- Email: [email protected]
Metamaterial-based fluid sensor for identifying different types of fuel oil samples
Accepted Manuscript
Metamaterial-Based Fluid Sensor for Identifying Different Types of Fuel Oil Samples Mehmet Ali Tumkaya , Muharrem Karaaslan , Cumali Sabah ¨ PII: DOI: Reference:
S0577-9073(18)30058-3 https://doi.org/10.1016/j.cjph.2018.08.018 CJPH 617
To appear in:
Chinese Journal of Physics
Received date: Revised date: Accepted date:
11 January 2018 7 August 2018 23 August 2018
Please cite this article as: Mehmet Ali Tumkaya , Muharrem Karaaslan , Cumali Sabah , ¨ Metamaterial-Based Fluid Sensor for Identifying Different Types of Fuel Oil Samples, Chinese Journal of Physics (2018), doi: https://doi.org/10.1016/j.cjph.2018.08.018
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT Highlights
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Metamaterial based sensor for distinguishing different types of gasoline and diesel samples was designed. Experimental and numerical analysis were done. High efficient sensing ability was achieved. The designed structure was manufactured and the experimental studies were carried out.
ACCEPTED MANUSCRIPT Metamaterial-Based Fluid Sensor for Identifying Different Types of Fuel Oil Samples
Mehmet Ali Tümkayaa, Muharrem Karaaslana, Cumali Sabahb,c * a
Department of Electrical and Electronics Engineering, İskenderun Technical
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University,Turkey 31200; Department of Electrical and Electronics Engineering, Middle East Technical
University, Northern Cyprus Campus, (METU-NCC), Kalkanli, Guzelyurt, 99738, TRNC / Mersin 10, Turkey.
Kalkanli Technology Valley (KALTEV), Middle East Technical University - Northern
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*corresponding author. Email: [email protected]
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Abstract. In this paper, we present, design and analyze a metamaterial (MTM) based sensor to distinguish different types of gasoline and diesel samples. Electromagnetic characterization of the samples is completed experimentally and the obtained data is used in the numerical analysis and in the design of the proposed sensor. Unlike the other studies performed in the literature, this structure offers a highly efficient sensing ability and operates in x-band frequency regime. The designed structure is fabricated and the experimental studies are carried out in the related frequency range. It is also demonstrated that numerical results are in a good agreement with the measurement results. The proposed sensor has highly enough bandwidth to sense the fuel oil samples including gasoline and diesel with different characteristics. The suggested structure can be used effectively as a fuel oil sensor in automotive industry. Besides, due to its simple design and high efficiency, the proposed structure can be adjusted to any other liquid sensing application in any desired frequency band by simple adjustments on the dimensions of the structure. Keywords: Metamaterial sensors; fuel-oil characterization; branded and unbranded gasoline sensing; liquid sensors; sensing applications.
ACCEPTED MANUSCRIPT Introduction
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The idea of having negative refraction was first proposed by Veselago in 1968 [1]. Even though this study was a milestone for this exciting electromagnetic field, it hadn’t received necessary attention from the scientific world until Pendry et al.’s work in 1996 and 1999 [2]. They experimentally verified Veselago’s idea of having negative permittivity and permeability at the same time by using periodic structures which is later called as metamaterials (MTMs). Another experimental study was also conducted in 2000s by Smith et al. [3]. These new amazing materials opened a new and exciting era in the scientific community. The studies about this new type of materials have grown exponentially and have been continuing to grow even more parallel to the developing technology. As the name stands, metamaterials are the materials having extraordinary features like negative refraction. MTMs find themselves many and various application areas such as, perfect lenses [4], perfect absorbers [5], polarization rotator [6], thin-film sensors [7-9] and etc. They can find a place in many industries from medical to military applications in all over the frequency spectrum from seismic to optical band [10]. In addition to the previously mentioned applications, MTMs provide numerous advantages on various other applications comparing to the naturally available materials. These amazing new types of materials can be used in the entire electromagnetic spectrum from microwaves to infrared and even to optics. In particular, sensor applications can be designed to determine the substances such as solid [11–13], liquid [14-17] and biomolecules [18–21] in proper frequency bands depending on the linear electromagnetic behaviors of the substances. Metamaterials have also been used as refractive index sensors. Vertical split-ring resonator (VSRR) based perfect absorber has a refractive index sensing behavior with improved sensing performance, hence it provides an efficient way to be used as a biosensor and optoelectronics device [22]. Besides, a multifunctional polarization conversion has been realized with ultrabroad bandwidth and large angular tolerance by using liquid metal based surface [23]. In addition, metasurface with fractal graphene is used as terahertz absorber with a high ratio of absorption between 0.5-60 THz [24]. Determination of surface plasmon resonance is also carried out by a biosensor based on oblique deposited silver nanorods. The phase difference is used to detect glucose level [25]. Split ring resonators have been also used as a plasmonic sensor to detect plasmon resonance depending on the refractive index changes. The highest sensitivity is reported by using split ring resonators in the optical frequency [26]. Star-shaped gold/silver