Open Access
Add to BibSonomy
Abstract
An ultrahigh sensitive optical fiber sensor for trace detection of Cu2+ concentration in aqueous solution with temperature calibration has been developed in this article. Based on the intermodal interference, the sensor is coated with a hydrogel sensing membrane with specific binding to Cu2+ on the no-core fiber/single mode fiber/no-core fiber structure by using our new spray coating method. The imidazole group in the sensing film combines with Cu2+ to produce chelation, which changes the refractive index of the sensing film. The Cu2+ at trace concentration can be detected by monitoring the displacement of the interference trough. The experimental limit of detection of 3.0×10−12 mol/L can be achieved with the spectral resolution of 0.02 nm. The sensor has also long-term stability of the concentration measurement with the average standard deviation of 1.610×10−12 mol/L over 2 hours observation time and can be compensated the influence of ambient temperature on concentration detection by conducting the temperature calibration. In addition, the sensor has the advantages of strong specificity, simple fabrication and low cost.
© 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
1. Introduction
Copper is one of the first heavy-metal elements discovered by human beings. It is an essential trace element in the body and plays a key role in many transfer proteins, such as laccase, ascorbate oxidase, and ceruloplasmin [1]. Copper has also been widely used in machinery manufacturing, construction industry, national defense industry, etc. However, improper treatments of industrial wastewater and the construction industry have caused serious pollution over maximum allowable concentration of Cu2+ in environmental soil [2]. Once a human body ingests excessive copper ions, they will cause the imbalances of proteins, lipids and nucleic acids in the body. In severe cases, it may even lead to neurodegenerative disease, cystic fibrosis and Menkes disease [3–5]. Therefore, the accurate detection of Cu2+ concentration is of great significance to many fields such as medical monitoring. The development of a low consumption, high efficiency and environmental protection detection method is also the goal that people have been pursuing. With unremitting efforts of researchers, various methods have been proposed to detect Cu2+, such as fluorescence spectrometry [6–8], electrochemical method [9,10], photothermal effect method [11], colorimetric method [12,13], and surface plasmon resonance (SPR) method [14]. All of these methods can effectively detect the concentration of Cu2+. However, the first four methods require more chemical reagents which is easy to cause the risk of pollution. Their experimental steps are also complicated and detection processes take a long time. The SPR method with good detection sensitivity requires precious metal materials such as gold, and the manufacturing process of the sensor is complex. Besides, all of the methods are hardly applicable to remote online monitoring. Therefore, it is necessary to develop a sensor with low detection limit and low production cost, and remote online.
Because of its advantages of insensitivity to electromagnetic interference, light weight, large bandwidth, corrosion resistance, and easy to realize multiband or distributed remote sensing [15], fiber optic sensors have been widely used in detections of temperature [16,17], humidity [18], refractive index [19–21] and gas [22]. In recent years, the field of heavy metal ions detection has become a hotspot. P. V. N. Kishore et al. reported the method based on fiber Bragg grating coated hydrogel to detect Cr(VI) with the detection limit around 0.83 ppb [23]. Li et al. proposed a new double-fluorescent-encapsulated hydrogel microsphere sensor to detect Al3+ and Hg2+ with the detection limit of 1.20×10−8 mol/L [24]. But at the same time, the cross-sensitivity of temperature is an important factor that cannot be avoided in the above sensor schemes. In order to compensate the influence of temperature, our team proposed a novel sensor based on Fresnel reflection for the detection of Cd2+ with temperature self-compensation and with the measurement limit was only 4.9×10−7 mol/L [25].
In this paper, we propose a new optical fiber sensor based on the principle of the intermodal interference involving in the specific hydrogel layer. The variation of Cu2+ concentration is quantitatively analyzed from the displacement of interference trough caused by refractive index change. Theoretical background and experimental realization are introduced in detail, and the feasibility of the scheme is verified. This is, to the best of our knowledge, the first time that the principle of mode-interference fiber sensing combined with specifically-sensitive hydrogel is used to detect Cu2+ concentration in aqueous solution with trace detection level, by using the Mach-Zehnder Interference (MZI) interferometer. The new spray coating method can improve the efficiency and quality of the coating greatly. It also simplifies the manufacturing process of the sensor and reduces the cost. The long-term stability and good specificity of the sensor are proved from stability and ionic interference experiments. Temperature calibration is realized by cascading a fiber Bragg grating (FBG). It has a good application prospect for the preparation of portable sensor with proper circuit design and packaging optimization.
