/dielectric/GF. This demonstrated the potential of the proposed Si3N4 metasurface for colorimetric biosensors by adding a gold film. The addition of a gold film onto the Si3N4 metasurface, which had been modified with biomolecules, is expected to be achieved by a wet transfer method.44 Besides, the more alterations in the refractive index on the surface of Si3N4 nanobricks contribute to the development of colorimetric biosensors. For instance, optimizing biological modification techniques facilitates the capture of more CEA and AuNP–Ab245,46 or refining the self-assembly method of AuNPs generates a dense layer of AuNPs on the surface of Si3N4 nanobricks modified by biomolecules.47

4. Conclusion

In conclusion, we focused on two different applications of the Si3N4 nanobrick metasurface in the sensing field. On the one hand, a size tuning of the nanobrick array provided different colors, each of which was sensitive to the refractive index change of surroundings. On the other hand, the potential for CEA detection was demonstrated by forming the structure of metasurface/silane-PEG–COOH/Ab1/CEA/AuNP–Ab2. In the process, the interactions of the Mie resonance caused by the Si3N4 nanobrick array and LSPR supported by AuNPs resulted in blueshifts of the resonance wavelength. Furthermore, we discussed a situation where a significant color change could appear with a gold film on the surface of Si3N4 nanobricks, which provided a guide for colorimetric biosensors.

Author contributions

Huimin Wang: conceptualization, data curation, formal analysis, investigation, methodology, visualization, software, writing – original draft, and writing – review & editing. Lu Wang: conceptualization, investigation, methodology, visualization, writing – original draft, and writing – review & editing. Tao Wang: funding acquisition, project administration, supervision, and writing – review & editing. Ming Shen: data curation, resources, and writing – review & editing. Xinzhao Yue: methodology, and validation. Enze Lv: investigation and validation. Jinwei Zeng: investigation and validation. Xuewen Shu: funding acquisition, project administration, supervision, and writing – review & editing. Jian Wang: funding acquisition and project administration. All the authors have accepted responsibility for the entire content of the submitted manuscript and approved the submission.

Data availability

The data supporting this article have been included as part of the ESI.

Conflicts of interest

There are no conflicts to declare.

Acknowledgements

This work was supported by the National Key Research and Development Program of China (2023YFE0105800), the National Natural Science Foundation of China (62275084 and 62275093), and the Key R and D Program of Hubei Province (2021BAA036). The authors thank Pan Li (engineer), Zhiwen li (engineer), Cheng Zeng (engineer), and Jun Su (engineer) in the Center of Optoelectronic Micro & Nano Fabrication and Characterizing Facility of WNLO for their support in PECVD, ICP, EBL, and SEM tests.

