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Abstract
In this study, a new type of sensors based on all-dielectric metamaterials that can measure temperature and relative humidity simultaneously was designed and theoretically analyzed in detail. The proposed metamaterial sensor consists of a quartz substrate in the bottom layer, polydimethylsiloxane (PDMS) in the middle layer, and a periodic silicon structure on the top layer. CST Studio Suite was used to determine the transmission spectrum of the metamaterials in the near-infrared band using finite integration, and two transmission dips were observed. Then, polyvinyl alcohol (PVA) was used as the humidity-sensitive material to be coated on the surface of this metamaterial sensor, and these two transmission dips were used to measure the temperature and relative humidity simultaneously. Simulation results showed that the sensitivities of the two dips to the temperature are −0.224 and −0.069 nm/°C, and the sensitivities to the relative humidity are −0.618 and −0.521 nm/%, respectively. Based on the sensitivity matrix, the temperature and the relative humidity can be measured simultaneously. The proposed sensor has the advantages of polarization insensitivity, small size and low loss, which makes it have many application potentials in various research fields, including physics, biology and chemical sensing.
© 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement
1. Introduction
Relative humidity (RH) and temperature are important parameters that must be monitored and controlled in many industrial applications, environmental monitoring, food science, biomedicine, human comfort, health applications, etc. [1,2]. To achieve this goal, various devices have been developed, and various methods have been researched to monitor temperature and relative humidity (RH). To measure relative humidity, most common hygrometers are currently electronic [3,4] and have a high sensitivity and response speed but are also vulnerable to electromagnetic interference. Therefore, fiber optic humidity sensors have been produced [5–8], which overcome the shortcomings of electronic hygrometers and have been widely used, even in some harsh environments. However, fiber optic sensors are relatively fragile and cannot integrate with light sources or spectrometers on-chip.
The effects of temperature can also strongly affect measurements. Due to their high sensitivity to the working environment, many precision measuring instruments can be affected by external temperature changes. Taking optical fiber sensors as examples, due to the thermo-optical effect of silica, the optical fiber humidity sensors may be severely disturbed by changes in the external temperature changes, resulting in higher measurement error [9,10]. In addition, some humidity-sensitive materials are also sensitive to temperature, causing cross-sensitivity issues. Because temperature itself is an important indicator for agricultural, industrial and special environmental monitoring, it is important to accurately detect these two environmental parameters concurrently.
Currently, multivariable sensors have been developed, and many studies have investigated multivariable sensors [11–14]. Similarly, many sensors that can measure temperature and RH concurrently have been proposed. To our knowledge, most of these sensors are fiber optic, and include the Fabry–Perot interferometer (FPI) [15–17], fiber Bragg grating (FBG) [18–20], FBG and FPI [21], Mach–Zehnder interferometer (MZI) [22,23], double D-type optical fiber sensor [24,25], long period grating (LPG) [26], etc. In 2016, Shengnan Wu et al. proposed an open-cavity FPI with a PVA coating and showed experimentally that interferometers can simultaneously measure RH and temperature [15]. This sensor achieved a temperature sensitivity of −6.14 pm/°C and a humidity sensitivity of −23.1 pm/%RH. Although this study mitigates the cross-influence of ambient temperature on humidity detection, its method still achieves low sensitivities. Recently, compared with previous studies of simultaneous measurements of temperature and RH, temperature sensitivities have been markedly improved, but RH sensitivities remain insufficient. In 2019, Anh Duy Duong Le et al. designed a polymer-coated two-mode microfiber knot resonator [23] composed of dual-mode ultrafine fibers and a two-mode microfiber knot resonator. By optimizing the waist diameter of the optical fiber, the sensor’s sensitivity to RH and temperature were markedly improved to 0.603 nm/% and −0.79 nm/°C, respectively. Although current dual-parameter detection is mature in the field of optical fiber sensing, some problems remain in optical fiber sensing. For example, transmission fibers between the light source and the spectrometer will limit sensor use. Silicon resonators and LC-type wireless sensors can also monitor the temperature and RH [27,28]. However, the problem with silicon resonators is the fiber connection between the light source and the spectrometer. Although LC-type wireless sensors overcome the limitations of optical fibers, the problem of interference between electromagnetic fields always exists. Fortunately, metamaterial sensors [29–31], which are planar, cost-effective, passive wireless, can be mass-produced, and can enhance the interaction between electromagnetic waves and samples, are one of the most promising solutions to the simultaneous measurement of the temperature and RH.
Current metamaterial sensors can be characterized as metallic [32–35] or all-dielectric [36–39] according to the material(s) they are constructed with. Compared with metallic metamaterials, all-dielectric metamaterials inherently have lower ohmic losses, which is beneficial for designs with high Q-factors [40], where the higher the Q factor is, the higher the field enhancement around the metamaterial. Therefore, all-dielectric metamaterials will be more sensitive to environmental changes, thereby exhibiting higher sensitivities [41]. In addition, all-dielectric metamaterials have low thermal conductivity; can effectively control electromagnetic waves; can also stimulate high-order Mie resonance; effectively control the amplitude, phase and polarization of incident waves; and offer more options for perfect reflectors and perfect absorbers [42]. Therefore, we prefer all-dielectric metamaterials as sensors.