2. Experimental apparatus and sensing principle
2.1 Experimental apparatus
Figure 1(a) shows the experimental setup for measuring Cu2+ concentration in aqueous solution, and Fig. 1(b) is the structural diagram of the Cu2+ sensing part. The broadband light source (Lightcomm company, ASE-C + L) operates in telecom C + L-band of wavelength region with the total power of 10 dB, and the optical spectrum analyzer (Yokogawa, AQ6370) is of the spectral resolution of 0.02 nm and power region from -90 dB to 20 dB in the wavelength range from 600 nm to 1700 nm. The programmable temperature controller (JieXin Testing Equipment Co., Ltd., J-TOPH-22-B) is of the temperature accuracy of ± 0.4°C and the relative humidity accuracy of ± 3%. During the experiments, the temperature was always kept constant at 24.0°C. The Cu2+ sensing part and the cascaded FBG were placed in the solution to avoid the difference of temperature between the air and the water solution. Moreover, the sensor is 10 cm with FBG and is 7 cm without FBG.
2.2 Working principle of sensor
As shown in Fig. 1(b), the cladding of the single mode fiber (SMF) in the middle was partly corroded with hydrofluoric acid and was coated with a layer of hydrogel as the sensing film (the orange area in figure). Undergoing the Bragg reflection of the FBG, the light of the source passes through the input SMF, and enters the first segment of no-core fiber (NCF). Then the light is split and stimulated simultaneously into the core mode and cladding mode in the etched SMF with sensing film. The phase difference between the two modes is caused from their different propagation constants. The two modes are combined in the second segment NCF, and finally, the interferometric light from the output SMF is received by the spectrometer for analysis.
Hydrogel is a kind of deformable material with strong adaptability, biocompatibility and reusability. The basic functional groups of hydrogels determine their swelling ability and specificity. In order to achieve the purpose of detecting the concentration of Cu2+, the hydrogel sensing membrane must contain functional groups which are extremely sensitive or specific to copper ions. Therefore, we chosed N-vinyl imidazole (NVI) as the functional monomer, and combined with polymer acrylamide (AM) and cross-linking agent N, N’ -Methylene-bisacrylamide (BIS) to prepare the hydrogel we needed. The polymer network of hydrogel can form complex with Cu2+. Adding Cu2+ will cause the change of polymer ion density, thus affecting the crosslinking degree of hydrogels. Our hydrogel polymer chains contain a large amount of imidazolium, which is easy to form a stable planar quadrangular coordination structure with Cu2+ to produce chelation [26]. Therefore, Cu2+ is bound to the gel wall, resulting in increased degree of hydrogel cross-linking and hydrogel contraction. On the other hand, when the Cu2+ forms a coordination complex with the imidazole group, the water molecules in the Cu2+ hydration shell will also cause the hydrogel to shrink, which will change the refractive index of the hydrogel sensing film and cause the movement of the interference spectrum. In addition, its refractive index is also affected by the ambient temperature, so the temperature cross sensitivity must be considered in the experiment.
The light intensity of $\; {I_{out}}$ transmitted from a splicing-type Mach-Zehnder interference structure can be expressed as follows:
Where ${I_1}$, $\; {I_2}$ are the core mode intensity of the middle SMF and the cladding mode intensity of the hydrogel sensing membrane respectively.$\; \Delta \varphi $ is the phase difference between the two beams, as given below:
the $\lambda $ is the wavelength of transmitted light and the L is the physical length of the middle SMF piece. For $\Delta \varphi = ({2m + 1} )\pi $, interference cancellation occurs. The m-th interference trough ${\lambda _m}$ can be expressed as:From Eq. (3), where$n_{eff}^{cor}$ and $n_{eff}^{cla}$ are effective refractive indices of the core-mode and the cladding-mode of the middle SMF coated with the sensing membrane, respectively. The C is the concentration of the Cu2+solution, and T is the ambient temperature. One can get the wavelength shift $\Delta {\lambda _m}$ from the equation below:
where ${\lambda _m}({0,{T_0}} )$ represents the wavelength of the interference trough at zero-concentration of the Cu2+solution and the reference temperature of ${T_0}$. Because the concentration of Cu2+ solution is very low (10−11∼10−10mol/L) and the temperature cross sensitivity exists, the effective refractive indices of $n_{eff}^{cor}$ and $n_{eff}^{cla}$ can be expanded as the Taylor series as follows:By combining the Eq. (7) and Eq. (8), it gives:
From Eq. (9), the wavelength shift of $\Delta {\lambda _m}$ is proportional to the concentration of Cu2+ and has a quadratic relationship with temperature.
