Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Ultraviolet-sensing metasurface for programmable electromagnetic scattering field manipulation by combining light control with a microwave field

Open Access Open Access

Abstract

Combining digital information science with metasurface technology is critical for achieving arbitrary electromagnetic wave manipulation. However, there is a scarcity of contemporary scholarly studies on this subject. In this paper, we propose an Ultraviolet (UV) sensing metasurface for programmable electromagnetic scattering field manipulation by combining light control with a microwave field. The active sensing of UV light and the real-time reaction of the scattering are achieved by integrating four UV sensors on the metasurface. On the metasurface, a UV sensor ML8511 and a voltage driver module are coupled to control each row of the Positive-Intrinsic-Negative (PIN) diodes. Due to the light sensing capability of the UV sensor, the on or off state of the PIN diode integrated into the programmable metasurface can be switched efficiently through the change of light. When the incident wave changes, various discrete data are transmitted to the FPGA. Then the FPGA performs the corresponding voltage distribution to control the state of the PIN diode. Finally, different metasurface coding sequences are generated to realize different electromagnetic functions. As a result, the spatial distribution of sensing light by sensors can be used to determine the electromagnetic field and connect sensing optical information with the microwave field. The simulation and measured results show that this design is feasible. This work provides a dimension for electromagnetic waves modulation.

© 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement

1. Introduction

Metasurfaces [13] are two-dimensional equivalents of metamaterials, which exhibit excellent ability in controlling electromagnetic (EM) waves [46]. Moreover, metasurface can realize a series of complex functional devices, such as holographic imaging [711], ultra-thin lenses [12,13], beam control [14,15], and amplitude control [1619]. Although metamaterials have been widely used, it is found that once passive metamaterials are processed, their functions are fixed. To solve this problem, researchers proposed digital coding and programmable metamaterials [2025]. This coding and programmable metasurface can achieve the dynamic and real-time control of electromagnetic waves, offering the extraordinary potential to establish meta-systems [26]. The main form of programmable metamaterials is phase value discrete coding. For 1-bit coding metamaterials, there are two coding states of “0” and “1” respectively. The metamaterials can be controlled and switched in real-time by changing the coding sequence and introducing Field Programmable Gate Array (FPGA). Coding metasurface can also be extended to multi-bit and multi-form coding [26,27], which can be used in wireless communication [28] and radar cross-section (RCS) [29].

In recent years, with the pursuit of innovative metasurface technology, an adaptive intelligent metasurface integrating sensor, programmable metasurface, and algorithm has been proposed [30,31]. This kind of adaptive intelligent metasurfaces [32] can realize the arbitrary adjustment of electromagnetic waves, which is a new direction of combining sensing and electromagnetic regulation. According to reports, light-controlled metasurface [33,34] can produce a variety of radiation patterns. ultraviolet A, ultraviolet B, and ultraviolet C bands of ultraviolet light are widely used in agriculture, medicine, printing, optical curing, and other fields. Compared with visible light control, the UV-driven method further expands the frequency band of the sensor and controller, and the UV light is invisible to the naked eye. Furthermore, because ultraviolet light is more penetrating than visible light, researchers frequently use it for perspective or identification. However, there are few studies on the combination of metasurface and UV sensing.

From the above perspective, we propose a UV sensing metasurface for programmable electromagnetic scattering field manipulation by combining light control with a microwave field. By integrating the UV sensors, the UV-sensing metasurface can flexibly and efficiently perceive the radiation light of 280m∼390nm in the electromagnetic spectrum. In addition, it can not only analyze the incident electromagnetic waves with different frequencies, but also manipulate the electromagnetic wave and scattering field by using reprogrammable array of Positive-Intrinsic-Negative (PIN) diodes. Based on the 1-bit phase-programmable metasurface, we designed and simulated 9 coding patterns, including dual-beam, four-beam, and RCS reduction. Four coding patterns with different scattering angles are tested and the results are in good agreement with the simulation results.