In this study, novel temperature and RH sensors based on metamaterials were theoretically investigated. The metamaterial sensor was based on the quartz substrate and the silicon PDMS double-layer structure, which were periodically arranged to determine the transmission spectrum with two dips. Then, the PVA film was used as the humidity-sensitive material to make the sensor sensitive to the relative humidity. The sensitivity matrix was solved to achieve simultaneous measurement of the temperature and relative humidity. Through simulation verification, the temperature response with sensitivities of −0.224 and −0.069 nm/°C and the humidity response with sensitivities of −0.618 and −0.521 nm/% were obtained. A comparison of the proposed method with others from the literature is summarized in Table 1. Then, these simulation results were confirmed by recalibration calculations with standard deviations of approximately 1.43°C and 0.71%, respectively. To our knowledge, this paper is the first to propose the simultaneous detection of temperature and humidity based on metamaterial sensors, which is important for real applications.
Table 1. Comparison of the proposed work with other dual-parameter sensors
2. Structural design and simulation results
Figure 1 shows the structure of the metamaterial sensor, where the substrate is fused silica, and its refractive index at 20 °C n1 is 1.48. The middle layer is PDMS, and its refractive index at 20 °C n2 is 1.40 [43]. The upper layer is a periodically arranged patterned silicon square with central hollow crosses, and its refractive index at 20 °C n3 is 3.7. The thickness of PDMS layer h is 1 µm, the period of unit structure p is 0.9 µm, the length of upper silicon structure a is 0.72 µm, the length of central hollow cross b is 0.54 µm, the width w is 0.09 µm, and the thickness of silicon layer t is 0.22 µm.
Fig. 1. (a) Schematic diagram of the metamaterial sensor. The substrate is quartz. The incident light is a plane wave with the electrical field along the y direction and the incident direction along the z direction, (b) top view and (c) side view of the metamaterial unit structure, where p = 0.9 µm, a = 0.72 µm, b = 0.54 µm, w = 0.09 µm, h = 1 µm, and t = 0.22 µm.
CST Studio Suite was used for the following simulations. The simulated transmission spectrum of this metamaterial sensor is shown in Fig. 2(a). The transmission spectrum forms two dips at 1422.34 and 1549.23 nm, which are referred to as Dip1 and Dip2, respectively. Apart from these two dips, high transmittance can be observed, which shows that the loss of the structure is small. Thus, the full width at half maximum (FWHM) of Dip1 is 39.51 nm, and the FWHM of Dip2 is 6.48 nm. According to Mie resonance theory [44], each dielectric particle can be equivalent to a magnetic dipole near Dip1 with a shorter wavelength and an electric dipole near Dip2 with a longer wavelength.
Fig. 2. (a) Transmission spectrum of the metamaterial sensor showing two dips for magnetic (λ=1422.34 nm) and electric (λ =1549.23 nm) resonances. (b) Electric field distributions at λ =1422.34 nm in a unit cell in the y-z plane. (c) Electric field distributions at λ =1549.23 nm in a unit cell in the y-z plane. (d) Magnetic field distributions at λ =1422.34 nm in a unit cell in the x-z plane. (e) Magnetic field distributions at λ =1549.23 nm in a unit cell in the x-z plane. The arrows indicate the direction of the electric and magnetic fields.
As shown in Fig. 2(b)–2(e), the electric and magnetic fields at the wavelengths of the two dips are used to explore the causes of the two dips. When the wavelength is 1422.34 nm (Dip 1), the electric field is a vortex, and the magnetic field is approximately linearly parallel to the x-axis, thus exhibiting the behavior of a magnetic dipole, as shown in Fig. 2(b) and 2(d). When the other resonance wavelength is 1549.23 nm (Dip 2), Fig. 2(c) and Fig. 2(e) show the linear parallel electric field and vortex-like magnetic field, corresponding to the characteristics of the electric dipole. Therefore, the dip at the shorter wavelength is likely formed by the magnetic dipole, and the dip at the longer wavelength is likely formed by the electric dipole.
Then we explore the effect of PDMS layer thickness on the sensor. As shown in Fig. 3, as the thickness of the PDMS layer continues to increase, the two dips of the transmission spectrum continue to produce blueshifts. When the thickness of PDMS reaches 0.8 µm, the wavelength shift reaches the saturation value. Increasing the thickness of PDMS at this time will have little effect on the spectral shift, and the two dips of the transmission spectrum are most sensitive to changes in the refractive index of the PDMS layer. Therefore, we chose the thickness of PDMS h to be 1 µm.