nanoparticles and hyperbolic metamaterial (HMM) structure is also used to enhance Raman intensity with a ratio of 30% for near infrared surface-enhanced Raman scattering operation [27]. As it can be seen, metamaterials have been used in many sensor applications. However, the application of this new type of materials, metamaterials, as a fuel sensor is carried out by us for the first time. The entire sensor structure has a special design and it has never been used in any other applications. The novelty and significance of the study is the differentiation of branded and unbranded diesel samples by using a transportable microwave sensor. The distinguishment of the oils is a real problem in many countries to prevent smuggling. Beside this, the existing systems need laboratory conditions. However, the proposed sensor can differentiate the samples in a short time without requiring any special lab condition. In addition, whereas the similar structures are used as a sensor by other scientists, the proposed structure is firstly used as a sensing layer. The purpose of this study is to design and analyze a MTM based liquid sensor particularly used to sense branded and unbranded fuel oil types. The studies are carried
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out by using both gasoline and diesel samples with different types classified as branded and unbranded. There is a difference between branded and unbranded gasoline (and also diesel) in ingredient. The unbranded gasoline is the gasoline which is taken directly from the oil refinery. It doesn't include chemical remarks of any company. It is well known that all gasoline/diesel companies add chemical remarks to follow and separate their products to the others. Besides, the branded one includes these special liquid chemical remarks. The sensor works by using the electromagnetic properties of the liquid samples. In order to obtain the electromagnetic behaviors of the samples, a dielectric probe integrated to a vector network analyzer is used. Since the sensor consider the variation of the electromagnetic response of the sample, the operating frequency band is selected by considering the electrical permittivity values. The frequency range where the permittivity values are linear is chosen as the operating frequency. The efficiency and the operating mechanism of the structure are tested by taking the scattering parameters into account. The proposed structure has a resonance frequency in X-band and this frequency point changes depending on the sample we want to distinguish. Resonance frequency shift provides enough margins to distinguish the fuel oil samples. Hence, it can be concluded that the designed structure can be used as a fuel-oil sensor for branded and unbranded gasoline or diesel type liquids. The sensor can also be designed to distinguish mixture of brand and unbranded oils. This sensing phenomenon can be achieved by measuring the electromagnetic properties of mixtures with different ratios and then the appropriate frequency in microwave range can be defined. Design and Fabrication Process
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The proposed MTM based sensor is designed and simulated by using a finite integration technique (FIT) method based commercial 3D EM Simulation Software. As can be seen in following measurement results, electrical permittivity of each sample is linear at Xband frequency range. Hence, a sensor structure is designed to operate in related frequency band. The design is composed of a unit cell with plus shaped resonators enclosed by a copper rectangle. It has a sensing reservoir layer capable of holding a liquid sample. The substrate is chosen as FR4 which is cheap and widely used material with low electromagnetic losses in microwave range. The permittivity, magnetic permeability and loss tangent of the substrate (FR4) are 4.2, 1 and 0.02, respectively. For the conductive part of the front side of the structure, copper is used with a conductivity of 5.8×107 S/m and the thickness of 0.035 mm. The back side of the sensor does not have any metallic part. In addition, the overall dimension of the structure is optimized to fit X-band waveguide to carry out the experimental studies and field applications. After obtaining the appropriate dimension for the sensor structure, the proposed structure is manufactured by the dimensions found in the design phase. The sensor structure is printed on a circuit board by using LPKF protomat prototyping PCB machine. The yellow region on the FR4 substrate seen in Figure 1 is constructed by copper with a conductivity of 5.8×107 S/m. The most appropriate dimensions of this metal structure are obtained by using parametric study with the values of L1=20 mm, L2=7.3 mm, L3=4.1 mm, L4=16.8 mm and L5=3 mm (Figure 1 and Figure 2).
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Figure 1. (a) General view and (b) dimension of the structure.
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Figure 2. (a) Front view and (b) side view with the dimensions of the fabricated sample
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Experimental Study
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Firstly, the electromagnetic properties of the fuel-oil samples are determined by using the dielectric probe compatible with the vector network analyzer. Before the measurement, the probe is calibrated by air and pure water whose electromagnetic properties are already known and included in the software along with the short circuit apparatus. After the calibration, the water is placed and the measurement is performed once more to check the accuracy of the calibration. Secondly, the vector network analyzer (VNA) is calibrated for its two regular ports by using the calibration kit in Xband frequency range. Fuel oil sample is filled into an appropriate cup and probe is immersed in the liquid sample with proper adaptors. The probe is connected to the VNA (PNA-L N5234 Model) network analyzer operating up to 43 GHz (Figure 3).
