In this paper, for the first time, a new generation of ultrafast reprogrammable multi-mission bias encoded metasurface is proposed for dynamic terahertz wavefront engineering by employing VO2 reversible and fast monoclinic to tetragonal phase transition. the multi-functionality of our designed VO2 based coding metasurface (VBCM) was guaranteed by elaborately designed meta-atom comprising three-patterned VO2 thin films whose operational statuses can be dynamically tuned among four states of "00"-"11" by merely changing the biasing voltage controlled by an external Field-programmable gate array platform. Capitalizing on such meta-atom design and by driving VBCM with different spiral-like and spiral-parabola-like coding sequences, single vortex beam and focused vortex beam with interchangeable orbital angular momentum modes were satisfactorily generated respectively. Additionally, by adopting superposition theorem and convolution operation, symmetric/asymmetric multiple beams and arbitrarily-oriented multiple vortex beams in pre-demined directions with different topological charges are realized. Several illustrative examples successfully have clarified that the proposed VBCM is a promising candidate for solving crucial terahertz challenges such as high data rate wireless communication where ultrafast switching between several missions is required. In recent years, the scope of THz science and technologies has reached a maturity and attracted massive attention due to their potential applications like biomedicine 1 , security checking and high data rate transmit through wireless communication 2-4. However, as the key technique, manipulating EM waves reveals the necessity of employing metasurfaces as the two-dimensional analogous of more general volumetric metamaterials to furnish an inspiring groundwork for realizing some rich diverse applications such as, but not limited to, invisibility cloaks 5,6 , negative refraction 7 , optical illusion 8 and epsilon near zero behaviors 9,10. Recently, T. Cui et al. has revolutionary introduced the concept of digital metasurfaces as a link between the physical and digital worlds, making it possible to revisit metamaterials from the viewpoint of information science where manipulation of EM waves with different functionalities can be realized by controlling sequences of digital coding states "0" and "1" with opposite phase responses 11. Due to the lower weight and being easier to design and fabricate, digital metasurfaces have experienced rapid development compared to traditional wave manipulation 12. By purposefully distributing coding particles over a 2D plane in a periodic or aperiodic manner, a variety of exquisite physics phenomena and innovative EM devices have been created 13-17. However, in most of these strategies, the metasurfaces are designed for a specific application and their functionalities remain fixed once they are constructed. For example, Shao et al. proposed a dielectric 2-bit coding metasurface with distinct functionalities from anomalous reflection to vortex b...

Beyond the scope of conventional metasurface, which necessitates plenty of computational resources and time, an inverse design approach using machine learning algorithms promises an effective way for metasurface design. In this paper, benefiting from Deep Neural Network (DNN), an inverse design procedure of a metasurface in an ultra-wide working frequency band is presented in which the output unit cell structure can be directly computed by a specified design target. To reach the highest working frequency for training the DNN, we consider 8 ring-shaped patterns to generate resonant notches at a wide range of working frequencies from 4 to 45 GHz. We propose two network architectures. In one architecture, we restrict the output of the DNN, so the network can only generate the metasurface structure from the input of 8 ring-shaped patterns. This approach drastically reduces the computational time, while keeping the network’s accuracy above 91%. We show that our model based on DNN can satisfactorily generate the output metasurface structure with an average accuracy of over 90% in both network architectures. Determination of the metasurface structure directly without time-consuming optimization procedures, an ultra-wide working frequency, and high average accuracy equip an inspiring platform for engineering projects without the need for complex electromagnetic theory.

Ultrawide-angle electromagnetic wave absorbers with excellent mechanical properties are required in many diverse applications such as sensing, and stealth technologies. Here, a novel 3D reconfigurable metamaterial absorber (MMA) consisting of honeycomb and VO2 films is proposed. The proposed MMA exhibits a strong absorptivity above 90% in the widest incident angle up to $$87^\circ $$ 87 ∘ for TM- and TE polarized oblique incidences for THz wave propagating in yoz-plane. Under normal incidence, when VO2 films are in the insulating state, the proposed absorber exhibits high absorptivity in the frequency band of 1–4 THz. By increasing the temperature of the whole structure, the structural transformation of VO2 occurs and turns into the metallic phase. We have shown that under oblique incidence, the ohmic losses of VO2 films especially those parallel to the direction of the incident electric field are the most important absorption principles of the proposed MMA. Due to the ultra wide-angle absorption (angular stability) and mechanical performance, it is expected that the presented MMA may find potential applications, such as camouflage technologies, electromagnetic interference, imaging, and sensing. To the best knowledge of authors, the proposed MMA configuration exhibits the absorptivity in the widest incident angle ever reported.

In this paper, we present a novel approach for the design of leaky-wave holographic antennas that generates OAMcarrying electromagnetic waves by combining Flat Optics (FO) and machine learning (ML) techniques. To improve the performance of our system, we use a machine learning technique to discover a mathematical function that can effectively control the entire radiation pattern, i.e., decrease the side lobe level (SLL) while simultaneously increasing the central null depth of the radiation pattern. Precise tuning of the parameters of the impedance equation based on holographic theory is necessary to achieve optimal results in a variety of scenarios. In this research, we applied machine learning to determine the approximate values of the parameters. We can determine the optimal values for each parameter, resulting in the desired radiation pattern, using a total of 77,000 generated datasets. Furthermore, the use of ML not only saves time, but also yields more precise and accurate results than manual parameter tuning and conventional optimization methods.

Monitoring and controlling the state of polarization of electromagnetic waves is of significant interest for various basic and practical applications such as linear position sensing and medical imaging. Here, we propose the first conformal digital metamaterial absorber to detect the polarization state of THz incident waves. The proposed polarimeter is capable of characterizing four independent polarization states of (TE, TM, ±45° linear, and RCP/LCP) by observing the reflectivity of the structure with respect to the x- and y-direction. Besides, the proposed structure displays a strong absorptivity above 90% up to the incidence angle of 50° for oblique incident waves with different polarizations. By mere changing the bias voltage of two orthogonal VO2 microwires via two independent computer-programmed multichannel DC network, distinct conditions for reflected waves occurs under excitations of different polarizations, whereby the polarization state of the incident wave may readily be estimated. We believe that the proposed metasurface-based polarimeter can pave the way for polarization detection applications on curved surfaces.