Fig. 3. Simulated results of the wavelength shift of the two dips versus the thickness of the PDMS layer. When the thickness of the PDMS layer is more than 0.8 µm, the wavelength shifts of both dips reach saturation. Then, the wavelength shifts remain constant.
To achieve adequate relative-humidity sensing, humidity-sensitive materials must be added to the surface of the metamaterial sensors. Many humidity-sensitive materials have been studied, including polyimide, graphene oxide, polymethyl methacrylate, and gelatin [2,7,21]. Among them, polyvinyl alcohol (PVA) [45–47], a polymer material with moisture-sensitive properties, has many advantages, such as a good swelling rate and film-forming properties and adhesion properties, and is less expensive than polyimide and agarose. Therefore, PVA was chosen as the humidity-sensitive material to increase the sensor's response to RH, as shown in Fig. 4. The PVA coating on the surface of the metamaterial sensor will expand after absorbing water molecules, resulting in a decrease in the refractive index. By calculating the relationship of the wavelength shift versus the refractive index and the relationship of the RH versus the refractive index, the RH of the external environment can be measured.
Fig. 4. Metamaterial sensor coated with PVA as the moisture-sensitive material on the surface, where the thickness of the PVA layer was 2 µm.
In addition, we explored the influence of the thickness of the PVA layer on the simulation results. As shown in Fig. 5, as the thickness of the PVA layer increases, the wavelength shifts of both Dips 1 and 2 gradually increase, and both reach saturation when the thickness of the PVA layer is more than 1 µm. To ensure that the wavelength shifts reach the maximum saturation points, and that the thickness of the PVA layer is relatively thin so that the response time is short, we choose the thickness of the PVA layer to be 2 µm. If the temperature is changed at this time, the thickness of the PVA will change, and the thermal expansion coefficient of the PVA is 3.4×10−4 /°C [48]; thus, after changing the temperature, the thickness can still be guaranteed to be greater than 1 µm to ensure that this has no effect on the wavelength of the resonance dips. Thus, the maximum humidity sensitivity can be determined, and the influence of thermal expansion effects on the simulation results can be removed.
Fig. 5. Simulated results of the wavelength shift of the two dips versus the thickness of the PVA layer. When the thickness of the PVA layer is more than 1 µm, the wavelength shifts of both dips reach saturation. Then, the wavelength shifts remain constant.
We also explored the influence of different structural parameters on the transmission spectra. As shown in Fig. 6(a), when the period p of the structure increases, the two dips continue to move in the longwave direction until they deviate from the observation wavelength range, and the two dips are getting closer, which is not good for observation. In addition, with the continuous increase of p, the transmittance of the spectrum gradually decreases, and the loss increases, which is harmful to the sensors. The results of changing the length a of the silicon squares are shown in Fig. 6(b). As a increases, the wavelength shifts of Dip1 are smaller than those of Dip2; thus, the wavelength distance between the two dips increases, and the transmittance at the non-resonant peak becomes larger, which is conducive for the sensors. The changes in the length b and width w of the central hollow cross are shown in Fig. 6(c) and 6(d). With the continuous increase of both b and w, these two dips move to the shorter wavelength direction. The changes in these two structure parameters have little effect on the waveform of the spectra; however, to increase the contact area between the metamaterial sensor and the analyte to increase the sensitivity, larger b and w can be appropriately selected. To measure a better transmission spectrum, higher sensitivity, the structural parameters p = 0.9 µm, a = 0.72 µm, b = 0.54 µm, and w = 0.09 µm are chosen.
Fig. 6. Change in the transmission spectra after changing the structural parameters: (a) substrate period p, (b) length of the silicon square a, (c) length b and (d) width w of the central hollow cross.
Also, the polarization-insensitive performance of this metamaterial sensor is verified. The incident direction of the input plane wave remains in the z direction, while the direction of the electric field changes from the y direction to the x direction and the direction of the magnetic field changes from the x direction to the y direction accordingly, following the TE and TM polarizations, respectively. As shown in Fig. 7, in these two situations, the transmission spectra are nearly identical, which shows that the sensor is polarization insensitive and markedly increases the application range of this sensor.
3. Principle and realization of dual parameter sensing
To achieve a dual-parameter sensor, these two well-separated dips of the resonance spectrum in Fig. 2(a) are used. When the external environment changes (i.e., when the temperature and RH change concurrently), the factors that affect the resonance wavelengths can be summarized into two parts: the wavelength shift caused by temperature changes and the wavelength shift caused by RH changes. Therefore, the wavelength shift after considering the above effects can be expressed as [49]:
Using the inverse calculation, the changes in the temperature and RH can be obtained concurrently:
Then, to determine these unknown sensitivity coefficients, the following simulations were performed. First, the temperature was kept at 20 °C, and the RH was changed. After changing the environmental humidity, the refractive index of PVA changes significantly, and its humidity coefficient is −1.44×10−3 RIU/% [50]. The calculated transmission spectra are shown in Fig. 8(a). In an environment when the relative humidity varied from 0% to 100%, the resonance wavelengths of both dips redshifted. To estimate the sensing characteristics, Fig. 8(b) shows the relationships between the wavelength shifts of the two dips and the RH. After linear fitting, the sensitivity of the resonance wavelength of the two dips to the relative humidity is −0.618 and −0.521 nm/%, respectively, and the linear response is excellent, with the degree of fitting both more than 0.99.