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The resulting electromagnetic responses of the fuel oil samples are tabulated and demonstrated in the following figures (Fig. 4 and 5). As seen in the figures, Gasoline samples have linear curves and distinct electrical permittivity values which makes it possible to distinguish them by designing an appropriate sensor mechanism.
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Figure 4.Real Part of Dielectric values for gasoline samples
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(gasoline_shell&gasoline_unbranded) within the range of 8-12 GHz
Figure 5. Real Part of Dielectric values for gasoline samples (diesel_shell & diesel_unbranded) within the range of 8-12 GHz
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For the working frequency band, all the electromagnetic characteristics of the samples including real dielectric constant values and loss tangent values are tabulated for each frequency points with 1 GHz steps and given in Table 1 below. The error analysis is also demonstrated for each measurement steps. This error analysis is obtained from 5 different measurements results.
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Table 1. Dielectric constant and loss tangent values of branded and unbranded fuel oil samples. Frequency Reel Dielectric Constants (ε)
Loss Tangent (Tang. )
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Diesel
Diesel
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(Unbranded)
(branded)
(Unbranded) (branded)
(Unbranded) (branded)
8
2.43±0.02
2.51±0.01
2.07±0.01
2.68±0.02
0.34±0.01
0.23±0.01
0.15±0.002 0.16±0.001
9
2.32±0.03
2.44±0.02
2.04±0.025
2.62±0.01
0.39±0.01
0.27±0.02
0.17±0.002 0.19±0.003
10
2.19±0.01
2.33±0.01
1.98±0.02
2.56±0.01
0.43±0.01
0.30±0.02
0.20±0.001 0.21±0.001
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2.08±0.005
2.24±0.01
1.95±0.03
2.50±0.01
0.47±0.02
0.32±0.01
0.22±0.002 0.24±0.002
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1.96±0.01
2.15±0.03
1.90±0.02
2.43±0.03
0.51±0.02
0.35±0.03
0.23±0.001 0.25±0.001
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Gasoline
Gasoline
Gasoline
Diesel
Diesel (Unbranded)
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Numerical and Experimental Results
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The suggested MTM based sensor design is simulated with a Finite Integration Technique (FIT) based simulation software. In order to introduce the fuel oil samples into the program, the electromagnetic responses (including dielectric and loss tangent values) of the samples obtained from the experimental tests are used. Reflection behaviors of the model are analyzed and the results are compared in this section for branded and unbranded gasoline and diesel samples in X-band frequency range. For the experimental tests, a waveguide operating in the corresponding frequencies and waveguide to N-type adaptors are used (Figure 6). The measurements are carried out in an X band waveguide operating between 8-12GHz. Since an X band waveguide supports only TE10 mode, the metamaterials and materials under test are exposed to this incident polarization in all tests shown from figures 8 to figure 12.
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Figure 6. X-band waveguide and the corresponding adaptors
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Experimental setup can be seen in Figure 7 below. The sample designed to fit the waveguide is placed inside the waveguide and connected to the testing coax cable through brand adaptors. The scattering curves of the structure for each sample are then obtained in X-band frequency regime and the shifts in the resonance frequencies and the variation between the reflection magnitudes are determined for the fuel oil samples.
Figure 7. Waveguide measurements setup
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Figure 8. Reflection Values of the Branded and Unbranded Diesel Samples
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As seen in Fig. 8, there is a significant difference between the branded and unbranded samples in terms of the transmission magnitude and resonance frequency point. While the branded diesel sample curve gives resonance at 10.352 GHz with -27 dB reflection level, the resonance frequency of unbranded diesel sample is 10.248 GHz with a reflection level of -37 dB. There is a frequency band with the size of 104 MHz between these two samples with 10 dB reflection difference which will allow us to distinguish diesel samples easily. The experimental results given in Fig. 9 below validate the simulation results shown in Fig. 8.
Figure 9. Reflection Measurement for the Branded and Unbranded diesel samples.
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Figure10. Simulated reflection values of the gasoline samples
(gasoline_shell&gasoline_unbranded) within the range of 10-11 GHz
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Reflection values for the gasoline samples are shown in Figure 10. It can be seen that there are observable differences in terms of frequency and reflection values in the resonance points between the branded and unbranded gasoline samples. While branded gasoline sample curve has a resonance at 10.324 GHz with -20 dB reflection value, the unbranded gasoline sample gives resonance at 10.296 GHz with -27 dB value. There is a 28 MHz difference in the frequency values between the samples as well as 7 dB difference in the reflection values. These values provide an adequate band to distinguish two gasoline samples effectively. For validation of the simulation results, experimental studies are also carried out in the lab environment by using a vector network analyzer and the results are shown in Figure 11. The experimental results are in a good agreement with the simulation results.
