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SPR sensor based on exposed core micro-structured optical fiber for salinity detection with temperature self-compensation

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Abstract

A surface plasmon resonance (SPR) sensor based on exposed core micro-structured optical fiber (EC-MOF) for temperature self-compensated salinity detection is proposed. The sensing channel is fabricated by sequentially coating indium tin oxide (ITO) and Au layers at the exposed region of the fiber core. Benefiting from the large dynamic refractive index (RI) range of ITO induced by dispersion, two separated SPR peaks with equal intensity can be excited at visible spectrum by Kretschmann configuration and near-infrared spectrum by Otto configuration. The RI sensing performance at 1.33–1.39 is investigated and optimized using finite element method, with maximum wavelength sensitivities of 2000 nm/RIU and 3000 nm/RIU, respectively. The distinct RI responses of two SPR peaks make the dual-parameter demodulation realizable, which shows great potential in multiplex or self-compensated sensing applications. The temperature self-compensated salinity sensing ability is demonstrated with high sensitivity of 4.45 nm/% and a temperature compensation coefficient of −0.12%/°C. To the best of our knowledge, this is the first time temperature self-compensation of fiber SPR sensors with a single sensing channel and the single demodulation method has been realized.

© 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

1. Introduction

Salinity plays an important role in scientific researches, including chemical and biological analysis, protection of marine ecosystem, mineral exploration, health monitoring of concrete structures, etc [1]. Various methods for salinity measurement have been reported, such as CTD (conductivity, temperature, depth) devices [2], ultrasonic techniques [3], chemical procedures [4], etc. But with some issues need to consider like power supply, corrosion, safety and pollution. Fiber-optic salinity sensors based on interferometers (MMI [5], MZI [6], FPI [7]), fiber gratings (FBG [8], LPG [9]) and specific fiber structures (tapered [10], side-polished [7], U-shaped [11]), have attracted lots of attentions in recent years due to the advantages of chemically inertness, electromagnetic immunity, remote and in situ measuring capabilities. Combined with surface plasmon resonance (SPR), the salinity sensitivity can be improved more than one order of magnitude. But in practical applications, the reduced accuracy caused by temperature fluctuation cannot be neglected due to the large thermo-optic coefficient of salty solution (≈ 2×10−4 RIU/°C in seawater [12]).

To solve the problem of cross-sensitivity caused by the temperature drift in fiber-SPR sensors, two separated SPR peaks with equal intensity are necessary for the construction of multivariate equations. But regrettably, almost all of the reported works are single-channeled as only one single intense SPR band can be supported by metallic geometry [13]. Generally, extra temperature sensing structure is cascaded [1417] or paralleled [18,19] for reference, resulting in expensive, complicated and unstable sensing systems. Using Terbium (III) as the light absorber at ∼350 nm affected by temperature, Wang et al. firstly realized temperature self-compensated RI sensing by bilayer structure with one single channel [20]. But both wavelength and intensity demodulation methods are required, with promotable temperature compensation coefficient.

Conducting metal oxide (ITO) based SPR sensors is increasingly reported recently [21,22], due to its excellent properties of tunable plasmonic resonance, large dynamic RI range, high transmissivity at visible light, etc. By sequentially coating ITO and Au layers on the surface of multimode fiber, Li et al. experimentally demonstrated a dual resonance fiber SPR sensor for multichannel biological analysis [23]. Two separated SPR peaks with equal intensity supported by Kretschmann and Otto configurations providing a new way for temperature self-compensated salinity detection by solving matrix equations. However, the wavelength sensitivity of 1345 nm/RIU is limited by the phase matching problem between core mode and surface plasmon polariton (SPP) mode, which can be improved further by using micro-structure optical fiber (MOF, also called photonic crystal fiber, PCF) [24]. Especially exposed core MOF (EC-MOF) which can avoid analyte filling and facilitate metal coating [25]. In 2021, Liu et al. reported a ITO coated U-shaped photonic quasi-crystal fiber based SPR sensor, the sensitivity can reach 42000nm/RIU [26]. MOF based SPR sensors with extremely high sensitivity and better figure of merit (FOM) become a research hot-spot recently [2729].

