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Applications of metamaterial sensors: a review

Published online by Cambridge University Press:  02 February 2021

Divya Prakash*
Affiliation:
Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand 835215, India
Nisha Gupta
Affiliation:
Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand 835215, India
*
Author for correspondence: Divya Prakash, E-mail: divyabit18@yahoo.com
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Abstract

Sensors based on metamaterial absorbers are very promising when it comes to high sensitivity and quality factor, cost, and ease of fabrication. The absorbers could be used to sense physical parameters such as temperature, pressure, density as well as they could be used for determining electromagnetic properties of materials and their characterization. In this work, an attempt has been made to explore the various possible applications of these sensors. Metamaterial-based sensors are very popular for its diverse applications in areas such as biomedical, chemical industry, food quality testing, agriculture. Split-ring resonators with various shapes and topologies are the most frequently used structures where the sensing principle is based on electromagnetic interaction of the material under test with the resonator. Overcoming the design challenges using metamaterial sensors involving several constraints such as cost, compactness, reusability, ease in fabrication, and robustness is also addressed.

Information

Type
Metamaterials and Photonic Bandgap Structures
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press in association with the European Microwave Association
Figure 0

Fig. 1. (a) Edge-coupled SRR, (b) broadside-coupled SRR. Marqués et al. (2003) [12].

Figure 1

Fig. 2. (a) SRR, (b) complementary SRR. Salim et al. (2018) [13].

Figure 2

Table 1. Resonator topologies and their applications in different sensors

Figure 3

Fig. 3. (a) Unit-cell structure of the sensor, (b) reflection characteristics for stale rice's different mass fractions in rice samples, (c) reflection characteristics for different varieties of rice samples filled in the sensor. Zhang et al. (2018) [24].

Figure 4

Fig. 4. (a) Epsilon negative fabricated sensor, (b) system configuration for converting the RF response of the sensor in to equivalent DC signal. Kumari et al. (2018) [25].

Figure 5

Fig. 5. (a) Sensor structure, (b) authentic and inauthentic diesel sample's measured S22 (dB) values. Tümkaya et al. (2017) [23].

Figure 6

Fig. 6. (a) Structure of the proposed sensor, (b) absorption curves for different chemical liquids. Abdulkarim et al. (2019) [27].

Figure 7

Fig. 7. (a) DSRR resonators, transmission line, and the equivalent circuit; (b) microfluid flow channels under both resonators; (c) measured values of the transmission coefficient for various concentrations of ethanol in the first channel; (d) measured values of the transmission coefficient for various concentrations of ethanol in the second channel. Zhou et al. (2018) [26].

Figure 8

Fig. 8. (a) Sensor with four CCSR, (b) MUT placed on the bottom side, (c) sensor fabricated prototype, (d) transmission coefficient S21 curve for different MUTs placed on the fabricated sensor. Ruan et al. (2019) [28].

Figure 9

Fig. 9. (a) Diametric view of the sensor, (b) MUT placed over bottom side resonator, (c) MUT (glass) placed over fabricated sensor with connectors to feed the transmission line. Haq et al. (2020) [30].

Figure 10

Fig. 10. (a) Perspective view of the proposed sensor, (b) absorption spectrum of the analyte medium having different permittivity. Huang et al. (2018) [8].

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Table 2. Sensor resonance frequencies, absorption nature, tunability, and shifts in resonance frequencies

Figure 12

Fig. 11. (a) Schematic of the sensor, (b) absorption curves at different applied reverse bias voltages, (c) simulated result showing shift in resonant frequency at different temperatures of the test sample and reverse bias voltages. Bakır et al. (2016) [22].

Figure 13

Fig. 12. (a) Layers of the proposed sensor structure, (b) rapeseed and its absorption curve at different temperatures when the design is used as temperature sensor. Bakir et al. (2017) [10].

Figure 14

Fig. 13. (a) Top side of the prototype sensor, (b) bottom side of the prototype sensor, (c) different over-layer thickness gives different transmission curves and resonant frequencies, (d) transmission curves for FR4 and Rogers RO4350 over-layers. Islam et al. (2018) [9].

Figure 15

Fig. 14. (a) V-shaped resonator, (b) back view and the MUT placed in the resonator for sensing, (c) transmission response curve for all the construction material samples. Akgol et al. (2019) [29].