In this paper, a fiber-optic temperature sensing system, based on surface plasmon resonance (SPR) and integrated with a smart-phone platform, is proposed and demonstrated. The sensing system is composed of a side-polished-fiber-based SPR sensor, which is illuminated by the LED flash from one end, and the output signals are recorded and processed by the camera and a designed application in the smart-phone. The sensing performance is evaluated by immersing the sensor in distilled water under different temperatures. Experimental results show that the measurement resolution of the proposed temperature sensor can reach 0.83°C in the range from 30 to 70°C, corresponding to a linear correlation coefficient of 0.9798. The low-cost and portable fiber optic SPR sensor based on a smart-phone platform has wide application potentials in the fields of health-care, environmental monitoring, etc.
© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
Surface plasmon resonance (SPR) is a physical phenomenon occurring at the interface between metal and dielectric medium, when the momentum-matching condition is satisfied for the light wave and the surface plasmon wave [1,2]. Because the surface plasmon wave is highly-sensitive to the change of the refractive index (RI) in the vicinity of the metal surface [3–5], SPR has served as a rapid, label-free, and real-time sensing technology in the biochemical analysis, food inspection, and environmental monitoring [6,7]. On the other hand, most of the materials naturally have the thermo-optical effect, that is, the RI of material varies with the temperature, which offers a way for temperature sensing by integrating an SPR sensor with thermo-optical material . Up to date, various temperature sensors have been developed based on this scheme. For example, Luan et al. filled the holes of a photonic crystal fiber (PCF) with liquid mixtures of ethanol and chloroform, and achieved a temperature sensitivity of 4 nm/°C in the range of −4 to 15°C . Zhao et al. immersed a fiber SPR sensor into alcohol to realize a temperature sensitivity of 1.57 nm/°C for the temperature ranging from 35 to 70°C . Liu et al. proposed a liquid-filled PCF-SPR temperature sensor, which has a sensitivity of 3.08 nm/°C for the temperature range of 0 to 100°C . Lu et al. realized temperature detection by filling liquid crystal into hollow optical fiber with gold-coated inner wall. In the temperature range from 20 to 34.5°C, the temperature sensitivity of the sensor can reach 4.72 nm/°C . Zhao et al. proposed an SPR sensor based on all-solid D-shaped PCF, which shows a simultaneous measurement capability to refractive index and temperature with a sensitivity of 4.22 nm/°C . It can be found from the above studies that fiber SPR sensor has its own unique advantages for temperature measurement, such as high sensitivity, small size, and anti-electromagnetic interference, etc. However, the aforementioned reports all require the bulky and expensive equipment including spectrometer and broad band light source, which hinders the applications in practice.
In recent years, smart-phones have experienced a significant development in the user scale and the functions, which promotes smart-phones from the initial communication tools to versatile platforms for processing, storing, and exchanging of various information and data. The LED flash, camera, and microprocessor embedded in a smart-phone can perfectly serve as the light source, optical detector, and processing system for a typical optical sensing system. Especially, when applied in the optical fiber sensing system, the LED flash and camera can be easily connected via a fiber. Preechaburana et al. proposed a smart-phone based angle-modulated SPR instrument to detect β2M macroglobulin . Gallegos et al. developed a PCF-SPR biosensor based on a smart-phone . Kort Bremer et al. reported a smart-phone based fiber SPR sensing system, and obtained a sensitivity of 5.96×10−4 RIU/pixel (RIU: refractive index unit) . Hasan Gunera et al. demonstrated a smart-phone-based SPR imaging platform for high-throughput biological detection . Liu et al. proposed a dual-channel optical fiber SPR refractive index sensing system based on a smart-phone, achieving a measurement resolution of 5.3×10−4 RIU in the RI range of 1.325 to 1.33 RIU . Although, smart-phone based SPR sensing applications have been demonstrated in both refractive index and bio-chemical sensing, the effect of temperature on the sensing system has not been considered yet.
In this paper, a portable optical fiber SPR temperature sensor based on smart-phone platform is proposed and demonstrated. The results show that the proposed sensor has a temperature response sensitivity of −0.0018 a.u./°C with a linearity coefficient of 0.9798 and a measurement resolution of 0.83°C. The proposed sensor, possessing the advantages in portability, miniaturization, and ease to integrate, may find great potential applications in the all-optical sensing network or Internet of Things.
2. Sensing system and principle
The schematic diagram of the proposed sensing platform and the sectional view of the sensor are depicted in Figs. 1(a) and 1(b), respectively. A convex lens and a narrow-band filter are used to collimate and filter the light from the flash LED to the fiber sensor. The fiber SPR sensor is fabricated by side-polishing a multi-mode fiber (MMF) and depositing a gold film on the polished surface.