Figure 11. Experimental test results of the suggested sensor for branded and unbranded gasoline samples.
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Figure 12: Surface current distribution of our sensor configuration
The surface current distribution of the metal resonator on the front face of the proposed structure is shown in Figure 12. Red arrows symbolizing the current are concentrated on the copper plate, which is the metal part of the sensor.
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By considering the agreement in the simulation and experimental test results, it can be said that the proposed structure can be successfully integrated into gasoline sensing applications for detecting branded and unbranded samples.
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Conclusion
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As a result of the study, we can conclude that the proposed MTM based liquid sensor structure works well for determining the fuel oil samples in a simple, less expensive and more effective way. A cost friendly, adjustable and highly efficient sensor design is performed and the structure is manufactured and the analytical and experimental studies are performed. Electromagnetic properties of the fuel oil samples including branded and unbranded gasoline as well as the diesel samples are obtained and used for the design of the structure for more effective sensing applications. The samples demonstrate linear responses in X-band, therefore, the structure is designed to operate in the same band. Besides, the proposed sensor design can be adjusted to any other desired frequency range for various liquid sensing applications by simple dimension adjustments. The obtained experimental and simulation results are compared and a good agreement between the results are determined. This study also contributes to the literature by not only providing a novel MTM based sensor design but it also tabulates the electromagnetic behaviors of the fuel oil samples which can be used for future sensor studies.
References [1] V.G. Veselago, Sov. Phys. Usp. 10(4), 509 (1968) [2] J.B. Pendry, A.J. Holden, D.J. Robbins, W.J. Steward, J. Phys. Condens. Matter 10, 4785 (1998)
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[3] R.A. Shelby, D.R. Smith, S. Schultz, Science 292(5514), 77 (2001). [4] O. Akgol, D. Erricolo, and P. L. E. Uslenghi, “Exact imaging by an elliptic lens,” IEEE Antennas Wireless Propag. Lett., vol. 10, pp.639–642, 2011. [5] F. Dincer, M. Karaaslan, E. Unal, C. Sabah, Prog. Electromagnet. Res. 141 (2013) 219. [6] C. Sabah, H. T. Tastan, F. Dincer, K. Delihacioglu, M. Karaaslan and E. Unal, Prog.Electromagn. Res. 138 (2013) 293–306. [7] A.I. Al-Hanib, C. Jansen, M. Koch, Appl. Phys. Lett. 93, 083507(2008). [8] F. O’Hara, R. Singh, I. Brener, E. Smirnova, J. Han, A.J. Taylor,W. Zhang, Opt. Express 16,1786 (2008). [9] X.-J. He, Y.Wang, J.-M.Wang, T.-L. Gui,Microsyst. Technol. 16,1735 (2010). [10] G. Dolling, M.Wegener, C.M.Soukoulis, S.Linden,Opt.Lett.32(2007)53. [11] J.F. O’Hara, R. Singh, I. Brener, E. Smirnova, J. Han, A.J. Taylor, W. Zhang,Thin film sensing with planar terahertz metamaterials: sensitivity and limitations, Optics Express16 (3) (2008) 1786–1795. [12] W. Withayachumnankul, H. Lin, K. Serita, C. Shah, S. Sriram, M. Bhaskaran, M. Tonouchi, C. Fumeaux, D. Abbott, Sub-diffraction thin-film sensing with planar terahertz metamaterials,Optics Express 20 (3) (2012) 3345–3352. [13] I.A.I. Al-Naib, C. Jansen, M. Koch, Thin-film Sensing with planar asymmetric metamaterial resonators, Applied Physics Letters 93 (2008)083507. [14]W. Withayachumnankul, K. Jaruwongrungsee, C. Fumeaux, D. Abbott, Metamaterial Inspired multichannel thin-film sensor, IEEE Sensors Journal 12 (5) (2012) 1455–1458. [15]B. Reinhard, K.M. Schmitt, V. Wollrab, J. Neu, R. Beigang, M. Rahm, Metamaterialnear-field sensor for deep-subwavelength thickness measurements and sensitive refractometry in theterahertz frequency range, Applied Physics Letters 100 (22) (2012) 221101. [16] Amir Ebrahimi, Withawat Withayachumnankul, Said Al-Sarawi, and Derek Abbott. High-Sensitivity Metamaterial-Inspired Sensor for Microfluidic Dielectric Characterization. IEEE sensors journal. 