Fig. 8. (a) Simulated transmission spectra when the RH varied from 0% to 100% and the temperature was kept constant at 20 °C, and (b) the graph of the wavelength shifts of two dips versus the relative humidity.
Second, RH was held constant at 20%, and the temperature was changed in the range of 0–100 °C. According to [48], the thermo-optical coefficient (TOC) of PVA is −2.16×10−4 RIU/°C. In addition, the TOC of PDMS is −4.67×10−4 RIU/°C [43]. As verified above, when the thicknesses of PDMS and PVA are increased, they will not affect the resonance positions of the transmission spectrum; thus, the thermal expansion effects of PDMS and PVA are ignored in this study. In addition, we consulted the literature and found that the Young's moduli of PDMS and silicon are 190 GPa [51] and 0.05–2 MPa [52], respectively. The Young's modulus of PDMS is much smaller than that of silicon, so the volume change of PDMS has little effect on the period of the silicon structure. Therefore, the effect of PDMS expansion on silicon can be ignored. Conversely, when the temperature is different, the refractive index and geometric parameters of the metamaterial sensor also change. Therefore, both the thermal expansion coefficient (TEC) and thermal optical coefficient of the silicon structure and the quartz substrate are considered. The TECs of silicon and quartz are 2.59×10−6 /°C [53] and 0.55×10−6 /°C [54], respectively. The TOC contents of silicon and quartz are 1.84×10−4 RIU/°C [53] and 8.6×10−6 RIU/°C [54], respectively. Figure 9(a) shows the calculated transmission spectra at different temperatures, where two dips move to the shorter wavelength direction as the temperature changes. Figure 9(b) shows the linear fitting between the wavelength shifts of these two resonance dips and the temperature. The sensitivities to temperature were calculated to be −0.224 nm/°C at Dip1 and −0.069 nm/°C at Dip2. The linear response is also good, showing a degree of fitting greater than 0.99.
Fig. 9. (a) Simulated transmission spectra when the RH was kept at 20% and the temperature varied from 0–100 °C, and (b) the graph of the wavelength shifts of two dips versus the temperature.
Substituting all of these results into (3), we obtain the following matrix:
Finally, after obtaining the sensitivity matrix of Eq. (4), both temperature and RH can be measured using the proposed metamaterial sensor.
The method proposed in Eq. (4) can be verified by changing the RH and temperature conditions. The system mechanism was tested in a simulation, where the metamaterial sensor was first subjected to a 0–100% variation at a constant temperature of 50 °C. Then, the sensor was monitored at 0–100 °C and a constant RH of 50%. We used Eq. (4) to process the simulation results of the two light transmission inclination angle positions, and the results are shown in Fig. 10.
Fig. 10. Recovered RH and temperature values measured with varying RH at a constant temperature level (red circle) and varying temperature at a constant RH level (black square). The dotted lines represent the constant temperature and RH levels in both cases.
As shown in Fig. 10, simulation results show an excellent fit in RH for any temperature variations in the 0–100% range. The standard deviation obtained in this case is 0.71%. Conversely, the temperature values recorded for different RHs showed a higher standard deviation of 1.43 °C. Thus, the wavelength shift-based measurement system proposed in this study has successfully extracted the changes in RH and temperature from the shifts of the two transmission dips of the metamaterial sensor.
Using matrix M instead of the matrix in Eq. (3), we can obtain:
The measurement error of the simultaneous multiparameter sensing can be described as [55]:
Finally, the realization of the proposed metamaterial sensor was discussed. As shown in Fig. 11, to fabricate the all-dielectric metamaterials, a clean silica substrate had to be prepared first. Then, the PDMS solution with a 10:1 mixing ratio of PDMS prepolymer and cross-linker was spin coated onto the 500-µm-thick fused silica substrate. The substrate was then placed in a thermostat at 100 °C. The prepolymer of the mixture was polymerized by baking it in the thermostat for 2 hours. Then, a layer of 220-nm-thick silicon was deposited onto the PDMS layer using plasma-enhanced chemical vapor deposition (PECVD). Then, a layer of polymethyl methacrylate (PMMA) photoresist was spin-coated on the silicon. Electron beam lithography (EBL) was then used to define the metamaterial patterns with an e-beam writer system. After electron beam exposure, the PMMA was developed by the developer, rinsed in deionized water, and blown dry with nitrogen gas. Plasma etching then etched the silicon layer in an inductively coupled plasma (ICP) etching system. The etching process was precisely controlled so that the PMMA resist layer was completely removed when the silicon was etched. The samples were finally cleaned with ethanol to remove PMMA and blown dry with nitrogen gas. This step completed the fabrication of the proposed metamaterial sensor.