Figure 1(c) illustrates the transmission spectra of the fiber SPR sensor, which are obtained by measurement and shown here to illustrate the sensing principle. The absorption dip caused by the plasmon resonance will shift when the ambient temperature changes, due to the thermo-optical effect thus the RI change of the surrounding media. Therefore, the temperature can be determined by tracing the resonance wavelength shift. On the other hand, when the incident light is fixed at a filtered wavelength, the intensity of the output light will change with temperature, because the temperature-induced spectral shift results in the transmission change at a fixed wavelength, as shown in Fig. 1(c). Such that, an intensity-modulated SPR sensing system based on a smart-phone can be easily constructed for temperature sensing application.
3. Sensor fabrication and system construction
The fabrication of optical fiber SPR sensor can be divided into two steps: side-polishing optical fiber and depositing gold film. A piece of MMF (MM-S105/125, Nufern, USA) was first coarsely polished by a homemade wheel-polishing system for ∼4 min, and then finely polished for ∼150 min to obtain the desired residual fiber thickness. Then, a chromium adhesion layer (∼5 nm) and a gold film (∼50 nm) were successively vacuum evaporated onto the surface of the polished region. The microscope images of the flat and transitional areas of the side-polished fiber are shown in Figs. 2(a) and 2(b), respectively. An optical microscope (Zeiss Axio, Scope A1) and a scanning electron microscope were used to characterize the longitudinal and sectional profiles of the polished fiber, respectively. As shown in Figs. 2(c) and 2(d), the polished length is ∼12.5 mm with a flat region of ∼6.5 mm and two transition regions of ∼3 mm in length, and the mean residual fiber thickness is ∼72.29 µm by averaging the measured data in the flat region.
The fabricated fiber SPR sensor is shown in Fig. 3(a). In order to improve the mechanical strength of the device, the side-polished segment is fixed onto a glass slide, with the polished surface facing upward. The lens and filter used in the sensing system are encapsulated in a customized phone case, whose 3D model is shown in Fig. 3(b) and the real object is fabricated by the 3D printing technology. The two ends of the SPR sensor are aligned to the flash-light and the camera at the back side of the smart-phone through the measurement channel (MC), and another piece of ordinary MMF without any modification is assembled through the reference channel (RC) to monitor the light intensity of the LED flash.
An Android-system-based application program was developed to control the camera, analyze the recorded images, and present the results. Figure 3(c) shows the interface of the application. The two light spots launched from fibers, corresponding to the RC and MC respectively, are imaged by the camera, and their intensities are converted to gray values for the further process. Because the intensity at each pixel corresponds a gray value between 0 and 255 indicating its brightness, the light intensity of an image can be calculated by summing the gray values of all the pixels inside the spot. Considering the unstable luminous power of LED flash during the experiment, we employed the relative gray value (IR) to effectively eliminate errors from the power fluctuations of the LED flash. The relative gray value is calculated by IR=Im/Ir, where Im and Ir are the gray values of the two light spots from the MC and RC, respectively. The data of each measurement can be calculated, displayed, stored, and shared by simply touching the corresponding buttons in the interface.
4. Experimental results
After a comprehensive comparison of the sensitivity and linear correlation coefficient at different wavelengths, a narrowband filter with a central wavelength of 630 nm was selected for this experiment. The schematic diagram of the fiber SPR temperature sensing experimental setup based on smart-phone is shown in Fig. 3(d). The section of the SPR sensor was immersed in distilled water, and the temperature of the water was monitored in real time using a thermometer. During the experiment, the response of the SPR sensor was recorded by the camera of the smart-phone, at different temperatures with a step of 5°C.
The images of the light spots recorded by the camera are shown in Fig. 4(a). For each temperature, we repeated three tests corresponding three recorded images, which are marked with 1st, 2nd, and 3rd. In each image, the left and right light spots are from the RC and MC, respectively. From Fig. 4(a), we can see that with the increase of temperature, the light spot from the RC remains unchanged in its brightness, but that from the MC becomes darker. Converting the brightness of an image to a certain gray value through the developed application, we can obtain the dependences of the gray values from the RC and MC on temperature, as shown in Figs. 4(b) and 4(c), respectively. It can be seen that the RC gray value only has a tiny fluctuation from 88 to 89 in arbitrary unit, while MC gray value consistently decreases with the temperature increasing from 30 to 70°C. This is because the fiber in RC is without any modification but the fiber SPR sensor in MC is immersed in water with a relatively-large negative thermo-optical coefficient, the increase of temperature will lead to the blue shift of the transmission spectrum, thus the decrease of the light intensity at the filtered wavelength 630 nm, which will be shown in the next section. Figure 4(d) shows the relationship between the temperature and the relative gray value. The fitting linearity coefficient of 0.9798 indicates the proposed SPR sensor system has a good linear temperature response with a sensitivity of −0.0018 a.u./°C. The measurement resolution can be calculated by the equation of R = abs(σ/S) , where S is the sensitivity and σ (∼0.0015, in our case) is the standard deviation of the relative grayscale, which is statistically obtained by repeating the measurement for 10 times at the same condition. Therefore, the measurement resolution for the sensing system is 0.83°C.
