Open Access
Add to BibSonomy
Abstract
Refractometry is a ubiquitous technique for process control and substance identification in the chemical and biomedical fields. Herein, we present an all-dielectric, wafer-scalable, and compact Fabry-Pérot microcavity (FPMC) device for refractive index (RI) sensing. The FPMC consists of a highly porous SiO2 microcavity capped with a thin, quasi-periodically patterned TiO2 hole array partial reflector that enables rapid, nanoliter-scale analyte transport to and from the sensor. Liquid (alcohols) or condensed-vapor (water from human breath) infiltration resulted in spectral redshifts up to 100 nm, highly apparent visible color change, rapid recovery (< 20 s), and RI sensitivity of up to 680 nm/RIU. The sensor can also be used in spectral or single-wavelength detection modes. Effective-medium and finite-difference time-domain optical simulations identified that Fano-resonant scattering modes induced by the quasi-periodic TiO2 outcoupling layer effectively filter higher-order Fabry-Pérot cavity modes and thereby confer an easily identifiable red-to-green color transition during analyte infiltration.
© 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
Optical refractive index sensing is employed in a variety of fields for process control, substance identification, and diagnostics [1–3]. It is generally performed with hand-held or bench-top instruments incorporating prisms, optical fibers, and/or attenuated total reflection (ATR) optics that rely on reflections from multiple interfaces; many of these approaches have impressive optical sensitivity and resolution [4–9]. However, development of multi-point, in-line process control and lab-on-a-chip diagnostics requires increasingly smaller sensors [10], and the need for a compact form factor often precludes straightforward integration of the aforementioned incumbent technologies.
Recent advances in optofluidics and nanophotonics have enabled the deployment of miniature refractometers [11]. These devices often incorporate microfluidic channels [12–17] and/or resonators that rely on waveguided or whispering-gallery optical modes [18–22] to minimize analyte volumes and deliver sensitive and high-quality spectral response, respectively. However, ultra-high resolution and defect-intolerant patterns are often necessary, leading to a costly tradeoff between production throughput and device sensitivity. To enable mass deployment of technologies fully leveraging these advances, there remains a need for scalable, defect-tolerant, and low-cost device schemes.
In this work, we present the fabrication, characterization, and optical simulation of a Fabry-Pérot microcavity (FPMC)-based refractive index sensing device that is mechanically and optically robust, sensitive, and can be feasibly scaled up to mass-producible wafer areas. A silicon high reflector (the substrate), porous SiO2 underlayer, and sub-λ thick TiO2 nanohole array membrane make up the FPMC. The high-index, quasi-ordered nanohole array filters high-order Fabry-Pérot (FP) cavity modes via Fano-like resonances while also allowing facile access of condensable vapors and nanoliter liquid analyte volumes to the FPMC. This provides an easy-to-assess color change, quick response and recovery, and spectral sensitivity of up to 680 nm/RIU.
2. Experimental and simulation methods
2.1 Structure fabrication
The FPMC device stack (Fig. 1) was fabricated by depositing 10 nm of Al2O3 (ALD), 600 nm of sacrificial Si (e-beam PVD), 132 nm of TiO2 (RF sputter), and an additional 100 nm sacrificial Si (e-beam PVD) in succession on a (100) Si wafer. Open square areas for each sensor, with edge lengths of 300, 500, and 800 µm, were defined via photolithography using AZ nLOF 2020 resist. A monolayer of 404 nm diameter SiO2 colloids (Bangs Lab) was then deposited using a Langmuir-Blodgett (LB) interfacial assembly method that has been detailed elsewhere [23]. The overall substrate coating area is only limited by LB trough dimensions. The square arrays of SiO2 particles remaining after photoresist lift-off (heated n-methyl pyrrolidone) were size-reduced in a CHF3/O2 ICP plasma (30 mTorr, 900 W, no bias), and subsequently used as a shadow mask to create an Ni hole array (60 nm thick, e-beam) with ultrasonication to remove the particles. The Ni hole array pattern was transferred into the device stack using an SF6/O2 RIE (10 mTorr, 300 V bias) with etch stop on the substrate; the metal was then lifted off and the sacrificial Si in the FPMC cavity was partially removed with a XeF2 vapor etch (Xetch System, Xactix). The TiO2 nanohole array membrane was thus suspended above the substrate with a partial SiO2 support (etch residue created by the SF6/O2 step, and not removed by XeF2), as illustrated in Fig. 1. Further details of the processing can be found elsewhere [24].