14 (5) 20141345 – 1351. [17] Jing Jing Yang, Ming Huang, Hao Tang, Jia Zeng, and Ling Dong. Metamaterial Sensors. International Journal of Antennas and Propagation. Volume 2013, http://dx.doi.org/10.1155/2013/637270 [18] H.-J. Lee, J.-G. Yook, Biosensing using split-ring resonators at microwave regime, Applied Physics Letters 92 (25) (2008) 254103. [19] H.-J. Lee, J.-H. Lee, H.-S. Moon, I.-S. Jang, J.-S. Choi, J.-G. Yook, H.-I. Jung, A planarsplit-Ring resonator-based microwave biosensor for label-free detection of biomolecules, Sensors and Actuators B: Chemical 169 (2012) 26–31. [20] A.W. Clark, A. Glidle, D.R.S. Cumming, J.M. Cooper, Plasmonic split-ring resonators as dichroic nanophotonic DNA biosensors, Journal of theAmerican Chemical Society 131 (48) (2009) 17615–17619. [21] Tao Chen, Suyan Li, and Hui Sun. Metamaterials Application in Sensing. Sensors 2012, 12, 2742-2765; doi:10.3390/s120302742 [22] P. C. Wu, W. M. Zhu, Z. X. Shen, P. H. J. Chong, W. Ser, D. P. Tsai, A.-Q. Liu, Advanced Optical Materials 2017, 5, 1600938.Adv. Opt. Mater. 5, 160581 (2017) [23] P. C. Wu, C. Y. Liao, J.-W. Chen, D. P. Tsai, Advanced Optical Materials 2017, 5, 1600581. [24] P. C. Wu, N. Papasimakis, and D. P. Tsai, Phys. Rev. Applied 6, 044019, 2016.
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[25] Hung-Yi Chung, Chih-Chia Chen, Pin Chieh Wu, Ming Lun Tseng, Wen-Chi Lin, Chih-Wei Chen and Hai-Pang Chiang, Enhanced sensitivity of surface plasmon resonance phase-interrogation biosensor by using oblique deposited silver nanorods, Nanoscale Research Letters 9:476 (2014) 1-5. [26] Pin Chieh Wu, Greg Sun, Wei Ting Chen, Kuang-Yu Yang, Yao-Wei Huang, YiHao Chen, Hsiang Lin Huang, Wei-Lun Hsu, Hai Pang Chiang, and Din Ping Tsai, Vertical split-ring resonator based nanoplasmonic sensor, Applied Physics Letters 105, (2014) 033105:1-4. [27] Chih-Hsien Lai, Guo-An Wang, Tsung-Kai Ling, Tzyy-Jiann Wang, Po-kai Chiu, Yuan-Fong Chou Chau, Chih-Ching Huang & Hai-Pang Chiang, Near infrared surface-enhanced Raman scattering based on star shaped gold/silver nanoparticles and hyperbolic metamaterial Scientific. Reports 7, (2017) 5446 .
Metamaterial-Based Fluid Sensor for Identifying Different Types of Fuel Oil Samples Mehmet Ali Tumkaya , Muharrem Karaaslan , Cumali Sabah ¨ PII: DOI: Reference:
S0577-9073(18)30058-3 https://doi.org/10.1016/j.cjph.2018.08.018 CJPH 617
To appear in:
Chinese Journal of Physics
Received date: Revised date: Accepted date:
11 January 2018 7 August 2018 23 August 2018
Please cite this article as: Mehmet Ali Tumkaya , Muharrem Karaaslan , Cumali Sabah , ¨ Metamaterial-Based Fluid Sensor for Identifying Different Types of Fuel Oil Samples, Chinese Journal of Physics (2018), doi: https://doi.org/10.1016/j.cjph.2018.08.018
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
ACCEPTED MANUSCRIPT Highlights
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Metamaterial based sensor for distinguishing different types of gasoline and diesel samples was designed. Experimental and numerical analysis were done. High efficient sensing ability was achieved. The designed structure was manufactured and the experimental studies were carried out.
ACCEPTED MANUSCRIPT Metamaterial-Based Fluid Sensor for Identifying Different Types of Fuel Oil Samples
Mehmet Ali Tümkayaa, Muharrem Karaaslana, Cumali Sabahb,c * a
Department of Electrical and Electronics Engineering, İskenderun Technical
b
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University,Turkey 31200; Department of Electrical and Electronics Engineering, Middle East Technical
University, Northern Cyprus Campus, (METU-NCC), Kalkanli, Guzelyurt, 99738, TRNC / Mersin 10, Turkey.