3. Preparation and materials
Acrylamide (AM, 99%), N, N’-Methylene-bisacrylamide (BIS), N-vinyl imidazole (NVI), 2, 2'-Azobis (2-methylpropionamidine) dihydrochloride (AIBA·2HCL), Hydrofluoric acid (40%) and CuCl2 were purchased from Shanghai Macklin Biochemical Co., Ltd. All materials were of analytical pure. The fibers we used include standard single-mode fiber (8.2/125 µm) and coreless fiber (125 µm), which were purchased from Wuhan Changfei optical cable Co., Ltd.
3.1 Preparation of the hydrogel
On the basis of previous work [25], we optimized the preparation process. In order to prepare the hydrogel sensing film, we used 4.620 g AM and 2.717 ml NVI as functional monomers, 0.771 g BIS as crosslinking agent and 0.030 g AIBN-2HCl as ultraviolet (UV) initiator. All of them were dissolved in a certain amount of 1.800 ml deionized water. In order to initiate polymerization, it was continuously stirred for 4 hours at constant temperature (24°C). After the preformed liquid was clear and transparent, nitrogen was added continuously for 10 minutes to remove the oxygen in the preformed liquid. At this moment, the state of the solution is relatively dilute. In order to facilitate coating, the preformed liquid was properly irradiated with 270 mW/cm2 UV light for 10 minutes to improve its viscosity (the dynamic viscosity is about 20 cp) and stored in dark environment at constant temperature (24°C). The temperature and UV irradiation time should be strictly controlled, otherwise it will cause implosion.
3.2 Preparation of copper (II) ion solutions
Through calculation, a proper amount of CuCl2 is dissolved in a certain amount of deionized water to prepare mother liquor. And then a very low concentration copper ion solution was prepared by continuously diluting the mother liquor in a volumetric flask (all deionized water was obtained from ultrapure water system).
3.3 Sensor fabrication and corrosion
In this study, the SMF has no inter mode dispersion and has weak temperature sensitivity, so we used it as the sensing part. Firstly, the coating layer on the fiber surface was removed with a special fiber stripping clamp, and then the fiber was cleaned with alcohol. After that, a 30 mm SMF was fusion-spliced between the two 9 mm-long NCF pieces, through the automatic mode of the fiber fusion machine, to form the NCF-SMF-NCF interference sensing structure. In order to improve the sensitivity of the fiber sensor to the variation of external refractive index, the evanescent field of cladding mode was enhanced by etching cladding. A corrosion platform was made by using polytetrafluoroethylene plate with strong hydrophobicity (good hydrophobicity can better control the action area of hydrofluoric acid droplets), and then a groove was formed in the middle of the plate to place optical fiber. It is important to ensure that only the sensing part of the SMF was corroded. After that, both ends of the optical fiber sensor were fixed on the corrosion platform, and the 30 mm SMF sensing part was corroded with 40% hydrofluoric acid (HF) for 15 minutes. When the time was up, the corrosion was finished by washing with a dilute solution of NaCl and deionized water. Figure 2(a) shows the effect of HF corrosion of the SMF. The diameter was reduced by about 25 µm.
Fig. 2. (a) SEM image of the SMF after HF acid corrosion. (b) SEM image of effect of spray coating method.
3.4 Innovative spray coating method
After the corrosion, the optical fiber sensor was evaporated the excess water after cleaning. In order to make the hydrogel tightly bonded on the surface of the etched SMF, the SMF was firstly coated with a layer of γ-aminopropyltriethoxysilane (APTES) (a dilute solution with a concentration of 0.5-1.0%). In the process of hydrogel coating, we used the pioneering spray coating method. We put the prepared precast fluid into the 5.0 ml sprayer with a nozzle radius of 100 µm (the main material is polyethylene terephthalate two ester. Its property is stable so it has no chemical reaction with the hydrogel we made). As shown in Fig. 3, the sprayer was used to spray at different angles when the sensor was fixed. After every spraying, we irradiated with ultraviolet light for 30 seconds to accelerate its solidification, until the hydrogel was evenly covered on the sensor (the orange part is the 3cm SMF sensing part). The coating morphology is shown in the Fig. 2(b). Finally, the fiber sensor should be dried at room temperature for 24 hours before experiment. Compared with the previous dip coating method [23] and grooved rotation coating method [25], this method can achieve thinner and controllable hydrogel coating. In addition, it has advantages such as highly effective UV curing and effective protecting the etched fiber part to be broken.