In this work, a temperature self-compensated SPR sensor based on EC-MOF coated with ITO and Au layers is designed. The RI sensing performance at 1.33–1.39 is investigated and optimized by finite element method (FEM). Results show that the wavelength sensitivity can be improved to 3000 nm/RIU and the peak at shorter wavelength (SPR-1) exhibits lower sensitivity than that at the longer (SPR-2), but much better linearity. The wavelength, intensity, sensitivity and figure of merit (FOM) of dual SPR can be effectively tuned by adjusting the thicknesses of ITO and Au layers. The temperature self-compensation ability is demonstrated by the sensing of NaCl solutions, with wavelength sensitivity of 4.45 nm/% and temperature compensation coefficient of −0.12%/°C. This is the first time of fiber SPR sensors to realize temperature self-compensation with single sensing channel and single demodulation method to our best knowledge.

2. Design and analysis

The schematic of the EC-MOF based SPR sensor is shown in Fig. 1(a). The diameters of EC-MOF, cladding air holes and fiber core are D = 125 µm, d = 80 µm and dc = 20 µm, respectively. The thickness of core strut is t = 2 µm. The thicknesses of ITO and Au layers are tITO = 100 nm and tAu = 35 nm, respectively. The EC-MOF can be fabricated by the methods of directly drawing [30], femtosecond laser [31] or focused ion beam ablation [32] using commercial available grapefruit fiber. The ITO and Au layers can be sputtered by using the Turbo Sputter Coater as described in Ref. [23]. FEM is used in two-dimensional simulation by COMSOL Multiphysics software and the boundary condition is set as perfectly matched layers. The whole section of the sensor is divided into many triangular subdomains by self-adaption. The total number of mesh elements is 98176. The RIs of EC-MOF related to temperature T and wavelength λ can be calculated by the Sellmeier equation and the Drude model, respectively [33]. The complex dielectric function of Au can be expressed as:

$${\varepsilon _m} = {\varepsilon _{mr}} + i{\varepsilon _{mi}} = 1 - \frac{{\omega _p^2}}{{\omega (\omega + i{\omega _c})}}$$

Where ωp is the electron plasma frequency, ωc is the collision frequency, and ω is the frequency of the incident light. The temperature-dependent parameters of plasma and collision frequencies can refer to Ref. [34]. The permittivity of ITO is given by:

$$\varepsilon (\omega ) = \varepsilon - \frac{{\omega _p^2}}{{{\omega ^2} + i\omega \Gamma }}$$

 figure: Fig. 1.

Fig. 1. (a) Schematic of the designed sensor, (b) RI relationships of EC-MOF core, ITO and Au, (c) electric field intensity distribution along Y-axis at the fiber core region, (d) dispersion relations of core mode and SPP mode, electric field distribution and confinement loss.

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Where ɛ is the intraband dielectric constant, Г is the damping coefficient, ωp2 = ne2/µɛ0, µ = 0.3me, me is free electron mass, ωp = 2.19 eV and Г = 0.111 eV [21,22].

The RI relationships of EC-MOF core, ITO and Au are shown in Fig. 1(b). To clarify the excitation principle of dual SPR peaks, the electric field intensity distribution along Y-axis at the fiber core region is illustrated in Fig. 1(c). When λ < 733 nm, the RI of ITO is larger than the fiber core and Au. Incident light refracted at the interface of fiber core and ITO, then passing through ITO layer and total internal reflection (TIR) occurs at the interface of ITO and Au. SPR-1 is excited at the outer surface of the Au layer similar to Kretschmann configuration. ITO and the fiber core can be treated as effective core mode as shown in Fig. 1(c)(ii). When λ > 733 nm, the RI of ITO is larger than Au but smaller than the fiber core. TIR occurs at the interface of fiber core and ITO, the generated evanescent wave passing through ITO layer to excite SPR-2 at both surfaces of Au layer with the inner surface dominant, which is similar to Otto configuration. In this case, ITO and Au can be treated as effective surface plasmon polariton (SPP) mode as shown in Fig. 1(c)(iii). For SPR-2, the lossy mode resonance (LMR) excited by ITO can also enhance the resonance intensity [35].

