Wireless power transmission (WPT) is a critical technology that provides an alternative for wireless power and communication with implantable medical devices (IMDs). This article provides a study concentrating on popular WPT techniques for IMDs including inductive coupling, microwave, ultrasound, and hybrid wireless power transmission (HWPT) systems. Moreover, an overview of the major works is analyzed with a comparison of the symmetric and asymmetric design elements, operating frequency, distance, efficiency, and harvested power. In general, with respect to the operating frequency, it is concluded that the ultrasound-based and inductive-based WPTs have a low operating frequency of less than 50 MHz, whereas the microwave-based WPT works at a higher frequency. Moreover, it can be seen that most of the implanted receiver’s dimension is less than 30 mm for all the WPT-based methods. Furthermore, the HWPT system has a larger receiver size compared to the other methods used. In terms of efficiency, the maximum power transfer efficiency is conducted via inductive-based WPT at 95%, compared to the achievable frequencies of 78%, 50%, and 17% for microwave-based, ultrasound-based, and hybrid WPT, respectively. In general, the inductive coupling tactic is mostly employed for transmission of energy to neuro-stimulators, and the ultrasonic method is used for deep-seated implants.

In this work, a dual-band printed planar antenna, operating at two ultra-high frequency bands (2.5 GHz/4.5 GHz), is proposed for wireless power transfer for wearable applications. The receiving antenna is printed on a Kapton polyimide-based flexible substrate, and the transmitting antenna is on FR-4 substrate. The receiver antenna occupies 2.1 cm 2 area. Antennas were simulated using ANSYS HFSS software and the simulation results are compared with the measurement results.

of metasurfaces, constructed with either all-dielectric [1][2][3] or plasmonic [4][5][6] nanoresonators, are capable of achieving engineered phase and amplitude control at the element level and thus enable accurate wave front control with subwavelength resolution. The most widely adopted metasurface design approach includes two steps: 1) calculate the amplitude and phase masks necessary for desired functionalities, fitted to square or hexagonal grids, and 2) find meta-atoms with performance closest to the target of each grid for the final design. Accurate and efficient meta-atom on-demand design approaches remain the main challenge with metasurface designs.To design meta-atoms with maximum efficiency and accurate phase gradients, a common method is to consider structures with simple geometric shapes (such as circles, [7,8] rectangles, [9,10] H-shapes, [11,12] and plasmonic thin layers [13,14] ) and perform a parameter sweep over all dimensions to assemble a library covering the full design space. Then best-fit metaatoms are selected from the library to approximate the ideal amplitude/phase map. Beyond this brute-force approach, previous literatures have also reported metasurface designs that based on solid physical considerations, such as waveguiding analysis, [15,16] Huygens surface, [11,17] surface integral equations, [18][19][20] and Pancharatnam-Berry (PB) phase. [4,21] In Metasurfaces have provided a novel and promising platform for realizing compact and high-performance optical devices. The conventional metasurface design approach assumes periodic boundary conditions for each element, which is inaccurate in most cases since near-field coupling effects between elements will change when the element is surrounded by nonidentical structures. In this paper, a deep learning approach is proposed to predict the actual electromagnetic (EM) responses of each target meta-atom placed in a large array with near-field coupling effects taken into account. The predicting neural network takes the physical specifications of the target metaatom and its neighbors as input, and calculates its actual phase and amplitude in milliseconds. This approach can be used to optimize metasurfaces' efficiencies when combined with optimization algorithms. To demonstrate the efficacy of this methodology, large improvements in efficiency for a beam deflector and a metalens over the conventional design approach are obtained. Moreover, it is shown that the correlations between a metasurface's performance and its design errors caused by mutual coupling are not bound to certain specifications (materials, shapes, etc.). As such, it is envisioned that this approach can be readily applied to explore the mutual coupling effects and improve the performance of various metasurface designs.

Tunable metasurfaces are of great potential for the next-generation electromagnetic systems (e.g. beamforming systems due to the capabilities for ultra-fast reconfiguration speed and agile beam programming on the go). The fundamental aspects of tunable metasurfaces laid on their freedom in manipulating the phase and amplitude of the outgoing wavefront. However, the current research heavily focused on the phase manipulation while left the amplitude manipulation capabilities of the metasurfaces barely explored. To unlock the full potential of tunable metasurfaces, in this article, a novel tunable metasurface design with the capability to control both amplitude and phase of transmitted wavefront has been designed, simulated, and characterized experimentally. By incorporating individual phase and amplitude control modules under the guidance of equivalent circuit models, the proposed metasurface achieved the arbitrary phase and amplitude tuning while maintaining reasonably low physical profile. The measurement results of fabricated samples validated the design procedure and fulfilled the flexibility in terms of phase and amplitude tuning, also paved the way towards achieving more powerful dynamic metasurfaces.

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