Fig. 1. (a) Scanning electron microscope (SEM) image of the on-wafer Fabry-Pérot microcavity (FPMC) sensor. (b) Schematic representation of the structure in (a). Optical images of multiple FPMC sensors in the (c) as-fabricated (in air) and (d) water vapor-infiltrated (i.e., detection of water in human breath) states. Scale bars in (c) and (d) are 3 mm.
2.2 Optical measurements
Reflectance (R) spectra of the FPMC sensor were measured at normal-incidence (±5°) using a six-around-one fiber bundle (solarized UV-vis with a 60 mm focal length lens, giving a ∼300 µm spot diameter); the bifurcated ends of the bundle were connected to a D2-halogen broadband white light source (center fiber) and OceanOptics USB2000+ spectrometer (outer six fibers). Reflectance was referenced to a UV-protected aluminum mirror (Thor labs PF10-03-F01).
2.3 Optical simulations
The optical behavior of the FPMC sensor was simulated using the transfer-matrix (TMM) [25] and finite-difference time-domain (FDTD) methods (Lumerical). Cross-sectional schematics of the simulated structures are shown in Fig. 2. The TMM simulation domain (Fig. 2(a)) was set up with three homogeneous layers, the effective refractive indices of which were obtained via the Bruggeman effective medium model [26]: top (partial reflector) layer (74.5 vol% TiO2, 25.5 vol% analyte fluid), intermediate (cavity) layer (40 vol% SiO2, 60 vol% analyte fluid), and Si substrate (high reflector). The relative fraction of FPMC material vs. air (and where the analyte fluid would be present in sensing mode) was first assessed with SEM imaging, and subsequently optimized to match the simulated reflectance (R) with experiment.
Fig. 2. Optical simulation domain configurations for the FPMC. (a) FPMC structure generated via effective-medium approximation, calculated via TMM. (b) Patterned TiO2 slab supported by a semi-infinite, effective-index underlayer, calculated via FDTD. (c) Patterned TiO2 and SiO2 slab on an Si substrate, calculated via FDTD. The resonances observed for all three configurations are schematically represented by blue and red arrows for short (λS < 600 nm) and long (λL > 600 nm) wavelengths, respectively. Simulation boundaries (orange), reflected field monitors (green, denoted “R”) and downward-injected broadband plane wave source (purple, denoted “S”) are positioned relative to the simulated geometries as shown.
The FDTD simulation setup for the sensor is shown in Figs. 2(b) and 2(c), which correspond to a TiO2 nanohole array supported by an effective-index, semi-infinite underlayer, and the full FPMC structure (as measured from SEM images), respectively. The TiO2 layer was 132 nm thick with 214 nm diameter holes on a hexagonal lattice with hole-to-hole pitch of 404 nm. The SiO2 underlayer for the full FPMC structure was 380 nm thick, contained coaxial holes with a diameter of 328 nm, and placed on a 200 nm thick Si (substrate) layer modeled with a perfectly matched boundary condition (i.e., no reflection of light that was transmitted into the Si layer). The cylindrical inclusions in both the TiO2 and SiO2 were filled with analyte having a refractive index of nfill. The simulation domain was set up with perfectly matched (absorbing) out-of-plane boundaries and periodic in-plane boundaries. A broadband plane wave source (λ = [300, 1000] nm, 1 µm above the FPMC structure) was injected downward at normal incidence onto the FPMC structure, and a reflection monitor was placed near the top simulation boundary.