The dispersion relations of core mode and SPP mode, electric field distribution and confinement loss are shown in Fig. 1(d). The confinement loss is defined as:

$${\alpha _{loss}}({dB/m} )= 8.686 \cdot \frac{{2\pi }}{\lambda } \cdot {\mathop{\rm Im}\nolimits} ({n_{eff}})$$

where Im(neff) is the imaginary part of effective RI (neff) of core mode. Due to the unsymmetrical sensing structure, core mode and SPP mode both exhibit strong birefringence which can support two orthogonal polarized SPR peaks (x-pol and y-pol) with y-pol about one order of magnitude higher than x-pol. So in the following analysis, only y-pol is considered as a higher resonance loss, a better FOM. FOM relative to the wavelength sensitivity Sλ and the full width at half maximum (FWHM) is defined as:

$$FOM = {{{S_\lambda }} / {FWHM}}$$

where Sλ can be calculated by:

$${S_\lambda }({nm/RIU} )= \frac{{\Delta {\lambda _{peak}}}}{{\Delta {n_a}}}$$

According to the mode coupling theory, two separated SPR peaks with equal intensity are excited at the point (phase matching point) where the real parts of neff (Re(neff)) of core mode and SPP mode coincide. The RI change Δna can be measured by tracking the shift of SPR peak Δλpeak.

3. Results and discussion

3.1 RI sensing performance

Before salinity detection, the RI response at 1.33–1.39 in steps of 0.01 is firstly investigated. As shown in Fig. 2(a), the transmittance Tr of SPR-1 and SPR-2 both shift to the longer wavelength with RI increasing, because the red-shift of phase matching points caused by the increased Re(neff) of SPP modes and unchanged core. Moreover, the resonance loss is transferred from SPR-2 to SPR-1 gradually, with an improving FWHM of SPR-1 while that decreasing of SPR-2.

 figure: Fig. 2.

Fig. 2. When RI increases from 1.33 to 1.39 in steps of 0.01 at tITO = 100 nm, tAu = 35 nm and L = 1 cm, (a) Tr relative to wavelength, (b) relationship between SPR wavelengths and RI.

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The phenomenon is caused by two different excitation mechanisms as described in Fig. 1. As is well-known, the phase matching of SPR requires the neff of SPP and core modes equating [24]. For SPR-1, the neff of core mode is determined by the fiber core and ITO, and the neff of SPP mode is determined by the analyte RI and Au. The gap between two modes decreases with RI increasing, leading to a stronger phase matching, then an increment of resonance loss and FWHM of SPR-1. Moreover, the red-shifting of SPR-1 reduces the RI of ITO which can also enhance the phase matching. For SPR-2, the neff of SPP mode is determined by ITO, Au and analyte RI, while the neff of core mode is nearly unchanged. The RI of ITO is decreased about 0.24 RIU with SPR-2 red-shifting when RI increases from 1.33 to 1.39 (increased 0.06 RIU). In other words, the neff of SPP mode is decreased with RI increasing, and thus a decrement of resonance loss and FWHM of SPR-2. The sensing principle of Kretschmann configuration will disappear when SPR-1 far exceeds 733 nm with only one SPR peak existed. Tr is defined as:

$${T_r} = 10\lg \left[ {\textrm{exp} \left( { - \frac{L}{\lambda } \cdot 4\pi \cdot {\mathop{\rm Im}\nolimits} ({{n_{eff}}} )} \right)} \right]$$

Where L is the length of the sensing region. The relationships between resonance wavelengths and RI are plotted in Fig. 2(b). SPR-1 exhibits much better linearity and FOM than SPR-2 but lower Sλ (maximum value) as listed in Table 1. The maximum Sλ of 3000 nm/RIU we obtained is more than two times higher than that in Ref. [23]. To realize dual-parameter demodulation, SPR-2 can be linear fit in different segments with small RI range as described in Ref. [33].

Tables Icon

Table 1. Sensing Performance of the Designed Sensor.

3.2 Effects of metal layers

The thickness of plasmonic metal layers have great influence on the designed sensor. The sensing performance with ITO thickness increasing from 80 nm to 110 nm in steps of 10 nm is investigated in Fig. 3.

 figure: Fig. 3.

Fig. 3. When tITO increases from 80 nm to 110 nm in steps of 10 nm at tAu = 35 nm and L = 1 cm, (a) Tr relative to wavelength at RI = 1.33, (b) relationship between SPR-1 wavelength and RI, (c) relationship between SPR-2 wavelength and RI.