2. Principle and design

In our design, we combine UV sensors, FPGA feedback systems, and algorithms to achieve adaptive UV light sensing on the metasurface, as shown in Fig. 1(a). When the metasurface senses the incident UV light by the integrated sensors, the sensing data is transformed into digital signals by FPGA, which can implement the corresponding EM functions according to the pre-loaded algorithm. For example, we designed metasurface with three selectable EM functions, dual-beam, four-beam, and RCS control. To prove our idea, we design, simulate, and measure various UV-sensing metasurface to demonstrate the ideas mentioned above. In order to more clearly show the working principle of the proposed metasurface, we present a flow chart in Fig. 1(b). The algorithm links the process of UV metasurfaces from detection to sensory data, analog to digital conversion, discrete data, data comparison, and finally the formation of different voltage distribution patterns on the metasurface. Specifically, the working principle of the proposed metasurface is that when UV metasurface detects UV sensing data (DC voltage), it first converts the voltage signal to digital, i.e. analog to digital conversion (ADC). Then the obtained digital signal is discretized into 0/1 code, and the obtained 0/1 digital signal of UV is compared with the designed pattern. Finally, when the digital signal matches with the designed coding sequence, the FPGA controls the on or off state of the PIN diode to produce a different pattern on the metasurface. Based on the above we can design different electromagnetic functions.

 figure: Fig. 1.

Fig. 1. (a) The schematic of the presented UV-sensing metasurface. The metasurface based on UV sensors can achieve various EM functions. (b) An illustration of how the UV metasurface works.

Download Full Size | PDF

Specifically, we propose a 1-bit reflection phase programmable element, as shown in Fig. 2(a). It consists of metal, FR-4 (lossy), and metal ground from top to bottom, and a PIN diode (Skyworks SMP1320) is soldered on an FR-4 substrate (a dielectric constant of 4.3 and loss tangent of 0.025). Figure 2(b) shows the top and bottom views of the unit, the top metal wire connects to the top metal patch, a PIN diode, and then connects to the back metal through a through-hole to form a biasing network. The PIN diode is rated for a bias value of 0.6V. The metamaterial unit with a period of a = 10mm, a thickness of 0.02mm for both the top metal structure and the bottom grounding layer, and a thickness of h = 2mm for the intermediate FR-4 dielectric layer. The back metal, the narrow band metal is the positive pole and the wide band metal is GND. The metal wires on both sides of the symmetrical patch metal with width w = 0.1mm and length l = 2.6mm. The diameter of the through-hole d = 0.3mm, the width of the narrow metal strip line w2 = 0.3mm, the distance of the narrow metal strip from the edge of the metamaterial unit w4 = 0.15mm, and the width of the broad metal strip w3 = 9.4mm. The other detailed dimensions of each element are b = 2.8mm, c = 2.5mm, and w = 4mm. In order to achieve tunability of the UV-sensing metasurface, CST Studio software is used to simulate and optimize the structure of the element. In the simulation optimization process using periodic boundary conditions to optimize the elements, the y-polarization plane incident wave is used as the excitation signal. Figure 2(c) is the operating state of the PIN diode, we use the RLC equivalent model for the simulation of PIN diodes. When R = 2.2Ω, C = 0pF, L = 0.4nH, the diode is in the off state, corresponding to the digital code “0”. When R = 0Ω, C = 0.4pF, L = 0.4nH, the diode is in the on state, corresponding to the digital code “1”. In addition, Fig. 2(d) depicts the relationship between the light intensity of the UV radiation on the UV sensors and output voltage, and Fig. 2(e) shows the light-sensitive band of the UV sensors. It was observed that there is a linear relationship between UV intensity and output voltage, also, the UV sensor senses the sensitive waveband of 280-390nm. In order to experimentally evaluate the UV-sensing metasurface which can flexibly and efficiently perceive the radiated light of 280nm∼390nm in the electromagnetic spectrum, we fabricate the metasurface as shown in Fig. 2(f). To achieve the desired phase difference and guarantee a high reflection amplitude response, we optimized the parameters of the metal patch that determine the performance of the element, like h and w. The magnitude and phase results of the optimized S-parameters are shown in Fig. 2(g) and Fig. 2(h) above. The digital states “0” and “1” are represented in dark blue and light red. By observing the S-parameter result plot, we get that the central frequency point is 7.1GHz.

 figure: Fig. 2.

Fig. 2. (a) The 3D model of the element. (b) Top view and bottom view of the metamaterial cell. (c) The RLC equivalent model for the simulation of PIN diodes. (d) The relationship of light intensity of the UV radiation on the UV sensors and output voltage. (e) The light-sensitive band of the UV sensors. (f) The metasurface with integrated UV sensors and microcontroller circuit. (g) and (h) The simulated reflection amplitude and phase responses of the coding elements.