4. Results and discussions
4.1 Typical interference spectrum of the MZ interferometer
Figure 4 shows a typical interference spectrum of the fiber sensor. The Dip-FBG is the transmission minimum of the cascaded FBG, and the change of the dip wavelength can be used to judge the change in temperature of the experimental environment during the measurement process. Therefore, the temperature calibration can improve the accuracy of the experimental measurement, especially for trace concentration detection, where the influence of the temperature-cross-sensitivity on concentration measurement is serious.
4.2 Sensor characterization
Figure 5 shows the interference spectra of the optical fiber sensor immersed in different concentrations of Cu2+ solution at T=24.0°C. The initial state is pure water and the solution concentration is from 2.0×10−11 mol/L to 1.2×10−10 mol/L. The interference spectrum has a blue shift with the increasing of Cu2+ concentration.
Fig. 5. Interference spectrum of the sensor in Cu2+ solutions at different concentrations at the temperature of T=24.0°C.
As shown in Fig. 6, the black bars are the experimental data, while the red solid line is the linear fit. From the figure, one can obtain the fitting formula of with the fitting coefficient of ${r^2} = 0.995$ in the very low concentration range (0 to 1.2×10−10 mol/L). The sensitivity of the sensor is $S = |{d\lambda /dC} |= 2.214 \times {10^{10}}\; \textrm{nm}/({\textrm{mol}/\textrm{L}} )$. If only considering the best resolution of the optical spectrum analyzer (OSA) of $P = 0.02\textrm{nm}$, the ultimate theoretical resolution of the sensor could be estimated to be $R = P / S \approx 9.032 \times {10^{ - 13}}\textrm{mol}/\textrm{L}$. However, in actual measurements, thermal fluctuation of experimental environment, light intensity fluctuation and background noises may be possibly have some small influence. Therefore, the actual resolution would be a bit worse than the theoretical resolution.
In order to find the real experimental limit of detection (LOD), we have conducted an experiment by using four different Cu2+ concentrations of 0, 2.0×10−12 mol/L, 3.0×10−12 mol/L and 4.0×10−12 mol/L. One can see that from Fig. 6 and its insert, the wavelength shifts for the concentrations of 0 (pure deionized water) and 2.0×10−12 mol/L are almost the same, and thus they cannot be distinguished. But when the concentration reaches 3.0×10−12 mol/L, the wavelength shift can be identified as 0.06 nm. Therefore, the experimental LOD of 3.0×10−12 mol/L is demonstrated.
4.3 Study on detection range
Detection range is another important feature of the sensor. Therefore, the experiment within the concentration range from 0 mol/L to 1.2×10−4 mol/L was done. The results are shown in Fig. 7, where the ordinate $|{\Delta {\lambda_m}} |$ is the absolute value of the wavelength shift. One can see that the wavelength shift of the sensor becomes slow for the concentration over 1.2×10−10 mol/L, and then tends to saturation for the concentration over 1.0×10−5 mol/L. Thus, the highest detectable concentration of the sensor is about 1.0×10−5 mol/L. It means the adsorption of Cu2+ in the sensing film takes place through chelation.
4.4 Temperature calibration
In order to verify the response characteristics of temperature of the sensor, we measured the relationship between the wavelength shift and the ambient temperature in Cu2+ solution. We immersed the sensor in the copper ion solution at the concentration of 4×10−11 mol/L and monitored the wavelength shift by changing the temperature. The experimental results are shown in Fig. 8(a). The black bars are the experimental data, and the red solid line is the second-order polynomial fitting with the formula of $\Delta \lambda = 1.382 \times {10^{ - 2}}({T - 24} )+ 7.205 \times {10^{ - 4}}{({T - 24} )^2}{\; }$ and ${r^2} = 0.998$ in the temperature range of 20.0-65.0°C.
Fig. 8. (a) Experimental data with its fitting for dip wavelength shift of the sensor versus temperature in Cu2+ solution of 4.0×10−11mol/L. (b) Experimental data with its fitting for dip wavelength shift of the sensor versus temperature in Cu2+ solution of 2.0×10−11mol/L. (C) The linear fit of Dip-FBG versus temperature.