Notes and references

  1. M. Puentes Vargas and M. Puentes Vargas, Planar Metamaterial Based Microwave Sensor Arrays for Biomedical Analysis and Treatment, 2014, pp. 7–31 Search PubMed .
  2. N. Yu and F. Capasso, Nat. Mater., 2014, 13, 139–150 CrossRef CAS PubMed .
  3. S. Jahani and Z. Jacob, Nat. Nanotechnol., 2016, 11, 23–36 CrossRef CAS PubMed .
  4. P. Genevet, F. Capasso, F. Aieta, M. Khorasaninejad and R. Devlin, Optica, 2017, 4, 139–152 CrossRef CAS .
  5. H. Liang, A. Martins, B.-H. V. Borges, J. Zhou, E. R. Martins, J. Li and T. F. Krauss, Optica, 2019, 6, 1461–1470 CrossRef CAS .
  6. S. A. Schulz, R. Oulton, M. Kenney, A. Alù, I. Staude, A. Bashiri, Z. Fedorova, R. Kolkowski, A. F. Koenderink and X. Xiao, et al., Appl. Phys. Lett., 2024, 124, 26 CrossRef .
  7. N. Li, Z. Xu, Y. Dong, T. Hu, Q. Zhong, Y. H. Fu, S. Zhu and N. Singh, Nanophotonics, 2020, 9, 3071–3087 CrossRef .
  8. M. A. Naveed, J. Kim, M. A. Ansari, I. Kim, Y. Massoud, J. Kim, D. K. Oh, T. Badloe, J. Lee and Y. Kim, et al., ACS Appl. Mater. Interfaces, 2022, 14, 31194–31202 CrossRef CAS PubMed .
  9. X. Li, M. Soler, C. I. Özdemir, A. Belushkin, F. Yesilköy and H. Altug, Lab Chip, 2017, 17, 2208–2217 RSC .
  10. J. Hu, S. Bandyopadhyay, Y.-H. Liu and L.-Y. Shao, Front. Phys., 2021, 8, 586087 CrossRef .
  11. A. Arbabi, Y. Horie, M. Bagheri and A. Faraon, Nat. Nanotechnol., 2015, 10, 937–943 CrossRef CAS PubMed .
  12. L. Wang, T. Wang, R. Yan, X. Yue, H. Wang, Y. Wang, J. Zhang, X. Yuan, J. Zeng and J. Wang, Nano Lett., 2023, 23, 5581–5587 CrossRef CAS PubMed .
  13. L. Wang, T. Wang, R. Yan, X. Yue, H. Wang, Y. Wang and J. Zhang, Opt. Express, 2022, 30, 7299–7307 CrossRef CAS PubMed .
  14. L. Wang, T. Wang, R. Yan, X. Yue, H. Wang, Y. Wang, J. Zhang and J. Wang, Opt. Laser Technol., 2023, 157, 108770 CrossRef CAS .
  15. G. Zheng, H. Mühlenbernd, M. Kenney, G. Li, T. Zentgraf and S. Zhang, Nat. Nanotechnol., 2015, 10, 308–312 CrossRef CAS PubMed .
  16. L. Wang, S. Kruk, H. Tang, T. Li, I. Kravchenko, D. N. Neshev and Y. S. Kivshar, Optica, 2016, 3, 1504–1505 CrossRef .
  17. J.-H. Yang, V. E. Babicheva, M.-W. Yu, T.-C. Lu, T.-R. Lin and K.-P. Chen, ACS Nano, 2020, 14, 5678–5685 CrossRef CAS PubMed .
  18. L. Zhu, J. Kapraun, J. Ferrara and C. J. Chang-Hasnain, Optica, 2015, 2, 255–258 CrossRef CAS .
  19. C. Zhang, J. Jing, Y. Wu, Y. Fan, W. Yang, S. Wang, Q. Song and S. Xiao, ACS Nano, 2019, 14, 1418–1426 CrossRef PubMed .
  20. G. H. Lee, T. M. Choi, B. Kim, S. H. Han, J. M. Lee and S.-H. Kim, ACS Nano, 2017, 11, 11350–11357 CrossRef CAS PubMed .
  21. Y. Xu, P. Bai, X. Zhou, Y. Akimov, C. E. Png, L.-K. Ang, W. Knoll and L. Wu, Adv. Opt. Mater., 2019, 7, 1801433 CrossRef .
  22. A. Shalabney and I. Abdulhalim, Sens. Actuators, A, 2010, 159, 24–32 CrossRef CAS .
  23. J. Proust, F. Bedu, B. Gallas, I. Ozerov and N. Bonod, ACS Nano, 2016, 10, 7761–7767 CrossRef CAS PubMed .
  24. V. Vashistha, G. Vaidya, R. S. Hegde, A. E. Serebryannikov, N. Bonod and M. Krawczyk, ACS Photonics, 2017, 4, 1076–1082 CrossRef CAS .
  25. R. M. Bakker, D. Permyakov, Y. F. Yu, D. Markovich, R. Paniagua-Domnguez, L. Gonzaga, A. Samusev, Y. Kivshar, B. Lukanyanchuk and A. I. Kuznetsov, Nano Lett., 2015, 15, 2137–2142 CrossRef CAS PubMed .