Download Full Size | PDF

 figure: Fig. 3.

Fig. 3. The simulation results of four dual-beam patterns. (a)-(d) Four coding patterns with horizontal coding of 00001111000011110000, 000001111110000011111, 000000111111100000011, 000000011111111000000 from left to right, labeled patterns A-D. (a)-(d) The column of patterns A-D show 3D far-field simulation results and two-dimensional results corresponding to each coding pattern at 7.1GHz.

Download Full Size | PDF

To verify our idea, we design nine metasurfaces with different coding sequences, including four different coding arrays (pattern A-D), four different chessboard coding patterns (only three patterns are shown in Fig. 3, as pattern E-G), and one RCS reduction pattern (pattern H), as shown in Fig. 3 and Fig. 4. Each metasurface is composed of 400 PIN diodes and four sensing sensors. The PIN diodes in the same line consume the same DC voltage through a bias line and work under the same conditions. In Fig. 3 and Fig. 4, the number “0” refers to PIN diode turn-off state marked in light blue, and the number “1” means the PIN diode turn-on state marked in light orange. Different coding patterns can be quickly formed by perceiving the changes in UV light intensity. For example, four ultraviolet sensors form a 4-bit 0/1 code, “1” indicates UV light is detected, “0” indicates no UV detection. Theoretically, for a coding metasurface composed of N×N elements, the calculation formula of beam deflection angle is as follows [35]:

$$\theta = {\sin ^{ - 1}}\left( {\frac{\lambda }{{nP}}} \right)$$
where λ is the wavelength at the central frequency, n is the number of units in each period, and P is the periodic size of each unit. In order to compare whether the data obtained from our design agrees with the theoretical values, we use CST Studio software to obtain the far-field scattering diagram under the condition of plane wave incidence. According to the above formula, the theoretical deflection angle of the dual-beam with coding sequence 00001111 shown in Fig. 3(a) should be ±31.9°. In the simulation results, the dual-beam deflection angle is ±31.7°. The error between theoretical and simulation results is small, which shows that the theoretical calculation is in good agreement with the simulation results. The far-field results of a larger period with the coding sequence “00000111110000011111” (pattern B) in Fig. 3(b) will produce a smaller deflection angle of ±22°, the deflection angle of sequence “00000011111100000011” (pattern C) is θ=±17°. Figure 3(d) shows the deflection angle of the coding sequence “00000001111111000000” (pattern D) is ±16°. After calculation and comparison, the theoretical and simulation values of deflection angles of dual-beam and four-beam in Fig. 3 and 4 are consistent. And the peaks of the energy of the double beam are 5.3dB for pattern A and pattern B, 4.8dB for pattern C, and 5.6dB for pattern D respectively.

 figure: Fig. 4.

Fig. 4. The simulation results of three multi-beam patterns at 7.1 GHz are presented. (a)-(c) Form left to right, three chess-boards coding patterns, in turn, marked as pattern E-G. The pattern E is the horizontal coding 00001111000011110000, in addition, the column corresponding to the pattern E is the far-field simulation results and the electric field distribution. The pattern F horizontal coding is 00001111000011110000, in addition, the column of mode F show the far-field simulation results and the electric field distribution. The pattern G is the horizontal coding 00001111000011110000, and the column of mode G show the far-field simulation results and the electric field distribution. (d) The RCS Reduction pattern. And the column in which the RCS coding mode corresponds to the coding pattern, the far-field simulation results, and electric field distribution.

Download Full Size | PDF

As shown in Fig. 4(a)–4(c), we realize three coding patterns for four-beam fields. In addition, the following far-field simulation is carried out at the frequency of 7.1 GHz. Figure 4(a) illustrates that pattern E reflects the incident wave at the angle of ±25°. The energy is mainly concentrated on both sides of the beam, forming four beams with an energy value of roughly 1.4dB. Figure 4(b) shows the metasurface with pattern F reflects the incident wave into direction angle of ±20° and the amplitude is 1.38dB. In Fig. 4(c), pattern G deflects the reflection of an incident wave at the angle of θ=±19°, with the main energy concentrated in the beams on either side with a peak of 0.85dB. And the peaks in the middle of the four beams are very small, -4.86dB for pattern E, -3.94dB for pattern F, and -5.31dB for pattern G. It is worth mentioning that we obtain the RCS reduction coding sequence according to the method of Ref. [36]. And the energy distribution of pattern H shows in Fig. 4(d). As can be seen, the RCS reduction pattern produced far-field results that are significantly different from coding arrays and chessboard metasurfaces.