3. Experimental results and discussion
3.1 Experimental results
The optical response of the sensor was investigated via liquid infiltration with isopropanol (IPA, Fig. 3(a)) and ethanol (EtOH, see Fig. 4), as well as with vapor infiltration (humid air, Fig. 3(b)) by breathing on it. For Fig. 3, reflectance spectra were collected from two different sensor areas (0.8 × 0.8 mm2) on the wafer surface, labeled sensor I and II, respectively. Infiltrating the structure with isopropanol (nIPA = 1.38, sensor I) resulted in a redshift of the reflectance spectrum above 600 nm by ∼100 nm, and reweighting of peaks below 600 nm. Visually, the sensor switched from deep red (as-fabricated) to bright green (infiltrated), as indicated by the optical image swatches (solid borders) in Fig. 3. Correspondence of spectra with the observed colors was evaluated by convolving spectra with the human photopic response according to the CIE 1931 XYZ color space via the open-source colorpy package [27] (dashed borders), and agreement was excellent. Due to a measured dependence of reflectance spectra on the collection angle (∼2 nm/degree, due to slightly longer path length in the FPMC) and a slight off-angle camera set-up, the simulated color swatches were obtained by red-shifting all spectra by 5 nm.
Fig. 3. (a) Normalized reflectance at normal-incidence (±5°) of the porous FPMC sensor in the as-fabricated (solid red, in open air) and infiltrated with isopropanol (solid black) states. Reflectance curves simulated with the effective-medium approximation (EMA) via the TMM are also shown (dashed). Key spectral features are labeled (P1-3). (b) Normalized time-dependent reflectance collected during water vapor infiltration (0 s, by breathing on it) and sensor recovery (17 s). Swatches containing optical images (solid border) and human photopic function-weighted simulation (dashed border) of the sensor color are featured for each spectrum. Sensor I and Sensor II denote two distinct square sensor areas on the wafer surface. λ* represents the maximum-reflectance wavelength for each un-infiltrated sensor.
Fig. 4. Refractive index sensitivity of the FPMC obtained by (a) spectral shifts of the P1 peak and the valley between P1 and P2 (680 and 635 nm/RIU, respectively), and (b) the ratio of reflected and maximum intensity at the un-infiltrated P1 mode wavelength, λ* (see Fig. 3).
Figure 3(b) shows time-resolved, normalized reflectance spectra collected during breath-based water vapor infiltration; observed and calculated colors were in good agreement, as in Fig. 3(a). The sensor rapidly responded to water vapor infiltration (< 1 s response, not shown) as water condensed onto the walls of the porous underlayer and the reflected intensity sharply decreased. Spectral shape and mode location remained unchanged as the infiltrated sensor recovered, before returning to its exact initial state upon complete analyte evaporation at 17 s.
3.2 Sensor performance
The refractive index sensitivity of the FPMC was obtained by tracking spectral shifts of the P1 peak and the valley between P1 and P2 in sensor I and II spectra (un-infiltrated features were used as reference), for all three tested analytes (IPA, EtOH, and water from human breath). This yielded a linear response to analyte refractive index (nfill), with sensitivities of 680 and 635 nm/RIU, respectively (Fig. 4(a)). Notably, these sensitivities are comparable to other reported photonic crystal and interference-based schemes [21,22,28–31]. The refractive index detection range is at least nfill = 1.3-1.4 as validated herein, which captures a variety of aqueous and organic solutions. Given the generic fabrication protocol, changes in structure and material composition may further extend this range of applicability. Additionally, a dramatic change in normalized reflectance at the un-infiltrated P1 peak wavelength (700 nm) was recorded, resulting in a negative change of up to 50%, equivalent to ∼600% change in normalized R per RIU (Fig. 4(b)). The latter suggests that the FPMC sensor may be used effectively in spectral or single-wavelength (laser-based) detection configurations. Moreover, each FPMC sensor cell (0.8 × 0.8 mm2) can hold up to 120 nL of analyte for full infiltration, calculated from the lateral dimensions, total thickness, and void fraction of the device. Temperature sensitivity of the sensor, i.e., due to thermal expansion of the cavity (SiO2 support and TiO2), was also considered via FDTD simulations, and found to result in less than a 1 nm redshift of the P1 mode peak for 100 K change.