A complete metamaterial sensor can be directly applied to real sensing applications in combination with a light source and a spectrometer. In the experiment, as shown in Fig. 12(a), two air pumps can be used to pump dry and humid air into the closed air chamber. By controlling the power of the two air pumps (i.e., the ratio of dry and humid air), the relative humidity in the air chamber can be adjusted and kept at a relatively stable RH. The relative humidity can also be directly observed by a hygrometer. In addition, as shown in Fig. 12(b), during temperature sensing, a ring-shaped thermostatic heating plate can be used to heat the metamaterial to different temperatures. In the experiment, the broadband light source that was used was manufactured by Hoyaket, and the spectrometer is a Yokogawa AQ6370D. In practical applications, because the sensor size is small, the sensor can be integrated on-chip. In the environment to be measured, the metamaterial sensor can be attached to the monitor. Also, with the development of technology, the sensor, the light source and the spectrometer can be integrated together into one chip and can be applied in various environments.
Figure 13 is a microscope image of another structure previously coated with humidity-sensitive material, from which the coated and uncoated areas can be clearly distinguished. In addition, the application of the humidity-sensitive material is also very uniform.
Furthermore, additional reliability experiments of time period should be performed to determine the stability of the designed sensor [56,57]. The sensor will be placed in a stable environment with humidity of 20% and a temperature of 20°C for 150 minutes. Among them, the spectrum will be measured every 10 minutes; the frequency of two dips will be recorded to observe whether the spectrum is stable over time.
4. Conclusions
In this study, we proposed a novel type of sensor based on all-dielectric metamaterials that can simultaneously measure the temperature and the relative humidity. The metamaterial consists of a quartz substrate, a PDMS intermediate layer, silicon structures and a PVA coating layer. Simulations showed that the sensor can obtain sensitivities to temperatures of −0.224 and −0.069 nm/°C and sensitivities to relative humidity of −0.618 and −0.521 nm/%, respectively. In addition, we also verified the feasibility of the sensor for temperature and humidity sensing by reconstructing the temperature and the relative humidity. Standard deviation errors are calculated, and these errors should be reduced in future research. This research applied simultaneous measurements of the temperature and the relative humidity to metamaterials and provided a solid basis for future research.
Funding
National Natural Science Foundation of China (61875251, 61875179); Fundamental Research Funds for the Provincial Universities of Zhejiang (2020YW08); Natural Science Foundation of Zhejiang Province (LY21F050006); Key R & D Project of Zhejiang Province (2021C01179).
Disclosures
The authors declare no conflicts of interest.
Data availability
Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request
References
1. A. M. Shrivastav, D. S. Gunawardena, Z. Liu, and H. Y. Tam, “Microstructured optical fiber based Fabry-Perot interferometer as a humidity sensor utilizing chitosan polymeric matrix for breath monitoring,” Sci. Rep. 10(1), 6002 (2020). [CrossRef]
2. T. Li, L. Zhu, X. Yang, X. Lou, and L. Yu, “A Refractive Index Sensor Based on H-Shaped Photonic Crystal Fibers Coated with Ag-Graphene Layers,” Sensors 20(3), 741 (2020). [CrossRef]
3. W. Y. Tan, Y. L. Then, Y. L. Lew, and F. S. Tay, “Newly calibrated analytical models for soil moisture content and pH value by low-cost YL-69 hygrometer sensor,” Measurement 134, 166–178 (2019). [CrossRef]
4. P. Zhen, C. Palego, J. C. M. Hwang, D. I. Forehand, C. L. Goldsmith, C. Moody, A. Malczewski, B. W. Pillans, R. Daigler, and J. Papapolymerou, “Impact of Humidity on Dielectric Charging in RF MEMS Capacitive Switches,” IEEE Microwave and Wireless Components Lett. 19(5), 299–301 (2009). [CrossRef]