The element we designed can realize independent manipulation, so in theory, the circuit connection mode of column-control or point-control can be adopted. It should be noted that the four-beam and RCS reduction mentioned in Fig. 4 adopt the circuit connection mode of point-control, which is a function expansion at the simulation level. As a fundamental verification, we only need to verify the basic performance of the unit, mainly to verify whether its phase difference can reach 180°. The circuit connection mode of column-control can meet the requirements of rational verification, so in the experiment, we use the circuit connection mode of column-control. The PIN diodes in the same line consume the same DC voltage through a bias line and work under the same conditions. To further demonstrate the design, we measured the far-field results in a standard microwave chamber room. Figure 5 shows the measuring arrangement. The relative position of the feed source and the receiving horn antenna is shown in Fig. 5(a). The customized metasurface, which is made up of 20*20 units and four sensing microcircuit modules, is shown in Fig. 5(b). The entire test structure is shown in detail in Fig. 5(c). We use two broadband horn antennas as a feed source and receivers respectively, and the prepared metasurface samples and feed source are fixed on a rotatable table. When the rotating table rotates, the far-field data are measured on a two-dimensional plane. The feed source horn antenna is arranged at 1.5 m away from the metasurface, and the receiving horn is placed about 10 meters away from the turntable. We draw the test schematic diagram as shown in Fig. 5 to better see the entire test structure.

 figure: Fig. 5.

Fig. 5. The measurement configuration of the design. (a) The schematic diagram of the feeding horn antenna and the receiving horn antenna. (b) The sample of the fabricated metasurface. (c) The measurement configuration. (d) The test schematic diagram. Two broadband horn antennas as feeding and receivers respectively, and the prepared metasurface samples and feeding are fixed on a rotatable table.

Download Full Size | PDF

As shown in Fig. 6, We provide the comparison diagram of dual-beam simulation and far-field measurement. Figure  6(a)–6(d) are the measured data of Pattern A–D respectively. The blue curve represents the simulation result, and the red curve is the measured result. We can observe that the scattering angle of the double beam diagram in the range of [-40°,50°] is in good agreement with the simulation results. The modest difference between measured and simulated results could be due to the following factors: (1) The slight angle deviation is due to the manual placement of horn antennas and metasurface samples; (2) the error is due to the extra reflection of the light-sensing module and fabrication error; (3) The metasurface size and emitting power of the measurement system are limited, which may cause interfering noise.

 figure: Fig. 6.

Fig. 6. The measured results of the presented four coding patterns of dual-beam fields. The simulation results are also listed in blue color for comparison. (a), (b), (c) and (d) The measured results in far-field of the patterns A, B, C, and D.

Download Full Size | PDF

3. Conclusion

We proposed a 1-bit coding metasurface based on UV-sensing sensors. By integrating the ultraviolet sensors and combining specific algorithms, the electromagnetic metasurface has different coding sequences under different light distributions, which can achieve multifunctional electromagnetic control. The programmable metasurface with sensing capabilities are tunable because UV sensing is sensitive to changes in light. The proposed coding metasurface can not only modulates the reflection phase response, but also realize the dual-beam, four-beam, and RCS reduction. At microwave frequencies, the design is simulated and tested. The simulation results are in good agreement with the experimental results, suggesting that the coding metasurface can dynamically manipulate the scattering field according to different light distributions. This work can be applied to specific communication scenarios because of its low cost and great performance.

Funding

National Natural Science Foundation of China (11404207, 52177185); SHIEP Foundation (K2014-054, Z2015-086); Local Colleges and Universities Capacity Building Program of the Science and Technology Commission of Shanghai Municipality (15110500900).