3.3 Operating principles
The operating principle of the sensor was deduced by assigning experimentally observed spectral features to optical modes. In order to discern modal origins, simulations were performed with an effective-medium approximated structure, an isolated TiO2 hole-array, and the full-device configuration. Figure 5 shows reflectance contours generated as a function of nfill (1 to 1.5) for each configuration. The effective-medium dielectric stack simulated in Fig. 5(a) shows three main Fabry-Pérot etalon modes (FP1-3). The most prominent and experimentally relevant mode is FP1, which redshifts significantly with nfill, and appears nearly identical to the FP1 mode seen in the full-scale simulation in Fig. 5(c), and experimentally observed feature P1 in Fig. 3. FP1 is the only mode with appreciable intensity in the 600-650 nm range, resulting in the bright red color observed for the un-infiltrated sensor. The remaining higher-order FP modes, FP2 and FP3, also redshift upon analyte infiltration, in line with expected thin-film interference. It is of note that the reflected intensities of these simulated modes are significantly greater than those of the measured P2 and P3 peaks; however, the model does not consider any scattering effects induced by nanostructuring in the TiO2 layer and therefore does not accurately represent optical behavior at shorter wavelengths.
Fig. 5. Simulated normal-incidence reflectance contour maps of the FPMC sensor with analyte refractive index nfill = 1 to 1.5, configured as shown in the simplified schematics in each panel corner (cf. Fig. 2). (a) Effective-medium approximated layers via TMM, (b) patterned TiO2 layer supported by an effective-index underlayer via FDTD, and (c) patterned TiO2 and SiO2 slab on an Si substrate via FDTD. FP1-3 denote Fabry-Pérot resonances.
Guided modes supported by high-index-contrast nanostructures are known to interact strongly with slowly-varying broadband continua, and this coupling can be modeled by Fano resonances [32–34]. In order to isolate these modal contributions within the sensor, a nanopatterned TiO2 slab was simulated with a semi-infinite, effective-medium approximated underlayer beneath it. Two sets of Fano resonances (denoted “Fano 1” and “Fano 2”) featuring the characteristic asymmetric and narrow-linewidth shape can be discerned in Fig. 5(b). The Fano lineshape varies based on the phase difference between the internal TiO2 Fabry-Pérot continuum state (out-of-plane FP modes) and localized states (guided in-plane modes), resulting in either enhanced (Fano 1) or attenuated (Fano 2) reflectance relative to the FP continuum. Although P2 and P3 track the central mode positions of Fano 1 and 2, respectively, they are neither as sharp nor as intense. We attribute the observed modal breadth to (i) the imperfect normal-incidence measurement (±5° solid angle) and (ii) high translational disorder in hole positions, given the high sensitivity of sharp optical Fano modes to angle and ordering [24,35]. Regardless of ordering, the TiO2 layer essentially acts as a highly wavelength-selective filtering element below 600 nm within the nfill range of interest.