5. M.-Q. Chen, Y. Zhao, H.-M. Wei, C.-l. Zhu, and S. Krishnaswamy, “3D printed castle style Fabry-Perot microcavity on optical fiber tip as a highly sensitive humidity sensor,” Sensors and Actuators B: Chemical 328, 128981 (2021). [CrossRef]
6. S. K. Al-Hayali, A. M. Salman, and A. H. Al-Janabi, “High sensitivity balloon-like interferometric optical fiber humidity sensor based on tuning gold nanoparticles coating thickness,” Measurement 170, 108703 (2021). [CrossRef]
7. C. Lang, Y. Liu, K. Cao, Y. Li, and S. Qu, “Ultra-compact, fast-responsive and highly-sensitive humidity sensor based on a polymer micro-rod on the end-face of fiber core,” Sensors and Actuators B: Chemical 290, 23–27 (2019). [CrossRef]
8. M. Hernaez, B. Acevedo, A. G. Mayes, and S. Melendi-Espina, “High-performance optical fiber humidity sensor based on lossy mode resonance using a nanostructured polyethylenimine and graphene oxide coating,” Sensors and Actuators B: Chemical 286, 408–414 (2019). [CrossRef]
9. N. Chen, X. Zhou, and X. Li, “Highly Sensitive Humidity Sensor With Low-Temperature Cross-Sensitivity Based on a Polyvinyl Alcohol Coating Tapered Fiber,” IEEE Trans. Instrum. Meas. 70, 1–8 (2021). [CrossRef]
10. F. Li, X. Li, X. Zhou, Y.-N. Zhang, R.-Q. Lv, Y. Zhao, L. Xie, L. V. Nguyen, H. Ebendorff-Heidepriem, and S. C. Warren-Smith, “Simultaneous measurement of temperature and relative humidity using cascaded C-shaped Fabry-Perot interferometers,” J. Lightwave Technol. 40(4), 1 (2021). [CrossRef]
11. A. Ebrahimi, J. Scott, and K. Ghorbani, “Dual-Mode Resonator for Simultaneous Permittivity and Thickness Measurement of Dielectrics,” IEEE Sens. J. 20(1), 185–192 (2020). [CrossRef]
12. C.-S. Lee and C.-L. Yang, “Thickness and Permittivity Measurement in Multi-Layered Dielectric Structures Using Complementary Split-Ring Resonators,” IEEE Sens. J. 14(3), 695–700 (2014). [CrossRef]
13. J. Hu, T. Lang, and G. H. Shi, “Simultaneous measurement of refractive index and temperature based on all-dielectric metasurface,” Opt. Express 25(13), 15241–15251 (2017). [CrossRef]
14. Z. Wang, Z. Fu, F. Sun, C. Wang, J. Zhou, and H. Tian, “Simultaneous sensing of refractive index and temperature based on a three-cavity-coupling photonic crystal sensor,” Opt. Express 27(19), 26471–26482 (2019). [CrossRef]
15. S. Wu, G. Yan, Z. Lian, X. Chen, B. Zhou, and S. He, “An open-cavity Fabry-Perot interferometer with PVA coating for simultaneous measurement of relative humidity and temperature,” Sensors and Actuators B: Chemical 225, 50–56 (2016). [CrossRef]
16. S. Pevec and D. Donlagic, “Miniature all-silica fiber-optic sensor for simultaneous measurement of relative humidity and temperature,” Opt. Lett. 40(23), 5646–5649 (2015). [CrossRef]
17. C. Wang, G. Yan, Z. Lian, X. Chen, S. Wu, and S. He, “Hybrid-cavity fabry-perot interferometer for multi-point relative humidity and temperature sensing,” Sensors and Actuators B: Chemical 255, 1937–1944 (2018). [CrossRef]
18. J. Li, J. Zhang, H. Sun, Y. Yang, Y. Ye, J. Cui, W. He, X. Yong, and Y. Xie, “An optical fiber sensor based on carboxymethyl cellulose/carbon nanotubes composite film for simultaneous measurement of relative humidity and temperature,” Opt. Commun. 467, 125740 (2020). [CrossRef]
19. M. Madry, L. Alwis, L. Binetti, L. Pajewski, and E. Beres-Pawlik, “Simultaneous Measurement of Temperature and Relative Humidity Using a Dual-Wavelength Erbium-Doped Fiber Ring Laser Sensor,” IEEE Sens. J. 19(20), 9215–9220 (2019). [CrossRef]
20. F. J. Arregui, I. R. Matias, K. L. Cooper, and R. O. Claus, “Simultaneous measurement of humidity and temperature by combining a reflective intensity-based optical fiber sensor and a fiber Bragg grating,” IEEE Sens. J. 2(5), 482–487 (2002). [CrossRef]
21. Y. Wang, Q. Huang, W. Zhu, and M. Yang, “Simultaneous Measurement of Temperature and Relative Humidity Based on FBG and FP Interferometer,” IEEE Photonics Technol. Lett. 30(9), 833–836 (2018). [CrossRef]