Kalkanli Technology Valley (KALTEV), Middle East Technical University - Northern
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*corresponding author. Email: [email protected]
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Abstract. In this paper, we present, design and analyze a metamaterial (MTM) based sensor to distinguish different types of gasoline and diesel samples. Electromagnetic characterization of the samples is completed experimentally and the obtained data is used in the numerical analysis and in the design of the proposed sensor. Unlike the other studies performed in the literature, this structure offers a highly efficient sensing ability and operates in x-band frequency regime. The designed structure is fabricated and the experimental studies are carried out in the related frequency range. It is also demonstrated that numerical results are in a good agreement with the measurement results. The proposed sensor has highly enough bandwidth to sense the fuel oil samples including gasoline and diesel with different characteristics. The suggested structure can be used effectively as a fuel oil sensor in automotive industry. Besides, due to its simple design and high efficiency, the proposed structure can be adjusted to any other liquid sensing application in any desired frequency band by simple adjustments on the dimensions of the structure. Keywords: Metamaterial sensors; fuel-oil characterization; branded and unbranded gasoline sensing; liquid sensors; sensing applications.
ACCEPTED MANUSCRIPT Introduction
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The idea of having negative refraction was first proposed by Veselago in 1968 [1]. Even though this study was a milestone for this exciting electromagnetic field, it hadn’t received necessary attention from the scientific world until Pendry et al.’s work in 1996 and 1999 [2]. They experimentally verified Veselago’s idea of having negative permittivity and permeability at the same time by using periodic structures which is later called as metamaterials (MTMs). Another experimental study was also conducted in 2000s by Smith et al. [3]. These new amazing materials opened a new and exciting era in the scientific community. The studies about this new type of materials have grown exponentially and have been continuing to grow even more parallel to the developing technology. As the name stands, metamaterials are the materials having extraordinary features like negative refraction. MTMs find themselves many and various application areas such as, perfect lenses [4], perfect absorbers [5], polarization rotator [6], thin-film sensors [7-9] and etc. They can find a place in many industries from medical to military applications in all over the frequency spectrum from seismic to optical band [10]. In addition to the previously mentioned applications, MTMs provide numerous advantages on various other applications comparing to the naturally available materials. These amazing new types of materials can be used in the entire electromagnetic spectrum from microwaves to infrared and even to optics. In particular, sensor applications can be designed to determine the substances such as solid [11–13], liquid [14-17] and biomolecules [18–21] in proper frequency bands depending on the linear electromagnetic behaviors of the substances. Metamaterials have also been used as refractive index sensors. Vertical split-ring resonator (VSRR) based perfect absorber has a refractive index sensing behavior with improved sensing performance, hence it provides an efficient way to be used as a biosensor and optoelectronics device [22]. Besides, a multifunctional polarization conversion has been realized with ultrabroad bandwidth and large angular tolerance by using liquid metal based surface [23]. In addition, metasurface with fractal graphene is used as terahertz absorber with a high ratio of absorption between 0.5-60 THz [24]. Determination of surface plasmon resonance is also carried out by a biosensor based on oblique deposited silver nanorods. The phase difference is used to detect glucose level [25]. Split ring resonators have been also used as a plasmonic sensor to detect plasmon resonance depending on the refractive index changes. The highest sensitivity is reported by using split ring resonators in the optical frequency [26]. Star-shaped gold/silver nanoparticles and hyperbolic metamaterial (HMM) structure is also used to enhance Raman intensity with a ratio of 30% for near infrared surface-enhanced Raman scattering operation [27]. As it can be seen, metamaterials have been used in many sensor applications. However, the application of this new type of materials, metamaterials, as a fuel sensor is carried out by us for the first time. The entire sensor structure has a special design and it has never been used in any other applications. The novelty and significance of the study is the differentiation of branded and unbranded diesel samples by using a transportable microwave sensor. The distinguishment of the oils is a real problem in many countries to prevent smuggling. Beside this, the existing systems need laboratory conditions. However, the proposed sensor can differentiate the samples in a short time without requiring any special lab condition. In addition, whereas the similar structures are used as a sensor by other scientists, the proposed structure is firstly used as a sensing layer. The purpose of this study is to design and analyze a MTM based liquid sensor particularly used to sense branded and unbranded fuel oil types. The studies are carried