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Two resonance peaks shift in opposite direction with SPR-1 red-shifting 9 nm and SPR-2 blue-shifting 19 nm at RI = 1.33, as shown in Fig. 3(a). For SPR-1, the Re(neff) of SPP mode is invariable with tITO increasing, but the Re(neff) of effective core mode will increase as the RI of ITO is larger than the fiber core. To satisfy the mode coupling condition i. e. Re(neff) of two modes are equal, SPR-1 will shift to the longer wavelength to reduce the RI of ITO. For SPR-2, the Re(neff) of core mode is invariable with tITO increasing, but the Re(neff) of effective SPP mode will decrease as the RI of ITO is smaller than the fiber core. To satisfy the mode coupling, SPR-2 will shift to the shorter wavelength to increase the RI of ITO. In other words, ITO works as a RI modulator here by changing wavelength to realize the balance of Re(neff) of core mode and SPP mode. Moreover, Sλ also changes conversely as shown in Fig. 3(b)-(c), with SPR-1 decreasing from 1879nm/RIU to 1711nm/RIU and SPR-2 increasing from 2700 nm/RIU to 3200 nm/RIU (maximum value). The dip losses damp gradually due to the increased light absorbtion of ITO for SPR-1 and the limited penetration depth of evanescent wave weakening the mode coupling strength for SPR-2.

The effect of Au layer thickness is also investigated with tAu increasing from 30 nm to 45 nm in steps of 5 nm. As shown in Fig. 4(a), similar with ITO increasing, SPR-1 red-shifts 17 nm and SPR-2 blue-shifts 55 nm at RI = 1.33. For SPR-1, the Re(neff) of SPP mode is decreased with tAu increasing as the RI of Au < 1.33, then SPR-1 will shift to the longer wavelength to reduce the RI of ITO for balance. For SPR-2, the Re(neff) of SPP mode is decreased as the RI of Au is smaller than ITO with unchanged core, correspondingly SPR-2 will shift to the shorter wavelength to increase the RI of ITO. The resonance loss of SPR-1 damps significantly as the core mode becomes screened from the SPP due to the limited penetration depth. The loss increment of SPR-2 is caused by the larger light absorbtion of metal layers at shorter wavelength. The relationships between resonance wavelengths and RI with different tAu is plotted in Fig. 4(b)-(c). Contrary to ITO increasing, Sλ of SPR-1 is increased 428 nm/RIU and that of SPR-2 is decreased 1100 nm/RIU (maximum value).

 figure: Fig. 4.

Fig. 4. When tAu increases from 30 nm to 45 nm in steps of 5 nm at tITO = 100 nm and L = 1 cm, (a) Tr relative to wavelength at RI = 1.33, (b) relationship between SPR-1 wavelength and RI, (c) relationship between SPR-2 wavelength and RI.

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In conclusion, a thinner ITO layer and a thicker Au layer will improve Sλ of SPR-1, conversely improve Sλ of SPR-2. But the resonance loss transformation caused by the metal layer change should be taken into consideration, as two separated SPR peaks with equal intensity are necessary for multiplex or self-compensated sensing. The fabrication tolerance should also be considered as the errors are inevitable in metal coating procedure. The maximum variations of Sλ are 3.22% and 6.67% with ±10% change in tITO, 6.21% and 9.33% with ±10% change in tAu, for SPR-1 and SPR-2, respectively.

3.3 Temperature self-compensated salinity sensing performance

The temperature self-compensated salinity sensing ability is demonstrated by the detection of NaCl solutions. To realize a higher sensitivity, the structure parameters is set as tITO = 80 nm, tAu = 50 nm and L = 1 cm. Figure 5(a) shows Tr of the sensor with salinity S increasing from 0 to 25% in steps of 5%, the resonance peaks both shift to the longer wavelength with increased resonance loss of SPR-1 and decreased resonance loss of SPR-2. The relationships between SPR wavelengths and salinity is plotted in Fig. 5(b). The fitting curves of SPR-1 can be expressed as λ1 = 4.45S+647 with correlations of 0.992. To obtain linear fit, the salinity range of SPR-2 is divided into two segments of 0–15% and 15%−25%, which can be expressed as λ2−1 = 0.66S+875 and λ2−2 = 2.10S+854 with correlations of 0.939 and 0.963, respectively. The average salinity sensitivity of 4.45 nm/% (445 pm/‰) we obtained is much higher than other fiber based salinity sensors like interferometers (< 280 pm/‰), fiber gratings (< 10 pm/‰), specific fiber structures (< 260 pm/‰) and other SPR works (< 200 pm/‰) [1].

 figure: Fig. 5.