5. Comparison and discussions
Two groups of control experiments were performed to eliminate the influence of temperature on optical fiber. Here, the fiber SPR sensor in MC is replaced with an ordinary multi-mode fiber without any modification and a side-polished fiber without gold deposition, respectively. Following the same measurement procedure in section 4, we can obtain the relative gray value depending on temperature for the control experiments, as shown in Fig. 5. It is indicated that the temperature has little effect on multi-mode fiber and uncoated side-polished fiber, which confirms the key role of the SPR in measuring the thermo effect of the surrounding medium in a highly sensitive manner.
An experiment was also carried out for the comparison to the conventional fiber SPR system. The transmission spectra of the sensor at different temperatures were also measured by connecting the two ends of the sensor to a broad-band light source and a spectrometer, respectively, as shown in Fig. 6(a). The spectral response of the SPR sensor was recorded by the spectrometer in the temperature range from 30 to 70°C with a step of 5°C, and the results are presented in Fig. 6(b). As we can see, the resonance wavelength of SPR sensor exhibits a blue shift when the temperature gradually increases. This phenomenon can be explained by the decrease of the RI of water resulted from the increase of temperature, because the water has a negative thermo-optical coefficient about −1.0×10−4 RIU/°C . Considering the RI sensitivity 2242.4 nm/RIU for the SPR sensor and the temperature change of 40°C (from 30 to 70°C), we can also theoretically calculate the total shift of resonant wavelength as 8.97 nm, which is close to the 9.65 nm shift (from 666.21 to 656.56 nm) obtained by measurement.
Then, the resonance wavelength depending on temperature is plotted and their linear fitting is also shown in Fig. 6(c). A linear equation can be obtained by linear fitting: y=−0.24x + 673.14, that is, the sensitivity of the fiber SPR sensor to temperature is −0.24 nm/°C, which seems to be lower than those obtained in some other works [10–12], and it can be well explained by the lower RI and thermo-optical coefficient of water than ethanol or liquid crystal, etc. We further picked out the transmittance at six wavelengths, i.e. 600, 610, 620, 630, 640, and 650 nm, depending on temperature, and plotted them in Fig. 6(d). At the six wavelengths, the linear fitting slopes are −0.00136, −0.00145, −0.00147, −0.00138, −0.00121, and −0.00096, corresponding to the linearity coefficients 0.9740, 0.9751, 0.9720, 0.9775, 0.9620 and 0.9364, respectively. Table 1 presents the comparison between the smart-phone and conventional spectrometer-based platform, which shows that the smart-phone based sensing platform has the better performance in both the sensitivity and the correlation coefficient than the conventional spectrometer-based platform.
In the present work, the temperature range of the sensor is mainly limited by the freezing and boiling points of water. Therefore, the maximum temperature range is 0-100°C, and the sensor is characterized in the range of 30-70°C. In fact, through carefully choosing or designing the thermal-optical materials, the temperature range can be adjusted or extended to favor the demand of various applications. For example, employing the polydimethylsiloxane as the thermal-optical material can extend the temperature upper limit over 100°C , or adopting a liquid mixture of ethanol and chloroform to lower the temperature limit down to −4°C .
A portable optical fiber SPR temperature sensing platform based on a smart-phone is proposed and demonstrated. The experimental results show that the proposed sensor system has a sensitivity of −0.0018 a.u./°C in the range of 30 to 70°C with the linear correlation coefficient of 0.9798, respectively. The sensitivity of the optical fiber SPR sensing platform based on smart-phone can be comparable to or even better than that of the traditional optical fiber SPR sensing platform. More importantly, the smart-phone-based sensing system proposed in this paper has the advantages of miniaturization and low cost, which will make it an important candidate for a portable and smart thermometer in a diverse of applications.
National Natural Science Foundation of China (61575084, 61705087, 61805108); Science and Technology Planning Project of Guangdong Province (2014B010117002, 2017A010101013); Science & Technology Project of Guangzhou (201605030002, 201704030105, 201707010500, 201807010077); Joint Fund of Pre-research for Equipment, Ministry of Education of the People's Republic of China (6141A02022124); Fundamental Research Funds for the Central Universities (21617332, 21618404).
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