22. J.-x. Li, Z.-r. Tong, L. Jing, W.-h. Zhang, J. Qin, and J.-w. Liu, “Fiber temperature and humidity sensor based on photonic crystal fiber coated with graphene oxide,” Opt. Commun. 467, 125707 (2020). [CrossRef]
23. A. D. D. Le, J. Hwang, M. Yusuf, K. H. Park, S. Park, and J. Kim, “Simultaneous Measurement of Humidity and Temperature with Cytop-reduced Graphene Oxide-overlaid Two-mode Optical Fiber Sensor,” Sensors and Actuators B: Chemical 298, 126841 (2019). [CrossRef]
24. Y. Ying, S. Cheng, N. Hu, Z. Gao, X. Guo, and G. Si, “Temperature and humidity sensor based on a double D-shaped optical fiber with incorporated toluene and polyethylene,” Instrum. Sci. Technol. 49(4), 404–415 (2021). [CrossRef]
25. J.-K. Wang, Y. Ying, N. Hu, and S.-Y. Cheng, “Double D-shaped optical fiber temperature and humidity sensor based on ethanol and polyvinyl alcohol,” Optik 242, 166972 (2021). [CrossRef]
26. A. Urrutia, J. Goicoechea, A. L. Ricchiuti, D. Barrera, S. Sales, and F. J. Arregui, “Simultaneous measurement of humidity and temperature based on a partially coated optical fiber long period grating,” Sensors and Actuators B: Chemical 227, 135–141 (2016). [CrossRef]
27. Z. Ding, P. Liu, J. Chen, D. Dai, and Y. Shi, “On-chip simultaneous sensing of humidity and temperature with a dual-polarization silicon microring resonator,” Opt. Express 27(20), 28649–28659 (2019). [CrossRef]
28. Q.-Y. Ren, L.-F. Wang, J.-Q. Huang, C. Zhang, and Q.-A. Huang, “Simultaneous Remote Sensing of Temperature and Humidity by LC-Type Passive Wireless Sensors,” J. Microelectromech. Syst. 24(4), 1117–1123 (2015). [CrossRef]
29. A. S. Saadeldin, M. F. O. Hameed, E. M. A. Elkaramany, and S. S. A. Obayya, “Highly Sensitive Terahertz Metamaterial Sensor,” IEEE Sens. J. 19(18), 7993–7999 (2019). [CrossRef]
30. X. Chen and W. Fan, “Ultrasensitive terahertz metamaterial sensor based on spoof surface plasmon,” Sci Rep 7(1), 2092 (2017). [CrossRef]
31. W. Wang, F. Yan, S. Tan, H. Zhou, and Y. Hou, “Ultrasensitive terahertz metamaterial sensor based on vertical split ring resonators,” Photonics Res. 5(6), 571–577 (2017). [CrossRef]
32. S. Wang, L. Xia, H. Mao, X. Jiang, S. Yan, H. Wang, D. Wei, H. Cui, and C. Du, “Terahertz biosensing based on a polarization-insensitive metamaterial,” IEEE Photonics Technol. Lett. 28(9), 1 (2016). [CrossRef]
33. X. Du, X. Zhang, Y. Wang, G. Ma, Y. Liu, B. Wang, and H. Mao, “Highly sensitive detection of plant growth regulators by using terahertz time-domain spectroscopy combined with metamaterials,” Opt. Express 29(22), 36535–36545 (2021). [CrossRef]
34. Y. Ye, Y. Zhang, Y. Zhao, Y. Ren, and X. Ren, “Sensitivity influencing factors during pesticide residue detection research via a terahertz metasensor,” Opt. Express 29(10), 15255–15268 (2021). [CrossRef]
35. C. Zhang, T. Xue, J. Zhang, L. Liu, J. Xie, G. Wang, J. Yao, W. Zhu, and X. Ye, “Terahertz toroidal metasurface biosensor for sensitive distinction of lung cancer cells,” Nanophotonics 11(1), 101–109 (2021). [CrossRef]
36. J. Hu, T. Lang, Z. Hong, C. Shen, and G. Shi, “Comparison of Electromagnetically Induced Transparency Performance in Metallic and All-Dielectric Metamaterials,” J. Lightwave Technol. 36(11), 2083–2093 (2018). [CrossRef]
37. S. Jahani and Z. Jacob, “All-dielectric metamaterials,” Nat Nanotechnol 11(1), 23–36 (2016). [CrossRef]
38. Y. Wang, D. Zhu, Z. Cui, L. Hou, L. Lin, F. Qu, X. Liu, and P. Nie, “All-Dielectric Terahertz Plasmonic Metamaterial Absorbers and High-Sensitivity Sensing,” ACS Omega 4(20), 18645–18652 (2019). [CrossRef]
39. W. Wang, L. Zheng, L. Xiong, J. Qi, and B. Li, “High Q-factor multiple Fano resonances for high-sensitivity sensing in all-dielectric metamaterials,” OSA Continuum 2(10), 2818–2825 (2019). [CrossRef]
40. D. C. Wang, R. Tang, Z. Feng, S. Sun, S. Xiao, and W. Tan, “Symmetry-Assisted Spectral Line Shapes Manipulation in Dielectric Double-Fano Metasurfaces,” Adv. Opt. Mater. 9(4), 2001874 (2021). [CrossRef]