Fig. 5. When S increases from 0 to 25% in steps of 5% at tITO = 80 nm, tAu = 50 nm and L = 1 cm, (a) Tr relative to wavelength, (b) relationship between resonance wavelengths and S for SPR-1 and SPR-2.

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The temperature response of the sensor ranging from 0 to 50 °C in steps of 10 °C is characterized in Fig. 6. Due to the negative thermo-optic coefficient of NaCl solution (−2×10−4 RIU/°C [12]), the resonance peaks exhibit converse changing trends compared with S increasing, as the RI of NaCl solution will decrease with T increasing while increase with S increasing. The average temperature sensitivities of −0.53 nm/°C and −0.20 nm/°C are obtained with correlations of 0.999 for SPR-1 and SPR-2, respectively.

 figure: Fig. 6.

Fig. 6. When T increases from 0 °C to 50 °C in steps of 10 °C at tITO = 80 nm, tAu = 50 nm and L = 1 cm, (a) Tr relative to wavelength, (b) relationship between resonance wavelengths and T for SPR-1 and SPR-2.

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The wavelength shifts of ΔλSPR-1 and ΔλSPR-2 caused by the variations of salinity ΔS and temperature ΔT can be summarized as:

$$\begin{array}{{cc}} {\left\{ \begin{array}{l} \Delta {\lambda _{SPR - 1}} = 4.45\Delta S - 0.53\Delta T\\ \Delta {\lambda _{SPR - 2}} = 0.66\Delta S - 0.20\Delta T \end{array} \right.}&{(0\, \lt \,S \lt {\rm{ }}15\% )} \end{array}$$
$$\begin{array}{*{20}{c}} {\left\{ \begin{array}{l} \Delta {\lambda _{SPR - 1}} = 4.45\Delta S - 0.53\Delta T\\ \Delta {\lambda _{SPR - 2}} = 2.10\Delta S - 0.20\Delta T \end{array} \right.}&{(15\% {\rm{ }} \lt S\, \lt \,25\% )} \end{array}$$

The dual-parameter demodulation can be realized by solving the matrix:

$$\begin{array}{{cc}} {\left[ \begin{array}{l} \Delta S\\ \Delta T \end{array} \right] = {{\left[ {\begin{array}{{cc}} {4.45}&{ - 0.53}\\ {0.66}&{ - 0.20} \end{array}} \right]}^{ - 1}}\left[ \begin{array}{l} \Delta {\lambda _{SPR - 1}}\\ \Delta {\lambda _{SPR - 2}} \end{array} \right]}&{(0\, \lt \,S \lt {\rm{ }}15\% )} \end{array}$$
$$\begin{array}{{cc}} {\left[ \begin{array}{l} \Delta S\\ \Delta T \end{array} \right] = {{\left[ {\begin{array}{{cc}} {4.45}&{ - 0.53}\\ {2.10}&{ - 0.20} \end{array}} \right]}^{ - 1}}\left[ \begin{array}{l} \Delta {\lambda _{SPR - 1}}\\ \Delta {\lambda _{SPR - 2}} \end{array} \right]}&{(15\% {\rm{ }} \lt S\, \lt \,25\% )} \end{array}$$

Combine the linear fitting equations response to S (λ1 = 4.45S+647) and T (λ1 = −0.53T+745) of SPR-1, the temperature compensation function for salinity detection can be obtained by eliminating λ1:

$$S ={-} 0.12T + 22$$

The temperature compensation coefficient is −0.12%/°C.

4. Conclusion

A new approach to realize the temperature self-compensation of EC-MOF based SPR sensor is proposed and demonstrated. The RI sensing performance is investigated and optimized by FEM with maximum wavelength sensitivities of 2000nm/RIU and 3000 nm/RIU, respectively. Results show that two SPR peaks supported by Kretschmann and Otto configurations exhibit distinct RI responses, making the dual-parameter demodulation realizable with single sensing channel and single demodulation method. The temperature self-compensation ability is demonstrated by salinity detection with high sensitivity of 4.45 nm/% and temperature compensation coefficient of −0.12%/°C. This work shows great potential in multiplex or other self-compensated sensing applications.

Funding

National Key Research and Development Program of China (2016YFE0118400); Science and Technology Research Program of Henan Province (192102310055, 202102310209); Henan Postdoctoral Science Foundation (20202025); National Natural Science Foundation of China Henan Provincial Joint Fund Key Project (U1604263); National Natural Science Foundation of China (61874099).

