The concentration induced permittivity change involves a dispersion which occurs at the resonant frequency, and is often not predictable by simulation using the traditional Cole-Cole model. To overcome this problem, a new Lorentz's model is proposed as a substitute for the Cole-Cole model. Under this new model, the glucose concentration is expected to be measured at the contact interface in the form of a resonant frequency shift. With the help of the model, a contact-based meander-line antenna sensor (CMS) is realized with a high ``sensitivity of 1.3158 dB/(mmol/L) in terms of d |S11|/dC, or of 17~18 MHz/(mmol/L) in terms of'' dω/dC. The model has been experimentally validated with in-vitro measurements and for proof-of-concept with in-vivo clinical investigations in the microwave frequency. Consistent with the predictions of model, a linear ``correlation is observed not only between the resonant frequency shift and the glucose concentration, but also between the S-parameters magnitude and glucose'' concentration.
Microwave staring correlated imaging (MSCI) is a super-resolution imaging technique based on temporal-spatial stochastic radiation fields (TSSRFs), which requires an accurate calculation of the electromagnetic field at the imaging plane. However, systematic errors always exist in practice, such as the time synchronization and frequency synchronization errors of radar systems, which make it difficult to calculate the required TSSRFs accurately, and this deteriorates the imaging results. Meanwhile, some imaging algorithms have problems such as high computational complexity. In this paper, an intelligent MSCI method based on the deep neural network (DNN) is proposed, which can accomplish imaging directly from the echoes, avoiding the computation of TSSRFs. A multi-level residual convolutional neural network (MRCNN) is developed for the DNN, and simulations and experiments are carried out to obtain the dataset for training and testing the MRCNN. Compared with the conventional MSCI methods, the imaging results verify the effectiveness of intelligent MSCI in terms of imaging quality and computational efficiency.
As one of the most important technologies for the next generation very-large scale integrated circuit fabrication, extreme ultraviolet (EUV) lithography has attracted more and more attention in recent years. However, in EUV lithography, the optical distortion of the printed image on wafer always has negative impacts on the imaging performance. Thus, to enhance the imaging performance of EUV system, especially for small critical dimensions, in this work, a novel optical proximity correction (OPC) system based on the deep learning technique is proposed. It includes a forward module and an inverse module, where the forward module is employed to fast and accurately map the mask to the corresponding near field of the plane above the stack to help the construction of training dataset for the inverse module operation, and the inverse module is employed to fast and accurately map the target printed image to the corrected mask. Numerical examples demonstrate that compared with traditional full-wave simulation, the forward module can greatly improve the computational efficiency including the required running time and memory. Meanwhile, different from time consuming iterative OPC methods, the corrected mask can be immediately obtained as the target printed image is input using the trained inverse module.
We extended the previous 2D method of BBGF-MST (Broadband Green's function-Multiple Scattering Theory) approach to 3D problems in periodic structures. Band Structures and Band Field Solutions are calculated. A feature of BBGF is that the lattice Green's functions are broadband so that the coefficients of the spherical wave expansions are calculated rapidly for many frequencies. These are then used for speedy calculations of the matrix elements of the KKR (Korringa-Kohn-Rostoker) eigenvalue equation. Using BBGF-MST, a low order matrix eigenvalue equation for the bands is derived. For the first two bands, the dimension of the KKR matrix equation is only 4 by 4. With the use of BBGF, the CPU requirement for the BBGF-MST technique is 0.27 secondson a standard laptop for solving the KKR eigenvalue equation. Numerical results of the band diagrams are illustrated. Higher order spherical waves are next used to calculate the normalized band field solutions for the entire cell.
Optical analog computing has recently sparked growing interest due to the appealing characteristics of low energy consumption, parallel processing, and ultrafast speed, spawning it complementary to conventional electronic computing. As the basic computing unit, optical logic operation plays a pivotal role for integrated photonics. However, the reported optical logic operations are volumetric and single-functional, which considerably hinders the practical cascadability and complex computing requirement. Here, we propose an on-chip combinational optical logic circuit using inverse design. By precisely engineering the scattering matrix of each small-footprint logic gate, all basic optical logic gates (OR, XOR, NOT, AND, XNOR, NAND, and NOR) are realized. On this foundation, we explore the assembly of these basic logic gates for general-purpose combinational logic circuits, including optical half-adder and code converter. Our work provides a path for the development of integrated, miniaturized, and cascadable photonic processor for future optical computing technologies.