41. J. Zhang, N. Mu, L. Liu, J. Xie, H. Feng, J. Yao, T. Chen, and W. Zhu, “Highly sensitive detection of malignant glioma cells using metamaterial-inspired THz biosensor based on electromagnetically induced transparency,” Biosens Bioelectron 185, 113241 (2021). [CrossRef]
42. J. Leng, J. Peng, A. Jin, D. Cao, D. Liu, X. He, F. Lin, and F. Liu, “Investigation of terahertz high Q-factor of all-dielectric metamaterials,” Opt. Laser Technol. 146, 107570 (2022). [CrossRef]
43. C. Moreno-Hernandez, D. Monzon-Hernandez, I. Hernandez-Romano, and J. Villatoro, “Single tapered fiber tip for simultaneous measurements of thickness, refractive index and distance to a sample,” Opt. Express 23(17), 22141–22148 (2015). [CrossRef]
44. M. I. Shalaev, J. Sun, A. Tsukernik, A. Pandey, K. Nikolskiy, and N. M. Litchinitser, “High-Efficiency All-Dielectric Metasurfaces for Ultracompact Beam Manipulation in Transmission Mode,” Nano Lett. 15(9), 6261–6266 (2015). [CrossRef]
45. H. Sun, X. Zhang, L. Yuan, L. Zhou, X. Qiao, and M. Hu, “An Optical Fiber Fabry-Perot Interferometer Sensor for Simultaneous Measurement of Relative Humidity and Temperature,” IEEE Sens. J. 15(5), 1 (2014). [CrossRef]
46. Y. Wang, Y. Liu, F. Zou, C. Jiang, C. Mou, and T. Wang, “Humidity Sensor Based on a Long-Period Fiber Grating Coated with Polymer Composite Film,” Sensors 19(10), 2263 (2019). [CrossRef]
47. Y. Liu, H. Deng, and L. Yuan, “A novel polyvinyl alcohol and hypromellose gap-coated humidity sensor based on a Mach–Zehnder interferometer with off-axis spiral deformation,” Sensors and Actuators B: Chemical 284, 323–329 (2019). [CrossRef]
48. B. Ben Doudou, H. Jaouadi, and C. Dridi, “Prism coupling technique investigation of optical and thermo-optical properties of polyvinyl alcohol and polyvinyl alcohol/silica nanocomposite films,” Opt. Commun. 492, 126984 (2021). [CrossRef]
49. D. Viegas, M. Hernaez, J. Goicoechea, J. L. Santos, F. M. Araujo, F. Arregui, and I. R. Matias, “Simultaneous Measurement of Humidity and Temperature Based on an SiO_2-Nanospheres Film Deposited on a Long-Period Grating In-Line With a Fiber Bragg Grating,” IEEE Sens. J. 11(1), 162–166 (2011). [CrossRef]
50. Tang Xuemin, An Jiali, and Jin Yongxing, “Study of Humidity Sensor Based on Mach-Zehnder Interference,” Laser & Optoelectronics Progress 51 (2014).
51. M. A. Hopcroft, W. D. Nix, and T. W. Kenny, “What is the Young's Modulus of Silicon?” J. Microelectromech. Syst. 19(2), 229–238 (2010). [CrossRef]
52. J. Peng, A. P. Tomsia, L. Jiang, B. Z. Tang, and Q. Cheng, “Stiff and tough PDMS-MMT layered nanocomposites visualized by AIE luminogens,” Nat. Commun. 12(1), 4539 (2021). [CrossRef]
53. Y. Okada and Y. Tokumaru, “Precise determination of lattice parameter and thermal expansion coefficient of silicon between 300 and 1500 K,” J. Appl. Phys. 56(2), 314–320 (1984). [CrossRef]
54. R. M. Andre, S. C. Warren-Smith, M. Becker, J. Dellith, M. Rothhardt, M. I. Zibaii, H. Latifi, M. B. Marques, H. Bartelt, and O. Frazao, “Simultaneous measurement of temperature and refractive index using focused ion beam milled Fabry-Perot cavities in optical fiber micro-tips,” Opt. Express 24(13), 14053–14065 (2016). [CrossRef]
55. Y. Xu, X. Zhao, Y. Li, Z. Qin, Y. Pang, and Z. Liu, “Simultaneous measurement of relative humidity and temperature based on forward Brillouin scattering in polyimide-overlaid fiber,” Sensors and Actuators B: Chemical 348, 130702 (2021). [CrossRef]
56. P. Nie, D. Zhu, Z. Cui, F. Qu, L. Lin, and Y. Wang, “Sensitive detection of chlorpyrifos pesticide using an all-dielectric broadband terahertz metamaterial absorber,” Sensors and Actuators B: Chemical 307, 127642 (2020). [CrossRef]
57. Z. Cui, Y. Wang, Y. Shi, Y. Zhu, D. Zhang, Z. Hong, and X. Feng, “Significant sensing performance of an all-silicon terahertz metasurface chip for Bacillus thuringiensis Cry1Ac protein,” Photonics Res. 10(3), 740–746 (2022). [CrossRef]