The simulation results in Fig. 5(c) depict reflectance contours for the full sensor structure calculated with analyte-infiltrated TiO2 hole array and SiO2 underlayer features, as well as a silicon substrate beneath. FP1 fully retains the behavior observed in Fig. 5(a), while FP2 and FP3 are modified by the Fano resonances observed in Fig. 5(b), induced by the nanostructured TiO2 layer. The convolution of FP2/3 modes and Fano 1/2 resonances, respectively, more accurately represent the mode locations and intensities of P2 and P3 than the pure FP2/FP3 modes in Fig. 5(a). Notably, Fano 2 retains high reflectivity despite a considerable redshift, which explains sustained increases in P2 intensity as the cavity is infiltrated (Fig. 3(a)). As discussed above, these distributed Fano modes tend to diffusely scatter light off-axis at or near the locations of FP2 and FP3, which favors a vivid red appearance in specular view. P2 is particularly prominent while the sensor is infiltrated and contributes most directly to the apparent green sensor color. We conclude that P1 is a pure Fabry-Pérot etalon mode, while P2 and P3 are comprised of convolved Fabry-Pérot and nanohole-induced, broadly distributed Fano resonances that suppress blue light and yield a striking red-to-green color transition.
When comparing experimental sensor performance in Fig. 4(a) to the simulated result in Fig. 5(c), it becomes evident that the approximately linear sensitivity in the simulated FP1 peak (∼250 nm/RIU) is less than demonstrated experimentally for nfill = 1.3-1.4 (∼650 nm/RIU). While we have no definitive justification for this, several plausible contributing factors may be (1) under-estimation of underlayer porosity due to presence of hollow/nanoporous SiO2 supports, and/or (2) inaccessible pockets of air inside the sensor, which can yield significant local differences in infiltration as dictated by the surface tension of the analyte. As such, further iterations of the sensor could feature surface treatments to help or control the degree of analyte infiltration.
4. Summary
We have demonstrated an all-dielectric Fabry-Pérot microcavity resonator, comprised of a high-index TiO2 output coupler and microporous SiO2 cavity, for refractive index sensing. Analyte infiltration increases the effective refractive index of the structure, red-shifting the primary Fabry-Pérot resonance wavelength. The TiO2 outcoupling membrane function is twofold, enabling facile analyte transport to the microcavity and acting as a diffusely scattering photonic slab that filters higher-order Fabry-Pérot cavity modes and affords an easily detectable color transition during operation. The sensor is made via wafer-scalable techniques, shows sensitivities on par with incumbent refractometers, and can be used in spectral and single-wavelength sensing modes, making it a versatile candidate for commercial deployment in applications ranging from in-line process control to respiratory measurements.
Funding
Army Research Office (W911NF-19-2-0026, W911NF-19-D-0001); Solid State Lighting and Energy Electronics Center, University of California Santa Barbara.
Acknowledgments
Device processing was carried out in the UCSB Nanofabrication Facility. The content of the information herein does not necessarily reflect the position or the policy of the U.S. Government, and no official endorsement should be inferred.
Disclosures
The authors declare no conflicts of interest.
References
1. L. G. Lindberg, H. Ugnell, and PÅ Öberg, “Monitoring of respiratory and heart rates using a fibre-optic sensor,” Med. Biol. Eng. Comput. 30(5), 533–537 (1992). [CrossRef]
2. J. G. Groetsch, “Theory and Use of In-Line Refractive Index Analyzers for Improved Process Control,” Sensors Ind. Conf. (November), 219–223 (2001).