Disclosures

The authors declare no competing financial 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. S. Maci, G. Minatti, M. Casaletti, and M. Bosiljevac, “Metasurfing: Addressing Waves on Impenetrable Metasurfaces,” Antennas Wirel. Propag. Lett. 10, 1499–1502 (2011). [CrossRef]  

2. C. Pfeiffer and A. Grbic, “Cascaded metasurfaces for complete phase and polarization control,” Appl. Phys. Lett. 102(23), 231116 (2013). [CrossRef]  

3. Y. Zhao and A. Alu, “Manipulating light polarization with ultrathin plasmonic metasurfaces,” Phys. Rev. B 84(20), 205428 (2011). [CrossRef]  

4. M. Qin, L. Zhang, X. Zhao, and H. Wu, “Defect Induced Polarization Loss in Multi-Shelled Spinel Hollow Spheres for Electromagnetic Wave Absorption Application,” Adv. Sci. 8(8), 2004640 (2021). [CrossRef]  

5. J.W. You, Q. Ma, Z. Lan, Q. Xiao, N.C. Panoiu, and T.J. Cui, “Reprogrammable plasmonic topological insulators with ultrafast control,” Nat. Commun. 12(1), 5468 (2021). [CrossRef]  

6. Q. Ma, Z.L. Mei, S.K. Zhu, T.Y. Jin, and T.J. Cui, “Experiments on Active Cloaking and Illusion for Laplace Equation,” Phys. Rev. Lett. 111(17), 173901 (2013). [CrossRef]  

7. Y. Bao, Y. Yu, H. Xu, C. Guo, J. Li, S. Sun, Z.-K. Zhou, C.-W. Qiu, and X.-H. Wang, “Full-colour nanoprint-hologram synchronous metasurface with arbitrary hue-saturation-brightness control,” Light: Sci. Appl. 8(1), 95 (2019). [CrossRef]  

8. Y. Rivenson, Y. Zhang, H. Gnaydin, D. Teng, and A. Ozcan, “Phase recovery and holographic image reconstruction using deep learning in neural networks,” Light: Sci. Appl. 7(2), 17141 (2018). [CrossRef]  

9. Y. Wu, Y. Rivenson, Y. Zhang, Z. Wei, H. Gunaydin, X. Lin, and A. Ozcan, “Extended depth-of-field in holographic imaging using deep-learning-based autofocusing and phase recovery,” Optica 5(6), 704–710 (2018). [CrossRef]  

10. Q. Xiao, Q. Ma, T. Yan, L.W. Wu, C. Liu, Z.X. Wang, X. Wan, Q. Cheng, and T.J. Cui, “Orbital-Angular-Momentum-Encrypted Holography Based on Coding Information Metasurface,” Adv. Opt. Mater. 9(11), 2002155 (2021). [CrossRef]  

11. C. Liu, W.M. Yu, Q. Ma, L. Li, and T.J. Cui, “Intelligent coding metasurface holograms by physics-assisted unsupervised generative adversarial network,” Photonics Res. 9(4), B159–B167 (2021). [CrossRef]  

12. K. Liu, G. Wang, T. Cai, W. Guo, Y. Zhuang, and G. Liu, “Ultra-thin circularly polarized lens antenna based on single-layered transparent metasurface,” Chin. Phys. B 27(8), 084101 (2018). [CrossRef]  

13. Q. Ma, C.B. Shi, T.Y. Chen, M.Q. Qi, Y.B. Li, and T.J. Cui, “Broadband metamaterial lens antennas with special properties by controlling both refractive-index distribution and feed directivity,” J. Opt. 20(4), 045101 (2018). [CrossRef]  

14. L. Cong, Y.K. Srivastava, H. Zhang, X. Zhang, J. Han, and R. Singh, “All-optical active THz metasurfaces for ultrafast polarization switching and dynamic beam splitting,” Light: Sci. Appl. 7(1), 28 (2018). [CrossRef]  

15. G. Zheng, H. Muehlenbernd, M. Kenney, G. Li, T. Zentgraf, and S. Zhang, “Metasurface holograms reaching 80% efficiency,” Nat. Nanotechnol. 10(4), 308–312 (2015). [CrossRef]  

16. W.-L. Guo, G.-M. Wang, X.-Y. Luo, K. Chen, H.-P. Li, and Y. Feng, “Dual-Phase Hybrid Metasurface for Independent Amplitude and Phase Control of Circularly Polarized Wave,” IEEE Trans. Antennas Propag. 68(11), 7705–7710 (2020). [CrossRef]  