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. Y. Qian, Y. Zhao, Q. L. Wu, and Y. Yang, “Review of salinity measurement technology based on optical fiber sensor,” Sens. Actuators B Chem. 260, 86–105 (2018). [CrossRef]  

2. R. A. Cox, F. Culkin, and J. P. Riley, “The electrical conductivity/chlorinity relationship in natural sea water,” Deep Sea Res. Oceanogr. Abstr. 14(2), 203–220 (1967). [CrossRef]  

3. V. Noto and M. Mecozzi, “Determination of seawater salinity by ultraviolet spectroscopic measurements,” Appl. Spectrosc. 51(9), 1294–1302 (1997). [CrossRef]  

4. F. Stevenson, D. Sparks, A. Page, P. Helmke, R. Loeppert, P. Soltanpour, M. Tabatabai, C. T. Johnston, and M. Sumner, “Nitrogen-organic forms: methods of soil analysis,” in Methods of Soil Analysis: Part 3 Chemical Methods (Soil Science Society of America1996), pp. 1185–1200.

5. Q. Q. Meng, X. Y. Dong, K. Ni, Y. Li, B. Xu, and Z. M. Chen, “Optical fiber laser salinity sensor based on multimode interference effect,” IEEE Sens. J. 14(6), 1813–1816 (2014). [CrossRef]  

6. Y. P. Liao, J. Wang, S. S. Wang, H. J. Yang, and X. Wang, “Simultaneous measurement of seawater temperature and salinity based on microfiber MZ interferometer with a knot resonator,” J. Lightwave Technol. 34(23), 5378–5384 (2016). [CrossRef]  

7. J. R. Guzman-Sepulveda, V. I. Ruiz-Perez, M. Torres-Cisneros, J. J. Sanchez-Mondragon, and D. A. May-Arrioja, “Fiber optic sensor for high-sensitivity salinity measurement,” IEEE Photonics Technol. Lett. 25(23), 2323–2326 (2013). [CrossRef]  

8. Q. Men, P. Lu, and Q. Y. Chen, “A multiplexed fiber Bragg grating sensor for simultaneous salinity and temperature measurement,” J. Appl. Phys. 103(5), 053107 (2008). [CrossRef]  

9. G. R. C. Possetti, R. C. Kamikawachi, C. L. Prevedello, M. Muller, and J. L. Fabris, “Salinity measurement in water environment with a long period grating based interferometer,” Meas. Sci. Technol. 20(3), 034003 (2009). [CrossRef]  

10. X. Wang, J. Wang, S. S. Wang, and Y. P. Liao, “Fiber-optic salinity sensing with a panda-microfiber-based multimode interferometer,” J. Lightwave Technol. 35(23), 5086–5091 (2017). [CrossRef]  

11. D. Z. Stupar, J. S. Bajić, A. V. Joža, B. M. Dakić, M. P. Slankamenac, M. B. Živanov, and E. Cibula, “Remote monitoring of water salinity by using side-polished fiber-optic U-shaped sensor,” 15th International Power Electronics and Motion Control Conference, LS4c.4–1–LS4c.4–5 (2012).

12. L. M. Zhao, Z. He, H. R. Huang, Y. C. Cheng, and B. J. Yun, “Relationship between the refractive index of seawater and salinity, temperature,” China Modern Educational Equipment 321, 49–51 (2019).

13. J. Zhu, J. J. Li, and J. W. Zhao, “Obtain quadruple intense plasmonic resonances from multilayered gold nanoshells by silver coating: application in multiplex sensing,” Plasmonics 8(3), 1493–1499 (2013). [CrossRef]  

14. B. Li, X. Yan, X. N. Zhang, F. Wang, S. G. Li, T. Suzuki, Y. Ohishi, and T. Cheng, “No-core optical fiber sensor based on surface plasmon resonance for glucose solution concentration and temperature measurement,” Opt. Express 29(9), 12930–12940 (2021). [CrossRef]  

15. E. Siyu, Y. -N. Zhang, B. Han, W. L. Zheng, Q. L. Wu, and H. K. Zheng, “Two-channel surface plasmon resonance sensor for simultaneous measurement of seawater salinity and temperature,” IEEE Trans. Instrum. Meas. 69(9), 7191–7199 (2020). [CrossRef]  

16. M. D. C. Alonso-Murias, J. S. Velázquez-González, and D. Monzón-Hernández, “SPR fiber tip sensor for the simultaneous measurement of refractive index, temperature, and level of a liquid,” J. Lightwave Technol. 37(18), 4808–4814 (2019). [CrossRef]  