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out by using both gasoline and diesel samples with different types classified as branded and unbranded. There is a difference between branded and unbranded gasoline (and also diesel) in ingredient. The unbranded gasoline is the gasoline which is taken directly from the oil refinery. It doesn't include chemical remarks of any company. It is well known that all gasoline/diesel companies add chemical remarks to follow and separate their products to the others. Besides, the branded one includes these special liquid chemical remarks. The sensor works by using the electromagnetic properties of the liquid samples. In order to obtain the electromagnetic behaviors of the samples, a dielectric probe integrated to a vector network analyzer is used. Since the sensor consider the variation of the electromagnetic response of the sample, the operating frequency band is selected by considering the electrical permittivity values. The frequency range where the permittivity values are linear is chosen as the operating frequency. The efficiency and the operating mechanism of the structure are tested by taking the scattering parameters into account. The proposed structure has a resonance frequency in X-band and this frequency point changes depending on the sample we want to distinguish. Resonance frequency shift provides enough margins to distinguish the fuel oil samples. Hence, it can be concluded that the designed structure can be used as a fuel-oil sensor for branded and unbranded gasoline or diesel type liquids. The sensor can also be designed to distinguish mixture of brand and unbranded oils. This sensing phenomenon can be achieved by measuring the electromagnetic properties of mixtures with different ratios and then the appropriate frequency in microwave range can be defined. Design and Fabrication Process
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The proposed MTM based sensor is designed and simulated by using a finite integration technique (FIT) method based commercial 3D EM Simulation Software. As can be seen in following measurement results, electrical permittivity of each sample is linear at Xband frequency range. Hence, a sensor structure is designed to operate in related frequency band. The design is composed of a unit cell with plus shaped resonators enclosed by a copper rectangle. It has a sensing reservoir layer capable of holding a liquid sample. The substrate is chosen as FR4 which is cheap and widely used material with low electromagnetic losses in microwave range. The permittivity, magnetic permeability and loss tangent of the substrate (FR4) are 4.2, 1 and 0.02, respectively. For the conductive part of the front side of the structure, copper is used with a conductivity of 5.8×107 S/m and the thickness of 0.035 mm. The back side of the sensor does not have any metallic part. In addition, the overall dimension of the structure is optimized to fit X-band waveguide to carry out the experimental studies and field applications. After obtaining the appropriate dimension for the sensor structure, the proposed structure is manufactured by the dimensions found in the design phase. The sensor structure is printed on a circuit board by using LPKF protomat prototyping PCB machine. The yellow region on the FR4 substrate seen in Figure 1 is constructed by copper with a conductivity of 5.8×107 S/m. The most appropriate dimensions of this metal structure are obtained by using parametric study with the values of L1=20 mm, L2=7.3 mm, L3=4.1 mm, L4=16.8 mm and L5=3 mm (Figure 1 and Figure 2).
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Figure 1. (a) General view and (b) dimension of the structure.
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Figure 2. (a) Front view and (b) side view with the dimensions of the fabricated sample
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Experimental Study
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Firstly, the electromagnetic properties of the fuel-oil samples are determined by using the dielectric probe compatible with the vector network analyzer. Before the measurement, the probe is calibrated by air and pure water whose electromagnetic properties are already known and included in the software along with the short circuit apparatus. After the calibration, the water is placed and the measurement is performed once more to check the accuracy of the calibration. Secondly, the vector network analyzer (VNA) is calibrated for its two regular ports by using the calibration kit in Xband frequency range. Fuel oil sample is filled into an appropriate cup and probe is immersed in the liquid sample with proper adaptors. The probe is connected to the VNA (PNA-L N5234 Model) network analyzer operating up to 43 GHz (Figure 3).
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The resulting electromagnetic responses of the fuel oil samples are tabulated and demonstrated in the following figures (Fig. 4 and 5). As seen in the figures, Gasoline samples have linear curves and distinct electrical permittivity values which makes it possible to distinguish them by designing an appropriate sensor mechanism.
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Figure 4.Real Part of Dielectric values for gasoline samples
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(gasoline_shell&gasoline_unbranded) within the range of 8-12 GHz
Figure 5. Real Part of Dielectric values for gasoline samples (diesel_shell & diesel_unbranded) within the range of 8-12 GHz
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For the working frequency band, all the electromagnetic characteristics of the samples including real dielectric constant values and loss tangent values are tabulated for each frequency points with 1 GHz steps and given in Table 1 below. The error analysis is also demonstrated for each measurement steps. This error analysis is obtained from 5 different measurements results.