17. Q. Ma, L. Chen, H.B. Jing, Q.R. Hong, H.Y. Cui, Y. Liu, L.L. Li, and T.J. Cui, “Controllable and Programmable Nonreciprocity Based on Detachable Digital Coding Metasurface,” Adv. Opt. Mater. 7(24), 1901285 (2019). [CrossRef]  

18. L. Chen, Q. Ma, H.B. Jing, H.Y. Cui, Y. Liu, and T.J. Cui, “Space-Energy Digital-Coding Metasurface Based on an Active Amplifier,” Phys. Rev. Appl. 11(5), 054051 (2019). [CrossRef]  

19. Q.R. Hong, Q. Ma, X.X. Gao, C. Liu, Q. Xiao, S. Iqbal, and T.J. Cui, “Programmable Amplitude-Coding Metasurface with Multifrequency Modulations,” Adv. Intell. Syst. Comput. 3(8), 2000260 (2021). [CrossRef]  

20. L. Bao and T.J. Cui, “Tunable, reconfigurable, and programmable metamaterials,” Microw. Opt. Technol. Lett. 62(1), 9–32 (2020). [CrossRef]  

21. Q. Ma and T.J. Cui, “Information Metamaterials: bridging the physical world and digital world,” PhotoniX 1(1), 1–32 (2020). [CrossRef]  

22. T.J. Cui, M.Q. Qi, X. Wan, J. Zhao, and Q. Cheng, “Coding metamaterials, digital metamaterials and programmable metamaterials,” Light: Sci. Appl. 3, e28 (2014). [CrossRef]  

23. B. Xiao, Y. Zhang, S. Tong, J. Yu, and L. Xiao, “Novel tunable graphene-encoded metasurfaces on an uneven substrate for beam-steering in far-field at the terahertz frequencies,” Opt. Express 28(5), 7125–7138 (2020). [CrossRef]  

24. J.W. You, Q. Ma, Z. Lan, Q. Xiao, N.C. Panoiu, and T.J. Cui, “Reprogrammable plasmonic topological insulators with ultrafast control,” Nature 12, 5468 (2020). [CrossRef]  

25. A programmable diffractive deep neural network based on a digital-coding metasurface array, Nature Electronics.

26. Q. Ma, C.B. Shi, G.D. Bai, T.Y. Chen, A. Noor, and T.J. Cui, “Beam-Editing Coding Metasurfaces Based on Polarization Bit and Orbital-Angular-Momentum-Mode Bit,” Adv. Opt. Mater. 5(23), 1 (2017). [CrossRef]  

27. Q. Ma, Q.R. Hong, G.D. Bai, H.B. Jing, R.Y. Wu, L. Bao, Q. Cheng, and T.J. Cui, “Editing Arbitrarily Linear Polarizations Using Programmable Metasurface,” Phys. Rev. Appl. 13(2), 021003 (2020). [CrossRef]  

28. D. Ushikoshi, M. Tanikawa, K. Asano, K. Sanji, M. Ikeda, D. Anzai, and H. Wakatsuchi, “Experimental demonstration of waveform-selective metasurface varying wireless communication characteristics at the same frequency band of 2.4 GHz,” Electron. Lett. 56(3), 160–162 (2020). [CrossRef]  

29. Y. Azizi, M. Soleimani, and S.H. Sedighy, “Low cost, simple and broad band radar cross section reduction by modulated and holography metasurfaces,” J. Phys. D: Appl. Phys. 52(43), 435003 (2019). [CrossRef]  

30. Q. Ma, Q.R. Hong, X.X. Gao, H.B. Jing, C. Liu, G.D. Bai, Q. Cheng, and T.J. Cui, “Smart sensing metasurface with self-defined functions in dual polarizations,” Nanophotonics 9(10), 3271–3278 (2020). [CrossRef]  

31. Q. Ma, G.D. Bai, H.B. Jing, C. Yang, L. Li, and T.J. Cui, “Smart metasurface with self-adaptively reprogrammable functions,” Light: Sci. Appl. 8(1), 98 (2019). [CrossRef]  