17. P. H. Zhang, B. Y. Lu, Y. W. Sun, H. X. Yu, K. X. Xu, and D. C. Li, “Side-polished flexible SPR sensor modified by graphene with in situ temperature self-compensation,” Biomed. Opt. Express 10(1), 215–225 (2019). [CrossRef]  

18. S. N. Wu, Q. Tan, E. Forsberg, S. Q. Hu, and S. L. He, “In-situ dual-channel surface plasmon resonance fiber sensor for temperature-compensated detection of glucose concentration,” Opt. Express 28(14), 21046–21061 (2020). [CrossRef]  

19. Y. Zhao, Q. L. Wu, and Y. N. Zhang, “Theoretical analysis of high-sensitive seawater temperature and salinity measurement based on C-type micro-structured fiber,” Sens. Actuators B Chem. 258, 822–828 (2018). [CrossRef]  

20. Q. Wang, J. Y. Jing, X. Z. Wang, L. Y. Niu, and W. M. Zhao, “A D-shaped fiber long-range surface plasmon resonance sensor with high Q-factor and temperature self-compensation,” IEEE Trans. Instrum. Meas. 69(5), 2218–2224 (2020). [CrossRef]  

21. J. N. Dash and R. Jha, “SPR biosensor based on polymer PCF coated with conducting metal oxide,” IEEE Photonics Technol. Lett. 26(6), 595–598 (2014). [CrossRef]  

22. T. Y. Huang, “Highly sensitive SPR sensor based on D-shaped photonic crystal fiber coated with indium tin oxide at near-infrared wavelength,” Plasmonics 12(3), 583–588 (2017). [CrossRef]  

23. L. X. Li, Y. Z. Liang, J. Y. Guang, W. L. Cui, X. P. Zhang, J. Masson, and W. Peng, “Dual Kretschmann and Otto configuration fiber surface plasmon resonance biosensor,” Opt. Express 25(22), 26950–26956 (2017). [CrossRef]  

24. A. Hassani and M. Skorobogatiy, “Design of the microstructured optical fiber-based surface plasmon resonance sensors with enhanced microfluidics,” Opt. Express 14(24), 11616–11621 (2006). [CrossRef]  

25. X. G. Li, L. V. Nguyen, M. Becker, H. Ebendorff-Heidepriem, D. Pham, and S. C. Warren-Smith, “Simultaneous measurement of temperature and refractive index using an exposed core microstructured optical fiber,” IEEE J. Sel. Top. Quant. 26(4), 1–7 (2020). [CrossRef]  

26. Q. Liu, Y. Jiang, Y. D. Sun, C. J. Hu, J. D. Sun, C. Liu, J. W. Lv, J. Zhao, Z. Yi, and P. K. Chu, “Surface plasmon resonance sensor based on U-shaped photonic quasi-crystal fiber,” Appl. Opt. 60(6), 1761–1766 (2021). [CrossRef]  

27. S. N. An, Y. Shi, Z. Yi, C. Liu, T. Sun, J. W. Lv, L. Yang, and P. K. Chu, “Ultra-short dual-core GaAs photonic crystal fiber splitter filled with nematic liquid crystal,” Opt. Eng. 60(05), 056104 (2021). [CrossRef]  

28. Z. H. Chen, H. Chen, J. K. Yin, R. Y. Zhang, H. Jile, D. Y. Xu, Z. Yi, Z. G. Zhou, S. S. Cai, and P. G. Yan, “Multi-band, tunable, high figure of merit, high sensitivity single-layer patterned graphene—perfect absorber based on surface plasmon resonance,” Diam. Relat. Mater. 116, 108393 (2021). [CrossRef]  

29. Y. Deng, G. T. Cao, H. Yang, X. Q. Zhou, and Y. W. Wu, “Dynamic control of double plasmon-induced transparencies in aperture-coupled waveguide-cavity system,” Plasmonics 13(1), 345–352 (2018). [CrossRef]  

30. S. C. Warren-Smith, H. Ebendorff-Heidepriem, T. C. Foo, R. Moore, C. Davis, and T. M. Monro, “Exposed-core microstructured optical fibers for real-time fluorescence sensing,” Opt. Express 17(21), 18533–18542 (2009). [CrossRef]  