By combining the fitting equations from Fig. 8(a) and Fig. 6, the dependence of the wavelength shift $\mathrm{\Delta }\lambda $ on the concentration of Cu2+ and the ambient temperature can be obtained as follows:
Formula (10) reveals again that there is a cross sensitive factor of temperature in the measurement of Cu2+ concentration in aqueous solution. In order to verify that the influences of Cu2+ concentration and ambient temperature on the wavelength shift of the interference spectrum is relatively independent, another group of experiments was carried to measure the response of the sensor to ambient temperature in 2.0×10−11 mol/L concentration of Cu2+ solution. As shown in Fig. 8(b), the experimental-data-fitting result in another concentration is also in good agreement with Eq. (10), which proves that the influences of the concentration and temperature on the wavelength shift are independent of each other, and that Formula (10) holds. From Eq. (10), it can be found that the spectral deviation can reach about 0.3 nm for the temperature fluctuation of 5.0°C. The spectral deviation of 0.3 nm is equivalent to the concentration deviation of 1.3×10−11 mol/L. It reveals that the temperature fluctuation will have a great impact on the accuracy of the detection results. When the concentration is very low, it is necessary to calibrate the temperature influence.
Figure 8(c) represents the experimental data for the dip wavelengths of the FBG at different temperatures and its numerical fitting. It can be observed that in a wide temperature range, the linear fitting can express as${\; }{\lambda _{fbg}} = 7.711 \times {10^{ - 3}}T + 1564.153$ with the fitting degree as high as ${r^2} = 0.998$. To sum up, in actual concentration measurements, we use the sensor-cascading-FBG method to obtain the ambient temperature. After that, the cross sensitivity of temperature to the measurement can be compensated by the calibration of temperature from Eq. (10), in order to obtain accurate results of the detection.
For the sake of comparison, detection methods of copper ion in recent years are summarized in Table 1. As can be seen from the table, we not only put forward the intermodal interference method for the first time to detect copper ions with temperature calibration, but also the detection limit has reached the leading level. Compared with other methods, our all-optic-fiber method also has the advantages of low detection cost, simple method and remote online measurement without manual sampling.
Table 1. Comparison of different methods for the Cu2+ detection.
4.5 Response time study
Response time is one of important factors in evaluating sensors. In the measurement of response time, the sensor was immersed into copper ion solution with a concentration of 6.0×10−11 mol/L for 15 minutes, and then was rapidly immersed into 0.001 mol/L NaCl solution. The rising and falling stages of the sensor are shown in Fig. 9. The rising time of $\; {T_r}$ and falling time of ${T_f}$ are 10 minutes at this concentration. Similarly, in other concentrations of Cu2+ solution, we also recorded the response time of the sensor. The average rising time is 10 minutes, and the average falling time is 9 minutes.
4.6 Stability study
Stability is also one of the important features of the sensor system. In order to verify the long-term stability of the designed sensor under different concentrations, we conducted a series of six experiments. The sensor was successively immersed into six different concentrations of Cu2+ solutions of 2.0, 4.0, 6.0, 8.0, 10.0 and 12.0×10−11 mol/L. The samples were kept in each concentration for 120 minutes, and data was collected every 10 minutes (due to the response time of the sensor of 10 minutes). As shown in Fig. 10, six groups of measured concentration curves were drawn, according to the experimental data. The average concentration standard deviation in the six groups of experiments is 1.610×10−12 mol/L within two hours, which is close to the statistical error of 1.463×10−12 mol/L obtained from all error bars in Fig. 6. The main reason for these deviations is attributed to the resolution of OSA of 0.02 nm (9.032×10−13 mol/L of the ultimate theoretical resolution). Other factors, including thermal fluctuation of the workbench, intensity fluctuation of the light intensity and background noise, may have very small influences on the deviations. For temperature, 0.5°C-variation will cause the deviation of 1.3×10−12 mol/L on concentration measurement, based on the previous analysis on 5°C-temperature influence.
In conclusion, the sensor has also long-term stability of the concentration measurement over 2 hours observation time, and can be applied to the actual environmental monitoring.
4.7 Specificity study - metal ions impurities + organic materials impurities
There may be many impurity metal ions in water sample to be tested. An excellent sensor system should not be affected by other metal ions. In order to check the influence of other ions on the sensor, we conducted a group of interionic interfering experiments. The sensor was immersed in solutions of Zn2+, Cr (VI), Pb2+, Cd2+, Mg2+, Mn2+, Ni2+, K+, Ca2+ and Hg2+ from 2.0×10−11 mol/L to 1.2×10−10 mol/L, individually. Figure 11(a) shows the distinct specificity response of the sensor to all ions. However, in actual detection, the concentration of some metal ion in natural water or biological fluid may be much higher, especially for potassium, calcium and magnesium. We carried out the experiment of these three typical elements with high concentrations from 2.0×10−3 mol/L to 1.2×10−2 mol/L (the concentration range is determined by Guidelines for Drinking Water Quality). The results are shown in Fig. 11(b). One can observe that the high concentration existences of the three ions have only little effect on the detection. The main reason why the sensor has different response to different metal ion [38] is that the imidazolidine force is different for different metal ion. It shows that the sensor is of high specificity towards Cu2+ ion.