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Table 1. Dielectric constant and loss tangent values of branded and unbranded fuel oil samples. Frequency Reel Dielectric Constants (ε)
Loss Tangent (Tang. )
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(GHz) Gasoline
Diesel
Diesel
(branded)
(Unbranded)
(branded)
(Unbranded) (branded)
(Unbranded) (branded)
8
2.43±0.02
2.51±0.01
2.07±0.01
2.68±0.02
0.34±0.01
0.23±0.01
0.15±0.002 0.16±0.001
9
2.32±0.03
2.44±0.02
2.04±0.025
2.62±0.01
0.39±0.01
0.27±0.02
0.17±0.002 0.19±0.003
10
2.19±0.01
2.33±0.01
1.98±0.02
2.56±0.01
0.43±0.01
0.30±0.02
0.20±0.001 0.21±0.001
11
2.08±0.005
2.24±0.01
1.95±0.03
2.50±0.01
0.47±0.02
0.32±0.01
0.22±0.002 0.24±0.002
12
1.96±0.01
2.15±0.03
1.90±0.02
2.43±0.03
0.51±0.02
0.35±0.03
0.23±0.001 0.25±0.001
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Gasoline
Gasoline
Gasoline
Diesel
Diesel (Unbranded)
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Numerical and Experimental Results
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The suggested MTM based sensor design is simulated with a Finite Integration Technique (FIT) based simulation software. In order to introduce the fuel oil samples into the program, the electromagnetic responses (including dielectric and loss tangent values) of the samples obtained from the experimental tests are used. Reflection behaviors of the model are analyzed and the results are compared in this section for branded and unbranded gasoline and diesel samples in X-band frequency range. For the experimental tests, a waveguide operating in the corresponding frequencies and waveguide to N-type adaptors are used (Figure 6). The measurements are carried out in an X band waveguide operating between 8-12GHz. Since an X band waveguide supports only TE10 mode, the metamaterials and materials under test are exposed to this incident polarization in all tests shown from figures 8 to figure 12.
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Figure 6. X-band waveguide and the corresponding adaptors
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Experimental setup can be seen in Figure 7 below. The sample designed to fit the waveguide is placed inside the waveguide and connected to the testing coax cable through brand adaptors. The scattering curves of the structure for each sample are then obtained in X-band frequency regime and the shifts in the resonance frequencies and the variation between the reflection magnitudes are determined for the fuel oil samples.
Figure 7. Waveguide measurements setup
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Figure 8. Reflection Values of the Branded and Unbranded Diesel Samples
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As seen in Fig. 8, there is a significant difference between the branded and unbranded samples in terms of the transmission magnitude and resonance frequency point. While the branded diesel sample curve gives resonance at 10.352 GHz with -27 dB reflection level, the resonance frequency of unbranded diesel sample is 10.248 GHz with a reflection level of -37 dB. There is a frequency band with the size of 104 MHz between these two samples with 10 dB reflection difference which will allow us to distinguish diesel samples easily. The experimental results given in Fig. 9 below validate the simulation results shown in Fig. 8.
Figure 9. Reflection Measurement for the Branded and Unbranded diesel samples.
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Figure10. Simulated reflection values of the gasoline samples
(gasoline_shell&gasoline_unbranded) within the range of 10-11 GHz
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Reflection values for the gasoline samples are shown in Figure 10. It can be seen that there are observable differences in terms of frequency and reflection values in the resonance points between the branded and unbranded gasoline samples. While branded gasoline sample curve has a resonance at 10.324 GHz with -20 dB reflection value, the unbranded gasoline sample gives resonance at 10.296 GHz with -27 dB value. There is a 28 MHz difference in the frequency values between the samples as well as 7 dB difference in the reflection values. These values provide an adequate band to distinguish two gasoline samples effectively. For validation of the simulation results, experimental studies are also carried out in the lab environment by using a vector network analyzer and the results are shown in Figure 11. The experimental results are in a good agreement with the simulation results.
Figure 11. Experimental test results of the suggested sensor for branded and unbranded gasoline samples.
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Figure 12: Surface current distribution of our sensor configuration
The surface current distribution of the metal resonator on the front face of the proposed structure is shown in Figure 12. Red arrows symbolizing the current are concentrated on the copper plate, which is the metal part of the sensor.
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By considering the agreement in the simulation and experimental test results, it can be said that the proposed structure can be successfully integrated into gasoline sensing applications for detecting branded and unbranded samples.
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Conclusion
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As a result of the study, we can conclude that the proposed MTM based liquid sensor structure works well for determining the fuel oil samples in a simple, less expensive and more effective way. A cost friendly, adjustable and highly efficient sensor design is performed and the structure is manufactured and the analytical and experimental studies are performed. Electromagnetic properties of the fuel oil samples including branded and unbranded gasoline as well as the diesel samples are obtained and used for the design of the structure for more effective sensing applications. The samples demonstrate linear responses in X-band, therefore, the structure is designed to operate in the same band. Besides, the proposed sensor design can be adjusted to any other desired frequency range for various liquid sensing applications by simple dimension adjustments. The obtained experimental and simulation results are compared and a good agreement between the results are determined. This study also contributes to the literature by not only providing a novel MTM based sensor design but it also tabulates the electromagnetic behaviors of the fuel oil samples which can be used for future sensor studies.
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