Antennas are essential devices to build everything connected in the era of information. However, the quality of communications would be degraded with the presence of raindrops on the antenna surface. Additional antiwater radomes may generate radiation loss and dispersive impedance mismatch over a broad frequency range, which is not acceptable for next-generation communication systems integrating multiple bands. Here, we report the first experimental demonstration of self-hydrophobic antennas that cover the bands of 1.7 GHz, 3.5 GHz, and 8.5 GHz through a laser-direct-writing treatment. Experimental results show that the return loss, radiation pattern, and efficiency of self-superhydrophobic antennas can be maintained in the mimicked rainy weather. Furthermore, writing hydrophobic nanostructures on both dielectrics and metals is compatible with commercial printed circuitry techniques widely used in industries. Our technique will augment the laser fabrication technology for specialized electromagnetic devices and serve as a powerful and generalized solution for all-weather wireless communication systems.
To shield undesirable microwave radiation to protect electronic systems and human health, microwave perfect absorbers have attracted increasing interests in recent years. However, the opaque or semitransparent nature of most implemented microwave absorbers limit their applications in optics. Here, we demonstrate a high-performance microwave absorber based on an impedance-assisted Fabry-Pérot resonant cavity with an ITO-dielectric-ITO structure without complex nanofabrication. The device features near-unity absorption (99.5% at 14.4 GHz with a 4.5 GHz effective bandwidth), excellent electromagnetic interference shielding performance (24 dB) in the Ku-band, and high optical transparency (89.0% from 400 nm to 800 nm). The peak absorption frequency of the device can be tuned by changing the thickness of glass slab and sheet resistance of ITO films. Our work provides a low-cost and feasible solution for highperformance optically transparent microwave shielding and stealth, paving the way towards applications in areas of microwave and optics.
Inspired by neural networks based on traditional electronic circuits, optical neural networks (ONNs) show great potential in terms of computing speed and power consumption. Though some progress has been made in devices and schemes, ONNs are still a long way from replacing electronic neural networks in terms of generalizability. Here, we present a complex optical neural network (cONN) for holographic image recognition, within which a high-speed parallel operating unit for complex matrices is proposed, targeting the real-imaginary-splitting and column splitting. Based on the proposed cONN, we have numerically demonstrated the training-recognition process on our cONN for holographic images converted from handwritten digit datasets, achieving an accuracy of 90% based on the back-propagation algorithm. Our training verification integrated architecture will enrich the further development and applications of on-chip photonic matrix computing.
An optically transparent and flexible coplanar waveguide (CPW)-fed wideband antenna is proposed and demonstrated experimentally based on sub-micron thick micro-metallic meshes (μ-MMs). Due to the high visible transmittance (83.1%) and low sheet resistance (1.75 Ω/sq) of the silver μ-MM with thickness of only 190 nm, the transparent CPW has very low insertion loss and provides a good feed to the high-performance transparent antenna. The measured S11 spectrum of our antenna matches well with that of the opaque counterpart. The measured fractional bandwidth is 22% from 3.4 to 4.25 GHz. Based on numerical modeling, whose accuracy is experimentally verified, the radiation efficiency and the peak gain of our transparent antenna at 3.45 GHz are calculated to be 89.7% and 3.03 dBi, respectively. Besides the good optical and electromagnetic properties, our transparent antenna is also highly flexible. Despite the sub-micron thick μ-MMs, the transparency, radiation efficiency and mechanical properties of our transparent antenna are obviously superior to those of the transparent antennas reported previously, and the overall size and radiation gain are also comparable. Therefore, our transparent antenna has an excellent comprehensive performance, showing great potential for practical applications as well as the emerging applications in the field of flexible and wearable electronics.
Exceptional point (EP) and exceptional ring (ER) are unique features for non-Hermitian systems, which have recently attracted great attentions in acoustics due to their rich physical significances and various potential applications. Despite the rapid development about the study of the EP and ER in one-dimensional acoustic systems, the realization of them in two-dimensional (2D) non-Hermitian structures is still facing a great challenge. To overcome this, we numerically and theoretically realize an ER in 2D reciprocal space based on a square-lattice non-Hermitian sonic crystal (SC). By introducing radiation loss caused by circular holes of each resonator in a Hermitian SC, we realize the conversion between a Dirac cone and the ER. Based on the theoretical analysis with the effective Hamiltonian, we obtain that the formation of the ER is closely related to different radiation losses of dipole and quadrupole modes in the resonators. Additionally, in the non-Hermitian SC, two eigenfunctions can be merged into a single self-orthogonal one on the ER, which does not exist in the Hermitian SC. Finally, by verifying the existence of the EP in every direction of 2D reciprocal space, we further demonstrate the ER in the proposed non-Hermitian SC. Our work may provide theoretical schemes and concrete methods for designing various types of non-Hermitian acoustic devices.
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