Fig. 11. Specificity study of metal ion impurities: (a) 2.0×10−11 mol/L to 1.2×10−10 mol/L concentrations, (b) 2.0×10−3 mol/L to 1.2×10−2 mol/L concentrations.
In addition, due to the presence of organic pollutants in industrial wastewater, we also explore the impact of organic matters on the concentration detection for the application scenarios of sensors. Two different concentrations of Cu2+ solutions were selected, including 2.0×10−11 mol/L for low concentration and 1.2×10−10 mol/L for high concentration. For organic matters, niacin (C6H5NO2) and ethanolamine (C2H7NO) were selected and prepared respectively in their solutions with the concentration of 1×10−11 mol/L. Before the experiment, each of the organic solutions was respectively added to the two Cu2+ solutions with different concentrations. The sensor was immersed in each of the two mixing solutions, and was measured its interference spectrum for 120 minutes. The data was collected every 10 minutes. As shown in Fig. 12, the stability curves before and after the addition of organic matters are basically consistent in both low and high concentrations, so the influence of organic matters on the sensor is negligible.
5. Conclusion
In this paper, an ultra-sensitive optical fiber sensor for trace detection of Cu2+ ions based on intermodal interference with temperature calibration is proposed. Combined a functional hydrogel with good specificity to Cu2+ and new spray coating method, the sensitivity of 2.2143×1010 nm/(mol/L) can be achieved. The experimental limit of detection of the sensor can reach 3.0×10−12 mol/L with the spectral resolution of 0.02 nm, which is far below the limit value of 1ppm for Cu2+ ions in the drinking water standard of World Health Organization (WHO). The relationship between wavelength shift and concentration-temperature is analyzed and the cross-sensitivity of temperature can be compensated. The sensor has also long-term stability of the concentration measurement with the average standard deviation of 1.610×10−12 mol/L over 2 hours observation time. In addition, the sensor is of good specificity, and is basically unaffected by organics. It has good application potential in environmental and biomedical monitoring.
Funding
National Natural Science Foundation of China (61935007).
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. K. Boal and A. C. Rosenzweig, “Structural Biology of Copper Trafficking,” Chem. Rev. 109(10), 4760–4779 (2009). [CrossRef]
2. X. Qing, Y. T. Zong, and S. G. Lu, “Assessment of heavy metal pollution and human health risk in urbansoils of steel industrial city (Anshan), Liaoning, Northeast China,” Ecotoxicol. Environ. Saf. 120, 377–385 (2015). [CrossRef]
3. S. S. Percival, G. P. A. Kauwell, E. Bowser, and M. Wagner, “Altered copper status in adult men with cystic fibrosis,” J. Am. Coll. Nutr. 18(6), 614–619 (1999). [CrossRef]
4. C. Vulpe, B. Levinson, S. Whitney, S. Packman, and J. Gitschier, “Isolation of a candidate gene for Menkes disease and evidence that it encodes a copper−transporting ATPase,” Nat. Genet. 3(1), 7–13 (1993). [CrossRef]
5. D. J. Waggoner, T. B. Bartnikas, and J. D. Gitlin, “The role of copper in neurodegenerative disease,” Neurobiol. Dis. 6(4), 221–230 (1999). [CrossRef]
6. C. S. Chu and C. Y. Chuang, “Optical fiber sensor for dual sensing of dissolved oxygen and Cu2+ ions based on PdTFPP/CdSe embedded in sol–gel matrix,” Sens. Actuators, B 209, 94–99 (2015). [CrossRef]
7. X. J. Meng, S. L. Li, W. B. Ma, J. L. Wang, Z. Y. Hu, and D. L. Cao, “Highly sensitive and selective chemosensor for Cu2+ and H2PO4- based on coumarin fluorophore,” Dyes Pigm. 154, 194–198 (2018). [CrossRef]