31. A. van Brakel, C. Grivas, M. N. Petrovich, and D. J. Richardson, “Micro-channels machined in microstructured optical fibers by femtosecond laser,” Opt. Express 15(14), 8731–8736 (2007). [CrossRef]  

32. C. Martelli, P. Olivero, J. Canning, N. Groothoff, B. Gibson, and S. Huntington, “Micromachining structured optical fibers using focused ion beam milling,” Opt. Lett. 32(11), 1575–1577 (2007). [CrossRef]  

33. X. C. Yang, L. Q. Zhu, Y. Lu, and J. Q. Yao, “Ultrasharp LSPR temperature sensor based on grapefruit fiber filled with a silver nanoshell and liquid,” J. Lightwave Technol. 38(7), 2015–2021 (2020). [CrossRef]  

34. C. S. Moreira, A. M. N. Lima, H. Neff, and C. Thirstrup, “Temperature-dependent sensitivity of surface plasmon resonance sensors at the gold–water interface,” Sens. Actuators B Chem. 134(2), 854–862 (2008). [CrossRef]  

35. Q. Wang and W. M. Zhao, “A comprehensive review of lossy mode resonance-based fiber optic sensors,” Opt. Laser. Eng. 100, 47–60 (2018). [CrossRef]  

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.

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Figures (6)

Fig. 1.
Fig. 1. (a) Schematic of the designed sensor, (b) RI relationships of EC-MOF core, ITO and Au, (c) electric field intensity distribution along Y-axis at the fiber core region, (d) dispersion relations of core mode and SPP mode, electric field distribution and confinement loss.
Fig. 2.
Fig. 2. When RI increases from 1.33 to 1.39 in steps of 0.01 at tITO = 100 nm, tAu = 35 nm and L = 1 cm, (a) Tr relative to wavelength, (b) relationship between SPR wavelengths and RI.
Fig. 3.
Fig. 3. When tITO increases from 80 nm to 110 nm in steps of 10 nm at tAu = 35 nm and L = 1 cm, (a) Tr relative to wavelength at RI = 1.33, (b) relationship between SPR-1 wavelength and RI, (c) relationship between SPR-2 wavelength and RI.
Fig. 4.
Fig. 4. When tAu increases from 30 nm to 45 nm in steps of 5 nm at tITO = 100 nm and L = 1 cm, (a) Tr relative to wavelength at RI = 1.33, (b) relationship between SPR-1 wavelength and RI, (c) relationship between SPR-2 wavelength and RI.
Fig. 5.
Fig. 5. When S increases from 0 to 25% in steps of 5% at tITO = 80 nm, tAu = 50 nm and L = 1 cm, (a) Tr relative to wavelength, (b) relationship between resonance wavelengths and S for SPR-1 and SPR-2.
Fig. 6.
Fig. 6. When T increases from 0 °C to 50 °C in steps of 10 °C at tITO = 80 nm, tAu = 50 nm and L = 1 cm, (a) Tr relative to wavelength, (b) relationship between resonance wavelengths and T for SPR-1 and SPR-2.

Tables (1)

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Table 1. Sensing Performance of the Designed Sensor.

Equations (11)

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ε m = ε m r + i ε m i = 1 ω p 2 ω ( ω + i ω c )
ε ( ω ) = ε ω p 2 ω 2 + i ω Γ
α l o s s ( d B / m ) = 8.686 2 π λ Im ( n e f f )
F O M = S λ / F W H M
S λ ( n m / R I U ) = Δ λ p e a k Δ n a
T r = 10 lg [ exp ( L λ 4 π Im ( n e f f ) ) ]
{ Δ λ S P R 1 = 4.45 Δ S 0.53 Δ T Δ λ S P R 2 = 0.66 Δ S 0.20 Δ T ( 0 < S < 15 % )
{ Δ λ S P R 1 = 4.45 Δ S 0.53 Δ T Δ λ S P R 2 = 2.10 Δ S 0.20 Δ T ( 15 % < S < 25 % )
[ Δ S Δ T ] = [ 4.45 0.53 0.66 0.20 ] 1 [ Δ λ S P R 1 Δ λ S P R 2 ] ( 0 < S < 15 % )
[ Δ S Δ T ] = [ 4.45 0.53 2.10 0.20 ] 1 [ Δ λ S P R 1 Δ λ S P R 2 ] ( 15 % < S < 25 % )
S = 0.12 T + 22
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