32. E. Bjornson, O. Ozdogan, and E.G. Larsson, “Intelligent Reflecting Surface Versus Decode-and-Forward: How Large Surfaces are Needed to Beat Relaying?” IEEE Wireless Commun. Lett. 9(2), 244–248 (2020). [CrossRef]  

33. X.G. Zhang, W.X. Jiang, and T.J. Cui, “Frequency-dependent transmission-type digital coding metasurface controlled by light intensity,” Appl. Phys. Lett. 113(9), 091601 (2018). [CrossRef]  

34. X.G. Zhang, W.X. Tang, W.X. Jiang, G.D. Bai, J. Tang, L. Bai, C.-W. Qiu, and T.J. Cui, “Light-Controllable Digital Coding Metasurfaces,” Adv. Sci. 5(11), 1801028 (2018). [CrossRef]  

35. S. Liu, T.J. Cui, L. Zhang, Q. Xu, Q. Wang, X. Wan, J.Q. Gu, W.X. Tang, M.Q. Qi, J.G. Han, W.L. Zhang, X.Y. Zhou, and Q. Cheng, “Convolution Operations on Coding Metasurface to Reach Flexible and Continuous Controls of Terahertz,” Adv. Sci. 3(10), 1600156 (2016). [CrossRef]  

36. X. Liu, J. Gao, L. Xu, X. Cao, Y. Zhao, and S. Li, “A Coding Diffuse Metasurface for RCS Reduction,” Antennas Wirel. Propag. Lett. 16, 724–727 (2017). [CrossRef]  

Data availability

Data underlying the results presented in this paper are not publicly available at this time but may be obtained from the authors upon reasonable request.

Cited By

Optica participates in Crossref's Cited-By Linking service. Citing articles from Optica Publishing Group journals and other participating publishers are listed here.

Alert me when this article is cited.


Figures (6)

Fig. 1.
Fig. 1. (a) The schematic of the presented UV-sensing metasurface. The metasurface based on UV sensors can achieve various EM functions. (b) An illustration of how the UV metasurface works.
Fig. 2.
Fig. 2. (a) The 3D model of the element. (b) Top view and bottom view of the metamaterial cell. (c) The RLC equivalent model for the simulation of PIN diodes. (d) The relationship of light intensity of the UV radiation on the UV sensors and output voltage. (e) The light-sensitive band of the UV sensors. (f) The metasurface with integrated UV sensors and microcontroller circuit. (g) and (h) The simulated reflection amplitude and phase responses of the coding elements.
Fig. 3.
Fig. 3. The simulation results of four dual-beam patterns. (a)-(d) Four coding patterns with horizontal coding of 00001111000011110000, 000001111110000011111, 000000111111100000011, 000000011111111000000 from left to right, labeled patterns A-D. (a)-(d) The column of patterns A-D show 3D far-field simulation results and two-dimensional results corresponding to each coding pattern at 7.1GHz.
Fig. 4.
Fig. 4. The simulation results of three multi-beam patterns at 7.1 GHz are presented. (a)-(c) Form left to right, three chess-boards coding patterns, in turn, marked as pattern E-G. The pattern E is the horizontal coding 00001111000011110000, in addition, the column corresponding to the pattern E is the far-field simulation results and the electric field distribution. The pattern F horizontal coding is 00001111000011110000, in addition, the column of mode F show the far-field simulation results and the electric field distribution. The pattern G is the horizontal coding 00001111000011110000, and the column of mode G show the far-field simulation results and the electric field distribution. (d) The RCS Reduction pattern. And the column in which the RCS coding mode corresponds to the coding pattern, the far-field simulation results, and electric field distribution.
Fig. 5.
Fig. 5. The measurement configuration of the design. (a) The schematic diagram of the feeding horn antenna and the receiving horn antenna. (b) The sample of the fabricated metasurface. (c) The measurement configuration. (d) The test schematic diagram. Two broadband horn antennas as feeding and receivers respectively, and the prepared metasurface samples and feeding are fixed on a rotatable table.
Fig. 6.
Fig. 6. The measured results of the presented four coding patterns of dual-beam fields. The simulation results are also listed in blue color for comparison. (a), (b), (c) and (d) The measured results in far-field of the patterns A, B, C, and D.

Equations (1)

Equations on this page are rendered with MathJax. Learn more.

θ = sin 1 ( λ n P )
Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.