  26. X. Zhu, W. Yan, U. Levy, N. A. Mortensen and A. Kristensen, Sci. Adv., 2017, 3, e1602487 CrossRef PubMed .
  27. A. Leitis, A. Heßler, S. Wahl, M. Wuttig, T. Taubner, A. Tittl and H. Altug, Adv. Funct. Mater., 2020, 30, 1910259 CrossRef CAS .
  28. J. Shen, F. Li, Z. Wang, X. Liu, Y. Xie, W. Chen, M. H. Fang and J. Zhu, IEEE J. Sel. Top. Quantum Electron., 2023, 29, 1–8 Search PubMed .
  29. H. Wang, J. Cai, T. Wang, R. Yan, M. Shen, J. Zhang, X. Yue, L. Wang, X. Yuan, E. Lv, J. Zeng, X. Shu and J. Wang, Biosens. Bioelectron., 2024, 257, 116295 CrossRef CAS PubMed .
  30. P. B. Johnson and R.-W. Christy, Phys. Rev. B: Condens. Matter Mater. Phys., 1972, 6, 4370 CrossRef CAS .
  31. L. J. Sherry, S.-H. Chang, G. C. Schatz, R. P. Van Duyne, B. J. Wiley and Y. Xia, Nano Lett., 2005, 5, 2034–2038 CrossRef CAS PubMed .
  32. H. S. Fairman, M. H. Brill and H. Hemmendinger, Color Research & Application: Endorsed by Inter-Society Color Council, The Colour Group (Great Britain), Canadian Society for Color, Color Science Association of Japan, Dutch Society for the Study of Color, The Swedish Colour Centre Foundation, Colour Society of Australia,Centre Français de la Couleur, 1997, 22, 11–23.
  33. V. R. Shrestha, C.-S. Park and S.-S. Lee, Opt. Express, 2014, 22, 3691–3704 CrossRef PubMed .
  34. E. Martinsson, B. Sepulveda, P. Chen, A. Elfwing, B. Liedberg and D. Aili, Plasmonics, 2014, 9, 773–780 CrossRef CAS .
  35. E. Martinsson, M. M. Shahjamali, K. Enander, F. Boey, C. Xue, D. Aili and B. Liedberg, J. Phys. Chem. C, 2013, 117, 23148–23154 CrossRef CAS .
  36. S. Sun, W. Yang, C. Zhang, J. Jing, Y. Gao, X. Yu, Q. Song and S. Xiao, ACS Nano, 2018, 12, 2151–2159 CrossRef CAS PubMed .
  37. A. Akjouj and A. Mir, et al., Vacuum, 2020, 180, 109497 CrossRef .
  38. W. Limbut, P. Kanatharana, B. Mattiasson, P. Asawatreratanakul and P. Thavarungkul, Anal. Chim. Acta, 2006, 561, 55–61 CrossRef CAS .
  39. H. Wang, T. Wang, X. Yuan, Y. Wang, X. Yue, L. Wang, J. Zhang and J. Wang, Sensors, 2023, 23, 8156 CrossRef CAS PubMed .
  40. T. Springer, M. L. Ermini, B. Spacková, J. Jablonku and J. Homola, Anal. Chem., 2014, 86, 10350–10356 CrossRef CAS PubMed .
  41. H. Wang, T. Wang, R. Yan, X. Yue, L. Wang, Y. Wang, J. Zhang and J. Wang, Nanotechnology, 2022, 33, 465203 CrossRef CAS PubMed .
  42. H. Wang, T. Wang, S. Zhong, J. Zhang, R. Yan, P. Xu, Y.-H. Zhang, X. Yue, L. Wang and Y. Wang, et al., Nanoscale, 2023, 15, 10826–10833 RSC .
  43. T. Kaelberer, V. Fedotov, N. Papasimakis, D. Tsai and N. Zheludev, Science, 2010, 330, 1510–1512 CrossRef CAS PubMed .
  44. J. Nan, S. Zhu, S. Ye, W. Sun, Y. Yue, X. Tang, J. Shi, X. Xu, J. Zhang and B. Yang, Adv. Mater., 2020, 32, 1905927 CrossRef CAS PubMed .
  45. C.-T. Yang, L. Wu, P. Bai and B. Thierry, J. Mater. Chem. C, 2016, 4, 9897–9904 RSC .
  46. S. Shi, L. Wang, R. Su, B. Liu, R. Huang, W. Qi and Z. He, Biosens. Bioelectron., 2015, 74, 454–460 CrossRef CAS PubMed .
  47. W.-G. Kim, J.-M. Lee, Y. Yang, H. Kim, V. Devaraj, M. Kim, H. Jeong, E.-J. Choi, J. Yang and Y. Jang, et al., Nano Lett., 2022, 22, 4702–4711 CrossRef CAS PubMed .

Footnotes

Electronic supplementary information (ESI) available. See DOI: https://doi.org/10.1039/d4tc01992j
These authors contributed equally to this work.

This journal is © The Royal Society of Chemistry 2024