3. I. Noiseux, W. Long, A. Cournoyer, and M. Vernon, “Simple fiber-optic-based sensors for process monitoring: An application in wine quality control monitoring,” Appl. Spectrosc. 58(8), 1010–1019 (2004). [CrossRef]
4. J. Rheims, J. Köser, and T. Wriedt, “Refractive-index measurements in the near-IR using an Abbe refractometer,” Meas. Sci. Technol. 8(6), 601–605 (1997). [CrossRef]
5. P. P. Herrmann, “Determination of thickness, refractive index, and dispersion of waveguiding thin films with an Abbe refractometer,” Appl. Opt. 19(19), 3261–3262 (1980). [CrossRef]
6. M. Shao, X. Qiao, Z. Jia, H. Fu, Y. Liu, H. Li, and X. Zhao, “Refractive index measurement based on fiber Bragg grating connected with a multimode fiber core,” Opt. Commun. 351, 70–74 (2015). [CrossRef]
7. S. W. James and R. P. Tatam, “Optical fibre long-period grating sensors: characteristics and application,” Meas. Sci. Technol. 14(5), R49–R61 (2003). [CrossRef]
8. V. Bhatia, “Applications of long-period gratings to single and multi-parameter sensing,” Opt. Express 4(11), 457–466 (1999). [CrossRef]
9. L. Coelho, D. Viegas, J. L. Santos, and J. M. M. M. de Almeida, “Enhanced refractive index sensing characteristics of optical fibre long period grating coated with titanium dioxide thin films,” Sens. Actuators, B 202, 929–934 (2014). [CrossRef]
10. A. A. P. Trichet, J. Foster, N. E. Omori, D. James, P. R. Dolan, G. M. Hughes, C. Vallance, and J. M. Smith, “Open-access optical microcavities for lab-on-a-chip refractive index sensing,” Lab Chip 14(21), 4244–4249 (2014). [CrossRef]
11. C. Monat, P. Domachuk, and B. J. Eggleton, “Integrated optofluidics: A new river of light,” Nat. Photonics 1(2), 106–114 (2007). [CrossRef]
12. D. Brennan, P. Lambkin, and P. Galvin, “Refractive index measurements in a shallow multichannel microfluidic system,” Meas. Sci. Technol. 19(8), 085403 (2008). [CrossRef]
13. G. A. C. Tellez, S. Hassan, R. N. Tait, P. Berini, and R. Gordon, “Atomically flat symmetric elliptical nanohole arrays in a gold film for ultrasensitive refractive index sensing,” Lab Chip 13(13), 2541–2546 (2013). [CrossRef]
14. W. Z. Song, X. M. Zhang, A. Q. Liu, C. S. Lim, P. H. Yap, and H. M. M. Hosseini, “Refractive index measurement of single living cells using on-chip Fabry-Pérot cavity,” Appl. Phys. Lett. 89(20), 203901 (2006). [CrossRef]
15. P. Domachuk, I. C. M. Littler, M. Cronin-Golomb, and B. J. Eggleton, “Compact resonant integrated microfluidic refractometer,” Appl. Phys. Lett. 88(9), 093513 (2006). [CrossRef]
16. R. St-Gelais, J. Masson, and Y. A. Peter, “All-silicon integrated Fabry-Pérot cavity for volume refractive index measurement in microfluidic systems,” Appl. Phys. Lett. 94(24), 243905 (2009). [CrossRef]
17. V. Lien, K. Zhao, and Y. H. Lo, “Fluidic photonic integrated circuit for in-line detection,” Appl. Phys. Lett. 87(19), 194106 (2005). [CrossRef]
18. Y. Xu, P. Bai, X. Zhou, Y. Akimov, C. E. Png, L. K. Ang, W. Knoll, and L. Wu, “Optical Refractive Index Sensors with Plasmonic and Photonic Structures: Promising and Inconvenient Truth,” Adv. Opt. Mater. 7(9), 1801433 (2019). [CrossRef]
19. S. M. Harazim, V. A. Bolaños Quiñones, S. Kiravittaya, S. Sanchez, and O. G. Schmidt, “Lab-in-a-tube: On-chip integration of glass optofluidic ring resonators for label-free sensing applications,” Lab Chip 12(15), 2649–2655 (2012). [CrossRef]
20. C. Li, G. Bai, Y. Zhang, M. Zhang, and A. Jian, “Optofluidics refractometers,” Micromachines 9(3), 136 (2018). [CrossRef]
21. S. Wang, Y. Liu, D. Zhao, H. Yang, W. Zhou, and Y. Sun, “Optofluidic Fano resonance photonic crystal refractometric sensors,” Appl. Phys. Lett. 110(9), 091105 (2017). [CrossRef]
22. W. Zhou, D. Zhao, Y. C. Shuai, H. Yang, S. Chuwongin, A. Chadha, J. H. Seo, K. X. Wang, V. Liu, Z. Ma, and S. Fan, “Progress in 2D photonic crystal Fano resonance photonics,” Prog. Quantum Electron. 38(1), 1–74 (2014). [CrossRef]
23. F. L. Gonzalez, L. Chan, A. Berry, D. E. Morse, and M. J. Gordon, “Simple colloidal lithography method to fabricate large-area moth-eye antireflective structures on Si, Ge, and GaAs for IR applications,” J. Vac. Sci. Technol., B: Nanotechnol. Microelectron.: Mater., Process., Meas., Phenom. 32(5), 051213 (2014). [CrossRef]
24. P. Shapturenka, F. Birkholz, N. I. Zakaria, S. P. DenBaars, and M. J. Gordon, “Quasiordered, subwavelength TiO2 hole arrays with tunable, omnidirectional color response,” J. Vac. Sci. Technol., A 38(5), 053403 (2020). [CrossRef]