8. X. Zhang, X. Guo, H. Yuan, X. Jia, and B. Dai, “One-pot synthesis of a natural phenol derived fluorescence sensor for Cu(II) and Hg(II) detection,” Dyes Pigm. 155, 100–106 (2018). [CrossRef]
9. S. J. Raneea, G. Sivaraman, A. M. Pushpalatha, Shanmugam, and Muthusubramanian, “Quinoline based sensors for bivalent copper ions in living cells,” Sens. Actuators, B 255, 630–637 (2018). [CrossRef]
10. M. A. Deshmukh, M. Gicevicius, A. Ramanaviciene, M. D. Shirsat, R. Viter, and A. Ramanavicius, “Hybrid electrochemical/electrochromic Cu(II) ion sensor prototype based on PANI/ITO-electrode,” Sens. Actuators, B 248, 527–535 (2017). [CrossRef]
11. S. Y. Xu, Y. Wang, Y. Sun, G. Y. Shan, Y. W. Chen, and Y. C. Liu, “The detection of copper ions based on photothermal effect of cysteine modified Au nanorods,” Sens. Actuators, B 248, 761–768 (2017). [CrossRef]
12. R. Hu, T. Furukawa, X. K. Wang, and M. Nagatsu, “Tailoring Amino-Functionalized Graphitic Carbon-Encapsulated Gold Core/Shell Nanostructures for the Sensitive and Selective Detection of Copper Ions,” Adv. Funct. Mater. 27(36), 1702232 (2017). [CrossRef]
13. C. D. Zhang, H. D. Li, Q. Z. Yu, L. J. and Lynn, and Y. Q. Wan, “Poly(aspartic acid) Electrospun Nanofiber Hydrogel Membrane-Based Reusable Colorimetric Sensor for Cu(II) and Fe(III) Detection,” ACS Omega 4(11), 14633–14639 (2019). [CrossRef]
14. M. Pesavento, A. Profumo, D. Merli, L. Cucca, L. Zeni, and N. Cennamo, “An Optical Fiber Chemical Sensor for the Detection of Copper(II) in Drinking Water,” Sensors 19(23), 5246–5532 (2019). [CrossRef]
15. B. Lee, “Review of the present status of optical fiber sensors,” Opt. Fiber Technol. 9(2), 57–79 (2003). [CrossRef]
16. H. A. Al-Rubaiyee, S. K. Al-Hayali, and A. H. Al-Janabi, “Nanostructured coating of graphene nanoparticles deposited onto a cladding etched no-core optical fiber for temperature measurement,” Appl. Opt. 59(15), 4663–4671 (2020). [CrossRef]
17. T. L. Cheng, X. D. Li, S. G. Li, X. Yan, X. N. Zhang, and F. Wang, “Surface plasmon resonance temperature sensor based on a photonic crystal fiber filled with silver nanowires,” Appl. Opt. 59(17), 5108–5113 (2020). [CrossRef]
18. M. Tian, Y. H. Huang, C. Li, and M. Lv, “High-performance humidity sensor based on a micro-nano fiber Bragg grating coated with graphene oxide,” Opt. Express 28(18), 26395–26406 (2020). [CrossRef]
19. J. T. Dong, C. H. Cheng, C. Wu, J. Li, and B. O. Guan, “Highly sensitive optofluidic refractive index sensor based on a seven-liquid-core Teflon-cladding fiber,” Opt. Express 28(18), 26218–26227 (2020). [CrossRef]
20. W. J. Zhang, X. Q. Wu, G. Zhang, J. H. Shi, C. Zuo, S. S. Fang, L. Gui, and B. L. Yu, “Simultaneous measurement of refractive index and temperature or temperature and axial strain based on an inline Mach–Zehnder interferometer with TCF–TF–TCF structure,” Appl. Opt. 60(6), 1522–1528 (2021). [CrossRef]
21. I. Pfalzgraf, S. Suntsov, and D. Kip, “Fiber-optic sensor measuring spatial distributions of refractive index and temperature,” Appl. Opt. 60(5), 1428–1433 (2021). [CrossRef]
22. B. Du, J. He, M. H. Yang, Y. Wang, X. Z. Xu, J. C. Wang, Z. Zhang, F. C. Zhang, K. K. Guo, and Y. P. Wang, “Highly sensitive hydrogen sensor based on an in-fiber Mach-Zehnder interferometer with polymer infiltration and Pt-loaded WO3 coating,” Opt. Express 29(3), 4147–4158 (2021). [CrossRef]
23. P. V. N. Kishorea, M. Sai Shankar, and M. Satyanarayana, “Detection of trace amounts of chromium(VI) using hydrogel coated Fiber Bragg grating,” Sens. Actuators, B 243, 626–633 (2017). [CrossRef]