25. S. J. Byrnes, “Multilayer optical calculations,” arXiv e-prints (2016).
26. D. A. G. Bruggeman, “Berechnung verschiedener physikalischer Konstanten von heterogenen Substanzen,” Ann. Phys. 416(7), 636–664 (1935). [CrossRef]
27. M. Kness, “ColorPy - A Python package for handling physical descriptions of color and light spectra,” (2012).
28. W. Knoll, O. Azzaroni, H. Duran, J. Kunze-Liebhäuser, K. H. A. Lau, E. Reimhult, and B. Yameen, “Nanoporous thin films in optical waveguide spectroscopy for chemical analytics,” Anal. Bioanal. Chem. 412(14), 3299–3315 (2020). [CrossRef]
29. W. Liu, J. Yan, and Y. Shi, “High sensitivity visible light refractive index sensor based on high order mode Si3N4 photonic crystal nanobeam cavity,” Opt. Express 25(25), 31739 (2017). [CrossRef]
30. F. B. Barho, F. Gonzalez-Posada, M.-J. Milla-Rodrigo, M. Bomers, L. Cerutti, and T. Taliercio, “All-semiconductor plasmonic gratings for biosensing applications in the mid-infrared spectral range,” Opt. Express 24(14), 16175 (2016). [CrossRef]
31. T. Wei, Y. Han, Y. Li, H.-L. Tsai, and H. Xiao, “Temperature-insensitive miniaturized fiber inline Fabry-Perot interferometer for highly sensitive refractive index measurement,” Opt. Express 16(8), 5764–5769 (2008). [CrossRef]
32. W. Zhou, Z. Ma, H. Yang, Z. Qiang, G. Qin, H. Pang, L. Chen, W. Yang, S. Chuwongin, and D. Zhao, “Flexible photonic-crystal Fano filters based on transferred semiconductor nanomembranes,” J. Phys. D: Appl. Phys. 42(23), 234007 (2009). [CrossRef]
33. B. C. P. Sturmberg, K. B. Dossou, L. C. Botten, R. C. McPhedran, and C. M. de Sterke, “Fano resonances of dielectric gratings: symmetries and broadband filtering,” Opt. Express 23(24), A1672–1686 (2015). [CrossRef]
34. O. Kilic, S. Kim, W. Suh, Y.-A. Peter, A. S. Sudbø, M. F. Yanik, S. Fan, and O. Solgaard, “Photonic crystal slabs demonstrating strong broadband suppression of transmission in the presence of disorders,” Opt. Lett. 29(23), 2782–2784 (2004). [CrossRef]
35. V. N. Astratov, I. S. Culshaw, R. M. Stevenson, D. M. Whittaker, M. S. Skolnick, T. F. Krauss, and R. M. De La Rue, “Resonant coupling of near-infrared radiation to photonic band structure waveguides,” J. Lightwave Technol. 17(11), 2050–2057 (1999). [CrossRef]