24. W. Li, C. Jiang, S. Lu, F. Wang, and X. Chen, “A hydrogel microsphere-based sensor for dual and highly selective detection of Al3+ and Hg2+,” Sens. Actuators, B 321, 128490 (2020). [CrossRef]
25. P. Q. Zhu, J. J. Wang, F. Rao, C. Yu, G. Zhou, and X. G. Huang, “Differential Fresnel-reflection-based fiber biochemical sensor with temperature self-compensation for high-resolution measurement of Cd2+ concentration in solution,” Sens. Actuators, B 282, 644–649 (2019). [CrossRef]
26. K. H. Wu, T. C. Chang, Y. T. Wang, Y. S. Hong, and T. S. Wu, “Interactions and mobility of copper(II)–imidazole-containing copolymers,” Eur. Polym. J. 39(2), 239–245 (2003). [CrossRef]
27. F. Asadi, S. N. Azizi, and M. J. Chaichi, “Green synthesis of fluorescent PEG-ZnS QDs encapsulated into Co-MOFs as an effective sensor for ultrasensitive detection of copper ions in tap water,” Mater. Sci. Eng., C 105, 110058 (2019). [CrossRef]
28. C. Y. Lee, Y. C. Lin, and H. F. Wu, “Green synthesis of carbon dots from prawn shells for highly selective and sensitive detection of copper ions,” Sens. Actuators, B 224, 396–403 (2016). [CrossRef]
29. B. B. Zhang, H. Y. Liu, F. X. Wu, G. F. Hao, Y. Z. Chen, C. Y. Tan, Y. Tan, and Y. Y. Jiang, “A dual-response quinoline-based fluorescent sensor for the detection of Copper (II) and Iron(III) ions in aqueous medium,” Sens. Actuators, B 243, 765–774 (2017). [CrossRef]
30. Z. F. Xu, P. H. Deng, J. H. Li, and S. P. Tang, “Fluorescent ion-imprinted sensor for selective and sensitive detection of copper (II) ions,” Sens. Actuators, B 255, 2095–2104 (2018). [CrossRef]
31. G. M. Khairy and A. Duerkop, “Dipsticks and Sensor Microtiterplate for Determination of Copper (II) in Drinking Water Using Reflectometric RGB Readout of Digital Images, Fluorescence or Eye-Vision,” Sens. Actuators, B 281, 878–884 (2019). [CrossRef]
32. F. Shi, S. Cui, H. Liu, and S. Pu, “A high selective fluorescent sensor for Cu2+ in solution and test paper strips,” Dyes Pigm. 173, 107914 (2020). [CrossRef]
33. S. Wang, J. Li, Y. Qiu, X. Zhuang, X. Wu, and J. Jiang, “Facile synthesis of oxidized multi-walled carbon nanotubes functionalized with 5-sulfosalicylic acid/MoS2 nanosheets nanocomposites for electrochemical detection of copper ions,” Appl. Surf. Sci. 487, 766–772 (2019). [CrossRef]
34. X. X. Wang, G. M. Liu, Y. X. Qi, Y. Yuan, J. Gao, X. L. Luo, and T. Yang, “Embedded Au Nanoparticles-Based Ratiometric Electrochemical Sensing Strategy for Sensitive and Reliable Detection of Copper Ions,” Anal. Chem. 91(18), 12006–12013 (2019). [CrossRef]
35. Z. Xu, Q. Meng, Q. Cao, Y. Xiao, and L. Wu, “Selective Sensing of Copper Ions by Mesoporous Porphyrinic Metal-Organic Framework Nanoovals,” Anal. Chem. 92(2), 2201–2206 (2020). [CrossRef]
36. L. Ding, Y. Gao, and J. Di, “A sensitive plasmonic copper(II) sensor based on gold nanoparticles deposited on ITO glass substrate,” Biosens. Bioelectron. 83, 9–14 (2016). [CrossRef]
37. I. Kaur, M. Sharma, S. Kaur, and A. Kaur, “Ultra-sensitive electrochemical sensors based on self-assembled chelating dithiol on gold electrode for trace level detection of copper(II) ions - ScienceDirect,” Sens. Actuators, B 312, 127935 (2020). [CrossRef]
38. C. M. H. Ferreira, I. S. S. Pinto, E. V. Soares, and H. M. V. M. Soares, “(Un)suitability of the use of pH buffers in biological, biochemical and environmental studies and their interaction with metal ions – a review,” RSC Adv. 5(39), 30989–31003 (2015). [CrossRef]
